@article{ WOS:000805610200001, Author = {Zhang, Wei and Sun, Linhui and Wang, Xinping and Wu, Anbo}, Title = {The influence of AI word-of-mouth system on consumers' purchase behaviour: The mediating effect of risk perception}, Journal = {SYSTEMS RESEARCH AND BEHAVIORAL SCIENCE}, Year = {2022}, Volume = {39}, Number = {3, SI}, Pages = {516-530}, Month = {MAY}, Abstract = {Artificial intelligence (AI) technology is playing an increasingly important role in achieving precision marketing. AI word-of-mouth system marketing focuses most on the entry point of consumers-the key information that leads consumers to buy. Based on consumer behaviour theory and information communication theory, this study constructs a research model of the influence of positive and negative online word of mouth on consumer purchase behaviour from the AI word-of-mouth system's four dimensions: professional degree, information quality, information quantity and information intensity. The results show that in the analysis of perceived risk, whether for positive or negative online word of mouth, consumers pay more attention to the number of information features than information quality and information intensity. In the purchase behaviour analysis, consumers are most concerned about information quality and information intensity. Perceived risk plays a mediating role in the influence of AI word of mouth on purchasing behaviour.}, Publisher = {WILEY}, Address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, Type = {Article}, Language = {English}, Affiliation = {Zhang, W; Wang, XP (Corresponding Author), Xian Univ Sci \& Technol, Sch Management, Xian 710054, Peoples R China. Zhang, Wei; Sun, Linhui; Wang, Xinping; Wu, Anbo, Xian Univ Sci \& Technol, Sch Management, Xian 710054, Peoples R China.}, DOI = {10.1002/sres.2871}, EarlyAccessDate = {JUN 2022}, ISSN = {1092-7026}, EISSN = {1099-1743}, Keywords = {AI word-of-mouth system; artificial intelligence (AI) technology; perceived risk; purchase intention}, Keywords-Plus = {REVIEWS; PRODUCT; INFORMATION; SALES; IMPACT; CONVERSATIONS; TECHNOLOGY; SEARCH}, Research-Areas = {Business \& Economics; Social Sciences - Other Topics}, Web-of-Science-Categories = {Management; Social Sciences, Interdisciplinary}, Author-Email = {zhangwei-shx@163.com wangxp@xust.edu.cn}, Affiliations = {Xi'an University of Science \& Technology}, ResearcherID-Numbers = {LU, Li/JFJ-9011-2023 JIN, LIYING/JFB-1980-2023 wang, chen/JED-7289-2023 Jiang, Yuan/JED-3759-2023 zhang, xu/JEO-4879-2023 wu, yi/JEP-1581-2023 LI, XIAO/IQV-9318-2023}, Funding-Acknowledgement = {Key Project of Philosophy and Social Prosperity of Xi'an University of Science and Technology {[}2019SZ01]}, Funding-Text = {Key Project of Philosophy and Social Prosperity of Xi'an University of Science and Technology, Grant/Award Number: 2019SZ01}, Cited-References = {{[}Anonymous], 2014, NANKAI BUSINESS REV, DOI DOI 10.3969/J.ISSN.1008-3448.2014.04.015. 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Sci.}, Doc-Delivery-Number = {2P0YQ}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000805610200001}, DA = {2023-10-04}, } @article{ WOS:001056220800001, Author = {Gerlich, Michael}, Title = {The Power of Virtual Influencers: Impact on Consumer Behaviour and Attitudes in the Age of AI}, Journal = {ADMINISTRATIVE SCIENCES}, Year = {2023}, Volume = {13}, Number = {8}, Month = {AUG}, Abstract = {In recent years, a new type of influencer has emerged in the field of social media marketing: virtual influencers. Though it is spreading fast, the trend is still new and, therefore, limited research has been conducted on the topic. This study aims to investigate the impact of virtual influencers on customers and whether there is a direct impact on human influencers due to the rise of virtual influencers in the industry. The study employed a questionnaire-based survey method to collect and analyse responses from a sample of 357 participants. 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Gerlich, Michael, SBS Swiss Business Sch, Dept Management, Flughafenstr 3, CH-8302 Zurich, Switzerland.}, DOI = {10.3390/admsci13080178}, Article-Number = {178}, EISSN = {2076-3387}, Keywords = {virtual influencers; consumer behaviour; artificial intelligence; consumer perception; social media marketing; influencer marketing}, Keywords-Plus = {CELEBRITY ENDORSER; COMMUNICATION}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Author-Email = {michael.gerlich@cantab.net}, Affiliations = {SBS Swiss Business School}, ResearcherID-Numbers = {Gerlich, Michael/GQA-3552-2022}, ORCID-Numbers = {Gerlich, Michael/0000-0003-4033-4403}, Cited-References = {Alboqami H, 2023, J RETAIL CONSUM SERV, V72, DOI 10.1016/j.jretconser.2022.103242. Amelina Dinna., 2016, PACIS 2016 P, P232. Amos C, 2008, INT J ADVERT, V27, P209, DOI 10.1080/02650487.2008.11073052. Anisa Matthews, 2021, VIRTUAL LY BLACK INF. 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Sci.}, Doc-Delivery-Number = {Q2YL1}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:001056220800001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000892323800028, Author = {Chaudhary, Prashant and Kiran, Prabha and Kate, Nilesh and Pandey, Shailesh}, Title = {Experiential tourism - role and application of micro-targeting in enhancing customer experience, engagement and loyalty}, Journal = {JOURNAL OF INFORMATION \& OPTIMIZATION SCIENCES}, Year = {2022}, Volume = {43}, Number = {6, SI}, Pages = {1463-1473}, Month = {AUG 18}, Abstract = {Micro-Targeting has emerged as preferred marketing and branding strategy in the travel and tourism sector across the world. `this strategic marketing approach essentially leverages the deep consumer insights in order to design and develop personalised marketing content and recommendations. The digital technologies like Artificial Intelligence (AI), big data analytics, Machine Learning (ML), Augmented Reality (AR), and Virtual Reality etc. are helping the brands in this sector to predict the taste, preferences, priorities, and overall buying behaviour of their target audience. These valuable insights are subsequently utilised for influencing these prospects through hyper-targeted content and advertising. The overarching objective of this research study is to understand the effectiveness of microtargeting for creating desired customer experience and subsequently its impact on the brand preference and purchase intention. Novelty of this study is reflected in its focus, which is on understanding the role micro-targeting can play in marketing and branding of offerings in experiential tourism category. It was observed that micro-targeting helps companies/ brands to create personalised customer experience across different touch-points during the buying process of the high involvement offerings like experiential travel and tourism services.}, Publisher = {TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Chaudhary, P (Corresponding Author), Dr Vishwanath Karad MIT World Peace Univ, Sch Management PG, Pune, Maharashtra, India. Chaudhary, Prashant, Dr Vishwanath Karad MIT World Peace Univ, Sch Management PG, Pune, Maharashtra, India. Kiran, Prabha, Westminster Int Univ, Sch Business \& Econ, Management \& Mkt Dept, Tashkent, Uzbekistan. Kate, Nilesh, Pune Inst Business Management PIBM, Dept Mkt, Pune, Maharashtra, India. 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R.}, Title = {AI, Behavioural Science, and Consumer Welfare}, Journal = {JOURNAL OF CONSUMER POLICY}, Year = {2023}, Month = {2023 JUL 24}, Abstract = {This article discusses the opportunities and costs of AI in behavioural science, with particular reference to consumer welfare. We argue that because of pattern detection capabilities, modern AI will be able to identify (1) new biases in consumer behaviour and (2) known biases in novel situations in which consumers find themselves. AI will also allow behavioural interventions to be personalised and contextualised and thus produce significant benefits for consumers. Finally, AI can help behavioural scientists to ``see the system,{''} by enabling the creation of more complex and dynamic models of consumer behaviour. While these opportunities will significantly advance behavioural science and offer great promise to improve consumer outcomes, we highlight several costs of using AI. We focus on some important environmental, social, and economic costs that are relevant to behavioural science and its application. For consumers, some of those costs involve privacy; others involve manipulation of choices.}, Publisher = {SPRINGER}, Address = {ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Mills, S (Corresponding Author), Univ Leeds, Leeds, England. Mills, S., Univ Leeds, Leeds, England. Costa, S., Univ Ghent, Dept Expt Psychol, Ghent, Belgium. Sunstein, C. R., Harvard Univ, Cambridge, MA USA.}, DOI = {10.1007/s10603-023-09547-6}, EarlyAccessDate = {JUL 2023}, ISSN = {0168-7034}, EISSN = {1573-0700}, Keywords = {Artificial intelligence; Behavioural science; Consumer welfare; Personalisation; Algorithmic harm}, Keywords-Plus = {CHALLENGES; NUDGES}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {s.mills1@leeds.ac.uk}, Affiliations = {University of Leeds; Ghent University; Harvard University}, ORCID-Numbers = {Costa, Samuel/0000-0001-8343-8240 Mills, Stuart/0000-0002-6698-0983}, Cited-References = {Abson DJ, 2017, AMBIO, V46, P30, DOI 10.1007/s13280-016-0800-y. Agrawal K, 2022, Arxiv, DOI arXiv:2208.13940. Aher G, 2022, Arxiv, DOI arXiv:2208.10264. Ahuja A., 2023, FINANC TIMES. Akgun Selin, 2022, AI Ethics, V2, P431, DOI 10.1007/s43681-021-00096-7. {[}Anonymous], 2015, INSIDE NUDGE UNIT. Aoki N, 2021, COMPUT HUM BEHAV, V114, DOI 10.1016/j.chb.2020.106572. 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Policy}, Doc-Delivery-Number = {M6PV4}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:001031425400001}, OA = {hybrid}, DA = {2023-10-04}, } @article{ WOS:000853146600035, Author = {Ljepava, Nikolina}, Title = {AI-Enabled Marketing Solutions in Marketing Decision Making: AI Application in Different Stages of Marketing Process}, Journal = {TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS}, Year = {2022}, Volume = {11}, Number = {3}, Pages = {1308-1315}, Month = {AUG}, Abstract = {The digital transformation led by disruptive technologies can help organizations address numerous challenges and deliver better customer value through innovative technologies in all business areas. Artificial intelligence (AI) is finding its application in various business disciplines and is expected to be one of the most important technological tools used in marketing in the years to come. The paper addresses the expected role of artificial intelligence solutions in marketing decision-making throughout the five steps of the marketing process. The study provides a systematic review of the research articles addressing the application of AI for marketing decision-making published in the period from 2020 to 2022. Identified applications are then mapped to five steps of the marketing process: analysis, strategy, tactics, customer relations, and value proposition creation. The findings indicate that most of the current AI applications are utilized in the first stage of the marketing process related to understanding and predicting customer behaviour and in the tactical stage of creating a marketing mix. The paper concludes with recommendations for marketing practitioners and recommendations for further research.}, Publisher = {UIKTEN - ASSOC INFORMATION COMMUNICATION TECHNOLOGY EDUCATION \& SCIENCE}, Address = {HILMA ROZAJCA 15, NOVI PAZAR, 36300, SERBIA}, Type = {Article}, Language = {English}, Affiliation = {Ljepava, N (Corresponding Author), Amer Univ Emirates, Dubai, U Arab Emirates. Ljepava, Nikolina, Amer Univ Emirates, Dubai, U Arab Emirates.}, DOI = {10.18421/TEM113-40}, ISSN = {2217-8309}, EISSN = {2217-8333}, Keywords = {AI marketing; machine learning; decision-making; marketing process}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Information Systems}, Author-Email = {nikolina.ljepava@aue.ae}, Cited-References = {Al-Ghamdi LM, 2021, SUSTAINABLE ENG INNO, V3, P15, DOI {[}10.37868/sei.v3i1.121, DOI 10.37868/SEI.V3I1.121]. {[}Anonymous], 2016, PRINCIPLE MARKETING. 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Yin JW, 2021, SUSTAINABILITY-BASEL, V13, DOI 10.3390/su13105671.}, Number-of-Cited-References = {45}, Times-Cited = {1}, Usage-Count-Last-180-days = {35}, Usage-Count-Since-2013 = {51}, Journal-ISO = {TEM J.}, Doc-Delivery-Number = {4M2GZ}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000853146600035}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000771642800001, Author = {Brooks, Ruby and Duy Nguyen and Bhatti, Asim and Allender, Steven and Johnstone, Michael and Lim, Chee Peng and Backholer, Kathryn}, Title = {Use of artificial intelligence to enable dark nudges by transnational food and beverage companies: analysis of company documents}, Journal = {PUBLIC HEALTH NUTRITION}, Year = {2022}, Volume = {25}, Number = {5}, Pages = {1291-1299}, Month = {MAY}, Abstract = {Objective: To describe the use of artificial intelligence (AI)-enabled dark nudges by leading global food and beverage companies to influence consumer behaviour. Design: The five most recent annual reports (ranging from 2014 to 2018 or 2015 to 2019, depending on the company) and websites from twelve of the leading companies in the global food and beverage industry were reviewed to identify uses of AI and emerging technologies to influence consumer behaviour. Uses of AI and emerging technologies were categorised according to the Typology of Interventions in Proximal Physical Micro-Environments (TIPPME) framework, a tool for categorising and describing nudge-type behaviour change interventions (which has also previously been used to describe dark nudge-type approaches used by the alcohol industry). Setting: Not applicable. Participants: Twelve leading companies in the global food and beverage industry. Results: Text was extracted from fifty-seven documents from eleven companies. AI-enabled dark nudges used by food and beverage companies included those that altered products and objects' availability (e.g. social listening to inform product development), position (e.g. decision technology and facial recognition to manipulate the position of products on menu boards), functionality (e.g. decision technology to prompt further purchases based on current selections) and presentation (e.g. augmented or virtual reality to deliver engaging and immersive marketing). Conclusions: Public health practitioners and policymakers must understand and engage with these technologies and tactics if they are to counter industry promotion of products harmful to health, particularly as investment by the industry in AI and other emerging technologies suggests their use will continue to grow.}, Publisher = {CAMBRIDGE UNIV PRESS}, Address = {EDINBURGH BLDG, SHAFTESBURY RD, CB2 8RU CAMBRIDGE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Backholer, K (Corresponding Author), Deakin Univ, Global Obes Ctr, Sch Hlth \& Social Dev, Inst Hlth Transformat, Geelong, Vic, Australia. Brooks, Ruby; Allender, Steven; Backholer, Kathryn, Deakin Univ, Global Obes Ctr, Sch Hlth \& Social Dev, Inst Hlth Transformat, Geelong, Vic, Australia. Duy Nguyen; Bhatti, Asim; Johnstone, Michael; Lim, Chee Peng, Deakin Univ, Inst Intelligent Syst Res \& Innovat, Geelong, Vic, Australia.}, DOI = {10.1017/S1368980022000490}, EarlyAccessDate = {MAR 2022}, Article-Number = {PII S1368980022000490}, ISSN = {1368-9800}, EISSN = {1475-2727}, Keywords = {Artificial intelligence; Marketing; Nudge; Food; Diet}, Research-Areas = {Public, Environmental \& Occupational Health; Nutrition \& Dietetics}, Web-of-Science-Categories = {Public, Environmental \& Occupational Health; Nutrition \& Dietetics}, Author-Email = {kathryn.backholer@deakin.edu.au}, Affiliations = {Deakin University; Deakin University}, ResearcherID-Numbers = {Lim, Chee Peng/AAS-4698-2021 Johnstone, Michael/B-3243-2010 Allender, Steven/G-9881-2011 Lim, CP/D-1999-2009 }, ORCID-Numbers = {Lim, CP/0000-0003-4191-9083 Johnstone, Michael/0000-0002-3005-8911 Brooks, Ruby/0000-0002-2647-6934}, Funding-Acknowledgement = {National Heart Foundation Future Leader Fellowship {[}102047]}, Funding-Text = {KB and RB were funded through a National Heart Foundation Future Leader Fellowship {[}102047]. The National Heart Foundation had no role in the design, analysis or writing of this article. Conflict of interest: There are no conflicts of interest. Authorship: K.B. and R.B. conceptualised the study. R.B., K.B. and D.N. contributed to data analysis. All authors provided input into the final version of the manuscript. Ethics of human subject participation: Not applicable.}, Cited-References = {Allen JR., 2020, BROOKINGS GLOSSARY E. Backholer K., 2020, UNSCN NUTR, V45, P103. Cadario R, 2020, MARKET SCI, V39, P465, DOI 10.1287/mksc.2018.1128. Carolan M, 2018, GEOFORUM, V90, P142, DOI 10.1016/j.geoforum.2018.02.006. Chester J., 2021, BIG FOOD BIG TECH GL. Curran T., 2018, P NE BUSINESS EC ASS, P74. Danone, 2018, SOC LIST CHANG WHATS. Ensaff H, 2021, P NUTR SOC, V80, P195, DOI 10.1017/S0029665120007983. Euromonitor International, 2020, PASSP GLOB MARK INF. Frankish K., 2014, CAMBRIDGE HDB ARTIFI, DOI {[}DOI 10.1017/CBO9781139046855, 10.1017/CBO9781139046855]. 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Brands, 2019, 10 WAYS KFC PIZZ HUT.}, Number-of-Cited-References = {41}, Times-Cited = {6}, Usage-Count-Last-180-days = {4}, Usage-Count-Since-2013 = {19}, Journal-ISO = {Public Health Nutr.}, Doc-Delivery-Number = {0X8LQ}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000771642800001}, OA = {Green Published, gold}, DA = {2023-10-04}, } @article{ WOS:000662510800001, Author = {Yin, Jiwang and Qiu, Xiaodong}, Title = {AI Technology and Online Purchase Intention: Structural Equation Model Based on Perceived Value}, Journal = {SUSTAINABILITY}, Year = {2021}, Volume = {13}, Number = {10}, Month = {MAY}, Abstract = {(1) Background: AI technology has been deeply applied to online shopping platforms to provide more accurate and personalized services for consumers. It is of great significance to study the different functional experiences of AI for consumers to improve the current application status of AI technology. (2) Method: Based on the ``SOR{''} model, this study divides the AI technology experienced by the consumers of online shopping platforms into three dimensions: accuracy, insight, and interaction experience. The perceived value is taken as the mediating variable from the prospect of perceived utility value and perceived hedonic value. This article uses empirical research methods to analyze the effect of the three dimensions of online shopping AI experience to research the internal influence mechanism of consumers' purchase intention. (3) Results: 1. The accuracy, insight, and interaction experience of AI marketing technology each have a significant positive impact on consumers' perceived utility value and hedonic value; 2. Both the perceived utility value and perceived hedonic value obtained by an AI technology experience can promote the formation of consumers' purchase intention; 3. The perceived hedonic value was better than perceived utility value at promoting the consumers' purchase intention.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Qiu, XD (Corresponding Author), Beijing Jiaotong Univ, Sch Econ \& Management, Beijing 100044, Peoples R China. Yin, Jiwang; Qiu, Xiaodong, Beijing Jiaotong Univ, Sch Econ \& Management, Beijing 100044, Peoples R China.}, DOI = {10.3390/su13105671}, Article-Number = {5671}, EISSN = {2071-1050}, Keywords = {artificial intelligence marketing; online shopping; perceived utility value; perceived hedonic value; purchase intention; SOR}, Keywords-Plus = {ACCEPTANCE; CONSUMERS; LOYALTY}, Research-Areas = {Science \& Technology - Other Topics; Environmental Sciences \& Ecology}, Web-of-Science-Categories = {Green \& Sustainable Science \& Technology; Environmental Sciences; Environmental Studies}, Author-Email = {19113075@bjtu.edu.cn xdqiu@bjtu.edu.cm}, Affiliations = {Beijing Jiaotong University}, Funding-Acknowledgement = {National Social Science Fund of China {[}15AGL002]}, Funding-Text = {This research was funded by a grant from the National Social Science Fund of China (15AGL002).}, Cited-References = {Aakash S., 2019, IRE J, V2, P37. 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Zhu HY, 2009, J MARKET MANAG-UK, V25, P295, DOI 10.1362/026725709X429764.}, Number-of-Cited-References = {67}, Times-Cited = {22}, Usage-Count-Last-180-days = {34}, Usage-Count-Since-2013 = {159}, Journal-ISO = {Sustainability}, Doc-Delivery-Number = {ST5VN}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000662510800001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000454090000012, Author = {Kaczorowska-Spychalska, Dominika}, Title = {Digital Technologies in the Process of Virtualization of Consumer Behaviour - Awareness of New Technologies}, Journal = {MANAGEMENT-POLAND}, Year = {2018}, Volume = {22}, Number = {2}, Pages = {187-203}, Month = {DEC}, Abstract = {Digital resolution is currently one of the most important forces determining changes and their dynamics in the social, cultural and economic dimension. Digital technologies such as the Internet of Things and Artificial Intelligence will, according to Gartner's Hype Cycle for Emerging Technologies 2017, play an increasingly important role while creating a new quality of the market space. Yet, these are multidimensional issues whose potential should be considered both, from the perspective of enterprises that create and/or adapt such technologies in their production, logistics or sale processes as well as in consumer perspective taking into account a degree of awareness, interest and fascination of potential buyers, users with such devices and solutions. This is determined by dualism of approach to digital technologies (economic approach vs. humanistic approach) and evaluation of their potential benefits and threats. It seems, however, that virtualization of consumer behaviour as a consequence of impact of technologies such as the Internet of Things and Artificial Intelligence, can at the same time be a significant driving force of further processes of digitalization, its dimensions and dynamics. The article attempts to identify the impact of digital technologies (IoT and AI) on attitudes, preferences and decisions of consumers and presented discussion was based on the results of own studies in the analysed area.}, Publisher = {DE GRUYTER POLAND SP ZOO}, Address = {BOGUMILA ZUGA 32A STR., 01-811 WARSAW, POLAND}, Type = {Article}, Language = {English}, Affiliation = {Kaczorowska-Spychalska, D (Corresponding Author), Univ Lodz, Fac Management, Dept Mkt, Lodz, Poland. Kaczorowska-Spychalska, Dominika, Univ Lodz, Fac Management, Dept Mkt, Lodz, Poland.}, DOI = {10.2478/manment-2018-0031}, ISSN = {1429-9321}, EISSN = {2299-193X}, Keywords = {Digital Technologies; Internet of Things; Artificial Intelligence; Consumer Behaviour}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Affiliations = {University of Lodz}, ORCID-Numbers = {Kaczorowska-Spychalska, DOMINIKA/0000-0002-2566-0297}, Cited-References = {Adamczyk D, 2015, INTERNET OF THINGS. {[}Anonymous], 2015, INTERNET THINGS SMAR. Borek A., 2016, MARKETING SMART MACH. Buya R., 2016, INTERNET THINGS PRIN. Carr N, 2013, PLYTKI UMYSL. Dawar N., 2013, HARVARD BUSINESS REV. Ford M., 2016, SWIT ROBOTOW. Harari Y. N, 2015, HOMODEUS. Kaczorowska-Spychalska D, 2016, ADV INTELLIGENT SYST, V490. Kotler P., 2010, MARKETING 3 0, DOI {[}10.1002/9781118257883, DOI 10.1002/9781118257883]. Kumar E., 2015, ARTIFICIAL INTELLIGE. Kurzweil R, 2005, HUMANS TRANSCEND BIO. 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Zaltman G., 2008, JAK MYSLA KLIENCI PO.}, Number-of-Cited-References = {21}, Times-Cited = {4}, Usage-Count-Last-180-days = {8}, Usage-Count-Since-2013 = {36}, Journal-ISO = {Manag.-Pol.}, Doc-Delivery-Number = {HF2TS}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000454090000012}, OA = {Green Submitted, gold}, DA = {2023-10-04}, } @article{ WOS:000607800400002, Author = {Chen, Fengzhang and Chen, Fengwen and Liao, Fangnan and Zhang, Lu and Zhang, Jing}, Title = {Dynamic governance of social network based on dynamic optimisation algorithm: a new perspective of AI system}, Journal = {INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT}, Year = {2020}, Volume = {84}, Number = {1-2, SI}, Pages = {25-49}, Abstract = {This study optimises the dynamic evolution of an entrepreneurial social network. Exploiting a dynamic optimisation algorithm-based (DOA-based) AI system as the exploratory model and unique customer-purchase-level big data based on Hadoop, we can maximise start-ups' revenue while minimising the dynamic governing cost of a social network to select the right time to evolve the entrepreneurial social network in the context of uncertainty in customer behaviour and the response of the social network. We find that the dynamic optimisation algorithm can effectively improve the dynamic governance of social networks through empirical testing of a real start-up's social network evolution problem. Moreover, the improvement is affected by the exploration efficiency, evolution efficiency, unit resource reliance cost, revenue and profit. These findings are great importance for exploring the roles played by artificial intelligence in entrepreneurial social networks, including measurement, dynamic research and governance.}, Publisher = {INDERSCIENCE ENTERPRISES LTD}, Address = {WORLD TRADE CENTER BLDG, 29 ROUTE DE PRE-BOIS, CASE POSTALE 856, CH-1215 GENEVA, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Chen, FW (Corresponding Author), Chongqing Univ, Sch Econ \& Business Adm, 174 Shazheng St, Chongqing, Peoples R China. Chen, Fengzhang, Chongqing Univ, Coll Comp Sci, 174 Shazheng St, Chongqing, Peoples R China. Chen, Fengwen; Zhang, Lu; Zhang, Jing, Chongqing Univ, Sch Econ \& Business Adm, 174 Shazheng St, Chongqing, Peoples R China. Liao, Fangnan, Southwest Univ, Coll Econ \& Management, 2 Tiansheng Rd, Chongqing, Peoples R China.}, ISSN = {0267-5730}, EISSN = {1741-5276}, Keywords = {dynamic optimisation; social network; network dynamism; dynamic network governance; AI system}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE; TIES}, Research-Areas = {Engineering; Business \& Economics; Operations Research \& Management Science}, Web-of-Science-Categories = {Engineering, Multidisciplinary; Management; Operations Research \& Management Science}, Author-Email = {chenfengzhang2019@163.com chenfengwen@cqu.edu.cn liaofangnan234@163.com zhanglu20100160@yeah.net 20160202019@cqu.edu.cn}, Affiliations = {Chongqing University; Chongqing University; Southwest University - China}, ORCID-Numbers = {Zhang, Jing/0000-0002-6431-9286}, Funding-Acknowledgement = {National Natural Science Foundation of China (NSFC) {[}71772019]; Fundamental Research Funds for the Central Universities {[}2020CDJSK02XK16]}, Funding-Text = {We are grateful for the financial support provided by the National Natural Science Foundation of China (NSFC) (No. 71772019) and the Fundamental Research Funds for the Central Universities (Project No. 2020CDJSK02XK16).}, Cited-References = {{[}Anonymous], 1993, ENTREPRENEURSHIP THE. 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Shu R, 2018, J BUS RES, V85, P197, DOI 10.1016/j.jbusres.2017.12.048. Slotte-Kock S, 2010, ENTREP THEORY PRACT, V34, P31, DOI 10.1111/j.1540-6520.2009.00311.x. Smith C, 2017, J BUS VENTURING, V32, P18, DOI 10.1016/j.jbusvent.2016.10.003. UK Information Commissioner's Office, 2017, BIG DAT ART INT MACH. Walz A., 2019, WORLD EC FORUM, P136. Wincent J, 2016, J SMALL BUS MANAGE, V54, P229, DOI 10.1111/jsbm.12140.}, Number-of-Cited-References = {37}, Times-Cited = {0}, Usage-Count-Last-180-days = {4}, Usage-Count-Since-2013 = {37}, Journal-ISO = {Int. J. Technol. Manage.}, Doc-Delivery-Number = {PS3BF}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000607800400002}, DA = {2023-10-04}, } @article{ WOS:000531543100001, Author = {Tupikovskaja-Omovie, Zofija and Tyler, David}, Title = {Clustering consumers' shopping journeys: eye tracking fashion m-retail}, Journal = {JOURNAL OF FASHION MARKETING AND MANAGEMENT}, Year = {2020}, Volume = {24}, Number = {3, SI}, Pages = {381-398}, Month = {JUL 13}, Abstract = {Purpose Despite the rapid adoption of smartphones among digital fashion consumers, their attitude to retailers' mobile apps and websites is one of increasing dissatisfaction. This suggests that understanding how mobile consumers use smartphones for fashion shopping is important in developing digital shopping platforms that fulfil consumer' expectations. Design/methodology/approach For this research, mobile eye-tracking technology was employed in order to develop unique shopping journeys for 30 consumers, using fashion retailers' websites on smartphones, documenting their differences and similarities in browsing and purchasing behaviour. Findings Based on scan path visualisations and observed shopping experiences, three prominent mobile shopping journeys and shopper types were identified: ``directed by retailer's website{''}, ``efficient self-selected journey{''} and ``challenging shopper{''}. These prominent behaviour patterns were used to characterise mixed cluster behaviours; three distinct mixed clusters were identified, namely, ``extended self-selected journey{''}, ``challenging shoppers directed by retailer's website{''} and ``focused challenging shopper{''}. Research limitations/implications This research argues that mobile consumers can be segmented based on their activities and behaviours on the mobile website. Knowing the prominent shopping behaviour types any other complex behaviour patterns can be identified, analysed and described. Practical implications The findings of this research can be used in developing personalised shopping experiences on smartphones by feeding these shopper types into retailers' digital marketing strategy and artificial intelligence (AI) systems. Originality/value This paper contributes to consumer behaviour literature by proposing a novel mobile consumer segmentation approach based on detailed shopping journey analysis using mobile eye-tracking technology.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Tupikovskaja-Omovie, Z (Corresponding Author), Manchester Metropolitan Univ, Sch Fash, Manchester, Lancs, England. Tupikovskaja-Omovie, Zofija; Tyler, David, Manchester Metropolitan Univ, Sch Fash, Manchester, Lancs, England.}, DOI = {10.1108/JFMM-09-2019-0195}, EarlyAccessDate = {MAY 2020}, ISSN = {1361-2026}, EISSN = {1758-7433}, Keywords = {Consumer behaviour; Mobile consumer; Fashion consumer behaviour; Consumer segmentation; Eye tracking; Shopping journey; Fashion retailing; Customer journey}, Keywords-Plus = {MOBILE COMMERCE; CUSTOMER SEGMENTATION; EXPERIENCES; MOTIVATION; ATTENTION; EXPOSURE; DESIGN; USAGE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, Author-Email = {zofi.t.omovie@gmail.com d.tyler@mmu.ac.uk}, Affiliations = {Manchester Metropolitan University}, ORCID-Numbers = {Tupikovskaja-Omovie, Zofija/0000-0003-3180-3458}, Cited-References = {Anderl E, 2016, INT J RES MARK, V33, P457, DOI 10.1016/j.ijresmar.2016.03.001. {[}Anonymous], 2012, INT J MOBILE MARKETI. {[}Anonymous], 2006, JOURNEY INTERFACE PU. 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Zomerdijk LG, 2011, J PROD INNOVAT MANAG, V28, P63, DOI 10.1111/j.1540-5885.2010.00781.x.}, Number-of-Cited-References = {72}, Times-Cited = {14}, Usage-Count-Last-180-days = {8}, Usage-Count-Since-2013 = {98}, Journal-ISO = {J. Fash. Mark. Manag.}, Doc-Delivery-Number = {NH0BM}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000531543100001}, OA = {Green Accepted}, DA = {2023-10-04}, } @article{ WOS:000794033300018, Author = {Kim, Juran and Kang, Seungmook and Bae, Joonheui}, Title = {Human likeness and attachment effect on the perceived interactivity of AI speakers}, Journal = {JOURNAL OF BUSINESS RESEARCH}, Year = {2022}, Volume = {144}, Pages = {797-804}, Month = {MAY}, Abstract = {Artificial intelligence (AI) platforms with interactive assistants allow consumers to avail information and help direct their choices, thus changing the ways in which companies interact with their customers. This study aims to explore the concept of human likeness, attachment, and perceived interactivity in the context of AI speakers and examine the effects of human likeness and attachment on their perceived interactivity with AI speakers. A survey was used to investigate whether consumers' perception of human likeness, attachment and their perceived interactivity with AI speakers eventually influence their purchase intention, and how attachment and the perceived interactivity mediate the effects of human likeness and purchase intention. The participants were 311 AI speaker users from South Korea. The results demonstrate how the direct effect and mediating effect of human likeness, attachment, and perceived interactivity on AI speakers boost purchase intention, thus providing meaningful implications for AI-driven marketing academics and practitioners.}, Publisher = {ELSEVIER SCIENCE INC}, Address = {STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA}, Type = {Article}, Language = {English}, Affiliation = {Kim, J (Corresponding Author), Jeonju Univ, Dept Business Adm, Mkt, 518 Res Bldg,303 Cheonjamro, Jeonju 55069, South Korea. Kang, S (Corresponding Author), Jeonju Univ, Dept Game Contents, Arts Hall Annex Room 303,303 Cheonjamro, Jeonju 55069, Jeonbuk, South Korea. Bae, J (Corresponding Author), Kyungpook Natl Univ, Sch Business Adm, Daegu, South Korea. Kim, Juran, Jeonju Univ, Dept Business Adm, Mkt, 518 Res Bldg,303 Cheonjamro, Jeonju 55069, South Korea. Kang, Seungmook, Jeonju Univ, Dept Game Contents, Arts Hall Annex Room 303,303 Cheonjamro, Jeonju 55069, Jeonbuk, South Korea. Bae, Joonheui, Kyungpook Natl Univ, Sch Business Adm, Daegu, South Korea.}, DOI = {10.1016/j.jbusres.2022.02.047}, EarlyAccessDate = {FEB 2022}, ISSN = {0148-2963}, EISSN = {1873-7978}, Keywords = {Artificial intelligence; AI speaker; Human likeness; Attachment; Perceived interactivity}, Keywords-Plus = {UNCANNY VALLEY; BRAND ATTACHMENT; CONSUMERS; ATTENTION; ROBOTS; ENDORSEMENTS; PERCEPTIONS; PERSONALITY; CONSISTENCY; EXPERIENCE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {jrkim@jj.ac.kr xevious@jj.ac.kr regina721@knu.ac.kr}, Affiliations = {Jeonju University; Jeonju University; Kyungpook National University}, ORCID-Numbers = {Bae, Joonheui/0000-0003-3272-7004}, Cited-References = {Aggarwal P, 2007, J CONSUM RES, V34, P468, DOI 10.1086/518544. {[}Anonymous], INT ENCY COMMUNICATI. {[}Anonymous], 2004, J COMPUTER MEDIATED, DOI DOI 10.1111/J.1083-6101.2004.TB00232.X. 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Wan Jing, 2015, STRONG BRANDS STRONG, P119. Yoo B, 2009, ADV CONSUM RES, V36, P280. You S, 2018, J ASSOC INF SYST, V19, P377, DOI 10.17705/1jais.00496.}, Number-of-Cited-References = {64}, Times-Cited = {5}, Usage-Count-Last-180-days = {55}, Usage-Count-Since-2013 = {135}, Journal-ISO = {J. Bus. Res.}, Doc-Delivery-Number = {1D8GB}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000794033300018}, DA = {2023-10-04}, } @article{ WOS:000733643400001, Author = {Lee, Crystal T. and Pan, Ling-Yen and Hsieh, Sara H.}, Title = {Artificial intelligent chatbots as brand promoters: a two-stage structural equation modeling-artificial neural network approach}, Journal = {INTERNET RESEARCH}, Year = {2022}, Volume = {32}, Number = {4}, Pages = {1329-1356}, Month = {JUL 4}, Abstract = {Purpose This study investigates the determinants of effective human and artificial intelligence (AI) relationship-building strategies for brands. It explores the antecedents and consequences of consumers' interactant satisfaction with communication and identifies ways to enhance consumer purchase intention via AI chatbot promotion. Design/methodology/approach Microsoft Xiaoice served as the focal AI chatbot, and 331 valid samples were obtained. A two-stage structural equation modeling-artificial neural network approach was adopted to verify the proposed theoretical model. Findings Regarding the IQ (intelligence quotient) and EQ (emotional quotient) of AI chatbots, the multi-dimensional social support model helps explain consumers' interactant satisfaction with communication, which facilitates affective attachment and purchase intention. The results also show that chatbots should emphasize emotional and esteem social support more than informational support. Practical implications Brands should focus more on AI chatbots' emotional and empathetic responses than functional aspects when designing dialogue content for human-AI interactions. Well-designed AI chatbots can help marketers develop effective brand promotion strategies. Originality/value This research enriches the human-AI interaction literature by adopting a multi-dimensional social support theoretical lens that can enhance the interactant satisfaction with communication, affective attachment and purchase intention of AI chatbot users.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Pan, LY (Corresponding Author), Natl Taiwan Univ, Profess Masters Program Business Adm, Taipei, Taiwan. Lee, Crystal T., Shantou Univ, Business Sch, Shantou, Peoples R China. Pan, Ling-Yen, Natl Taiwan Univ, Profess Masters Program Business Adm, Taipei, Taiwan. Hsieh, Sara H., Tunghai Univ, Dept Business Adm, Taichung, Taiwan.}, DOI = {10.1108/INTR-01-2021-0030}, EarlyAccessDate = {DEC 2021}, ISSN = {1066-2243}, Keywords = {AI chatbot; Human-AI interaction; Social support; Interactant satisfaction with communication; Affective attachment; Purchase intention}, Keywords-Plus = {MOBILE PAYMENT ACCEPTANCE; SOCIAL SUPPORT; ADVERTISING EFFECTIVENESS; RELATIONSHIP QUALITY; EMOTIONAL SUPPORT; SATISFACTION; IMPACT; TRUST; DETERMINANTS; EXPERIENCE}, Research-Areas = {Business \& Economics; Computer Science; Telecommunications}, Web-of-Science-Categories = {Business; Computer Science, Information Systems; Telecommunications}, Author-Email = {claudiapan@ntu.edu.tw}, Affiliations = {Shantou University; National Taiwan University; Tunghai University}, ResearcherID-Numbers = {Pan, Ling-Yen/GLT-4218-2022 }, ORCID-Numbers = {Pan, Ling-Yen/0000-0002-1218-1254 Lee, Crystal T./0000-0002-2451-1353}, Funding-Acknowledgement = {Shantou University STU Scientific Research Initiation Grant {[}STF20010]; Natural Science Foundation of Guangdong Province, Guangdong Basic and Applied Basic Research Foundation {[}2021A1515012259]}, Funding-Text = {This work was supported by the Shantou University STU Scientific Research Initiation Grant {[}STF20010] and by the Natural Science Foundation of Guangdong Province, Guangdong Basic and Applied Basic Research Foundation Grant {[}2021A1515012259]. The authors would like to thank three anonymous referees of this journal for their constructive comments, the editor and the associate editor for their support and encouragement. The authors would like to acknowledge the proceeding of American Marketing Association (AMA) Summer Academic Conference entitled ``AI Companionship: Examining Social Support of Artificially Intelligent Social Chatbot{''} written by Crystal T. Lee, Sara H. Hsieh and Ling-Yen Pan, on which this manuscript is developed upon.}, Cited-References = {Abubakar AM, 2019, INT J INFORM MANAGE, V49, P45, DOI 10.1016/j.ijinfomgt.2019.02.006. Agatonovic-Kustrin S, 2000, J PHARMACEUT BIOMED, V22, P717, DOI 10.1016/S0731-7085(99)00272-1. Ahani A, 2017, COMPUT HUM BEHAV, V75, P560, DOI 10.1016/j.chb.2017.05.032. {[}Anonymous], 2010, CASES ONLINE DISCUSS. Araujo T, 2018, COMPUT HUM BEHAV, V85, P183, DOI 10.1016/j.chb.2018.03.051. Ashfaq M, 2020, TELEMAT INFORM, V54, DOI 10.1016/j.tele.2020.101473. 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Zhao JJ, 2014, PERS INDIV DIFFER, V64, P126, DOI 10.1016/j.paid.2014.02.026.}, Number-of-Cited-References = {102}, Times-Cited = {9}, Usage-Count-Last-180-days = {39}, Usage-Count-Since-2013 = {153}, Journal-ISO = {Internet Res.}, Doc-Delivery-Number = {2O9EL}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000733643400001}, DA = {2023-10-04}, } @article{ WOS:000485056100001, Author = {Liang, Yuli and Lee, Seung-Hee and Workman, Jane E.}, Title = {Implementation of Artificial Intelligence in Fashion: Are Consumers Ready?}, Journal = {CLOTHING AND TEXTILES RESEARCH JOURNAL}, Year = {2020}, Volume = {38}, Number = {1}, Pages = {3-18}, Month = {JAN}, Abstract = {Given the growing interest in combinations of fashion and digital innovations, it is critical for both researchers and retailers to understand how consumers respond to new technologies, especially artificial intelligence (AI). The purpose of the study was to examine consumers' attitudes and purchase intention toward an AI device. By adapting the technology acceptance model, a conceptual model was constructed and tested related to consumers' attitudes and purchase intention toward an AI device-Echo Look. A total of 313 subjects (61\% female) between 18 and 65 years old in the top 10 metropolitan areas in the United States participated in the study. The results indicated that perceived usefulness, perceived ease of use, and performance risk were significant in consumers' attitude toward AI. Positive attitudes toward technology positively influenced the purchase intention. Based on these results, theoretical and practical implications are discussed.}, Publisher = {SAGE PUBLICATIONS INC}, Address = {2455 TELLER RD, THOUSAND OAKS, CA 91320 USA}, Type = {Article}, Language = {English}, Affiliation = {Liang, YL (Corresponding Author), Southern Illinois Univ, Sch Architecture, Fash Design \& Merchandising Program, 311 G Quigley Hall,875 S Normal Ave, Carbondale, IL 62901 USA. Liang, Yuli; Lee, Seung-Hee; Workman, Jane E., Southern Illinois Univ, Sch Architecture, Fash Design \& Merchandising Program, 311 G Quigley Hall,875 S Normal Ave, Carbondale, IL 62901 USA.}, DOI = {10.1177/0887302X19873437}, EarlyAccessDate = {SEP 2019}, Article-Number = {0887302X19873437}, ISSN = {0887-302X}, EISSN = {1940-2473}, Keywords = {fashion artificial intelligence; technology attitudes; purchase intention}, Keywords-Plus = {MASS CUSTOMIZATION; USER ACCEPTANCE; PERCEIVED RISK; TECHNOLOGY; INTENTIONS; INFORMATION; ATTITUDES; MODEL; ADOPTION; SCALE}, Research-Areas = {Business \& Economics; Social Sciences - Other Topics}, Web-of-Science-Categories = {Business; Social Sciences, Interdisciplinary}, Author-Email = {yuli.liang@siu.edu}, Affiliations = {Southern Illinois University System; Southern Illinois University}, ORCID-Numbers = {Liang, Yuli/0000-0002-5697-2234}, Cited-References = {Ajzen I., 1980, UNDERSTANDING ATTITU, DOI DOI 10.1007/978-3-642-69746-3\_2. 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Wu LH, 2016, COMPUT HUM BEHAV, V64, P383, DOI 10.1016/j.chb.2016.07.005. Yang YX, 2019, COMPUT EDUC, V133, P116, DOI 10.1016/j.compedu.2019.01.015.}, Number-of-Cited-References = {60}, Times-Cited = {18}, Usage-Count-Last-180-days = {18}, Usage-Count-Since-2013 = {79}, Journal-ISO = {Cloth. Text. Res. J.}, Doc-Delivery-Number = {JQ9HF}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000485056100001}, DA = {2023-10-04}, } @article{ WOS:000816564200001, Author = {Gkikas, Dimitris C. and Theodoridis, Prokopis K. and Beligiannis, Grigorios N.}, Title = {Enhanced Marketing Decision Making for Consumer Behaviour Classification Using Binary Decision Trees and a Genetic Algorithm Wrapper}, Journal = {INFORMATICS-BASEL}, Year = {2022}, Volume = {9}, Number = {2}, Month = {JUN}, Abstract = {An excessive amount of data is generated daily. A consumer's journey has become extremely complicated due to the number of electronic platforms, the number of devices, the information provided, and the number of providers. The need for artificial intelligence (AI) models that combine marketing data and computer science methods is imperative to classify users' needs. This work bridges the gap between computer and marketing science by introducing the current trends of AI models on marketing data. It examines consumers' behaviour by using a decision-making model, which analyses the consumer's choices and helps the decision-makers to understand their potential clients' needs. This model is able to predict consumer behaviour both in the digital and physical shopping environments. It combines decision trees (DTs) and genetic algorithms (GAs) through one wrapping technique, known as the GA wrapper method. Consumer data from surveys are collected and categorised based on the research objectives. The GA wrapper was found to perform exceptionally well, reaching classification accuracies above 90\%. With regard to the Gender, the Household Size, and Household Monthly Income classes, it manages to indicate the best subsets of specific genes that affect decision making. These classes were found to be associated with a specific set of variables, providing a clear roadmap for marketing decision-making.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Gkikas, DC (Corresponding Author), Univ Patras, Sch Business \& Econ, Dept Business Adm Food \& Agr Enterprises, 2 George Seferi Str, Agrinion 30100, Greece. Gkikas, Dimitris C.; Theodoridis, Prokopis K.; Beligiannis, Grigorios N., Univ Patras, Sch Business \& Econ, Dept Business Adm Food \& Agr Enterprises, 2 George Seferi Str, Agrinion 30100, Greece.}, DOI = {10.3390/informatics9020045}, Article-Number = {45}, EISSN = {2227-9709}, Keywords = {marketing; consumer behaviour; artificial intelligence; decision making; predictive analytics; machine learning; data mining; genetic algorithm wrapper; decision trees; optimal feature selection}, Keywords-Plus = {FEATURE-SELECTION; INDUCTION; ENSEMBLE; SYSTEM}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Interdisciplinary Applications}, Author-Email = {dgkikas@upatras.gr proth@upatras.gr gbeligia@upatras.gr}, Affiliations = {University of Patras}, ResearcherID-Numbers = {Gkikas, Dimitris C/AFE-7104-2022 Theodoridis, Prokopis/J-8569-2016 }, ORCID-Numbers = {Gkikas, Dimitris C/0000-0002-6522-2128 Theodoridis, Prokopis/0000-0002-8133-4509 BELIGIANNIS, GRIGORIOS/0000-0002-6896-5218}, Cited-References = {{[}Anonymous], DATA ETHICS. {[}Anonymous], 2003, ARTIF INTELL. 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Yu EZ, 2006, COMPUT IND ENG, V51, P111, DOI 10.1016/j.cie.2006.07.004.}, Number-of-Cited-References = {24}, Times-Cited = {4}, Usage-Count-Last-180-days = {2}, Usage-Count-Since-2013 = {4}, Journal-ISO = {Informatics-Basel}, Doc-Delivery-Number = {2K8FF}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000816564200001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000742398700006, Author = {Chen, Cheng-Chung and Chen, Ying}, Title = {The Influence of Message Direction on Attribute Benefit and Purchase Intention Applied to the Logical Design of an AI Chatbot}, Journal = {INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE}, Year = {2021}, Volume = {35}, Number = {15}, Month = {DEC 15}, Abstract = {This study aims to explore the influence of various possible combinations of consumer attribute benefits and the message direction provided by merchants on the final purchase intention of consumers. A two-factor experimental design was used to collect data from Generation Z consumers. Four experimental combination scenarios were designed based on consumer attribute benefits (hedonic or utilitarian) and message direction (positive or negative messages). A total of 160 valid samples were obtained, and the influence of variable-final purchase intention was analyzed. The results showed that the combination of product attributes and message direction has a significant impact on purchase intention and that hedonic products should be recommended to process-benefit consumers through positive messages. However, chatbots should choose utilitarian products and negative messages to effectively improve consumers' purchase intention and willingness. In practical application, by finding out the best correspondence method of message transmission and providing the AI chatbot with a reference for the logical construction of content transmission, the communication efficiency between merchants and consumers can be enhanced, and the scientific and technological service capability of merchants can be improved.}, Publisher = {WORLD SCIENTIFIC PUBL CO PTE LTD}, Address = {5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE}, Type = {Article}, Language = {English}, Affiliation = {Chen, CC (Corresponding Author), Tunghai Univ, Dept Hospitality Management, 1727,Sec 4,Taiwan Blvd, Taichung, Taiwan. Chen, Cheng-Chung; Chen, Ying, Tunghai Univ, Dept Hospitality Management, 1727,Sec 4,Taiwan Blvd, Taichung, Taiwan.}, DOI = {10.1142/S0218001421590540}, Article-Number = {2159054}, ISSN = {0218-0014}, EISSN = {1793-6381}, Keywords = {Attribute benefit; message direction; purchase intention; experimental design research method; AI chatbot}, Keywords-Plus = {CONSUMER; CONSUMPTION; PRODUCTS}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Artificial Intelligence}, Author-Email = {jims@thu.edu.tw bear10051005@gmail.com}, Affiliations = {Tunghai University}, Cited-References = {Ajzen I., 1985, ORG BEHAV HUMAN DECI, V50, P211. Androutsopoulou A, 2019, GOV INFORM Q, V36, P358, DOI 10.1016/j.giq.2018.10.001. {[}Anonymous], 1972, P 3 ANN C ASS CONS R. BABIN BJ, 1994, J CONSUM RES, V20, P644, DOI 10.1086/209376. Bagchi M, 2020, DESIDOC J LIB INF TE, V40, P329, DOI 10.14429/djlit.40.6.15611. Campbell MC, 2003, J CONSUM RES, V30, P292, DOI 10.1086/376800. 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Zhang Y, 1999, J ADVERTISING, V28, P1.}, Number-of-Cited-References = {34}, Times-Cited = {0}, Usage-Count-Last-180-days = {6}, Usage-Count-Since-2013 = {14}, Journal-ISO = {Int. J. Pattern Recognit. Artif. Intell.}, Doc-Delivery-Number = {YG3NH}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000742398700006}, DA = {2023-10-04}, } @article{ WOS:000733667200001, Author = {Ganeshkumar, C. and Jena, Sanjay Kumar and Sivakumar, A. and Nambirajan, T.}, Title = {Artificial intelligence in agricultural value chain: review and future directions}, Journal = {JOURNAL OF AGRIBUSINESS IN DEVELOPING AND EMERGING ECONOMIES}, Year = {2023}, Volume = {13}, Number = {3}, Pages = {379-398}, Month = {MAY 12}, Abstract = {Purpose This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research. Design/methodology/approach The authors systematically collected literature from several databases covering 25 years (1994-2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis. Findings Fifty percent of the reviewed studies were empirical, and 35\% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour. Research limitations/implications The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study. Originality/value Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Review}, Language = {English}, Affiliation = {Ganeshkumar, C (Corresponding Author), Indian Inst Plantat Management, Decis Sci \& Operat Management, Bangalore, Karnataka, India. Ganeshkumar, C., Indian Inst Plantat Management, Decis Sci \& Operat Management, Bangalore, Karnataka, India. Jena, Sanjay Kumar, Indian Inst Management Ahmedabad, Ahmadabad, Gujarat, India. Sivakumar, A., Vellore Inst Technol, VIT Business Sch, Vellore, Tamil Nadu, India. Nambirajan, T., Pondicherry Univ, Management Studies, Pondicherry, India.}, DOI = {10.1108/JADEE-07-2020-0140}, EarlyAccessDate = {DEC 2021}, ISSN = {2044-0839}, EISSN = {2044-0847}, Keywords = {Artificial intelligence; Agricultural value chain; Literature review; Nvivo}, Keywords-Plus = {PRECISION AGRICULTURE; NIR SPECTROSCOPY; ELECTRONIC NOSE; NEURAL-NETWORKS; IMAGE TEXTURE; BIG DATA; SYSTEM; CLASSIFICATION; PERFORMANCE}, Research-Areas = {Agriculture; Business \& Economics}, Web-of-Science-Categories = {Agricultural Economics \& Policy; Economics}, Author-Email = {gcganeshkumar@gmail.com sanjayj@iima.ac.in sivakumar.a@vit.ac.in rtnambirajan@gmail.com}, Affiliations = {Indian Institute of Management (IIM System); Indian Institute of Management Ahmedabad; Vellore Institute of Technology (VIT); VIT Vellore; Pondicherry University}, ResearcherID-Numbers = {Jena, Sanjay Kumar/ACD-9622-2022 Ganeshkumar, C/E-4917-2016}, ORCID-Numbers = {Jena, Sanjay Kumar/0000-0003-3911-8877 Ganeshkumar, C/0000-0002-0913-2849}, Funding-Acknowledgement = {Indian Council of Social Science Research (ICSSR)-Impactful Policy Research in Social Science (IMPRESS) scheme, Government of India {[}P156]}, Funding-Text = {Authors would like to thank the Indian Council of Social Science Research (ICSSR)-Impactful Policy Research in Social Science (IMPRESS) scheme, Government of India, for funding this project (P156).}, Cited-References = {Adarsh A.P.P.M., 2018, INT J TREND SCI RES, V2, P351. 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S. and Estevez, M.}, Title = {Consumers awareness of white-striping as a chicken breast myopathy affects their purchasing decision and emotional responses}, Journal = {LWT-FOOD SCIENCE AND TECHNOLOGY}, Year = {2020}, Volume = {131}, Month = {SEP}, Abstract = {The aim of this study was to evaluate consumers' degree of knowledge, acceptability, and purchase intention of chicken breasts affected by the white striping (WS) myopathy. The emotions evoked in consumers in two different consumption situations (before {[}BI] and after {[}AI] being informed of the WS condition) was also assessed. Raw WS samples presented lower acceptability and purchase intent than N counterparts. In the AI scenario, acceptability of WS samples significantly decreased while consumer's rejection increased found. One fifth of consumers refused to eat WS meat after the report of myopathy. Upon cooking, consumers who decided to taste, detected no differences between WS and N chicken breasts for color, flavor and overall acceptability and the informed situation had a negligible impact. However, the WS samples had higher scores of acceptability for odor and texture parameters compared to the N counterparts. WS myopathy increases the emotions ``interested{''} and ``enthusiastic{''}, although no major differences in the emotional profile were observed. The degree of knowledge about WS myopathy was inversely proportional to the consumer's acceptability and purchase intention of commercial fresh chicken breasts. Further studies are required to confirm this trend in a larger group of population as well as in other countries and cultures.}, Publisher = {ELSEVIER}, Address = {RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}, Type = {Article}, Language = {English}, Affiliation = {Estevez, M (Corresponding Author), Univ Extremadura, Inst Meat \& Meat Prod IPROCAR, Avd Univ Sn, Caceres 10003, Spain. Carvalho, L. M. de; Olegario, L. S.; Madruga, M. S., Univ Fed Paraiba, Dept Food Engn, Postgrad Program Food Sci \& Technol, Joao Pessoa, Paraiba, Brazil. Ventanas, S.; Estevez, M., Univ Extremadura, TECAL Res Grp, Inst Meat \& Meat Prod IPROCAR, Caceres, Spain.}, DOI = {10.1016/j.lwt.2020.109809}, Article-Number = {109809}, ISSN = {0023-6438}, EISSN = {1096-1127}, Keywords = {Muscle defects; Consumer consciousness; Acceptability; Emotions}, Keywords-Plus = {MEAT QUALITY; BROILER; FILLETS; GROWTH; IMPACT}, Research-Areas = {Food Science \& Technology}, Web-of-Science-Categories = {Food Science \& Technology}, Author-Email = {mariovet@unex.es}, Affiliations = {Universidade Federal da Paraiba; Universidad de Extremadura}, ResearcherID-Numbers = {Estevez, Mario/D-6889-2011 Ventanas, Sonia/D-8222-2012 Olegario, Lary S/X-6628-2018 Carvalho, Leila/GLT-9257-2022}, ORCID-Numbers = {Estevez, Mario/0000-0002-8509-2789 Olegario, Lary S/0000-0002-7251-1294 Carvalho, Leila/0000-0002-0057-398X}, Funding-Acknowledgement = {CNPq -Brazilian National Council for Scientific and Technological Development {[}430832/2016-8]; Government of Extremadura (Consejeria de Economia e Infrastructures) {[}IB16043]; European Union {[}IB16043]}, Funding-Text = {The authors acknowledge the CNPq -Brazilian National Council for Scientific and Technological Development (Process number 430832/2016-8). 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Petracci M, 2014, ITAL J ANIM SCI, V13, DOI 10.4081/ijas.2014.3138. Sanchez-Sabate R, 2019, INT J ENV RES PUB HE, V16, DOI 10.3390/ijerph16071220. USDA, 2018, POULTR PROD VAL 2018.}, Number-of-Cited-References = {30}, Times-Cited = {14}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {16}, Journal-ISO = {LWT-Food Sci. Technol.}, Doc-Delivery-Number = {NM0WS}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000567826100009}, DA = {2023-10-04}, } @article{ WOS:000515444000004, Author = {Sohn, Kwonsang and Kwon, Ohbyung}, Title = {Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products}, Journal = {TELEMATICS AND INFORMATICS}, Year = {2020}, Volume = {47}, Month = {APR}, Abstract = {The rapid growth of artificial intelligence (AI) technology has prompted the development of AI-based intelligent products. Accordingly, various technology acceptance theories have been used to explain acceptance of these products. This comparative study determines which models best explain consumer acceptance of AI-based intelligent products and which factors have the greatest impact in terms of purchase intention. We assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Value-based Adoption Model (VAM) using data collected from a survey sample of 378 respondents, modeling user acceptance in terms of behavioral intention to use AI-based intelligent products. In addition, we employed decomposition analysis to compare each factor included in these models in terms of influence on purchase intention. We found that the VAM performed best in modeling user acceptance. Among the various factors, enjoyment was found to influence user purchase intention the most, followed by subjective norms. The findings of this study confirm that acceptance of highly innovative products with minimal practical value, such as AI-based intelligent products, is more influenced by interest in technology than in utilitarian aspects.}, Publisher = {ELSEVIER}, Address = {RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}, Type = {Article}, Language = {English}, Affiliation = {Kwon, O (Corresponding Author), Kyung Hee Univ, Sch Management, Kyungheedae Ro 26, Seoul, South Korea. Sohn, Kwonsang; Kwon, Ohbyung, Kyung Hee Univ, Sch Management, Kyungheedae Ro 26, Seoul, South Korea.}, DOI = {10.1016/j.tele.2019.101324}, Article-Number = {101324}, ISSN = {0736-5853}, Keywords = {AI-based intelligent products; Technology adoption; Purchase intention; Technology acceptance theory; Decomposition analysis}, Keywords-Plus = {VALUE-BASED ADOPTION; PERCEIVED USEFULNESS; INFORMATION-TECHNOLOGY; USER ACCEPTANCE; INITIAL TRUST; MODEL; EASE; CONSUMERS; TAM; SIMULATION}, Research-Areas = {Information Science \& Library Science}, Web-of-Science-Categories = {Information Science \& Library Science}, Author-Email = {miroo1215@khu.ac.kr obkwon@khu.ac.kr}, Affiliations = {Kyung Hee University}, ResearcherID-Numbers = {Sohn, Kwonsang/AAV-2594-2020}, ORCID-Numbers = {Sohn, Kwonsang/0000-0003-0692-0425}, Funding-Acknowledgement = {Ministry of Education of the Republic of Korea; National Research Foundation of Korea {[}NRF-2017S1A3A2066740]; National Research Foundation of Korea {[}2017S1A3A2066740] Funding Source: Korea Institute of Science \& Technology Information (KISTI), National Science \& Technology Information Service (NTIS)}, Funding-Text = {This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A3A2066740).}, Cited-References = {ADAMS DA, 1992, MIS QUART, V16, P227, DOI 10.2307/249577. 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Wu B, 2017, COMPUT HUM BEHAV, V67, P221, DOI 10.1016/j.chb.2016.10.028. Yang H, 2017, IND MANAGE DATA SYST, V117, P68, DOI 10.1108/IMDS-01-2016-0017. Yang K, 2009, J RETAIL CONSUM SERV, V16, P502, DOI 10.1016/j.jretconser.2009.08.005. Cabada RZ, 2018, TELEMAT INFORM, V35, P611, DOI 10.1016/j.tele.2017.03.005. Zhang T, 2007, J BUS RES, V60, P912, DOI 10.1016/j.jbusres.2007.02.006.}, Number-of-Cited-References = {73}, Times-Cited = {130}, Usage-Count-Last-180-days = {114}, Usage-Count-Since-2013 = {426}, Journal-ISO = {Telemat. Inform.}, Doc-Delivery-Number = {KO3JF}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000515444000004}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:000663722100004, Author = {Pelau, Corina and Dabija, Dan-Cristian and Ene, Irina}, Title = {What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry}, Journal = {COMPUTERS IN HUMAN BEHAVIOR}, Year = {2021}, Volume = {122}, Month = {SEP}, Abstract = {Intelligent AI devices have become a common presence in the business landscape, offering a wide range of services, from the medical sector to the hospitality industry. From an organizational perspective, AI devices have several advantages, by performing certain tasks quicker and more accurately in comparison to humans while at the same time being more cost-efficient. However, in order to maintain the high standards of a brand, they have to be accepted by consumers and deliver socially adequate performance. Therefore, it is important to determine the characteristics of AI devices which make them accepted and trusted by consumers. Based on the Computers as Social Actors (CASA) Theory, we have researched on the role of psychological anthropomorphic characteristics, perceived empathy, and interaction quality in the acceptance of AI devices in the service industry. The results show that anthropomorphic characteristics alone do not influence acceptance and trust towards AI devices. However, both perceived empathy and interaction quality mediate the relation between anthropomorphic characteristics and acceptance. A human-like AI device has higher acceptance when it has the ability to show empathy and interaction in relation to the human consumer. This result reveals the importance of developing forms of strong intelligence and empathetic behaviour in service robots and AI devices.}, Publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Pelau, C (Corresponding Author), Bucharest Univ Econ Studies, Bucharest, Romania. Pelau, Corina, Bucharest Univ Econ Studies, Fac Business Adm Foreign Languages, Calea Grivitei 2-2A,Sect 1, Bucharest, Romania. Dabija, Dan-Cristian, Babes Bolyai Univ Cluj Napoca, Fac Econ \& Business Adm, Str Teodor Mihali 58-60, Cluj Napoca, Romania. Ene, Irina, Bucharest Univ Econ Studies, Doctoral Sch Business Adm, Piata Romana 6, Bucharest, Romania.}, DOI = {10.1016/j.chb.2021.106855}, EarlyAccessDate = {MAY 2021}, Article-Number = {106855}, ISSN = {0747-5632}, EISSN = {1873-7692}, Keywords = {Artificial intelligence; Consumer behaviour; AI device; Anthropomorphism; Human-AI interaction; Computers as social actors; Human-computer interaction; Robots}, Keywords-Plus = {CONVERSATIONAL AGENT; BRAND; SALESPERSON; IMPACT; ROBOTS; ANTECEDENTS; PERFORMANCE; TECHNOLOGY; EXPERIENCE; MODEL}, Research-Areas = {Psychology}, Web-of-Science-Categories = {Psychology, Multidisciplinary; Psychology, Experimental}, Author-Email = {corina.pelau@fabiz.ase.ro dan.dabija@ubbcluj.ro ene1irina13@stud.ase.ro}, Affiliations = {Bucharest University of Economic Studies; Babes Bolyai University from Cluj; Bucharest University of Economic Studies}, ResearcherID-Numbers = {Dabija, Dan-Cristian/I-8101-2012 Pelau, Corina/F-4663-2015}, ORCID-Numbers = {Dabija, Dan-Cristian/0000-0002-8265-175X Pelau, Corina/0000-0002-6139-028X}, Cited-References = {Aggarwal P, 2012, J CONSUM RES, V39, P307, DOI 10.1086/662614. 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Sorell T, 2014, ETHICS INF TECHNOL, V16, P183, DOI 10.1007/s10676-014-9344-7. van Doorn J, 2017, J SERV RES-US, V20, P43, DOI 10.1177/1094670516679272. Venkatesh V, 2012, MIS QUART, V36, P157. Vinas S, 2021, BUSINESS INSIDER ESP. Wan Jing, 2015, STRONG BRANDS STRONG, P119. Wang WH, 2017, COMPUT HUM BEHAV, V68, P334, DOI 10.1016/j.chb.2016.11.022. Weisz E, 2021, TRENDS COGN SCI, V25, P213, DOI 10.1016/j.tics.2020.12.002. Wieseke J, 2012, J SERV RES-US, V15, P316, DOI 10.1177/1094670512439743.}, Number-of-Cited-References = {64}, Times-Cited = {123}, Usage-Count-Last-180-days = {174}, Usage-Count-Since-2013 = {536}, Journal-ISO = {Comput. Hum. Behav.}, Doc-Delivery-Number = {SV3KT}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000663722100004}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:000639514600004, Author = {Balakrishnan, Janarthanan and Dwivedi, Yogesh K.}, Title = {Conversational commerce: entering the next stage of AI-powered digital assistants}, Journal = {ANNALS OF OPERATIONS RESEARCH}, Year = {2021}, Month = {2021 APR 12}, Abstract = {Digital assistant is a recent advancement benefited through data-driven innovation. Though digital assistants have become an integral member of user conversations, but there is no theory that relates user perception towards this AI powered technology. The purpose of the research is to investigate the role of technology attitude and AI attributes in enhancing purchase intention through digital assistants. A conceptual model is proposed after identifying three major AI factors namely, perceived anthropomorphism, perceived intelligence, and perceived animacy. To test the model, the study employed structural equation modeling using 440 sample. The results indicated that perceived anthropomorphism plays the most significant role in building a positive attitude and purchase intention through digital assistants. Though the study is built using technology-related variables, the hypotheses are proposed based on various psychology-related theories such as uncanny valley theory, the theory of mind, developmental psychology, and cognitive psychology theory. The study's theoretical contributions are discussed within the scope of these theories. Besides the theoretical contribution, the study also offers illuminating practical implications for developers and marketers' benefit.}, Publisher = {SPRINGER}, Address = {VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Dwivedi, YK (Corresponding Author), Swansea Univ, Sch Management, Emerging Markets Res Ctr EMaRC, Bay Campus,Fabian Way, Swansea SA1 8EN, W Glam, Wales. Balakrishnan, Janarthanan, Natl Inst Technol, Dept Management Studies, Tiruchirappalli, Tamil Nadu, India. Dwivedi, Yogesh K., Swansea Univ, Sch Management, Emerging Markets Res Ctr EMaRC, Bay Campus,Fabian Way, Swansea SA1 8EN, W Glam, Wales.}, DOI = {10.1007/s10479-021-04049-5}, EarlyAccessDate = {APR 2021}, ISSN = {0254-5330}, EISSN = {1572-9338}, Keywords = {Anthropomorphism; Intelligence; Animacy; Artificial intelligence; Digital assistants; Purchase intention}, Keywords-Plus = {TECHNOLOGY ACCEPTANCE MODEL; BIG DATA ANALYTICS; ARTIFICIAL-INTELLIGENCE; PURCHASE INTENTION; VOICE ASSISTANTS; USER ACCEPTANCE; PERCEIVED INTELLIGENCE; CONTINUANCE INTENTION; PREDICTIVE ANALYTICS; CONSUMERS ACCEPTANCE}, Research-Areas = {Operations Research \& Management Science}, Web-of-Science-Categories = {Operations Research \& Management Science}, Author-Email = {reachjanarthanan@gmail.com ykdwivedi@gmail.com}, Affiliations = {National Institute of Technology (NIT System); National Institute of Technology Tiruchirappalli; Swansea University}, ResearcherID-Numbers = {Dwivedi, Yogesh Kumar/A-5362-2008 Balakrishnan, Janarthanan/H-9687-2012}, ORCID-Numbers = {Dwivedi, Yogesh Kumar/0000-0002-5547-9990 Balakrishnan, Janarthanan/0000-0003-2456-2617}, Cited-References = {Aggarwal P, 2012, J CONSUM RES, V39, P307, DOI 10.1086/662614. 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However, few studies have focused on studying the differences in the effects of types of customer service on customer purchase intentions. Based on service encounter theory and superposition theory, we designed two shopping experiments to capture customers' thoughts and feelings, in order to explore the differences in the effects of three different types of online customer service (AI customer service, manual customer service, and human-machine collaboration customer service) on customer purchase intention, and analyses the superposition effect of human-machine collaboration customer service. The results show that the consumer's perceived service quality positively influences the customer's purchase intention, and plays a mediating role in the effect of different types of online customer service on customer purchase intention; the product type plays a moderating role in the relationship between online customer service and customer purchase intention, and human-machine collaboration customer service has a superposition effect. This study helped to deepen the understanding of AI developers and e-commerce platforms regarding the application of AI in online business service, and provides reference suggestions for the formulation of more perfect business service strategies.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Zhu, W (Corresponding Author), Jiangxi Normal Univ, Res Ctr Management Sci \& Engn, Nanchang 330022, Jiangxi, Peoples R China. Zhu, W (Corresponding Author), Jiangxi Normal Univ, Sch Software, Nanchang 330022, Jiangxi, Peoples R China. Qin, Min; Zhu, Wei, Jiangxi Normal Univ, Res Ctr Management Sci \& Engn, Nanchang 330022, Jiangxi, Peoples R China. Qin, Min; Zhu, Wei; Zhao, Shiyue; Zhao, Yu, Jiangxi Normal Univ, Sch Software, Nanchang 330022, Jiangxi, Peoples R China.}, DOI = {10.3390/su14073974}, Article-Number = {3974}, EISSN = {2071-1050}, Keywords = {artificial intelligence; service encounter theory; perceived service quality; superposition effect; customer purchase intention; e-commerce}, Keywords-Plus = {MODEL; TECHNOLOGY; SUPERPOSITION; SATISFACTION; INFORMATION; QUALITY; SEARCH; DESIGN; CUES}, Research-Areas = {Science \& Technology - Other Topics; Environmental Sciences \& Ecology}, Web-of-Science-Categories = {Green \& Sustainable Science \& Technology; Environmental Sciences; Environmental Studies}, Author-Email = {minqin@jxnu.edu.cn zhuwei2020@jxnu.edu.cn zhaoshiyue0201@163.com zhaoyu021711@163.com}, Affiliations = {Jiangxi Normal University; Jiangxi Normal University}, ResearcherID-Numbers = {Zhao, Shiyue/IXW-7626-2023 }, ORCID-Numbers = {Zhu, Wei/0000-0002-9624-0724}, Funding-Acknowledgement = {National Natural Science Foundation of China {[}71762018]; Jiangxi University Humanities and Social Science Research Project {[}GL20132]; Jiangxi Province Graduate Education Reform Research Project Key Project {[}JXYJG-2020-041]}, Funding-Text = {This research was supported by the National Natural Science Foundation of China (Grant No. 71762018), Jiangxi University Humanities and Social Science Research Project (Grant No. GL20132) and Jiangxi Province Graduate Education Reform Research Project Key Project (Grant No. JXYJG-2020-041).}, Cited-References = {Adam M, 2021, ELECTRON MARK, V31, P427, DOI 10.1007/s12525-020-00414-7. 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Zhu ZX, 2022, ASLIB J INFORM MANAG, V74, P265, DOI 10.1108/AJIM-02-2021-0054.}, Number-of-Cited-References = {71}, Times-Cited = {4}, Usage-Count-Last-180-days = {29}, Usage-Count-Since-2013 = {113}, Journal-ISO = {Sustainability}, Doc-Delivery-Number = {0K4BX}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000780736500001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:001011635800001, Author = {Zhang, Yaqiong and Wang, Shifu}, Title = {The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types}, Journal = {JOURNAL OF RETAILING AND CONSUMER SERVICES}, Year = {2023}, Volume = {74}, Month = {SEP}, Abstract = {While artificial intelligence products are widely used in the market, their anthropomorphic appearance design is becoming a frontier issue in product strategy and consumer behavior research. The aim of this study was to investigate the influence of anthropomorphic appearance on consumer behavior and brand evaluation under different AI product types. It was conducted in China, a new but rapidly-growing country in the field of Internet, AI technology and AI product consumption. This study conducted four situational experiments with a 2 (anthropomorphic design: anthropomorphic vs. non-anthropomorphic) x 2 (product type: hedonic vs. utilitarian) between subjects' experimental design. Data was collected from 1172 Chinese ``Digital Natives{''} by using a structured questionnaire. The findings revealed that for hedonic AI products, anthropomorphic appearance improves consumers' purchase intention and brand evaluation through perceived entertainment, and intelligence level significantly moderates the mediating effect of perceived entertainment; while for practical AI products, anthropomorphic appearance improves consumers' purchase intention and brand evaluation through perceived usefulness, and intelligence level does not significantly moderate the mediating effect of perceived usefulness. There is no significant moderating effect of intelligence level on perceived usefulness. The study contributes to development and validation of a more comprehensive understanding and theoretical foundation of anthropomorphism, and furthermore explores the impact of anthropomorphic appearance on consumer behavior and brand evaluation under different AI product types. This study also provides insights for companies to apply anthropomorphic strategies.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Zhang, YQ (Corresponding Author), China Univ Polit Sci \& Law, Business Sch, Beijing, Peoples R China. Zhang, Yaqiong; Wang, Shifu, China Univ Polit Sci \& Law, Business Sch, Beijing, Peoples R China.}, DOI = {10.1016/j.jretconser.2023.103432}, EarlyAccessDate = {JUN 2023}, Article-Number = {103432}, ISSN = {0969-6989}, EISSN = {1873-1384}, Keywords = {Artificial intelligence; Product anthropomorphism; Consumer perception; Purchase intention; Brand evaluation}, Keywords-Plus = {PURCHASE INTENTION; MODERATING ROLE; REALITY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {zyqqianqian@hotmail.com 1316752156@qq.com}, Affiliations = {China University of Political Science \& Law}, Cited-References = {Akcayir M, 2016, COMPUT HUM BEHAV, V60, P435, DOI 10.1016/j.chb.2016.02.089. Alzayat A, 2021, J BUS RES, V130, P348, DOI 10.1016/j.jbusres.2021.03.017. Amatulli C, 2020, PSYCHOL MARKET, V37, P523, DOI 10.1002/mar.21320. {[}Anonymous], 2016, MANAG REV. Anshu K, 2022, J RETAIL CONSUM SERV, V64, DOI 10.1016/j.jretconser.2021.102798. 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Zhao TY, 2020, ASIA PAC J MARKET LO, V32, P1343, DOI 10.1108/APJML-02-2019-0072.}, Number-of-Cited-References = {74}, Times-Cited = {0}, Usage-Count-Last-180-days = {39}, Usage-Count-Since-2013 = {39}, Journal-ISO = {J. Retail. Consum. Serv.}, Doc-Delivery-Number = {J7UM0}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:001011635800001}, DA = {2023-10-04}, } @article{ WOS:000814582700001, Author = {Jiang, Hua and Cheng, Yang and Yang, Jeongwon and Gao, Shanbing}, Title = {AI-powered chatbot communication with customers: Dialogic interactions, satisfaction, engagement, and customer behavior}, Journal = {COMPUTERS IN HUMAN BEHAVIOR}, Year = {2022}, Volume = {134}, Month = {SEP}, Abstract = {The present study is grounded in social exchange theory and resource exchange theory. By exploring customers' satisfaction with chatbot services and their social media engagement, it examined the effects of responsiveness and a conversational tone in dialogic chatbot communication on customers. To test the proposed mediation model, we surveyed a representative sample of customers (N = 965) living in the U.S. After examining the validity and reliability of our measurement model, we tested the hypothesized model using structural equation modeling (SEM) procedures. All proposed hypotheses were supported, indicating the significant direct effects of (1) responsiveness and a conversational tone on customers' satisfaction with chatbot services, (2) customers' chatbot use satisfaction on social media engagement, (3) customers' social media engagement on price premium and purchase intention, and (4) purchase intention on price premium. In addition, we examined satisfaction, social media engagement, and purchase intention as significant mediators in the proposed model. Theoretical and practical implications of the study were then discussed.}, Publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Gao, SB (Corresponding Author), Nanjing Normal Univ, Sch Journalism \& Commun, 122 Ninghai Rd, Nanjing, Jiangsu, Peoples R China. Jiang, Hua; Yang, Jeongwon, Syracuse Univ, SI Newhouse Sch Publ Commun, 215 Univ PL, Syracuse, NY 13244 USA. Cheng, Yang, North Carolina State Univ, Dept Commun, 2301 Hillsborough St,Winston Hall,Box 8104, Raleigh, NC 27695 USA. Gao, Shanbing, Nanjing Normal Univ, Sch Journalism \& Commun, 122 Ninghai Rd, Nanjing, Jiangsu, Peoples R China.}, DOI = {10.1016/j.chb.2022.107329}, EarlyAccessDate = {JUN 2022}, Article-Number = {107329}, ISSN = {0747-5632}, EISSN = {1873-7692}, Keywords = {Dialogic chatbot communication; Engagement-facilitating AI technologies; Chatbot use satisfaction; Social media engagement; Purchase intention; Price premium}, Keywords-Plus = {CONSUMER BRAND ENGAGEMENT; SERVICE-DOMINANT LOGIC; GROUP BUYING INTENTION; WILLINGNESS-TO-PAY; VALUE CO-CREATION; SOCIAL MEDIA; CONVERSATIONAL AGENT; PURCHASE INTENTION; TECHNOLOGY ACCEPTANCE; COMMUNITY ENGAGEMENT}, Research-Areas = {Psychology}, Web-of-Science-Categories = {Psychology, Multidisciplinary; Psychology, Experimental}, Author-Email = {hjiang07@syr.edu ycheng20@ncsu.edu jyang97@syre.du gao@njnu.edu.cn}, Affiliations = {Syracuse University; North Carolina State University; Nanjing Normal University}, ResearcherID-Numbers = {yang, Jeongwon/GXG-1323-2022}, Cited-References = {Aaker DA, 1996, CALIF MANAGE REV, V38, P102, DOI 10.2307/41165845. 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Yang SU, 2009, J PUBLIC RELAT RES, V21, P341, DOI 10.1080/10627260802640773. Yazdanparast A, 2016, YOUNG CONSUM, V17, P243, DOI 10.1108/YC-03-2016-00590. Yoo B, 2001, J BUS RES, V52, P1, DOI 10.1016/S0148-2963(99)00098-3. Youn S, 2021, COMPUT HUM BEHAV, V119, DOI 10.1016/j.chb.2021.106721. Zaglia ME, 2013, J BUS RES, V66, P216, DOI 10.1016/j.jbusres.2012.07.015. Zhang B, 2018, J CLEAN PROD, V197, P1498, DOI 10.1016/j.jclepro.2018.06.273. Zhu DH, 2016, J RETAIL CONSUM SERV, V31, P287, DOI 10.1016/j.jretconser.2016.04.013.}, Number-of-Cited-References = {163}, Times-Cited = {14}, Usage-Count-Last-180-days = {100}, Usage-Count-Since-2013 = {249}, Journal-ISO = {Comput. Hum. Behav.}, Doc-Delivery-Number = {2H9BR}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000814582700001}, DA = {2023-10-04}, } @article{ WOS:000909819800001, Author = {Gu, Li and Li, Yong}, Title = {Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention}, Journal = {FRONTIERS IN PSYCHOLOGY}, Year = {2022}, Volume = {13}, Month = {AUG 5}, Abstract = {Investigating how people respond to and view AI-created artworks is becoming increasingly crucial as the technology's current application spreads due to its affordability and accessibility. This study examined how AI art alters people's evaluation, purchase intention, and collection intention toward Chinese-style and Western-style paintings, and whether art expertise plays a role. Study 1 recruited participants without professional art experience (non-experts) and found that those who made the paintings would not change their liking rating, purchase intention, and collection intention. In addition, they showed ingroup preference, favoring Chinese-style relative to Western-style paintings, in line with previous evidence on cultural preference in empirical aesthetics. Study 2 further investigated the modulation effect of art expertise. Art experts evaluated less favorably (less liking, lower purchase, and collection intentions) AI-generated paintings relative to artist-made paintings, while non-experts showed no preference. There was also an interaction effect between the author and the art expertise and interaction between the painting style and the art expertise. Collectively, the findings in this study showed that who made the art matters for experts and that the painting style affects aesthetic evaluation and ultimate reception of it. These results would also provide implications for AI-art practitioners.}, Publisher = {FRONTIERS MEDIA SA}, Address = {AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Gu, L; Li, Y (Corresponding Author), Guangzhou Acad Fine Arts, Guangzhou, Peoples R China. Gu, Li; Li, Yong, Guangzhou Acad Fine Arts, Guangzhou, Peoples R China.}, DOI = {10.3389/fpsyg.2022.941163}, Article-Number = {941163}, ISSN = {1664-1078}, Keywords = {artificial intelligence; painting style; art expertise; framing effect; liking; purchase intention}, Keywords-Plus = {ART EXPERTISE; JAPANESE}, Research-Areas = {Psychology}, Web-of-Science-Categories = {Psychology, Multidisciplinary}, Author-Email = {guli7@mail2.sysu.edu.cn 412346385@qq.com}, Affiliations = {Guangzhou Academy of Fine Arts}, Funding-Acknowledgement = {Guangdong Basic and Applied Basic Research Foundation {[}2020A1515010610]; Art Project of the National Social Science Foundation of China {[}19BG110]}, Funding-Text = {This research was supported by the Guangdong Basic and Applied Basic Research Foundation (2020A1515010610) to LG and the Art Project of the National Social Science Foundation of China (19BG110) to YL.}, Cited-References = {Bao Y, 2016, FRONT PSYCHOL, V7, DOI 10.3389/fpsyg.2016.01596. 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Mastandrea S, 2016, FRONT HUM NEUROSCI, V10, DOI 10.3389/fnhum.2016.00201. Moffat D. C., 2006, ASSESSMENT, V13, P1. Mullennix JW, 2018, PERCEPTION, V47, P359, DOI 10.1177/0301006617752314. Ploin A., 2022, REPORTFROM CREATIVE. Reymond C, 2020, FRONT PSYCHOL, V11, DOI 10.3389/fpsyg.2020.615575. Silveira S, 2015, FRONT HUM NEUROSCI, V9, DOI 10.3389/fnhum.2015.00528. Yang TX, 2019, FRONT PSYCHOL, V10, DOI 10.3389/fpsyg.2019.00798.}, Number-of-Cited-References = {35}, Times-Cited = {0}, Usage-Count-Last-180-days = {38}, Usage-Count-Since-2013 = {80}, Journal-ISO = {Front. Psychol.}, Doc-Delivery-Number = {7R1DY}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000909819800001}, OA = {Green Published, gold}, DA = {2023-10-04}, } @article{ WOS:000952327400001, Author = {Malhotra, Gunjan and Ramalingam, Mahesh}, Title = {Perceived anthropomorphism and purchase intention using artificial intelligence technology: examining the moderated effect of trust}, Journal = {JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT}, Year = {2023}, Month = {2023 MAR 28}, Abstract = {PurposeThis study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.Design/methodology/approachThe study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.FindingsThe results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.Originality/valueThe study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Malhotra, G (Corresponding Author), Inst Management Technol Ghaziabad, Dept Operat Management, Ghaziabad, India. Malhotra, Gunjan, Inst Management Technol Ghaziabad, Dept Operat Management, Ghaziabad, India. Ramalingam, Mahesh, Inst Management Technol Hyderabad, Dept IT \& Analyt, Hyderabad, India.}, DOI = {10.1108/JEIM-09-2022-0316}, EarlyAccessDate = {MAR 2023}, ISSN = {1741-0398}, EISSN = {1758-7409}, Keywords = {Perceived anthropomorphism; Perceived animacy; Perceived intelligence; Purchase intention; Trust; Artificial intelligence}, Keywords-Plus = {MEDIA RICHNESS; BEHAVIORAL-RESEARCH; E-COMMERCE; CONSUMERS; ANIMACY; BRAND; ACCEPTANCE; CUES}, Research-Areas = {Computer Science; Information Science \& Library Science; Business \& Economics}, Web-of-Science-Categories = {Computer Science, Interdisciplinary Applications; Information Science \& Library Science; Management}, Author-Email = {mailforgunjan@gmail.com mahesh@imthyderabad.edu.in}, Affiliations = {Institute of Management Technology, Ghaziabad}, ORCID-Numbers = {Malhotra, Gunjan/0000-0002-6508-8002}, Cited-References = {Aggarwal P, 2007, J CONSUM RES, V34, P468, DOI 10.1086/518544. 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Manag.}, Doc-Delivery-Number = {A0SY5}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000952327400001}, DA = {2023-10-04}, } @article{ WOS:000572369400001, Author = {Sohn, Kwonsang and Sung, Christine Eunyoung and Koo, Gukwon and Kwon, Ohbyung}, Title = {Artificial intelligence in the fashion industry: consumer responses to generative adversarial network (GAN) technology}, Journal = {INTERNATIONAL JOURNAL OF RETAIL \& DISTRIBUTION MANAGEMENT}, Year = {2021}, Volume = {49}, Number = {1}, Pages = {61-80}, Month = {JAN 11}, Abstract = {Purpose This study examines consumers' evaluations of product consumption values, purchase intentions and willingness to pay for fashion products designed using generative adversarial network (GAN), an artificial intelligence technology. This research investigates differences between consumers' evaluations of a GAN-generated product and a non-GAN-generated product and tests whether disclosing the use of GAN technology affects consumers' evaluations. Design/methodology/approach Sample products were developed as experimental stimuli using cycleGAN. Data were collected from 163 members of Generation Y. Participants were assigned to one of the three experimental conditions (i.e. non-GAN-generated images, GAN-generated images with disclosure and GAN-generated images without disclosure). Regression analysis and ANOVA were used to test the hypotheses. Findings Functional, social and epistemic consumption values positively affect willingness to pay in the GAN-generated products. Relative to non-GAN-generated products, willingness to pay is significantly higher for GAN-generated products. Moreover, evaluations of functional value, emotional value and willingness to pay are highest when GAN technology is used, but not disclosed. Originality/value This study evaluates the utility of GANs from consumers' perspective based on the perceived value of GAN-generated product designs. Findings have practical implications for firms that are considering using GANs to develop products for the retail fashion market.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Kwon, O (Corresponding Author), Kyung Hee Univ, Sch Management, Seoul, South Korea. Sohn, Kwonsang; Koo, Gukwon; Kwon, Ohbyung, Kyung Hee Univ, Sch Management, Seoul, South Korea. Sung, Christine Eunyoung, Montana State Univ, Jake Jabs Coll Business \& Entrepreneurship, Bozeman, MT 59717 USA.}, DOI = {10.1108/IJRDM-03-2020-0091}, EarlyAccessDate = {SEP 2020}, ISSN = {0959-0552}, EISSN = {1758-6690}, Keywords = {Artificial intelligence (AI); Generative adversarial networks (GANs); Consumption value theory; AI aversion; Fashion consumer behaviour}, Keywords-Plus = {DECISION-MAKING; PERCEIVED VALUE; DESIGN; CONSUMPTION; VALUES; DETERMINANTS; INFORMATION; PERCEPTIONS; BEHAVIOR; MODEL}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, Author-Email = {miroo1215@khu.ac.kr Christinemsu.sung@gmail.com qas6125@khu.ac.kr obkwon@khu.ac.kr}, Affiliations = {Kyung Hee University; Montana State University System; Montana State University Bozeman}, ResearcherID-Numbers = {Sohn, Kwonsang/AAV-2594-2020}, ORCID-Numbers = {Sohn, Kwonsang/0000-0003-0692-0425}, Funding-Acknowledgement = {Ministry of Education of the Republic of Korea; National Research Foundation of Korea {[}NRF-2017S1A3A2066740]; National Research Foundation of Korea {[}2017S1A3A2066740] Funding Source: Korea Institute of Science \& Technology Information (KISTI), National Science \& Technology Information Service (NTIS)}, Funding-Text = {This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A3A2066740).}, Cited-References = {Aghazadeh H., 2014, NEW MARK RES J, V3, P221. 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Zhu SZ, 2017, IEEE I CONF COMP VIS, P1689, DOI 10.1109/ICCV.2017.186. 박은희, 2012, {[}Journal of Fashion Business, 패션 비즈니스], V16, P109.}, Number-of-Cited-References = {105}, Times-Cited = {11}, Usage-Count-Last-180-days = {30}, Usage-Count-Since-2013 = {118}, Journal-ISO = {Int. J. Retail Distrib. Manag.}, Doc-Delivery-Number = {PM1TF}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000572369400001}, DA = {2023-10-04}, } @article{ WOS:000945002500001, Author = {Kautish, Pradeep and Purohit, Sonal and Filieri, Raffaele and Dwivedi, Yogesh K.}, Title = {Examining the role of consumer motivations to use voice assistants for fashion shopping: The mediating role of awe experience and eWOM}, Journal = {TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE}, Year = {2023}, Volume = {190}, Month = {MAY}, Abstract = {Artificial intelligence-enabled voice assistant services have received notable scholarly attention. Fashion retailers offer AI-based voice assistants to facilitate online shoppers. However, the consumer motivations to use digital voice assistants and their effect on the purchase intentions of online fashion shoppers are unexplored. To bridge this literature gap, this study presents a unique theoretical model grounded in the consumer innovativeness concept, broaden-and-built theory, and stimulus-organism-response model to explore the effect of motivated consumer innovativeness to use digital voice assistants on purchase intention and awe experience of online shoppers. The study used data collected from 538 users of digital voice assistants for online shopping of fashion products. Structural equation modeling analysis revealed that the functional, hedonic, social, and cognitive motivated consumer innovativeness for using voice assistants affects purchase intention and awe experience. Further, the awe experience mediates the relationship between motivated consumer innovativeness and purchase intention; and electronic word-of-mouth mediates the relationship between awe experience and purchase intention. The study theoretically contributes to the extant literature on consumer innovativeness, AI-based voice assistants, and fashion shopping. The findings offer insights to fashion retailers for improved use of voice as-sistants by online shoppers.}, Publisher = {ELSEVIER SCIENCE INC}, Address = {STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA}, Type = {Article}, Language = {English}, Affiliation = {Dwivedi, YK (Corresponding Author), Swansea Univ, Sch Management, Digital Futures Sustainable Business \& Soc Res Grp, Bay Campus,Fabian Bay, Swansea SA1 8EN, Wales. Kautish, Pradeep, Nirma Univ, Inst Management, Dept Mkt, Ahmadabad, Gujarat, India. Purohit, Sonal, Mudra Inst Commun, Ahmadabad, Gujarat, India. Filieri, Raffaele, Audencia Business Sch, Dept Mkt, 8 Route Jonelie re, F-44312 Nantes, France. Dwivedi, Yogesh K., Swansea Univ, Sch Management, Digital Futures Sustainable Business \& Soc Res Grp, Bay Campus,Fabian Bay, Swansea SA1 8EN, Wales. Dwivedi, Yogesh K., Pune \& Symbiosis Int Univ, Symbiosis Inst Business Management, Dept Management, Pune, Maharashtra, India.}, DOI = {10.1016/j.techfore.2023.122407}, EarlyAccessDate = {FEB 2023}, Article-Number = {122407}, ISSN = {0040-1625}, EISSN = {1873-5509}, Keywords = {AI-enabled services; Voice assistants; Motivated consumer innovativeness; Awe experience; eWOM; Purchase intentions}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE; VIRTUAL-REALITY; CONTINUANCE INTENTION; PERCEIVED VALUE; BUILD THEORY; INNOVATIVENESS; ADOPTION; TECHNOLOGY; ACCEPTANCE; ENGAGEMENT}, Research-Areas = {Business \& Economics; Public Administration}, Web-of-Science-Categories = {Business; Regional \& Urban Planning}, Author-Email = {pradeep.kautish@nirmauni.ac.in sonal.purohit@micamail.in raffaele.filieri@audencia.com y.k.dwivedi@swansea.ac.uk}, Affiliations = {Nirma University; MICA; Audencia; Swansea University; Symbiosis International University; Symbiosis Institute of Business Management (SIBM) Pune}, ResearcherID-Numbers = {Kautish, Pradeep/E-3516-2018 Filieri, Raffaele/H-4945-2019 Dwivedi, Yogesh Kumar/A-5362-2008 }, ORCID-Numbers = {Kautish, Pradeep/0000-0002-2908-6720 Filieri, Raffaele/0000-0002-3534-8547 Dwivedi, Yogesh Kumar/0000-0002-5547-9990 Purohit, Sonal/0000-0002-3827-1266}, Cited-References = {Aeschlimann S, 2020, COMPUT HUM BEHAV, V112, DOI 10.1016/j.chb.2020.106466. 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Chang.}, Doc-Delivery-Number = {9Q5KK}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000945002500001}, OA = {hybrid, Green Published}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:000593042200024, Author = {Waliszewski, Krzysztof and Warchlewska, Anna}, Title = {ATTITUDES TOWARDS ARTIFICIAL INTELLIGENCE IN THE AREA OF PERSONAL FINANCIAL PLANNING: A CASE STUDY OF SELECTED COUNTRIES}, Journal = {ENTREPRENEURSHIP AND SUSTAINABILITY ISSUES}, Year = {2020}, Volume = {8}, Number = {2}, Pages = {399-420}, Month = {DEC}, Abstract = {The financial sector's focus on simplifying decision-making processes, maximally shortening procedures via cooperation with the fintech industry, robotisation and the use of artificial intelligence are a response to market needs and becoming an important element of how financial service groups compete on the market. The theory of consumer behaviour assumes that consumers have needs that they will hierarchise, and that they will make choices to maximise their own satisfaction. The purpose of the article is to diagnose the sociological and economic determinants underlying consumer satisfaction in terms of planning personal finances using modern technologies. Comparisons of international data were conducted via quantitative analysis of robo-advice using Mann-Whitney U tests, the Chi-square test and Spearman's rho correlation. The survey results show that the majority of socioeconomic characteristics of households are statistically significant when considering satisfaction with robo-advisory financial services and spending analysis, as well as with artificial intelligence suggesting improvements. This study is a contribution to the literature on consumer behaviour in the modern world.}, Publisher = {ENTERPRENEURSHIP \& SUSTAINABILITY CENTER}, Address = {M K CIURLIONIO STR 86A, VILNUS, 03100, LITHUANIA}, Type = {Article}, Language = {English}, Affiliation = {Waliszewski, K (Corresponding Author), Poznan Univ Econ \& Business, Al Niepodleglosci 10, PL-61875 Poznan, Poland. Waliszewski, Krzysztof; Warchlewska, Anna, Poznan Univ Econ \& Business, Al Niepodleglosci 10, PL-61875 Poznan, Poland.}, DOI = {10.9770/jesi.2020.8.2(24)}, ISSN = {2345-0282}, Keywords = {modern financial technologies; personal finance management; robo-advice; personal financial planning}, Keywords-Plus = {SELF-SERVICE TECHNOLOGY; ROBO-ADVISERS; CUSTOMER SATISFACTION; DETERMINANTS; INVESTMENT; ADOPTION}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {krzysztof.waliszewski@ue.poznan.pl anna.warchlewska@ue.poznan.pl}, Affiliations = {Poznan University of Economics \& Business}, ResearcherID-Numbers = {Warchlewska, Anna/AAK-5347-2021 Waliszewski, Krzysztof/AAV-4347-2020}, ORCID-Numbers = {Warchlewska, Anna/0000-0003-0142-7877 Waliszewski, Krzysztof/0000-0003-4239-5875}, Funding-Acknowledgement = {Regional Initiative for Excellence programme of the Minister of Science and Higher Education of Poland {[}004/RID/2018/19]}, Funding-Text = {The project was financed within the Regional Initiative for Excellence programme of the Minister of Science and Higher Education of Poland, years 2019-2022, grant no. 004/RID/2018/19, financing 3,000,000 PLN.}, Cited-References = {ANAND P, 1990, J MARKETING RES, V27, P345, DOI 10.2307/3172591. {[}Anonymous], 2018, DIGITAL HUMAN 4 REVO. {[}Anonymous], 2016, J INNOVATION MGMT. 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SHETH JN, 1991, J BUS RES, V22, P159, DOI 10.1016/0148-2963(91)90050-8. Statista, 2019, ROB ADV WORLDW REP. Swiecka B, 2020, SUSTAINABILITY-BASEL, V12, DOI 10.3390/su12020700. Taillon BJ, 2019, J STRATEG MARK, V27, P268, DOI 10.1080/0965254X.2017.1411387. Tanda A, 2019, PALGR MAC STUD BANK, P1, DOI 10.1007/978-3-030-22426-4. Thorun C, 2020, J CONSUM POLICY, V43, P177, DOI 10.1007/s10603-019-09411-6. Xie M, 2019, J PHYS C SERIES, V1187, P1. Zhu Z, 2007, J ACAD MARKET SCI, V35, P492, DOI 10.1007/s11747-007-0019-3. Zopounidis C, 2018, EURO J DECIS PROCESS, V6, P63, DOI 10.1007/s40070-018-0078-3.}, Number-of-Cited-References = {51}, Times-Cited = {4}, Usage-Count-Last-180-days = {5}, Usage-Count-Since-2013 = {40}, Journal-ISO = {Entrep. Sustain. Iss.}, Doc-Delivery-Number = {OW7DI}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000593042200024}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000967684400001, Author = {Tan, Leonard and Tan, Ooi Kiang and Sze, Chun Chau and Bin Goh, Wilson Wen}, Title = {Emotional Variance Analysis: A new sentiment analysis feature set for Artificial Intelligence and Machine Learning applications}, Journal = {PLOS ONE}, Year = {2023}, Volume = {18}, Number = {1}, Month = {JAN 12}, Abstract = {Sentiment Analysis (SA) is a category of data mining techniques that extract latent representations of affective states within textual corpuses. This has wide ranging applications from online reviews to capturing mental states. In this paper, we present a novel SA feature set; Emotional Variance Analysis (EVA), which captures patterns of emotional instability. Applying EVA on student journals garnered from an Experiential Learning (EL) course, we find that EVA is useful for profiling variations in sentiment polarity and intensity, which in turn can predict academic performance. As a feature set, EVA is compatible with a wide variety of Artificial Intelligence (AI) and Machine Learning (ML) applications. Although evaluated on education data, we foresee EVA to be useful in mental health profiling and consumer behaviour applications. EVA is available at . Our results show that EVA was able to achieve an overall accuracy of 88.7\% and outperform NLP (76.0\%) and SentimentR (58.0\%) features by 15.8\% and 51.7\% respectively when predicting student experiential learning grade scores through a Multi-Layer Perceptron (MLP) ML model.}, Publisher = {PUBLIC LIBRARY SCIENCE}, Address = {1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA}, Type = {Article}, Language = {English}, Affiliation = {Bin Goh, WW (Corresponding Author), Nanyang Technol Univ, Sch Biol Sci, Singapore, Singapore. Bin Goh, WW (Corresponding Author), Nanyang Technol Univ, Lee Kong Chian Sch Med, Singapore, Singapore. Bin Goh, WW (Corresponding Author), Nanyang Technol Univ, Ctr Biomed Informat, Singapore, Singapore. Tan, Leonard; Sze, Chun Chau; Bin Goh, Wilson Wen, Nanyang Technol Univ, Sch Biol Sci, Singapore, Singapore. Tan, Ooi Kiang, Nanyang Technol Univ, Coll Engn, Singapore, Singapore. Bin Goh, Wilson Wen, Nanyang Technol Univ, Lee Kong Chian Sch Med, Singapore, Singapore. Bin Goh, Wilson Wen, Nanyang Technol Univ, Ctr Biomed Informat, Singapore, Singapore.}, DOI = {10.1371/journal.pone.0274299}, Article-Number = {e0274299}, ISSN = {1932-6203}, Keywords-Plus = {PREDICTION}, Research-Areas = {Science \& Technology - Other Topics}, Web-of-Science-Categories = {Multidisciplinary Sciences}, Author-Email = {wilsongoh@ntu.edu.sg}, Affiliations = {Nanyang Technological University \& National Institute of Education (NIE) Singapore; Nanyang Technological University; Nanyang Technological University \& National Institute of Education (NIE) Singapore; Nanyang Technological University; Nanyang Technological University \& National Institute of Education (NIE) Singapore; Nanyang Technological University; Nanyang Technological University \& National Institute of Education (NIE) Singapore; Nanyang Technological University}, ResearcherID-Numbers = {Sze, Chun Chau/A-2200-2011 Goh, Wilson Wen Bin/K-1637-2015}, ORCID-Numbers = {Sze, Chun Chau/0000-0003-2245-9050 Goh, Wilson Wen Bin/0000-0003-3863-7501}, Funding-Acknowledgement = {ACE grant from Nanyang Technological University; EdeX Teaching and Learning grant from Nanyang Technological University; MOE AcRF Tier 1 award {[}RG35/20]}, Funding-Text = {WWBG, CCS and TOK acknowledge funding from an ACE grant from Nanyang Technological University. WWBG acknowledges funding from an EdeX Teaching and Learning grant from Nanyang Technological University. WWBG acknowledge support from an MOE AcRF Tier 1 award (RG35/20). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.}, Cited-References = {Altrabsheh N, 2014, PROC INT C TOOLS ART, P419, DOI 10.1109/ICTAI.2014.70. Bahrainian SA, 2013, 2013 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY - WORKSHOPS (WI-IAT), VOL 3, P26, DOI 10.1109/WI-IAT.2013.145. Barron-estrada M. L., 2019, RES COMPUTING SCI, V148, P71, DOI {[}DOI 10.13053/RCS-148-5-8, 10.13053/rcs-148-5-8]. Belabbas MA, 2009, P NATL ACAD SCI USA, V106, P369, DOI 10.1073/pnas.0810600105. Cambria E, 2017, SOCIO AFFECT COMPUT, V5, P1, DOI 10.1007/978-3-319-55394-8. Chatterjee I, 2021, ENTROPY-SWITZ, V23, DOI 10.3390/e23121645. Chen CH, 2018, INFORM PROCESS MANAG, V54, P1325, DOI 10.1016/j.ipm.2018.05.008. 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Zhang SX, 2018, FUTURE GENER COMP SY, V81, P395, DOI 10.1016/j.future.2017.09.048. Zhou J, 2023, INTERACT LEARN ENVIR, V31, P1252, DOI 10.1080/10494820.2020.1826985. Zhou MG, 2023, ENVIRON TECHNOL, V44, P3063, DOI 10.1080/09593330.2022.2049894.}, Number-of-Cited-References = {40}, Times-Cited = {2}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {2}, Journal-ISO = {PLoS One}, Doc-Delivery-Number = {D3IC7}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000967684400001}, OA = {Green Published, gold}, DA = {2023-10-04}, } @article{ WOS:000629250500009, Author = {Curth, Marcelo and da Silveira, Alexandre Borba and Pinheiro, Juciele Pires}, Title = {MOBILE GREEN COMMUNITIES: A STUDY ON THE RELATIONSHIP BETWEEN SOCIAL IDENTITY AND PURCHASE INTENTION}, Journal = {GESTAO E DESENVOLVIMENTO}, Year = {2021}, Volume = {18}, Number = {1}, Pages = {172-193}, Month = {JAN-APR}, Abstract = {The use of technology has been widely used to influence conscious consumption, especially in the formation of communities in the virtual context. The present study aimed to analyze the relationships between cognitive involvement (CI), affective involvement (AI), social identity (SI) and flow (FL) with purchase intention (PI). Therefore, a survey was conducted with 152 participants in a mobile community (m-community) connected to green consumption. For the theoretical model, the Structural Equation Modeling (SEM). Results showed the positive relationship for social identity and purchase intention and for social identity and flow, in addition to the positive influence of the cognitive involvement for the formation of the social identity of the community members. The results contribute to understanding that participation in such communities starts with utilitarian elements and that the purchase would be in a flow state after identity formation. The study contributes to the literature by proposing a relationship of participation in green communities related to the identity of the participants.}, Publisher = {UNIV FEEVALE, INST CIENCIAS SOCIAIS APLICADASICSA}, Address = {ERS 239, 2755-B VILA NOVA, NOVO HAMBURGO, CEP93525-075, BRAZIL}, Type = {Article}, Language = {Portuguese}, Affiliation = {Curth, M (Corresponding Author), Univ Feevale, Novo Hamburgo, Brazil. Curth, Marcelo, Univ Feevale, Novo Hamburgo, Brazil. da Silveira, Alexandre Borba, Univ Vale Rio dos Sinos, Sao Leopoldo, Brazil.}, DOI = {10.25112/rgd.v18i1.2110}, ISSN = {1807-5436}, EISSN = {2446-6875}, Keywords = {Social Identity; Purchase intention; Mobile Green Communities; Social Identity; Flow}, Keywords-Plus = {CONTINUANCE INTENTION; SELF-CATEGORIZATION; CONSUMER-BEHAVIOR; NETWORKING SITES; INVOLVEMENT; FLOW; IDENTIFICATION; ENVIRONMENTS; INNOVATION; FRAMEWORK}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {marcelocurth@feevale.br alexandreborba@unisinos.br juciele.pires@gmail.com}, Affiliations = {Universidade Feevale; Universidade do Vale do Rio dos Sinos (Unisinos)}, Cited-References = {{[}Anonymous], 2000, IDENTITY READER. {[}Anonymous], 1988, SOCIAL IDENTIFICATIO. {[}Anonymous], 2009, AN LISE MULTIVARIADA. ASHFORTH BE, 1989, ACAD MANAGE REV, V14, P20, DOI 10.2307/258189. 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Tsiotsou R., 2006, INT J CONSUM STUD, V30, P207, DOI {[}DOI 10.1111/J.1470-6431.2005.00477.X, 10.1111/j. 1470- 6431.20 05.00477.x]. Tsiotsou RH, 2015, COMPUT HUM BEHAV, V48, P401, DOI 10.1016/j.chb.2015.01.064. Witmer BG, 1998, PRESENCE-TELEOP VIRT, V7, P225, DOI 10.1162/105474698565686. ZAICHKOWSKY JL, 1985, J CONSUM RES, V12, P341, DOI 10.1086/208520. ZAICHKOWSKY JL, 1994, J ADVERTISING, V23, P59, DOI 10.1080/00913367.1943.10673459.}, Number-of-Cited-References = {63}, Times-Cited = {0}, Usage-Count-Last-180-days = {6}, Usage-Count-Since-2013 = {20}, Journal-ISO = {GEST. Desenvolv.}, Doc-Delivery-Number = {QX3MN}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000629250500009}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000618860400001, Author = {Payne, Elizabeth H. Manser and Dahl, Andrew J. and Peltier, James}, Title = {Digital servitization value co-creation framework for AI services: a research agenda for digital transformation in financial service ecosystems}, Journal = {JOURNAL OF RESEARCH IN INTERACTIVE MARKETING}, Year = {2021}, Volume = {15}, Number = {2}, Pages = {200-222}, Month = {JUN 21}, Abstract = {Purpose Innovative firms have rapidly developed artificial intelligence (AI) capabilities into their service ecosystems, essentially changing perceptions of what is service quality and service delivery in their respective industries. Nonetheless, the issues surrounding AI services remain relatively unknown. The purpose for this paper is to offer a digital servitization framework for understanding how AI services impact value perceptions, consumer engagement and firm performance measures. The authors use the financial service ecosystem to explore this topic. Design/methodology/approach The authors explore relevant literature on digital servitization, service-dominant logic and AI/disruptive innovation. Next, a conceptual framework, organized by AI-Service Exchange Antecedents, Context of AI Usage and Digital Servitization Consequences, is developed. The authors conceptualize consequences for consumers and firms. Findings The main findings suggest that the linkages between consumers, financial institutions and fintech companies with AI usage in a service ecosystem should be identified; how value is created among multiple SD Logic-AI network actors should be analyzed; and the effects of AI-consumer interactions (lower-level and higher levels of engagement) on firm performance measures should be explored. Research limitations/implications The conceptual framework identifies gaps in the literature and suggests research questions for future studies. Practical implications This paper may assist practitioners with the development of AI-enabled banking activities that involve direct consumer engagement. Originality/value To the authors' best knowledge, this research agenda is the first comprehensive framework for understanding value co-creation in the context of AI in financial services, linking antecedents, usage and consequences.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Payne, EHM (Corresponding Author), Univ South Dakota, Dept Mkt, Vermillion, SD 57069 USA. Payne, Elizabeth H. Manser, Univ South Dakota, Dept Mkt, Vermillion, SD 57069 USA. Dahl, Andrew J.; Peltier, James, Univ Wisconsin Whitewater, Coll Business \& Econ, Dept Mkt, Whitewater, WI USA.}, DOI = {10.1108/JRIM-12-2020-0252}, EarlyAccessDate = {FEB 2021}, ISSN = {2040-7122}, EISSN = {2040-7130}, Keywords = {Online consumer behavior; Customer value; Services marketing; Financial services; e-commerce; Consumer behaviour internet; Service quality; Information technology; Eservice quality; Blogs; Digitalizations}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {liz.manserpayne@usd.edu dahlaj18@uww.edu peltierj@uww.edu}, Affiliations = {University of South Dakota; University of Wisconsin System; University of Wisconsin Whitewater}, ORCID-Numbers = {Manser Payne, Elizabeth/0000-0002-7734-2282 Dahl, Andrew/0000-0002-0202-6955}, Cited-References = {Adapa S, 2020, J RETAIL CONSUM SERV, V52, DOI 10.1016/j.jretconser.2019.101901. Akaka MA, 2014, INF SYST E-BUS MANAG, V12, P367, DOI 10.1007/s10257-013-0220-5. 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Zhou T, 2012, INFORM TECHNOL MANAG, V13, P27, DOI 10.1007/s10799-011-0111-8.}, Number-of-Cited-References = {120}, Times-Cited = {52}, Usage-Count-Last-180-days = {69}, Usage-Count-Since-2013 = {309}, Journal-ISO = {J. Res. Interact. Mark.}, Doc-Delivery-Number = {SW1CO}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000618860400001}, DA = {2023-10-04}, } @article{ WOS:000713016600001, Author = {Flavian, Carlos and Casalo, Luis V.}, Title = {Artificial intelligence in services: current trends, benefits and challenges}, Journal = {SERVICE INDUSTRIES JOURNAL}, Year = {2021}, Volume = {41}, Number = {13-14, SI}, Pages = {853-859}, Month = {OCT 26}, Abstract = {The automation of services taking advantage of the significant opportunities offered by artificial intelligence and other Industry 4.0 technologies is receiving increasing attention both from academics and practitioners. Interest in the subject has been boosted significantly by the healthcare crisis generated by COVID-19 and the need to maintain social distancing while continuing to provide efficient services. The purpose of this brief paper is threefold: (i) to introduce and summarize the current state of automated forms of interaction in services; (ii) to provide an overview of the six papers published in this special issue; and (iii) to describe the possibilities for future research that emerged at the AIRSI2019 (Artificial Intelligence and Robotics in Service Interactions) Conference. The AIRSI2019 conference was the precursor to this special issue and provided an excellent opportunity to explore with leading international researchers the extraordinary development possibilities presented in this research context.}, Publisher = {ROUTLEDGE JOURNALS, TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND}, Type = {Editorial Material}, Language = {English}, Affiliation = {Flavian, C (Corresponding Author), Univ Zaragoza, Mkt Management \& Market Res, Zaragoza, Spain. Flavian, Carlos; Casalo, Luis V., Univ Zaragoza, Mkt Management \& Market Res, Zaragoza, Spain.}, DOI = {10.1080/02642069.2021.1989177}, ISSN = {0264-2069}, EISSN = {1743-9507}, Keywords = {Artificial Intelligence; Service Interaction; Robot; Virtual assistant; Agenda for future research; Consumer behaviour}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Author-Email = {cflavian@unizar.es}, Affiliations = {University of Zaragoza}, ResearcherID-Numbers = {Flavian, Carlos/G-4365-2013 Casaló, Luis V./T-7450-2019}, ORCID-Numbers = {Flavian, Carlos/0000-0001-7118-9013 Casaló, Luis V./0000-0002-9643-2814}, Cited-References = {AJZEN I, 1975, PSYCHOL BULL, V82, P261, DOI 10.1037/h0076477. Akdim K, 2023, INT J CONTEMP HOSP M, V35, P2816, DOI 10.1108/IJCHM-12-2020-1406. Belanche D, 2021, PSYCHOL MARKET, V38, P2357, DOI 10.1002/mar.21532. Belanche D, 2020, SERV IND J, V40, P203, DOI 10.1080/02642069.2019.1672666. 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J.}, Doc-Delivery-Number = {WP3DL}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000713016600001}, OA = {Bronze}, DA = {2023-10-04}, } @article{ WOS:000958697200001, Author = {Paul, Justin and Ueno, Akiko and Dennis, Charles}, Title = {ChatGPT and consumers: Benefits, Pitfalls and Future Research Agenda}, Journal = {INTERNATIONAL JOURNAL OF CONSUMER STUDIES}, Year = {2023}, Volume = {47}, Number = {4}, Pages = {1213-1225}, Month = {JUL}, Abstract = {The need of the hour is to encourage research on topics with newness and novelty. In this context, this article discusses multidimensional benefits and potential pitfalls of using artificial intelligence-based Chat Generative Pre-trained Transformer (ChatGPT), and provides numerous ideas for future research in consumer studies and marketing in the context of ChatGPT. ChatGPT provides algorithm-generated conversational responses to text-based prompts. Since its launch in the late 2022, ChatGPT has generated significant debate surrounding its hallmarks, benefits and potential pitfalls. On the one hand, ChatGPT can offer enhanced consumer engagement, improved customer service, personalization and shopping, social interaction and communication practice, cost-effectiveness, insights into consumer behaviour and improved marketing campaigns. On the other hand, potential pitfalls include concerns about consumer well-being, bias, misinformation, lack of context, privacy concerns, ethical considerations and security. The article concludes by outlining a potential future research agenda in the area of ChatGPT and consumer studies. Overall, this article provides valuable insights into the benefits and challenges associated with ChatGPT, shedding light on its potential applications and the need for further research.}, Publisher = {WILEY}, Address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, Type = {Editorial Material}, Language = {English}, Affiliation = {Paul, J (Corresponding Author), Univ Reading, Henley Business Sch, Reading, England. Paul, Justin, Univ Puerto Rico, San Juan, PR USA. Paul, Justin, Univ Reading, Henley Business Sch, Reading, England. Paul, Justin, Parul Univ, Vadodara, India. Ueno, Akiko; Dennis, Charles, Middlesex Univ, Business Sch, Mkt Branding \& Tourism Dept, London, England.}, DOI = {10.1111/ijcs.12928}, EarlyAccessDate = {MAR 2023}, ISSN = {1470-6423}, EISSN = {1470-6431}, Keywords = {benefits; ChatGPT; pitfalls; research agenda}, Keywords-Plus = {SELF-DETERMINATION THEORY; ARTIFICIAL-INTELLIGENCE; AI}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {j.paul@reading.ac.uk}, Affiliations = {University of Puerto Rico; University of Reading; Parul University; Middlesex University}, ORCID-Numbers = {Ueno, Akiko/0000-0001-6157-3193}, Cited-References = {Ahmed A., 2023, CHATGPT ACHIEVED ONE. Akter S, 2021, INT J INFORM MANAGE, V60, DOI 10.1016/j.ijinfomgt.2021.102387. Arnott D, 2019, DECIS SUPPORT SYST, V122, DOI 10.1016/j.dss.2019.05.003. Atlas S., 2023, CHATGPT HIGHER ED PR. Aw ECX, 2022, TECHNOL FORECAST SOC, V180, DOI 10.1016/j.techfore.2022.121711. 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Stud.}, Doc-Delivery-Number = {I1JE5}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000958697200001}, DA = {2023-10-04}, } @article{ WOS:000821383400001, Author = {Huh, Jennifer and Whang, Claire and Kim, Hye-Young}, Title = {Building trust with voice assistants for apparel shopping: The effects of social role and user autonomy}, Journal = {JOURNAL OF GLOBAL FASHION MARKETING}, Year = {2023}, Volume = {14}, Number = {1, SI}, Pages = {5-19}, Month = {JAN 2}, Abstract = {Voice shopping creates a novel shopping experience as it is prompted by human-AI interaction. It greatly reduces the time required in consumer decision-making, while it could impair consumers' autonomy. This study thus investigates how the social role of voice assistants and user autonomy affect consumers' relationships and buying decisions. Using media equation theory, two experimental studies examined the effects of social role and user autonomy on perceived human-likeness, trust, and purchase intention. Study 1 (86 participants) and Study 2 (112 participants) found that perceived human-likeness and trust serially mediated the relationship between user autonomy and purchase intention. This finding contributes to the media equation research by affirming the effectiveness of implicit anthropomorphism processing and highlights the importance of improving consumers' confidence via voice channels.}, Publisher = {TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Kim, HY (Corresponding Author), Univ Minnesota, Retail Merchandising Program, 240 McNeal Hall,1985 Buford Ave, St Paul, MN 55108 USA. Huh, Jennifer; Kim, Hye-Young, Univ Minnesota, Retail Merchandising Program, 240 McNeal Hall,1985 Buford Ave, St Paul, MN 55108 USA. Whang, Claire, Calif State Polytech Univ Pomona, Apparel Merchandising \& Management Dept, Pomona, CA 91768 USA.}, DOI = {10.1080/20932685.2022.2085603}, EarlyAccessDate = {JUN 2022}, ISSN = {2093-2685}, EISSN = {2325-4483}, Keywords = {Human-AI interaction; voice assistant; voice shopping; social role; user autonomy}, Keywords-Plus = {CONSUMER; SELF; PERSPECTIVE; INTENTIONS; EXPERIENCE; RESPONSES; MACHINES; FASHION; CHOICE; NEED}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {hykim@umn.edu}, Affiliations = {University of Minnesota System; University of Minnesota Twin Cities; California State University System; California State Polytechnic University Pomona}, ORCID-Numbers = {Kim, Hye-Young/0000-0002-1062-0823 Huh, Jennifer/0000-0001-8171-3747}, Cited-References = {Balakrishnan J, 2021, ANN OPER RES, DOI 10.1007/s10479-021-04049-5. Bertacchini F, 2017, COMPUT HUM BEHAV, V77, P382, DOI 10.1016/j.chb.2017.02.064. 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Mark.}, Doc-Delivery-Number = {8O4TE}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000821383400001}, DA = {2023-10-04}, } @article{ WOS:000915350600001, Author = {Zhu, Yao and Zhang, Rongteng (Renata) and Zou, Yongguang and Jin, Dan}, Title = {Investigating customers' responses to artificial intelligence chatbots in online travel agencies: the moderating role of product familiarity}, Journal = {JOURNAL OF HOSPITALITY AND TOURISM TECHNOLOGY}, Year = {2023}, Volume = {14}, Number = {2}, Pages = {208-224}, Month = {FEB 17}, Abstract = {PurposeThis paper aims to examine how consumers' perceptions of artificial intelligence (AI) chatbots influence individuals' cognitive and emotional states and their subsequent behavioural intentions vis-a-vis online travel agencies (OTAs). Design/methodology/approachThe survey sample comprised 566 customers who had experienced the use of travel AI chatbots in China using a combination of online and offline questionnaires. Partial least squares structural equation modelling was used to test the hypotheses. FindingsThe results revealed that interaction and information quality, as AI chatbot stimuli, significantly increase potential tourists' trust and purchase intention. Perceived usefulness plays a mediating role in the relationship among interactivity, information quality, customer trust and purchase intention. Furthermore, the findings indicated that customers with high product familiarity exhibited greater trust in products demonstrating a high level of perceived usefulness. Originality/valueBy integrating cognitive consistency theory, this study theoretically validates the applicability of the stimulus-organism-response framework on AI chatbots and provides academics with useful insights regarding the influence mechanisms of human-computer interaction and information quality on customer response within OTA settings.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Zhang, RT (Corresponding Author), Univ Putra Malaysia, Sch Business \& Econ, Serdang, Malaysia. Zhu, Yao, Ocean Univ China, Management Coll, Qingdao, Peoples R China. Zhang, Rongteng (Renata), Univ Putra Malaysia, Sch Business \& Econ, Serdang, Malaysia. Zou, Yongguang, Huaqiao Univ, Coll Tourism Management, Quanzhou, Peoples R China. Jin, Dan, Univ Tennessee, Retail Hospitality \& Tourism Management, Knoxville, TN USA.}, DOI = {10.1108/JHTT-02-2022-0041}, EarlyAccessDate = {JAN 2023}, ISSN = {1757-9880}, EISSN = {1757-9899}, Keywords = {Travel chatbot; Human-computer interaction; Information quality; SOR paradigm; Cognitive consistency theory; Tourism internet marketing; ???????; ????; ????; SOR??; ???????; ??????}, Keywords-Plus = {TRUST; INTENTION; TECHNOLOGY; ACCEPTANCE; MODEL; RISK}, Research-Areas = {Social Sciences - Other Topics}, Web-of-Science-Categories = {Hospitality, Leisure, Sport \& Tourism}, Author-Email = {yzhu2017@126.com rongtengzhang@gmail.com ygzou2009@126.com djin4@utk.edu}, Affiliations = {Ocean University of China; Universiti Putra Malaysia; Huaqiao University; University of Tennessee System; University of Tennessee Knoxville}, Cited-References = {Abubakar AM, 2016, J DESTIN MARK MANAGE, V5, P192, DOI 10.1016/j.jdmm.2015.12.005. 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Zhang RT, 2022, CURR ISSUES TOUR, V25, P3694, DOI 10.1080/13683500.2022.2070459. Zhou RR, 2004, J CONSUM RES, V31, P125, DOI 10.1086/383429.}, Number-of-Cited-References = {57}, Times-Cited = {3}, Usage-Count-Last-180-days = {70}, Usage-Count-Since-2013 = {103}, Journal-ISO = {J. Hosp. Tour. Technol.}, Doc-Delivery-Number = {8T3JM}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000915350600001}, DA = {2023-10-04}, } @article{ WOS:000852636600001, Author = {Bhagat, Rohit and Chauhan, Vinay and Bhagat, Pallavi}, Title = {Investigating the impact of artificial intelligence on consumer's purchase intention in e-retailing}, Journal = {FORESIGHT}, Year = {2023}, Volume = {25}, Number = {2, SI}, Pages = {249-263}, Month = {APR 4}, Abstract = {Purpose Technology has been witnessing a rapid growth. The advent of artificial intelligence has further enhanced the satisfaction level of consumers, which makes it even more vital in the current scenario. This paper aims to explore the factors affecting practical implacability of artificial intelligence and its impact on consumers' online purchase intention. Design/methodology/approach This paper has used a technology-based model as the base to explore the different factors affecting consumers' purchase intention towards e-retailing. This study has formulated a model that demonstrates the integration of artificial intelligence in retailing by the business organizations so as to understand the needs of customers and help them accept technology. This study has further explored faith, subjective norms and consciousness as constructs which enhance the implacability of artificial intelligence. Findings This study shows that artificial intelligence positively influences consumers' buying behaviour. This study through a model also shows that integration of artificial intelligence enhances consumers' purchase intention. Research limitations/implications The study has been focusing on a portion of target population. So there is scope to include the whole set of the population to get closer-to-accurate results. Practical implications The study offers useful inputs for academicians as well as marketers for predicting buying behaviour of consumers. Marketing managers can use artificial intelligence-embedded technology to enhance online purchase intention. Social implications The study shows that an increase in consciousness towards e-retailing has made consumers keenly analyse and purchase products on the basis of merit and usefulness of the products. Originality/value The contribution has been made with the best of knowledge in formulating an integrated artificial intelligence model for consumers' purchase intention in e-retailing.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Bhagat, R (Corresponding Author), Univ Jammu, Business Sch, Bhaderwah Campus, Jammu, India. Bhagat, Rohit; Chauhan, Vinay, Univ Jammu, Business Sch, Bhaderwah Campus, Jammu, India. Bhagat, Pallavi, GDC Boys, Jammu, India.}, DOI = {10.1108/FS-10-2021-0218}, EarlyAccessDate = {SEP 2022}, ISSN = {1463-6689}, EISSN = {1465-9832}, Keywords = {e-retailing; faith; subjective norms; consciousness; artificial intelligence; consumer's purchase intention}, Keywords-Plus = {DECISION-MAKING; TECHNOLOGY ACCEPTANCE; BEHAVIORAL INTENTION; BIG DATA; FUTURE; MODEL; AI; READINESS; SERVICES; COMMERCE}, Research-Areas = {Public Administration}, Web-of-Science-Categories = {Regional \& Urban Planning}, Author-Email = {rohitbhagat.ju@gmail.com}, Affiliations = {University of Jammu}, Cited-References = {Aakash S., 2019, IRE J, V2, P37. AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T. Al-Debei MM, 2015, INTERNET RES, V25, P707, DOI 10.1108/IntR-05-2014-0146. Anica-Popa I, 2021, AMFITEATRU ECON, V23, P120, DOI 10.24818/EA/2021/56/120. Astawa I.G.N.M.W., 2019, INT J MANAG COMMER I, V6, P1232. 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Yoo WS, 2010, J RETAIL CONSUM SERV, V17, P89, DOI 10.1016/j.jretconser.2009.10.003.}, Number-of-Cited-References = {66}, Times-Cited = {2}, Usage-Count-Last-180-days = {17}, Usage-Count-Since-2013 = {35}, Journal-ISO = {Foresight}, Doc-Delivery-Number = {C8EU3}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000852636600001}, DA = {2023-10-04}, } @article{ WOS:000838824200020, Author = {Senguler, Hasan and Inel, Mehmet}, Title = {An Empirical Study Based on Artificial Intelligence for Determining Brand Value Based on Financial Data}, Journal = {SOSYOEKONOMI}, Year = {2022}, Volume = {30}, Number = {53}, Pages = {395-424}, Month = {JUL}, Abstract = {Brand value is determined by financial methods, methods based on consumer behaviour, and mixed methods in which these two methods are used together. In the study, after determining the appropriate variables of the financial techniques that define the brand value, it is aimed to approach the brand value determined by the ``Brand Finance{''} firm with artificial neural networks by using these variables and selecting the most appropriate model. R-square, MAPE and RMSE values of the models built with artificial neural networks were determined, and the models were compared. These values were interpreted and stated that the models were good.}, Publisher = {SOSYOEKONOMI SOC}, Address = {ELIF SOKAK, 7-98 ZUBEYDE HANIM MAHALLESI, ISKITLER, ALTINDAG, ANKARA, 06070, TURKEY}, Type = {Article}, Language = {Turkish}, Affiliation = {Senguler, H (Corresponding Author), Istanbul Medeniyet Univ, Istanbul, Turkey. Senguler, Hasan, Istanbul Medeniyet Univ, Istanbul, Turkey. Inel, Mehmet, Marmara Univ, Istanbul, Turkey.}, DOI = {10.17233/sosyoekonomi.2022.03.20}, ISSN = {1305-5577}, Keywords = {Brand; Brand Value; Artificial Intelligence; Artificial Neural Networks}, Keywords-Plus = {NEURAL-NETWORKS; EQUITY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Economics}, Author-Email = {hasansenguler@medeniyet.edu.tr mninel@marmara.edu.tr}, Affiliations = {Istanbul Medeniyet University; Marmara University}, ResearcherID-Numbers = {şengüler, hasan/HLP-6274-2023}, Cited-References = {Aaker D. A., 2009, MANAGING BRAND EQUIT. Akgun O., 2014, SELCUK UNIVERSITESI, P1. Alsu E., 2017, ULUSLARARASI AFRO AV, V2, P175. Anderson D., 1992, ARTIFICIAL NEURAL NE. {[}Anonymous], 2019, BIL SAN TER SOZL. {[}Anonymous], 2011, MUHASEBE FINANSMAN D. {[}Anonymous], 2002, J MARKET MANAG, DOI DOI 10.1362/0267257022775882. {[}Anonymous], 2001, J PROD BRAND MANAG, DOI DOI 10.1108/EUM0000000005674. Asilkan Ozcan, 2009, S DEMIREL U IKTISADI, V14, P375. 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Zhang GQ, 1998, INT J FORECASTING, V14, P35, DOI 10.1016/S0169-2070(97)00044-7. Zimmermann R, 2001, BRAND VALUATION BRAN, P1.}, Number-of-Cited-References = {82}, Times-Cited = {1}, Usage-Count-Last-180-days = {2}, Usage-Count-Since-2013 = {8}, Journal-ISO = {Sosyoekonom}, Doc-Delivery-Number = {3R3NO}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000838824200020}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000829873800001, Author = {Sanchez, Thomas W. and Shumway, Hannah and Gordner, Trey and Lim, Theo}, Title = {The prospects of artificial intelligence in urban planning}, Journal = {INTERNATIONAL JOURNAL OF URBAN SCIENCES}, Year = {2023}, Volume = {27}, Number = {2}, Pages = {179-194}, Month = {APR 3}, Abstract = {Over the past several decades, urban planning has considered a variety of advanced analysis methods with greater and lesser degrees of adoption. Geographic Information Systems (GIS) is probably the most notable, with others such as database management systems (DBMS), decision support systems (DSS), planning support systems (PSS), and expert systems (ES), having mixed levels of recognition and acceptance (Kontokosta, C. E. (2021). Urban informatics in the science and practice of planning. Journal of Planning Education and Research, 41(4), 382-395. doi:10.1177/0739456X18793716; Yigitcanlar, T., Desouza, K. C., Butler, L., \& Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6), 1473). Advances in information technologies have moved very slowly in the field of urban planning, more recently concerning `smart city' technologies while revolutionizing other domains, such as consumer goods and services. Baidu, Amazon, Netflix, Google, and many others are using these technologies to gain insights into consumer behaviour and characteristics and improve supply chains and logistics. This is an opportune time for urban planners to consider the application of AI-related techniques given vast increases in data availability, increased processing speeds, and increased popularity and development of planning related applications. Research on these topics by urban planning scholars has increased over the past few years, but there is little evidence to suggest that the results are making it into the hands of professional planners (Batty, M. (2018). Artificial intelligence and smart cities. Environment and Planning B: Urban Analytics and City Science, 45(1), 3-6; Batty, M. (2021). Planning education in the digital age. Environment and Planning B: Urban Analytics and City Science, 48(2), 207-211). Others encourage planners to leverage the ubiquity of data and advances in computing to enhance redistributive justice in information resources and procedural justice in decision-making among marginalized communities (Boeing, G., Besbris, M., Schachter, A., \& Kuk, J. (2020). Housing search in the Age of Big data: Smarter cities or the same Old blind spots? Housing Policy Debate, 31(1), 112-126; Goodspeed, R. (2015). Smart cities: Moving beyond urban cybernetics to tackle wicked problems. Cambridge journal of regions, Economy and Society, 8(1), 79-92). This article highlights findings from a recent literature review on AI in planning and discusses the results of a national survey of urban planners about their perspectives on AI adoption and concerns they have expressed about its broader use in the profession. Currently, the outlook is mixed, matching how urban planners initially viewed the early stages of computer adoption within the profession. And yet today, personal computers are essential to any job.}, Publisher = {ROUTLEDGE JOURNALS, TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Sanchez, TW (Corresponding Author), Virginia Tech, Urban Affairs \& Planning, Arlington, VA 22203 USA. Sanchez, Thomas W., Virginia Tech, Urban Affairs \& Planning, Arlington, VA 22203 USA. Shumway, Hannah, Esri, Arlington, VA USA. Gordner, Trey, US Digital Corps, Washington, DC USA. Lim, Theo, Virginia Tech, Urban Affairs \& Planning, Blacksburg, VA USA.}, DOI = {10.1080/12265934.2022.2102538}, EarlyAccessDate = {JUL 2022}, Article-Number = {2102538}, ISSN = {1226-5934}, EISSN = {2161-6779}, Keywords = {Urban planning; technology; artificial intelligence; data science}, Keywords-Plus = {SMART CITIES; AUTOMATA; MODELS}, Research-Areas = {Environmental Sciences \& Ecology; Urban Studies}, Web-of-Science-Categories = {Environmental Studies; Urban Studies}, Author-Email = {tom.sanchez@vt.edu}, Affiliations = {Virginia Polytechnic Institute \& State University; Virginia Polytechnic Institute \& State University}, ResearcherID-Numbers = {Sanchez, Thomas/IAN-5364-2023 Sanchez, Thomas W./D-5093-2012}, ORCID-Numbers = {Sanchez, Thomas W./0000-0002-8259-0088}, Funding-Acknowledgement = {National Science Foundation {[}2125259]; Virginia Tech, Institute for Society, Culture and Environment; Division Of Computer and Network Systems; Direct For Computer \& Info Scie \& Enginr {[}2125259] Funding Source: National Science Foundation}, Funding-Text = {This work was supported by National Science Foundation: {[}grant number 2125259]; Virginia Tech, Institute for Society, Culture and Environment.}, Cited-References = {Adadi A, 2018, IEEE ACCESS, V6, P52138, DOI 10.1109/ACCESS.2018.2870052. {[}Anonymous], 2011, P 3 ACM INT WORKSH M. 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Zhang XY, 2020, ISPRS J PHOTOGRAMM, V161, P1, DOI 10.1016/j.isprsjprs.2020.01.005.}, Number-of-Cited-References = {42}, Times-Cited = {10}, Usage-Count-Last-180-days = {23}, Usage-Count-Since-2013 = {53}, Journal-ISO = {Int. J. Urban Sci.}, Doc-Delivery-Number = {F6YO6}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000829873800001}, DA = {2023-10-04}, } @article{ WOS:001050972300004, Author = {Rosli, Nadzirah and Zaki, Hafizah Omar}, Title = {A BIBLIOMETRIC REVIEW OF RESEARCH ON GAMIFICATION IN MARKETING: REFLECTIONS FOR MOVING FORWARD}, Journal = {INTERNATIONAL JOURNAL OF MANAGEMENT STUDIES}, Year = {2023}, Volume = {30}, Number = {2}, Pages = {271-300}, Month = {JUL}, Abstract = {Gamification has become increasingly popular among businesses, institutions and consumers, especially since the emergence of Covid-19 pandemic. It has been widely used to promote positive changes in user behaviour, improve companies' digital presence and provide immersive and engaging brand experiences. Though bibliometric studies on gamification have been conducted previously, information on citations and networking analysis emphasises marketing and consumer behaviour remains scarce. Thus, the purpose of this bibliometric study is to describe how gamification is structured and how it has evolved over time. To achieve this, we utilise citation analysis and co-word analysis to visually uncover the intellectual, conceptual and social network structures in gamification research. A total of 558 articles published between 2011 and 2021 were extracted from the Dimension.ai database through the PRISMA review process. The results reveal positive growth in gamification research between 2011 and 2021. The United States was the most productive and most cited country and the most productive and influential institution was Tampere University in Finland, which houses Juho Hamari, the most influential and most cited author. Additionally, the results reveal recent trends in gamification research including those related to value, brand and attitude as well as emerging trends including artificial intelligence. The results also reveal collaborations through co-authorship among authors, institutions and countries. Together, they depict the intellectual landscape of gamification as related to marketing and consumer behaviour. This is beneficial for both inexperienced and experienced scholars, practitioners, funding agencies and policymakers.}, Publisher = {UNIV UTARA MALAYSIA PRESS}, Address = {UNIV UTARA MALAYSIA PRESS, SINTOK, KEDAH 06010, MALAYSIA}, Type = {Review}, Language = {English}, Affiliation = {Rosli, N (Corresponding Author), Univ Kebangsaan Malaysia, Fac Econ \& Management, Kuala Lumpur, Malaysia. Rosli, Nadzirah; Zaki, Hafizah Omar, Univ Kebangsaan Malaysia, Fac Econ \& Management, Kuala Lumpur, Malaysia.}, DOI = {10.32890/ijms2023.30.2.4}, ISSN = {2232-1608}, EISSN = {2180-2467}, Keywords = {Bibliometric; gamification; marketing; consumer behaviour; PRISMA; VOSviewer}, Keywords-Plus = {IMPACT; ENGAGEMENT; INTENTION; BEHAVIOR; ATTITUDE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Author-Email = {nadzirah.rosli@ukm.edu.my}, Affiliations = {Universiti Kebangsaan Malaysia}, Funding-Acknowledgement = {Geran Inovasi Pengajaran dan Pembelajaran, Universiti Kebangsaan Malaysia {[}EP-2022-026]; Geran Inisiatif Penyelidikan (GIP), Universiti Kebangsaan Malaysia {[}EP-2021-021]}, Funding-Text = {This work was supported by Geran Inovasi Pengajaran dan Pembelajaran, Universiti Kebangsaan Malaysia (EP-2022-026) and Geran Inisiatif Penyelidikan (GIP), Universiti Kebangsaan Malaysia (EP-2021-021).}, Cited-References = {Ab Rahman R, 2018, INT J EDUC TECHNOL H, V15, DOI 10.1186/s41239-018-0123-0. 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Wang Y., 2003, Electronic Markets, V13, P33, DOI 10.1080/1019678032000052934. Wolf T, 2020, J BUS RES, V106, P353, DOI 10.1016/j.jbusres.2018.12.058. Xi NN, 2019, INT J INFORM MANAGE, V46, P210, DOI 10.1016/j.ijinfomgt.2018.12.002. Xu Y, 2020, FRONT PSYCHOL, V11, DOI 10.3389/fpsyg.2020.581200. Yaminfirooz Mousa, 2018, Acta Inform Med, V26, P10, DOI 10.5455/aim.2018.26.10-14. Yang Y, 2017, COMPUT HUM BEHAV, V73, P459, DOI 10.1016/j.chb.2017.03.066. Youngblood M, 2018, PALGR COMMUN, V4, DOI 10.1057/s41599-018-0175-8. Zupic I, 2015, ORGAN RES METHODS, V18, P429, DOI 10.1177/1094428114562629.}, Number-of-Cited-References = {54}, Times-Cited = {0}, Usage-Count-Last-180-days = {4}, Usage-Count-Since-2013 = {4}, Journal-ISO = {Int. J. Manag. Stud.}, Doc-Delivery-Number = {P5HA0}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:001050972300004}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:001043979600001, Author = {Sun, Yuting and Li, Yixuan}, Title = {Effects of misleading online advertisements on the purchase intention of mature Chinese consumers for dietary supplements}, Journal = {BRITISH FOOD JOURNAL}, Year = {2023}, Month = {2023 AUG 8}, Abstract = {PurposeAdvertisements for dietary supplements (DS) often include misleading claims regarding their health benefits. In this study, the authors designed an online advertisement for plant-based DS featuring misleading claims and investigated its effects on mature Chinese consumers before and after revealing the false claims. A consumer involvement framework was developed to evaluate the mediating effect of advertising involvement (AI) on the correlation between product involvement (PI), situational involvement (SI) and purchase intention (PI).Design/methodology/approachA total of 467 mature adults aged over 40 years who resided in China's Yangtze River Delta region and had experience in purchasing DS online were recruited. Relevant data were collected through an online survey and analysed through structural equation modelling.FindingsCognitive PI was positively correlated with both SI and PI and SI was positively correlated with PI. AI negatively moderated the correlation between affective PI and SI. Both cognitive PI and AI were positively correlated with PI and the correlation was mediated through SI.Originality/valueDS consumption is a rational decision-making process driven by utilitarian motives. Consumers who are aware of the misleading claims adopt a cautious evaluation approach and place themselves in specific purchase situations before making a purchase decision. This study advances the literature by incorporating the consideration of misleading advertisements into the consumer involvement model within the context of online DS consumption. The study's findings provide insights to intensify monitoring of false advertisements in the DS industry and design effective consumer education programmes.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Sun, YT (Corresponding Author), Hohai Univ, Sch Publ Adm, Nanjing, Peoples R China. Sun, Yuting; Li, Yixuan, Hohai Univ, Sch Publ Adm, Nanjing, Peoples R China.}, DOI = {10.1108/BFJ-01-2023-0029}, EarlyAccessDate = {AUG 2023}, ISSN = {0007-070X}, EISSN = {1758-4108}, Keywords = {Consumer involvement; Mature consumer; Misleading advertisement; Plant-based dietary supplement; Purchase intention}, Keywords-Plus = {HEALTH-INFORMATION-SEEKING; ORGANIC FOOD-CONSUMPTION; PRODUCT INVOLVEMENT; MODERATING ROLE; ADVERTISING EFFECTIVENESS; FUNCTIONAL FOOD; UNITED-STATES; OLDER-ADULTS; US ADULTS; ATTITUDES}, Research-Areas = {Agriculture; Food Science \& Technology}, Web-of-Science-Categories = {Agricultural Economics \& Policy; Food Science \& Technology}, Author-Email = {yutingsun@hhu.edu.cn liyixuan0209@163.com}, Affiliations = {Hohai University}, ORCID-Numbers = {SUN, YUTING/0000-0001-7590-3106}, Funding-Acknowledgement = {Fundamental Research Funds for the Central Universities, Hohai University, China {[}B220201066]}, Funding-Text = {This work was supported by the Fundamental Research Funds for the Central Universities, Hohai University, China (grant number B220201066).The authors highly appreciate the reviewers' insightful and helpful comments on our manuscript.}, Cited-References = {Abd Wahab MS, 2021, BMC COMPLEMENT MED, V21, DOI 10.1186/s12906-021-03287-1. 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Food J.}, Doc-Delivery-Number = {O5CC8}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:001043979600001}, DA = {2023-10-04}, } @article{ WOS:000449487800007, Author = {Wirtz, Jochen and Patterson, Paul G. and Kunz, Werner H. and Gruber, Thorsten and Lu, Vinh Nhat and Paluch, Stefanie and Martins, Antje}, Title = {Brave new world: service robots in the frontline}, Journal = {JOURNAL OF SERVICE MANAGEMENT}, Year = {2018}, Volume = {29}, Number = {5, SI}, Pages = {907-931}, Abstract = {Purpose The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers. Design/methodology/approach This paper uses a conceptual approach that is rooted in the service, robotics and AI literature. Findings The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level. Practical implications This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots. Originality/value This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Wirtz, J (Corresponding Author), Natl Univ Singapore, Dept Mkt, Singapore, Singapore. Wirtz, Jochen, Natl Univ Singapore, Dept Mkt, Singapore, Singapore. Patterson, Paul G., Univ New South Wales, Dept Mkt, Sydney, NSW, Australia. Kunz, Werner H., Univ Massachusetts, Dept Mkt, Boston, MA 02125 USA. Gruber, Thorsten, Loughborough Univ, Ctr Serv Management, Loughborough, Leics, England. Lu, Vinh Nhat, Australian Natl Univ, Res Sch Management, Canberra, ACT, Australia. Paluch, Stefanie, Rheinisch Westfalische Tech Hsch Aachen Univ, Sch Business \& Econ, Aachen, Germany. Martins, Antje, Univ Queensland, Business Sch, Brisbane, Qld, Australia.}, DOI = {10.1108/JOSM-04-2018-0119}, ISSN = {1757-5818}, EISSN = {1757-5826}, Keywords = {Consumer behaviour; Ethics; Artificial intelligence; Privacy; Service robots; Markets}, Keywords-Plus = {UNIVERSAL DIMENSIONS; PROFIT CHAIN; TECHNOLOGY; FUTURE; MODEL; ACCEPTANCE; METAANALYSIS; PERCEPTION; ALGORITHMS; SURFACE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Author-Email = {bizwirtz@nus.edu.sg}, Affiliations = {National University of Singapore; University of New South Wales Sydney; University of Massachusetts System; University of Massachusetts Boston; Loughborough University; Australian National University; RWTH Aachen University; University of Queensland}, ResearcherID-Numbers = {Wirtz, Jochen/P-3235-2015 Wirtz, Jochen/AAQ-9331-2021 Martins, Antje/R-6542-2018 Klitzke, Karina/IXD-3488-2023 Gruber, Thorsten/C-3445-2013 }, ORCID-Numbers = {Wirtz, Jochen/0000-0002-6297-4498 Wirtz, Jochen/0000-0002-6297-4498 Martins, Antje/0000-0003-1534-8598 Lu, Vinh/0000-0001-6995-5313}, Cited-References = {Allen C, 2000, J EXP THEOR ARTIF IN, V12, P251, DOI 10.1080/09528130050111428. 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Manage.}, Doc-Delivery-Number = {GZ5SN}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000449487800007}, OA = {Green Published, Green Submitted, hybrid}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:001060595700003, Author = {Meng, Lingxing and Dong, Tianyu}, Title = {RETRACTION: Study on factors influencing e-commerce in short videos based on artificial intelligence-supported recommendation (Retraction of November, 2022)}, Journal = {JOURNAL OF ELECTRONIC IMAGING}, Year = {2023}, Volume = {32}, Number = {3}, Month = {MAY-JUN}, Abstract = {Short video platforms, represented by TikTok, are gaining popularity across the world. Although mainly for entertainment and social interactions, short video mobile apps are intensively testing embedded e-commerce in short videos based on artificial intelligence (AI)-supported recommendation in the United States, Europe, China, and other countries and regions. To study users' acceptance of embedded e-commerce in short videos based on AI-supported recommendation, we make an analysis with a number of factors as independent variables, concluding that perceived risk and perceived cost have a significant negative influence on purchase intention, whereas other independent variables have a significant positive influence on purchase intention. In addition, perceived enjoyment and conformity, embodying the entertainment and social features of short video apps, have a significant positive influence on perceived usefulness. We provide a guideline for enterprises to improve functions of the technology and informs public oversight of the technology's development. (C) 2022 SPIE and IS\&T}, Publisher = {SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS}, Address = {1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98225 USA}, Type = {Retraction}, Language = {English}, Affiliation = {Dong, TY (Corresponding Author), China Univ Polit Sci \& Law, Dept Theoret Econ, Coll Business, Beijing, Peoples R China. Meng, Lingxing, China Univ Polit Sci \& Law, Dept Law \& Business, Coll Business, Beijing, Peoples R China. Dong, Tianyu, China Univ Polit Sci \& Law, Dept Theoret Econ, Coll Business, Beijing, Peoples R China.}, DOI = {10.1117/1.JEI.32.3.031805}, Article-Number = {031805}, ISSN = {1017-9909}, EISSN = {1560-229X}, Keywords = {artificial intelligence; e-commerce in short videos; technology acceptance model; perceived enjoyment; conformity}, Keywords-Plus = {ACCEPTANCE}, Research-Areas = {Engineering; Optics; Imaging Science \& Photographic Technology}, Web-of-Science-Categories = {Engineering, Electrical \& Electronic; Optics; Imaging Science \& Photographic Technology}, Author-Email = {2002060230@cupl.edu.cn}, Affiliations = {China University of Political Science \& Law; China University of Political Science \& Law}, Cited-References = {Bauer R. A., 2001, MARKET CRIT PERSPECT, V3, P13. Chen CC, 2018, TELEMAT INFORM, V35, P293, DOI 10.1016/j.tele.2017.12.003. Childers TL, 2001, J RETAILING, V77, P511, DOI 10.1016/S0022-4359(01)00056-2. 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Zhang Y., 2018, INFORM SCIENCES, V36, P111. Zulli D, 2022, NEW MEDIA SOC, V24, P1872, DOI 10.1177/1461444820983603.}, Number-of-Cited-References = {20}, Times-Cited = {0}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {1}, Journal-ISO = {J. Electron. Imaging}, Doc-Delivery-Number = {Q9JA9}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:001060595700003}, DA = {2023-10-04}, } @article{ WOS:000665551600001, Author = {Toubes, Diego R. and Araujo Vila, Noelia and Fraiz Brea, Jose A.}, Title = {Changes in Consumption Patterns and Tourist Promotion after the COVID-19 Pandemic}, Journal = {JOURNAL OF THEORETICAL AND APPLIED ELECTRONIC COMMERCE RESEARCH}, Year = {2021}, Volume = {16}, Number = {5}, Pages = {1332-1352}, Month = {AUG}, Abstract = {The COVID-19 pandemic has entailed an unprecedented health crisis with significant economic impacts in many sectors worldwide. The tourism sector has been one of the most affected, with significant impacts on the number of cancelled reservations, a decrease in international travel and changes in consumption behaviour. This study aims to analyse the main changes in promotion and marketing in the tourism sector in Spain after the pandemic. To this end, a qualitative analysis was carried out via questionnaire-based interviews with 65 experts in the areas of marketing, consumer behaviour and tourism. The main findings show that online information sources gained weight over consulting friends and relatives, and a great advance in digitization is expected, where physical travel agencies will be displaced by online platforms, except for specialized and advisory services. Additionally, technologies such as virtual reality (VR) or artificial intelligence (AI) may play an increasingly important role in the medium term.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Vila, NA (Corresponding Author), Univ Vigo, Fac Business \& Tourism, Orense 32004, Spain. Toubes, Diego R.; Araujo Vila, Noelia; Fraiz Brea, Jose A., Univ Vigo, Fac Business \& Tourism, Orense 32004, Spain.}, DOI = {10.3390/jtaer16050075}, ISSN = {0718-1876}, Keywords = {consumption; marketing; promotion; tourism; digitalization; COVID-19}, Keywords-Plus = {IMPACTS; RISK; INDUSTRY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {drtoubes@uvigo.es naraujo@uvigo.es jafraiz@uvigo.es}, Affiliations = {Universidade de Vigo}, ResearcherID-Numbers = {FRAIZ BREA, JOSE ANTONIO/G-4431-2015 Toubes, Diego/E-9399-2019 }, ORCID-Numbers = {FRAIZ BREA, JOSE ANTONIO/0000-0002-3190-6492 Toubes, Diego/0000-0001-7017-6659 ARAUJO VILA, NOELIA/0000-0002-3395-8536}, Cited-References = {Akram U, 2018, ASIA PAC J MARKET LO, V30, P235, DOI 10.1108/APJML-04-2017-0073. Al-Ghraibah O.B., 2020, J CRIT REV, V7, P2464, DOI DOI 10.31838/JCR.07.09.399. 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Res.}, Doc-Delivery-Number = {SX9YB}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000665551600001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000523963700001, Author = {Yen, Chiahui and Chiang, Ming-Chang}, Title = {Trust me, if you can: a study on the factors that influence consumers' purchase intention triggered by chatbots based on brain image evidence and self-reported assessments}, Journal = {BEHAVIOUR \& INFORMATION TECHNOLOGY}, Year = {2021}, Volume = {40}, Number = {11}, Pages = {1177-1194}, Month = {AUG 18}, Abstract = {Nowadays, chatbots is one of the fast rising artificial intelligence (AI) trend relates to the utilisation of applications that interact with users in a conversational format and mimic human conversation. Chatbots allow business to enhance customer experiences and fulfil expectations through real-time interactions in e-commerce environment. Therefore, factors influence consumer's trust in chatbots is critical. This study demonstrates a chatbots trust model to empirically investigate consumer's perception by questionnaire from self-reported approach and by electroencephalography (EEG) from neuroscience approach. This study starts from integrating three key elements of chatbots, in terms of machine communication quality aspect, human-computer interaction (HCI) aspect, and human use and gratification (U\&G) aspects. Moreover, this study chooses EEG instrument to explore the relationship between trust and purchase intention in chatbots condition. We collect 204 questionnaires and invite 30 respondents to participate the survey. The results indicated that credibility, competence, anthropomorphism, social presence, and informativness have influence on consumer's trust in chatbots, in turn, have effect on purchase intention. Moreover, the findings show that the dorsolateral prefrontal cortex and the superior temporal gyrus are significantly associated with building a trust relationship by inferring chatbots to influence subsequent behaviour.}, Publisher = {TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Chiang, MC (Corresponding Author), Fu Jen Catholic Univ, Dept Life Sci, Taipei 242, Taiwan. Yen, Chiahui, Ming Chuan Univ, Dept Int Business, Taipei, Taiwan. Chiang, Ming-Chang, Fu Jen Catholic Univ, Coll Sci \& Engn, Dept Life Sci, Taipei, Taiwan.}, DOI = {10.1080/0144929X.2020.1743362}, EarlyAccessDate = {MAR 2020}, ISSN = {0144-929X}, EISSN = {1362-3001}, Keywords = {Trust; chatbots; neuroscience; electroencephalography (EEG); purchase intention}, Keywords-Plus = {PRODUCT RECOMMENDATION AGENTS; SOCIAL NETWORKING SITES; CONVERSATIONAL AGENT; E-COMMERCE; MEDIA; NEUROSCIENCE; MODEL; GRATIFICATIONS; CREDIBILITY; PERSPECTIVE}, Research-Areas = {Computer Science; Engineering}, Web-of-Science-Categories = {Computer Science, Cybernetics; Ergonomics}, Author-Email = {cmcphd@gmail.com}, Affiliations = {Ming Chuan University; Fu Jen Catholic University}, Funding-Acknowledgement = {Ministry of Science and Technology}, Funding-Text = {This work was supported by Ministry of Science and Technology.}, Cited-References = {Anderson BB, 2016, J MANAGE INFORM SYST, V33, P713, DOI 10.1080/07421222.2016.1243947. 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Xu CY, 2012, INFORM MANAGE-AMSTER, V49, P210, DOI 10.1016/j.im.2012.05.001. Zahn R, 2007, P NATL ACAD SCI USA, V104, P6430, DOI 10.1073/pnas.0607061104. Zumstein D., 2017, IADIS INT J WWW INTE, V15, P96.}, Number-of-Cited-References = {112}, Times-Cited = {57}, Usage-Count-Last-180-days = {40}, Usage-Count-Since-2013 = {189}, Journal-ISO = {Behav. Inf. Technol.}, Doc-Delivery-Number = {UY1WD}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000523963700001}, DA = {2023-10-04}, } @article{ WOS:000817724600018, Author = {Li, Xia}, Title = {The Impact of the Live Delivery of Goods on Consumers' Purchasing Behaviour in Complex Situations Based on Artificial Intelligence Technology}, Journal = {COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE}, Year = {2022}, Volume = {2022}, Month = {JUN 15}, Abstract = {With the development of information technology, the purchase of goods online has acquired a different dimension. This type of online purchase has made life easier for individuals by reducing the time required to travel and purchase. This online purchasing and delivery of goods or products follow the concept of supply chain management. Mobile Internet, tracking sensors, and tags that aid in tracking processes are used in online supply chain management. For data transfer and status updates, these devices rely on wireless sensor networking technology. This research analyses consumer behaviour after the delivery of goods using wireless sensor networks and artificial intelligence. This behaviour analysis focuses on whether the consumer is satisfied with the product in complex situations or not. The analysis is performed with the Differential-Evolutionary Multiobjective Optimization (D-EMO) algorithm with the aid of artificial intelligence. The proposed system's results were compared with the existing random forest algorithm, and it was observed that the proposed system had provided a 5\% increase in accuracy.}, Publisher = {HINDAWI LTD}, Address = {ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON, W1T 5HF, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Li, X (Corresponding Author), Shandong Vocat Coll Sci \& Technol, Text \& Garment Dept, Weifang 261053, Shandong, Peoples R China. Li, Xia, Shandong Vocat Coll Sci \& Technol, Text \& Garment Dept, Weifang 261053, Shandong, Peoples R China.}, DOI = {10.1155/2022/1424099}, Article-Number = {1424099}, ISSN = {1687-5265}, EISSN = {1687-5273}, Keywords-Plus = {DECISION}, Research-Areas = {Mathematical \& Computational Biology; Neurosciences \& Neurology}, Web-of-Science-Categories = {Mathematical \& Computational Biology; Neurosciences}, Author-Email = {0021090@yzpc.edu.cn}, Cited-References = {Alghamdi EA, 2020, INT J ONLINE MARKET, V10, P72, DOI 10.4018/IJOM.2020010105. Alversia Y, 2016, DEV MKT SCI, P849. {[}Anonymous], 2016, CONSUMER BEHAV TOURI. Bandara D.M., 2020, SSRN ELECT J, DOI {[}10.2139/ssrn.3862941, DOI 10.2139/SSRN.3862941]. Chen J.I.-Z., 2021, J ARTIFICIAL INTELLI, V2, P232, DOI {[}10.36548/jaicn.2020.4.006, DOI 10.36548/JAICN.2020.4.006]. Chhabra D., 2018, J ADV SCHOLARLY RESE, V15, P131, DOI {[}10.29070/15/57735, DOI 10.29070/15/57735]. 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Pappas N, 2016, J RETAIL CONSUM SERV, V29, P92, DOI 10.1016/j.jretconser.2015.11.007. Pradeep A.K., 2018, AI MARKETING PRODUCT. Stankevich A., 2017, J INT BUSINESS RES M, V2, P7, DOI {[}10.18775/jibrm.1849-8558.2015.26.3001, DOI 10.18775/JIBRM.1849-8558.2015.26.3001]. Sultana, 2020, OPEN J BUSINESS MANA, V8, P2696, DOI DOI 10.4236/OJBM.2020.86167. Van Esch P, 2021, J ASSOC CONSUM RES, V6, P394, DOI 10.1086/714503.}, Number-of-Cited-References = {22}, Times-Cited = {1}, Usage-Count-Last-180-days = {4}, Usage-Count-Since-2013 = {9}, Journal-ISO = {Comput. Intell. Neurosci.}, Doc-Delivery-Number = {2M5FJ}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000817724600018}, OA = {Green Published, gold}, DA = {2023-10-04}, } @article{ WOS:000747545600002, Author = {Yuan, Chunlin and Zhang, Chenlei and Wang, Shuman}, Title = {Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values}, Journal = {JOURNAL OF RETAILING AND CONSUMER SERVICES}, Year = {2022}, Volume = {65}, Month = {MAR}, Abstract = {This study develops a comprehensive research model to explain user willingness to accept AI assistants, and the acceptance path pertaining to this process. User data was used to test how the advantages of AI assistant (accuracy, responsiveness, compatibility, anthropomorphism, \& affinity) influence consumer utilitarian and hedonic value, and explore how their willingness to accept AI assistants is affected by their value perceptions. This research also examines whether social anxiety moderates the relationship between AI assistant advantages and utilitarian/hedonic value. The study reveals that AI assistant advantages are important factors affecting the utilitarian/hedonic value perceived by users, which further influence user willingness to accept AI assistants. The relationships between AI assistant advantages and utilitarian and hedonic value are affected differently by social anxiety. Marketers and managers in the AI context can refer to the study methods to help improve AI assistants and develop more effective marketing strategies for product promotion.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Wang, SM (Corresponding Author), Shanghai Jiao Tong Univ, Antai Coll Econ \& Management, Shanghai, Peoples R China. Yuan, Chunlin, Henan Univ, Business Sch, Business Management Inst, Kaifeng City, Henan, Peoples R China. Zhang, Chenlei, Beijing Jiaotong Univ, Sch Econ \& Management, Beijing, Peoples R China. Wang, Shuman, Shanghai Jiao Tong Univ, Antai Coll Econ \& Management, Shanghai, Peoples R China.}, DOI = {10.1016/j.jretconser.2021.102878}, EarlyAccessDate = {DEC 2021}, Article-Number = {102878}, ISSN = {0969-6989}, EISSN = {1873-1384}, Keywords = {Artificial intelligence assistant; Utilitarian value; Hedonic value; Social anxiety}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE; PARASOCIAL RELATIONSHIP; PURCHASE INTENTION; PRIVACY CONCERNS; INTERNET USE; INFORMATION; ADOPTION; MOTIVATIONS; INNOVATION; MODEL}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {marketingycl@163.com Freedom135@163.com 15617130566@163.com}, Affiliations = {Henan University; Beijing Jiaotong University; Shanghai Jiao Tong University}, ResearcherID-Numbers = {Klitzke, Karina/IXD-3488-2023 }, ORCID-Numbers = {, Chunlin/0000-0003-4110-2348}, Funding-Acknowledgement = {National Natural Science Foundation of China {[}72172044, 71702049]; China Postdoctoral Science Foundation {[}2021T140178, 2018M630816]}, Funding-Text = {This research is supported by the National Natural Science Foundation of China (Grant No. 72172044 and 71702049) and the China Postdoctoral Science Foundation Grant (Grant No. 2021T140178 and 2018M630816).}, Cited-References = {Ameen N, 2021, COMPUT HUM BEHAV, V114, DOI 10.1016/j.chb.2020.106548. 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Serv.}, Doc-Delivery-Number = {YN9BJ}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000747545600002}, DA = {2023-10-04}, } @article{ WOS:000886641800001, Author = {Sharma, Shavneet and Singh, Gurmeet and Gaur, Loveleen and Afaq, Anam}, Title = {Exploring customer adoption of autonomous shopping systems}, Journal = {TELEMATICS AND INFORMATICS}, Year = {2022}, Volume = {73}, Month = {SEP}, Abstract = {Autonomous technology is on the rise, allowing customers to delegate shopping tasks and decisions to such artificial intelligence-based systems. However, trust and privacy issues are impeding the adoption of such technology. This study examines the factors affecting the adoption of autonomous shopping systems. A conceptual framework is developed by adding trust and moderating variables of privacy concern to the UTAUT model. Using a quantitative research design, data is collected from 454 respondents and analysed using covariance-based structural equation modelling. Results show that performance expectancy, effort expectancy, social influence, and facilitating conditions positively impact perceived trust in autonomous shopping systems. Privacy concern as a moderator dampens the positive relationship between performance expectancy and perceived trust. Also, privacy concerns dampen the positive relationship between social influence and perceived trust. This study is one of the first to empirically examine customers' autonomous shopping system intention by revising the UTAUT with trust and privacy concerns. These findings generate valuable insights into an under-researched area of customer behaviour and artificial intelligence.}, Publisher = {ELSEVIER}, Address = {RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}, Type = {Article}, Language = {English}, Affiliation = {Singh, G (Corresponding Author), Univ South Pacif, Sch Business \& Management, Suva, Fiji. Sharma, Shavneet; Singh, Gurmeet, Univ South Pacif, Sch Business \& Management, Suva, Fiji. Gaur, Loveleen; Afaq, Anam, Amity Univ, Amity Int Business Sch, Noida, India.}, DOI = {10.1016/j.tele.2022.101861}, EarlyAccessDate = {JUL 2022}, Article-Number = {101861}, ISSN = {0736-5853}, Keywords = {Autonomous shopping systems; Artificial intelligence; UTAUT; Trust; Privacy concern; Covariance-based structural equation modelling}, Keywords-Plus = {INFORMATION-TECHNOLOGY; CONSUMERS ACCEPTANCE; EXTENDING UTAUT2; PRIVACY CONCERNS; USER ACCEPTANCE; PERCEIVED RISK; TRUST; ADVERTISEMENT; WILLINGNESS; VEHICLES}, Research-Areas = {Information Science \& Library Science}, Web-of-Science-Categories = {Information Science \& Library Science}, Author-Email = {singh\_g@usp.ac.fj}, Affiliations = {Amity University Noida}, ResearcherID-Numbers = {Afaq, Anam/AAA-6441-2022 Singh, Gurmeet/Q-7326-2019 Gaur, Loveleen/ABB-9664-2020}, ORCID-Numbers = {Afaq, Anam/0000-0003-3181-7630 Singh, Gurmeet/0000-0003-2931-0670 Gaur, Loveleen/0000-0002-0885-1550}, Cited-References = {Aguirre E, 2015, J RETAILING, V91, P34, DOI 10.1016/j.jretai.2014.09.005. 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Widjaja AE, 2019, COMPUT HUM BEHAV, V91, P167, DOI 10.1016/j.chb.2018.09.034. Wong LW, 2020, INT J PROD RES, V58, P2100, DOI 10.1080/00207543.2020.1730463. Xu Z, 2019, TECHNOL FORECAST SOC, V143, P297, DOI 10.1016/j.techfore.2019.01.018. Zarifis A, 2021, J INTERNET COMMER, V20, P66, DOI 10.1080/15332861.2020.1832817. Zhao YY, 2020, INT J HOSP MANAG, V91, DOI 10.1016/j.ijhm.2020.102683. Zhou M, 2020, J RETAIL CONSUM SERV, V52, DOI 10.1016/j.jretconser.2019.101911.}, Number-of-Cited-References = {84}, Times-Cited = {2}, Usage-Count-Last-180-days = {12}, Usage-Count-Since-2013 = {27}, Journal-ISO = {Telemat. Inform.}, Doc-Delivery-Number = {6J2FD}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000886641800001}, OA = {Green Accepted}, DA = {2023-10-04}, } @article{ WOS:000893405000001, Author = {Rohden, Simoni F. and Zeferino, Diully Garcia}, Title = {Recommendation agents: an analysis of consumers' risk perceptions toward artificial intelligence}, Journal = {ELECTRONIC COMMERCE RESEARCH}, Year = {2022}, Month = {2022 DEC 3}, Abstract = {Tools that use artificial intelligence to improve consumer experiences and automate processes, such as recommendation agents have been widely adopted by companies. However, the use of this type of technology can increase a user's perception of a risk to data privacy. This article aims to go more in-depth into what is known about the variables that impact this perception of risk related to recommendation agents. By way of an exploratory study with in-depth interviews followed by a survey, it was possible to identify how aspects such as a concern with data and the perceived risk in online shopping increase the sense of a risk to privacy. Consumers are generally unaware of how recommendation agents work, which makes them unsure about their usability and purpose. Consumer trust, however, mediates this relationship by mitigating the negative effects of risk perception.}, Publisher = {SPRINGER}, Address = {VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Rohden, SF (Corresponding Author), IPAM Lisboa, Portuguese Mkt Management Inst, Estr Correia 54, P-1500210 Lisbon, Portugal. Rohden, Simoni F., IPAM Lisboa, Portuguese Mkt Management Inst, Estr Correia 54, P-1500210 Lisbon, Portugal. Zeferino, Diully Garcia, Unisinos Univ, Unisinos Business Sch, Sao Leopoldo, Brazil.}, DOI = {10.1007/s10660-022-09626-9}, EarlyAccessDate = {DEC 2022}, ISSN = {1389-5753}, EISSN = {1572-9362}, Keywords = {Recommendation agents; Online consumer behaviour; Data privacy; Risk; Trust}, Keywords-Plus = {TRUST}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, Author-Email = {simoni.rohden@universidadeeuropeia.pt diully.g@gmail.com}, Affiliations = {Universidade do Vale do Rio dos Sinos (Unisinos)}, ResearcherID-Numbers = {Rohden, Simoni F./IUN-5431-2023}, ORCID-Numbers = {Rohden, Simoni F./0000-0002-6173-066X}, Cited-References = {Barth S, 2019, TELEMAT INFORM, V41, P55, DOI 10.1016/j.tele.2019.03.003. Cabiddu F., 2022, EUR MANAG J, V40, P685. Chakraborty S, 2021, INFORMATICS-BASEL, V8, DOI 10.3390/informatics8030049. Dabholkar PA, 2012, SERV IND J, V32, P1433, DOI 10.1080/02642069.2011.624596. 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Commer. Res.}, Doc-Delivery-Number = {6T0WV}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000893405000001}, DA = {2023-10-04}, } @article{ WOS:000822651400005, Author = {Rashidin, Md Salamun and Gang, Dong and Javed, Sara and Hasan, Morshadul}, Title = {The Role of Artificial Intelligence in Sustaining the E-Commerce Ecosystem: Alibaba vs. Tencent}, Journal = {JOURNAL OF GLOBAL INFORMATION MANAGEMENT}, Year = {2022}, Volume = {30}, Number = {8}, Abstract = {A large number of customers have used traditional e-commerce portals, where there are no assurances of product quality, display of all features, picture search, virtual chat service, product recommendation, and tracking facility. Due to these disadvantages, the customers have switched to Alibaba and Tencent products line and remain in the ecosystem. The present study drew on Quo Bias theory to investigate the customer behaviour to remain on the e-commerce platform. Twenty-eight in-depth interviews were conducted to extract the variables and propose a model based on risk theory as well as CRCB framework. An offline survey was distributed to 649 (valid) ecommerce users; valid data was assessed and analyzed using structural equation modeling (SEM). Results show CRCB was influenced by switching cost and comparative attraction. Moreover, negative (undesirable) attitudes mediate the relationship between risk perception and CRCB, which has a positive impact on undesirable WoM. The study findings help the managers and policy makers to devise a new policy and serve the customers in a better way.}, Publisher = {IGI GLOBAL}, Address = {701 E CHOCOLATE AVE, STE 200, HERSHEY, PA 17033-1240 USA}, Type = {Article}, Language = {English}, Affiliation = {Rashidin, MS (Corresponding Author), Univ Int Business \& Econ, Beijing, Peoples R China. Rashidin, Md Salamun; Javed, Sara, Univ Int Business \& Econ, Beijing, Peoples R China. Gang, Dong, Cent Supply Chain Cloud Finance Co Ltd, Beijing, Peoples R China. Hasan, Morshadul, Murdoch Univ, Murdoch Business Sch, Murdoch, WA, Australia.}, DOI = {10.4018/JGIM.304067}, ISSN = {1062-7375}, EISSN = {1533-7995}, Keywords = {AI; Alibaba; China; Ecommerce; Sustainable; Tencent}, Keywords-Plus = {CUSTOMER LOYALTY; SWITCHING COSTS; PERCEIVED RISK; INITIAL TRUST; E-WOM; MODEL; SATISFACTION; RESISTANCE; INTENTIONS; INNOVATION}, Research-Areas = {Information Science \& Library Science}, Web-of-Science-Categories = {Information Science \& Library Science}, Affiliations = {University of International Business \& Economics; Murdoch University}, ResearcherID-Numbers = {Rashidin, Md.Salamun/Z-2050-2019 , 卢帅/AAK-2185-2020}, ORCID-Numbers = {Rashidin, Md.Salamun/0000-0003-1273-8494 , 卢帅/0000-0001-9857-9265}, Cited-References = {Abu-ELSamen Amjad A., 2011, International Journal of Commerce \& Management, V21, P349, DOI 10.1108/10569211111189365. 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Manag.}, Doc-Delivery-Number = {2T7LM}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000822651400005}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000870957700001, Author = {Yuan, Chunlin and Wang, Shuman and Liu, Yue}, Title = {Al service impacts on brand image and customer equity: empirical evidence from China}, Journal = {JOURNAL OF BRAND MANAGEMENT}, Year = {2023}, Volume = {30}, Number = {1}, Pages = {61-76}, Month = {JAN}, Abstract = {This paper examines the relations among AI service attributes, brand image, brand familiarity and customer equity. The proposed relationships were tested by structural equation modeling of survey data of 210 usable responses in China. Test results indicate that problem-solving ability, accuracy, and customization of AI service have significant positive effects on brand image; the three constructs of customer equity (value equity, brand equity, and relationship equity) are all positively and strongly affected by brand image. Moreover, brand familiarity moderates the effect of customization, interaction, and problem-solving ability on brand image. By bringing together AI literature and consumer behavior literature, this research sheds light on the effectiveness of AI service in enhancing brand image and customer equity. This has important theoretical value in enriching the streams of AI and brand research. Additionally, this research integrates the AI technology within a corporate brand management strategy and offers practitioners and marketers in post-COVID era with a model with which they can find new ways to meet consumer demands and improve brand image via AI technology.}, Publisher = {PALGRAVE MACMILLAN LTD}, Address = {BRUNEL RD BLDG, HOUNDMILLS, BASINGSTOKE RG21 6XS, HANTS, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Wang, SM (Corresponding Author), Henan Univ, Business Sch, Kaifeng City, Henan, Peoples R China. Yuan, Chunlin, Henan Univ, Business Management Inst, Kaifeng City, Henan, Peoples R China. Wang, Shuman; Liu, Yue, Henan Univ, Business Sch, Kaifeng City, Henan, Peoples R China.}, DOI = {10.1057/s41262-022-00292-8}, EarlyAccessDate = {OCT 2022}, ISSN = {1350-231X}, EISSN = {1479-1803}, Keywords = {Artificial intelligence service; Brand image; Customer equity; Brand familiarity}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE; PURCHASE INTENTION; PARASOCIAL RELATIONSHIP; ANTHROPOMORPHISM; FAMILIARITY; VARIANCE; TRUST; DIMENSIONS; MANAGEMENT; CONSUMERS}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, Author-Email = {marketingycl@163.com 15617130566@163.com 990195328@qq.com}, Affiliations = {Henan University; Henan University}, Funding-Acknowledgement = {National Natural Science Foundation of China {[}72172044, 71702049]; China Postdoctoral Science Foundation {[}2021T140178]}, Funding-Text = {This research is supported by the National Natural Science Foundation of China (Grant No. 72172044; 71702049) and the China Postdoctoral Science Foundation Grant (Grant No. 2021T140178).}, Cited-References = {Aaker DA, 1996, CALIF MANAGE REV, V38, P102, DOI 10.2307/41165845. 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Brand Manag.}, Doc-Delivery-Number = {7Y5WF}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000870957700001}, DA = {2023-10-04}, } @article{ WOS:000641329700004, Author = {Ameen, Nisreen and Hosany, Sameer and Tarhini, Ali}, Title = {Consumer interaction with cutting-edge technologies: Implications for future research}, Journal = {COMPUTERS IN HUMAN BEHAVIOR}, Year = {2021}, Volume = {120}, Month = {JUL}, Abstract = {This article provides an overview of extant literature addressing consumer interaction with cutting-edge technologies. Six focal cutting-edge technologies are identified: artificial intelligence, augmented reality, virtual reality, wearable technology, robotics and big data analytics. Our analysis shows research on consumer interaction with cutting-edge technologies is at a nascent stage, and there are several gaps requiring attention. To further advance knowledge, our article offers avenues for future interdisciplinary research addressing implications of consumer interaction with cutting-edge technologies. More specifically, we propose six main areas for future research namely: rethinking consumer behaviour models, identifying behavioural differences among different generations of consumers, understanding how consumers interact with automated services, ethics, privacy and the blackbox, consumer security concerns and consumer interaction with new-age technologies during and after a major global crisis such as the COVID-19 pandemic.}, Publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Ameen, N (Corresponding Author), Royal Holloway Univ London, Sch Management, Egham TW20 0EX, Surrey, England. Ameen, Nisreen; Hosany, Sameer, Royal Holloway Univ London, Sch Business \& Management, Egham, Surrey, England. Tarhini, Ali, Sultan Qaboos Univ, Dept Informat Syst, Muscat, Oman.}, DOI = {10.1016/j.chb.2021.106761}, EarlyAccessDate = {MAR 2021}, Article-Number = {106761}, ISSN = {0747-5632}, EISSN = {1873-7692}, Keywords = {Consumer interaction; Cutting-edge technologies; Artificial intelligence; Virtual reality and augmented reality; Robotics; Wearable technology; Big data analytics}, Keywords-Plus = {BIG DATA ANALYTICS; AUGMENTED REALITY TECHNOLOGY; VIRTUAL-REALITY; OMNICHANNEL; EXPERIENCE; IMPACT; TRANSFORMATION; INTENTION; COMMERCE; ROBOTS}, Research-Areas = {Psychology}, Web-of-Science-Categories = {Psychology, Multidisciplinary; Psychology, Experimental}, Author-Email = {nisreen.ameen@rhul.ac.uk}, Affiliations = {University of London; Royal Holloway University London; Sultan Qaboos University}, ResearcherID-Numbers = {Gui, Yuliang/AAP-5071-2021 Hosany, Sameer/AAY-6908-2021 Tarhini, Ali/B-5045-2016}, ORCID-Numbers = {Hosany, Sameer/0000-0003-2654-9096 Tarhini, Ali/0000-0002-8698-1764}, Cited-References = {Adadi A, 2018, IEEE ACCESS, V6, P52138, DOI 10.1109/ACCESS.2018.2870052. 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Yim MYC, 2017, J INTERACT MARK, V39, P89, DOI 10.1016/j.intmar.2017.04.001. Zaatarti S., 2019, GULF NEWS ASKS GEN Z. Zakariah A, 2021, COMPUT HUM BEHAV, V118, DOI 10.1016/j.chb.2021.106699. Zaki M, 2019, J SERV MARK, V33, P429, DOI 10.1108/JSM-01-2019-0034.}, Number-of-Cited-References = {84}, Times-Cited = {45}, Usage-Count-Last-180-days = {13}, Usage-Count-Since-2013 = {122}, Journal-ISO = {Comput. Hum. Behav.}, Doc-Delivery-Number = {RO8ZR}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000641329700004}, DA = {2023-10-04}, } @article{ WOS:000762853600001, Author = {Lee, Minsun and Park, Jee-Sun}, Title = {Do parasocial relationships and the quality of communication with AI shopping chatbots determine middle-aged women consumers' continuance usage intentions?}, Journal = {JOURNAL OF CONSUMER BEHAVIOUR}, Year = {2022}, Volume = {21}, Number = {4}, Pages = {842-854}, Month = {JUL}, Abstract = {Artificial intelligence (AI) assistants, or chatbots, have become widely used on several retailers' websites. Effective interaction and communication with AI chatbots can deliver a better consumer experience by assisting with decision-making, ultimately supporting purchase intentions. Based on parasocial theory, this study focuses on how interactions with AI shopping chatbots impact consumers' perceptions of communication quality, satisfaction, and continuance usage intentions. Partial least squares structural equation modeling (PLS-SEM) was employed to assess the proposed research model using data from 184 Korean middle-aged women who shop online. Participants completed the shopping process with the assistance of an AI shopping chatbot and responded to survey items about their experiences. In particular, the findings reveal the structural process whereby a consumer's parasocial relationship with an AI shopping chatbot ultimately increases continuance usage intentions through perceived communication quality and satisfaction. The results indicate that a parasocial relationship positively influences communication quality with the chatbot, which in turn increases satisfaction and continuance usage intentions. These findings provide marketers with theoretical and practical guidance for enhancing consumer experiences in the online shopping environment.}, Publisher = {WILEY}, Address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, Type = {Article}, Language = {English}, Affiliation = {Park, JS (Corresponding Author), Incheon Natl Univ, Dept Fash Ind, 119 Acad Ro, Incheon 22012, South Korea. Lee, Minsun, Konkuk Univ, Dept Fash Design, Glocal Campus, Chungju, South Korea. Park, Jee-Sun, Incheon Natl Univ, Dept Fash Ind, 119 Acad Ro, Incheon 22012, South Korea.}, DOI = {10.1002/cb.2043}, EarlyAccessDate = {MAR 2022}, ISSN = {1472-0817}, EISSN = {1479-1838}, Keywords-Plus = {COMMON METHOD VARIANCE; PURCHASE INTENTION; SOCIAL COMMERCE; SATISFACTION; PERCEPTIONS; MODEL; ANTECEDENTS; PERFORMANCE; ASSISTANTS; EXPERIENCE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {jpark@inu.ac.kr}, Affiliations = {Konkuk University; Incheon National University}, ORCID-Numbers = {lee, minsun/0000-0001-6354-2956}, Cited-References = {Agarwal R., 2018, 10 EXAMPLES ARTIFICI. Akhtar M, 2019, CONF BUS INFORM, P397, DOI 10.1109/CBI.2019.00052. Al Serhan YN, 2015, J SMALL BUS ENTERP D, V22, P288, DOI 10.1108/JSBED-02-2012-0017. Araujo T, 2020, SMART INNOV SYST TEC, V167, P278, DOI 10.1007/978-981-15-1564-4\_26. Ashfaq M, 2020, TELEMAT INFORM, V54, DOI 10.1016/j.tele.2020.101473. 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Behav.}, Doc-Delivery-Number = {2U0BM}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000762853600001}, DA = {2023-10-04}, } @inproceedings{ WOS:000821855600279, Author = {Toplu, A. and Liu, H.}, Book-Group-Author = {IEEE}, Title = {Designing a Deceptive Comment Detection Platform with a Rule-based Artificial Intelligent Architecture}, Booktitle = {2021 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEE IEEM21)}, Series = {International Conference on Industrial Engineering and Engineering Management IEEM}, Year = {2021}, Pages = {1442-1445}, Note = {IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), ELECTR NETWORK, DEC 13-16, 2021}, Organization = {IEEE; IEEE Singapore Sect; IEEE TEMS Singapore Chapter; IEEE TEMS Hong Kong Chapter}, Abstract = {One of the most important factors in a purchasing decision nowadays is the evaluation of comments online. Businesses or individuals use deceptive comments to mislead people for the sake of economic gain and thus hurt the benefit of the customers and the welfare of society. In this research, we propose a rule-based artificial intelligence (AI) machine learning (ML) architecture for online review fraud detection. The proposed methodology features an AI and ML hybrid architecture, where ML refers to the common well-developed machine learning models, and the AI part features a rules-based controller that prioritizes and customizes the fraud detection rules based on human intelligence to improve the accuracy of the result and computational efficiency.}, Publisher = {IEEE}, Address = {345 E 47TH ST, NEW YORK, NY 10017 USA}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Liu, H (Corresponding Author), San Jose State Univ, Dept Ind \& Syst Engn, San Jose, CA 95192 USA. Toplu, A.; Liu, H., San Jose State Univ, Dept Ind \& Syst Engn, San Jose, CA 95192 USA.}, DOI = {10.1109/IEEM50564.2021.9672994}, ISSN = {2157-3611}, ISBN = {978-1-6654-3771-4}, Keywords = {Deceptive comment detection; fake review; machine learning; rule-based system}, Research-Areas = {Engineering; Operations Research \& Management Science}, Web-of-Science-Categories = {Engineering, Industrial; Operations Research \& Management Science}, Author-Email = {Hongrui.liu@sjsu.edu}, Affiliations = {California State University System; San Jose State University}, ResearcherID-Numbers = {Liu, Hongrui/HLP-7261-2023}, Cited-References = {Agnihotri R, 2016, IND MARKET MANAG, V53, P172, DOI 10.1016/j.indmarman.2015.09.003. {[}Anonymous], 2010, P 1 WORKSHOP SOCIAL, DOI DOI 10.1145/1964858.1964860. {[}Anonymous], 2014, ARXIV14041982. CORTES C, 1995, MACH LEARN, V20, P273, DOI 10.1023/A:1022627411411. Gregory GD, 2019, IND MARKET MANAG, V78, P146, DOI 10.1016/j.indmarman.2017.03.002. Harris C. 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Sharma A, 2020, COMPANION OF THE 2020 IEEE 20TH INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY, AND SECURITY (QRS-C 2020), P609, DOI {[}10.1109/QRS-051114.2020.00104, 10.1109/QRS-C51114.2020.00104].}, Number-of-Cited-References = {15}, Times-Cited = {0}, Usage-Count-Last-180-days = {2}, Usage-Count-Since-2013 = {3}, Doc-Delivery-Number = {BT3OT}, Web-of-Science-Index = {Conference Proceedings Citation Index - Science (CPCI-S)}, Unique-ID = {WOS:000821855600279}, DA = {2023-10-04}, } @article{ WOS:001039094200001, Author = {Yim, Alexis and Cui, Annie Peng and Walsh, Michael}, Title = {The role of cuteness on consumer attachment to artificial intelligence agents}, Journal = {JOURNAL OF RESEARCH IN INTERACTIVE MARKETING}, Year = {2023}, Month = {2023 JUL 29}, Abstract = {PurposeThis paper identifies the effects of different dimensions of the cuteness (i.e. baby schema cuteness and whimsical cuteness) of artificial intelligence (AI) agents on attachment to them. In addition, the current paper examines the consequences of the attachment to AI agents.Design/methodology/approachA pretest to validate the measurement scale for the attachment to AI agents and a survey study were conducted with AI agent users. The authors used structural equation modeling to analyze the data for hypothesis testing.FindingsThe baby schema and whimsical cuteness of AI agents drive consumers to develop stronger attachments to their AI agents. This is because consumers perceive cute AI agents as being more trustworthy. As a result, consumers who feel attached to their AI agents are more inclined to report higher satisfaction and commitment levels. They are also more likely to purchase products or services recommended by their AI agents and use them more frequently.Originality/valueDespite the growing popularity of AI agents, there is a lack of understanding regarding which characteristics of AI agents affect consumer behavior. Therefore, this research examines how the attribute of cuteness influences consumers' attachment to AI agents and subsequently affects their satisfaction and purchase intention toward products recommended by AI agents. Our study demonstrates that the element of cuteness in AI agents plays a crucial role in shaping perceptions of benevolence trustworthiness, as well as fostering users' attachment to AI agents. Furthermore, we observe positive consumer behaviors as a result of their attachment to AI agents. The findings from this study provide valuable insights for practitioners on how to effectively utilize cuteness in AI agents.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Yim, A (Corresponding Author), Radford Univ, Davis Coll Business \& Econ, Dept Mkt, Radford, VA 24142 USA. Yim, Alexis, Radford Univ, Davis Coll Business \& Econ, Dept Mkt, Radford, VA 24142 USA. Cui, Annie Peng; Walsh, Michael, West Virginia Univ, John Chambers Coll Business \& Econ, Dept Mkt, Morgantown, WV USA.}, DOI = {10.1108/JRIM-02-2023-0046}, EarlyAccessDate = {JUL 2023}, ISSN = {2040-7122}, EISSN = {2040-7130}, Keywords = {Cuteness; Attachment; Artificial intelligence; Artificial intelligence agent}, Keywords-Plus = {BRAND ATTACHMENT; EMOTIONAL ATTACHMENT; PRODUCT ATTACHMENT; INFANT FACES; ANTECEDENTS; SENSITIVITY; ENGAGEMENT; BEHAVIORS; LOYALTY; LIGHT}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {ayim@radford.edu}, Affiliations = {Radford University; West Virginia University}, Cited-References = {AINSWORTH MDS, 1989, AM PSYCHOL, V44, P709, DOI 10.1037/0003-066X.44.4.709. ALPERSTEIN NM, 1991, J BROADCAST ELECTRON, V35, P43. Ashfaq M, 2020, TELEMAT INFORM, V54, DOI 10.1016/j.tele.2020.101473. 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Mark.}, Doc-Delivery-Number = {N7XJ6}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:001039094200001}, DA = {2023-10-04}, } @article{ WOS:000572987800012, Author = {Pillai, Rajasshrie and Sivathanu, Brijesh and Dwivedi, Yogesh K.}, Title = {Shopping intention at AI-powered automated retail stores (AIPARS)}, Journal = {JOURNAL OF RETAILING AND CONSUMER SERVICES}, Year = {2020}, Volume = {57}, Month = {NOV}, Abstract = {Artificial Intelligence (AI) is transforming the way retail stores operate. AI-Powered Automated Retail Stores are the next revolution in physical retail. Consumers are facing fully automated technology in these retail stores. Therefore, it is necessary to scrutinize the antecedents of consumers' intention to shop at AI-Powered Automated Retail Stores. This study delves into this area to find the predictors of consumers' intention to shop at AI-Powered Automated Retail Stores. It extends the technology readiness and acceptance model by the addition of AI context specific constructs such as Perceived Enjoyment, Customization and Interactivity from the present literature. The proposed model is tested by surveying 1250 consumers \& the data is analyzed using the PLS-SEM technique and empirically validated. The outcome of the study reveals that Innovativeness and Optimism of consumers affect the perceived ease and perceived usefulness. Insecurity negatively affects the perceived usefulness of AI-powered automated retail stores. Perceived ease of use, perceived usefulness, perceived enjoyment, customization and interactivity are significant predictors of shopping intention of consumers in AI-powered automated stores. This research presents insightful academic and managerial implications in the domain of retailing and technology in retail.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Pillai, R (Corresponding Author), Pune Inst Business Management, Pune, Maharashtra, India. Pillai, Rajasshrie, Pune Inst Business Management, Pune, Maharashtra, India. Sivathanu, Brijesh, Sri Balaji Univ, Pune, Maharashtra, India. Dwivedi, Yogesh K., Swansea Univ, Emerging Markets Res Ctr, Sch Management, Swansea, W Glam, Wales.}, DOI = {10.1016/j.jretconser.2020.102207}, Article-Number = {102207}, ISSN = {0969-6989}, EISSN = {1873-1384}, Keywords = {TRAM; PLS-SEM; Perceived enjoyment; Customization; Interactivity; Artificial intelligence-powered automated; retail stores}, Keywords-Plus = {INTEGRATING TECHNOLOGY READINESS; IMAGE INTERACTIVITY TECHNOLOGY; ONLINE PURCHASE INTENTION; ARTIFICIAL-INTELLIGENCE; CONSUMER ACCEPTANCE; AUGMENTED REALITY; USER ACCEPTANCE; VIRTUAL-REALITY; BIG DATA; INTRINSIC MOTIVATION}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {rajasshrie1@gmail.com brij.jesh2002@gmail.com ykdwivedi@gmail.com}, Affiliations = {Swansea University}, ResearcherID-Numbers = {S, BRIJESH/AAQ-4753-2021 Dwivedi, Yogesh Kumar/A-5362-2008 Pillai, Rajasshrie/GRO-0859-2022}, ORCID-Numbers = {S, BRIJESH/0000-0003-2505-9140 Dwivedi, Yogesh Kumar/0000-0002-5547-9990 }, Cited-References = {Adapa S, 2020, J RETAIL CONSUM SERV, V52, DOI 10.1016/j.jretconser.2019.101901. 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Serv.}, Doc-Delivery-Number = {NT5NP}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000572987800012}, OA = {Green Accepted}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:000666079300001, Author = {Khan, Mohammad Farhan and Haider, Farnaz and Al-Hmouz, Ahmed and Mursaleen, Mohammad}, Title = {Development of an Intelligent Decision Support System for Attaining Sustainable Growth within a Life Insurance Company}, Journal = {MATHEMATICS}, Year = {2021}, Volume = {9}, Number = {12}, Month = {JUN}, Abstract = {Consumer behaviour is one of the most important and complex areas of research. It acknowledges the buying behaviour of consumer clusters towards any product, such as life insurance policies. Among various factors, the three most well-known determinants on which human conjecture depends for preferring a product are demographic, economic and psychographic factors, which can help in developing an accurate market design and strategy for the sustainable growth of a company. In this paper, the study of customer satisfaction with regard to a life insurance company is presented, which focused on comparing artificial intelligence-based, data-driven approaches to classical market segmentation approaches. In this work, an artificial intelligence-based decision support system was developed which utilises the aforementioned factors for the accurate classification of potential buyers. The novelty of this paper lies in developing supervised machine learning models that have a tendency to accurately identify the cluster of potential buyers with the help of demographic, economic and psychographic factors. By considering a combination of the factors that are related to the demographic, economic and psychographic elements, the proposed support vector machine model and logistic regression model-based decision support systems were able to identify the cluster of potential buyers with collective accuracies of 98.82\% and 89.20\%, respectively. The substantial accuracy of a support vector machine model would be helpful for a life insurance company which needs a decision support system for targeting potential customers and sustaining its share within the market.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Mursaleen, M (Corresponding Author), China Med Univ Taiwan, China Med Univ Hosp, Dept Med Res, Taichung 40402, Taiwan. Khan, Mohammad Farhan, Cranfield Univ, Sch Water Energy \& Environm, Cranfield MK43 0AL, Beds, England. Haider, Farnaz, Aligarh Muslim Univ, Dept Agr Econ \& Business Management, Aligarh 202002, Uttar Pradesh, India. Al-Hmouz, Ahmed, Middle East Univ, Dept Comp Informat Syst, Amman 11831, Jordan. Mursaleen, Mohammad, China Med Univ Taiwan, China Med Univ Hosp, Dept Med Res, Taichung 40402, Taiwan.}, DOI = {10.3390/math9121369}, Article-Number = {1369}, EISSN = {2227-7390}, Keywords = {consumer behaviour; life insurance; support vector machine; logistic regression; demographic factors; economic factors; psychographic factors; data-driven approach}, Keywords-Plus = {DEMAND; DETERMINANTS; EXPENDITURES; OWNERSHIP; ECONOMICS; BEHAVIOR; MOTIVES; MACHINE}, Research-Areas = {Mathematics}, Web-of-Science-Categories = {Mathematics}, Author-Email = {farhan7787@gmail.com farnaz.mgmt@gmail.com ahmouz@meu.edu.jo mursaleenm@gmail.com}, Affiliations = {Cranfield University; Aligarh Muslim University; Middle East University; China Medical University Taiwan; China Medical University Hospital - Taiwan}, ResearcherID-Numbers = {Khan, Mohammad Farhan/J-2346-2019 Mursaleen, M./A-6146-2013}, ORCID-Numbers = {Khan, Mohammad Farhan/0000-0001-8773-8726 Mursaleen, M./0000-0003-4128-0427}, Cited-References = {Abakouy R., 2019, P 4 INT C SMART CITY, P1. 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Zelizer V., 2017, MORALS MARKETS DEV L.}, Number-of-Cited-References = {67}, Times-Cited = {1}, Usage-Count-Last-180-days = {5}, Usage-Count-Since-2013 = {22}, Journal-ISO = {Mathematics}, Doc-Delivery-Number = {SY7RA}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000666079300001}, OA = {gold, Green Published}, DA = {2023-10-04}, } @inproceedings{ WOS:000720304600040, Author = {Sajja, Shravan and Aggarwal, Nupur and Mukherjee, Sumanta and Manglik, Kushagra and Dwivedi, Satyam and Raykar, Vikas}, Book-Group-Author = {ASSOC COMP MACHINERY}, Title = {Explainable AI based Interventions for Pre-season Decision Making in Fashion Retail}, Booktitle = {CODS-COMAD 2021: PROCEEDINGS OF THE 3RD ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE \& MANAGEMENT OF DATA (8TH ACM IKDD CODS \& 26TH COMAD)}, Year = {2021}, Pages = {281-289}, Note = {3rd ACM India Joint International Conference on Data Science and Management of Data (CODS-COMAD), ELECTR NETWORK, JAN 02-04, 2021}, Organization = {Assoc Comp Machinery}, Abstract = {Future of sustainable fashion lies in adoption of AI for a better understanding of consumer shopping behaviour and using this understanding to further optimize product design, development and sourcing to finally reduce the probability of overproducing inventory. Explainability and interpretability are highly effective in increasing the adoption of AI based tools in creative domains like fashion. In a fashion house, stakeholders like buyers, merchandisers and financial planners have a more quantitative approach towards decision making with primary goals of high sales and reduced dead inventory. Whereas, designers have a more intuitive approach based on observing market trends, social media and runways shows. Our goal is to build an explainable new product forecasting tool with capabilities of interventional analysis such that all the stakeholders (with competing goals) can participate in collaborative decision making process of new product design, development and launch.}, Publisher = {ASSOC COMPUTING MACHINERY}, Address = {1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Sajja, S (Corresponding Author), IBM Res India, New Delhi, India. Sajja, Shravan; Aggarwal, Nupur; Mukherjee, Sumanta; Manglik, Kushagra; Dwivedi, Satyam; Raykar, Vikas, IBM Res India, New Delhi, India.}, DOI = {10.1145/3430984.3430995}, ISBN = {978-1-4503-8817-7}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Interdisciplinary Applications}, Author-Email = {suryasku@in.ibm.com nupaggar@in.ibm.com sumanm03@in.ibm.com kmangli1@in.ibm.com satydw10@in.ibm.com viraykar@in.ibm.com}, Affiliations = {International Business Machines (IBM)}, Cited-References = {Al Daoud E., 2019, INT J COMPUT INF ENG, V13, P6. Baardman L., 2017, LEVERAGING COMPARABL. Chase CW, 2013, WILEY SAS BUS SER, P1, DOI 10.1002/9781118691861. Chen TQ, 2016, KDD'16: PROCEEDINGS OF THE 22ND ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P785, DOI 10.1145/2939672.2939785. Garro Andres, 2011, THESIS MIT. 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Zhao QY, 2021, J BUS ECON STAT, V39, P272, DOI 10.1080/07350015.2019.1624293.}, Number-of-Cited-References = {19}, Times-Cited = {6}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {13}, Doc-Delivery-Number = {BS4LW}, Web-of-Science-Index = {Conference Proceedings Citation Index - Science (CPCI-S)}, Unique-ID = {WOS:000720304600040}, OA = {Green Submitted}, DA = {2023-10-04}, } @inproceedings{ WOS:000346281500027, Author = {Suomala, Jyrki and Suomala, Ville}, Editor = {Zheng, R}, Title = {Modified Reinforcement Learning Infrastructure}, Booktitle = {PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON APPLIED SOCIAL SCIENCE RESEARCH}, Series = {Advances in Intelligent Systems Research}, Year = {2014}, Volume = {104}, Pages = {95-97}, Note = {2nd International Conference on Applied Social Science Research (ICASSR), Shanghai, PEOPLES R CHINA, JUL 10-11, 2014}, Abstract = {The reinforcement learning (RL) model has been very successful in behavioral sciences, artificial intelligence and neuroscience. Despite its fruitfulness in many simple situations, the RL model does not always cope well with real life situations involving a large space of possible world states or a large set of possible actions. We propose a modified version of the RL learning model. The benefit of this model is that the temporal difference prediction error can be used directly to update not only the value of the latest action of the learning agent, but the values of many possible future actions. An example application of this modified reinforcement learning infrastructure (MRLI) is presented for a customer behaviour in a complex shopping environment.}, Publisher = {ATLANTIS PRESS}, Address = {29 AVENUE LAVMIERE, PARIS, 75019, FRANCE}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Suomala, Jyrki, Laurea Univ Appl Sci, NeuroLab, FI-02650 Espoo, Finland. Suomala, Ville, Univ Oulu, FI-90014 Oulu, Finland.}, ISSN = {1951-6851}, ISBN = {978-94-62520-24-0}, Keywords = {MRLI; Graph Theory; Learning; Behavioral model; Decision-making}, Keywords-Plus = {DECISION-MAKING; PREDICTION; REWARD}, Research-Areas = {Social Sciences - Other Topics}, Web-of-Science-Categories = {Social Sciences, Interdisciplinary}, Author-Email = {Jyrki.suomala@laurea.fi ville.suomala@oulu.fi}, Affiliations = {Laurea University of Applied Sciences; University of Oulu}, Cited-References = {Botvinick MM, 2009, COGNITION, V113, P262, DOI 10.1016/j.cognition.2008.08.011. Botvinick MM, 2012, CURR OPIN NEUROBIOL, V22, P956, DOI 10.1016/j.conb.2012.05.008. Daw Nathaniel D., 2014, NEUROECONOMICS, P299, DOI DOI 10.1016/B978-0-12-416008-8.00016-4. Glimcher PW, 2003, BRADFORD BOOKS, P1. Kahneman D, 1997, Q J ECON, V112, P375, DOI 10.1162/003355397555235. Li J, 2006, PLOS ONE, V1, DOI 10.1371/journal.pone.0000103. Markov NT, 2013, SCIENCE, V342, P578, DOI 10.1126/science.1238406. 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Suomala J, 2012, TECHNOL INNOV MANAG, P12.}, Number-of-Cited-References = {17}, Times-Cited = {0}, Usage-Count-Last-180-days = {0}, Usage-Count-Since-2013 = {1}, Doc-Delivery-Number = {BB8BX}, Web-of-Science-Index = {Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH)}, Unique-ID = {WOS:000346281500027}, DA = {2023-10-04}, } @article{ WOS:000826717600001, Author = {Kumar, Dilip and Singh, Rohit and Choudhuri, Sajjan and Shandilya, Abhinav Kumar}, Title = {Food Waste Consumer Behaviour: A Bibliometric Review}, Journal = {INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION}, Year = {2022}, Volume = {14}, Number = {3}, Pages = {4006-4019}, Abstract = {Food is produced for consumption, either in raw form or cooked form. Still, when it gets wasted due to wasteful consumer behaviour, it becomes alarming for society and the environment. When thrown into the bin, food fit for human consumption turns into food waste. Various drivers were identified for food waste, such as consumer behaviour, unskilled workforce, intention, perceived behavioural control, and increasing disposable income. In the present study, a bibliometric analysis of 2498 publications from 2000 to 2022 (February) is done with the help of VOSviewer to investigate the research publication trends in food waste generating due to consumer behaviour. To find out the most dominated journals, researchers, and research organisationshandling consumer behaviour leading to food waste, to figure out the highly cited research publications in the present research area and their impact on society. To prepare a thematic research cluster and determine the most dominant research terms in wasteful consumer behaviour. www.dimensions.ai free database app is used to extract the data to analyse the objectives mentioned above. A tremendous increase in the publication was found since 2015, i.e., 500\%. Journal of cleaner publication is the leading Journal having 3836 citations and a total link strength (TLS) of 140329. The University of Oxford (17 documents, 1979 citations, and 2635 of TLS) was the most influential organisation in consumer behaviour, leading to food waste research. The University of Oxford (17 documents, 1979 citations, and 2635 TLS) was the leading organisation in the present study. The United States topped the ranking with 428 articles, having citations of 6745 and a TLS of 108742. ``Food waste within food supply chains . quantification and potential for change to 2050{''} was the most-cited research publication. Product (787), use (563), data (502), production (489), and review (484) are the most occurred keywords found in the present study. The present study helps in connecting the relation between FW and consumer behaviour, which is one of the most significant concerns in the current scenario, justified by the massive increase in the publication in the last five years. More research is required in this field to fight against this global concern to achieve the SDGs12 and 13.}, Publisher = {ANADOLU UNIV}, Address = {INST FINE ARTS, ESKISEHIR, 26470, TURKEY}, Type = {Review}, Language = {English}, Affiliation = {Kumar, D (Corresponding Author), AURO Univ, Sch Hospitality Management, Surat, Gujarat, India. Kumar, Dilip, AURO Univ, Sch Hospitality Management, Surat, Gujarat, India. Singh, Rohit, AURO Univ, Sch Business, Surat, Gujarat, India. Choudhuri, Sajjan, Chandigarh Univ, Univ Sch Business, Ludhiana, Punjab, India. Shandilya, Abhinav Kumar, Birla Inst Technol, Dept Hotel Management \& Catering Technol, Ranchi, Jharkhand, India.}, DOI = {10.9756/INT-JECSE/V14I3.507}, ISSN = {1308-5581}, Keywords = {Bibliometric analysis; VOSviewer; Food Waste; Consumer Behaviour; SDG}, Keywords-Plus = {SUSTAINABILITY; MANAGEMENT; ATTITUDES; LOSSES}, Research-Areas = {Education \& Educational Research}, Web-of-Science-Categories = {Education, Special}, Author-Email = {dilipraj81@gmail.com rohit@aurouniversity.edu.in sajjan.usb@cumail.in sabhinavkumar@bitmesra.ac.in}, Affiliations = {Chandigarh University; Birla Institute of Technology Mesra}, ResearcherID-Numbers = {Kumar, Dr. Dilip/AAA-4924-2022 Kumar Shandilya, Abhinav/AHD-0059-2022}, ORCID-Numbers = {Kumar, Dr. Dilip/0000-0002-2503-1394 Kumar Shandilya, Abhinav/0000-0001-5186-9433}, Cited-References = {Alexander P, 2017, AGR SYST, V153, P190, DOI 10.1016/j.agsy.2017.01.014. Bene C, 2020, FOOD SECUR, V12, P805, DOI 10.1007/s12571-020-01076-1. 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Xue L, 2017, ENVIRON SCI TECHNOL, V51, P6618, DOI 10.1021/acs.est.7b00401.}, Number-of-Cited-References = {28}, Times-Cited = {0}, Usage-Count-Last-180-days = {10}, Usage-Count-Since-2013 = {25}, Journal-ISO = {Int. J. Early Child. Spec. Educ.}, Doc-Delivery-Number = {2Z6XH}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000826717600001}, DA = {2023-10-04}, } @article{ WOS:000562543500001, Author = {Deng, Guangkuan and Zhang, Jianyu and Ye, Naiyi and Chi, Rui}, Title = {Consumers' human nature and their shopping channel choices in the emerging artificial intelligence era: based on Xunzi's humanity hypothesis}, Journal = {INTERNATIONAL MARKETING REVIEW}, Year = {2021}, Volume = {38}, Number = {4, SI}, Pages = {736-755}, Month = {JUL 22}, Abstract = {Purpose Drawing from the ancient Chinese philosopher Xunzi's insights on humanity, this study aims to address human nature's critical role in influencing and shaping consumers' shopping channel choices in the emerging artificial intelligence (AI) era and the implications for non-East Asian countries. Design/methodology/approach Based on the theory of planned behaviour and accessibility-diagnosticity theory, our approach created a holistic model conceptualising human nature, shopping orientations, channel choice intentions, subjective norms and perceived AI usefulness. A questionnaire survey method served to test the framework. Findings The results validated human nature's role in shaping and influencing consumers' channel choices through shopping orientation. Subjective norms weaken the positive relationship between human nature and shopping orientation, while the positive relationship between shopping orientation and online purchase intention is stronger when consumers perceived AI as highly useful. Originality/value This paper contributes to humanity hypotheses literature in management by introducing Xunzi's theory that views human nature as evil. Additionally, it enriches channel choice literature by introducing perceived AI usefulness.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Deng, GK (Corresponding Author), Southwestern Univ Finance \& Econ, Sch Business Adm, Chengdu, Peoples R China. Deng, Guangkuan; Zhang, Jianyu; Chi, Rui, Southwestern Univ Finance \& Econ, Sch Business Adm, Chengdu, Peoples R China. Ye, Naiyi, Southwest Jiaotong Univ, Sch Econ \& Management, Chengdu, Peoples R China.}, DOI = {10.1108/IMR-01-2019-0026}, EarlyAccessDate = {AUG 2020}, ISSN = {0265-1335}, EISSN = {1758-6763}, Keywords = {Xunzi; Human nature is evil; Perceived AI usefulness; Shopping orientation; Subjective norms}, Keywords-Plus = {STRUCTURAL EQUATION MODELS; HUMAN-NATURE HELD; PERSONALIZED RECOMMENDATION; ETHICAL JUDGMENTS; UTILITARIAN; INFORMATION; ACCEPTANCE; BELIEFS; PREFERENCE; COMMERCE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {styzdgk@126.com}, Affiliations = {Southwestern University of Finance \& Economics - China; Southwest Jiaotong University}, ResearcherID-Numbers = {G.K., Deng/AAZ-7371-2020 Chi, Jasmine/GRJ-9418-2022}, ORCID-Numbers = {G.K., Deng/0000-0002-5071-463X }, Funding-Acknowledgement = {National Natural Science Foundation of China {[}71472153]}, Funding-Text = {This work was supported by the National Natural Science Foundation of China (Grant No. 71472153)}, Cited-References = {Ahluwalia R, 2000, J CONSUM RES, V27, P371, DOI 10.1086/317591. 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Rev.}, Doc-Delivery-Number = {TN5MJ}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000562543500001}, DA = {2023-10-04}, } @inproceedings{ WOS:000717224200032, Author = {Del Vacchio, Erica and Laddaga, Cesare and Bifulco, Francesco}, Editor = {Schiuma, G}, Title = {How AI Affects the Motivations Tourists Photographs}, Booktitle = {15TH INTERNATIONAL FORUM ON KNOWLEDGE ASSET DYNAMICS (IFKAD 2020): KNOWLEDGE IN DIGITAL AGE}, Series = {Proceedings IFKAD}, Year = {2020}, Pages = {434-454}, Note = {15th International Forum on Knowledge Asset Dynamics (IFKAD) - Knowledge in Digital Age, ELECTR NETWORK, SEP 09-11, 2020}, Abstract = {Service literature suggests that identifying the motivations of tourists is fundamental (e.g., Woosnam et al., 2016; Pomfret \& Bramwell, 2016) to be able to adapt marketing strategies according to the different users' needs. However, today digital technologies and more generally service innovations have profoundly changed the decision-making of the tourists photographers. Some contributions (Lo et al., 2011; Ozansoy cardici et al., 2019) agree that the motivation that drives users to take photos is no longer linked just to memory but to the communication of personal identity, especially for the new generations. These changes depend on the use of digital tools such as the introduction of mobile with camera, social networks, and AI. Indeed, Huyn et al (2009) conceptualized the tourism in the mobile context, recognizing the use of mobile to search travel information through photo of other visitors; then, Prideaux \& Coghlan (2010) investigated the photographic habits, using mobile phones or cameras as a tool of memory. Several recent contributions (Munar \& Jacobsen, 2014; Kozinets, 2017; Trinanda \& Sari, 2019) focus on the evolution of tourist's motivation photo due to the development of social networks. Indeed, Munar \& Jacobsen (2014) examined the reasons that drive tourists to share their photos on social networks, showing that the findings provide insights into motivational factors such as personal and community-related benefits, as well as social capital that influences the sharing of user-generated content. Besides, according to Kozinets (2017) the visitor became part of art domain with the selfie, not only for narcissistic reasons, as exposed by Fox and Rooney (2015), Sorokowski et al. (2015), and Lee and Sung (2016), but to express aspects of themselves through the art. Findings show that AI is actually a tool able to influence and add new motivations for tourist photographer: in particular, AI improve the game and curiosity motivations, with the consequent rise of a different and new interaction with art. Future research could use a customer survey (Hulland et al., 2018) to better understand which features of AI are the most appreciated by tourist photographers. The purpose of the research is to verify, through a content analysis, what emerged in the literature on the first two steps of the tourist photographer motivations. Furthermore, after investigating through the observation, the theoretical framework, we will proceed to define a theoretical framework inherent in the emerging phenomenon of AI implementation also in tourism which at the moment is little treated in managerial literature.}, Publisher = {IKAM-INST KNOWLEDGE ASSET MANAGEMENT}, Address = {VIA D SCHIAVONE 1, MATERA, MT 75100, ITALY}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Del Vacchio, E (Corresponding Author), Univ Naples Federico II, Dept Econ Management Inst, Via Cintia 26, I-80126 Na, Italy. Del Vacchio, Erica; Laddaga, Cesare; Bifulco, Francesco, Univ Naples Federico II, Dept Econ Management Inst, Via Cintia 26, I-80126 Na, Italy.}, ISSN = {2280-787X}, ISBN = {978-88-96687-13-0}, Keywords = {Cultural heritage; artificial intelligence; consumer behaviour; digital tourism; hospitality}, Keywords-Plus = {SELF-PRESENTATION; NARCISSISM; TRAVEL; INFORMATION; BEHAVIORS}, Research-Areas = {Business \& Economics; Computer Science; Information Science \& Library Science; Operations Research \& Management Science}, Web-of-Science-Categories = {Business; Computer Science, Interdisciplinary Applications; Information Science \& Library Science; Management; Operations Research \& Management Science}, Affiliations = {University of Naples Federico II}, Cited-References = {{[}Anonymous], 1990, TOURIST GAZE LEISURE. {[}Anonymous], 2006, GEOGRAPHIES COMMUNIC. {[}Anonymous], 2015, INFORM COMMUNICATION. {[}Anonymous], 2005, J BETRIEBSWIRTSCHAFT, DOI DOI 10.1007/S11301-004-0002-8. {[}Anonymous], 2002, APPL CASE STUDY RES. {[}Anonymous], 2008, INT C INFORM COMMUNI, DOI DOI 10.1007/978-3-211-77280-5\_4. 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Woosnam K. M., 2016, USING VALUES PREDICT. Xiang Z, 2015, J RETAIL CONSUM SERV, V22, P244, DOI 10.1016/j.jretconser.2014.08.005.}, Number-of-Cited-References = {81}, Times-Cited = {0}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {3}, Doc-Delivery-Number = {BS4CI}, Web-of-Science-Index = {Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH)}, Unique-ID = {WOS:000717224200032}, DA = {2023-10-04}, } @article{ WOS:000614164800001, Author = {Tigre Moura, Francisco and Maw, Charlotte}, Title = {Artificial intelligence became Beethoven: how do listeners and music professionals perceive artificially composed music?}, Journal = {JOURNAL OF CONSUMER MARKETING}, Year = {2021}, Volume = {38}, Number = {2}, Pages = {137-146}, Month = {FEB 23}, Abstract = {Purpose - Artificial intelligence (AI) has reached creative industries such as music. Algorithms now produce high-quality artistic content (e.g. original songs), for hedo consumption and utilitarian business applications. While available literature to-date focuses mainly on technological development and applications, this paper aims to address the resulting research gap by investigating listeners' perceptions towards music composed by AI. Design/methodology/approach - First, an online survey was conducted with 446 respondents and compared perceptions of music professionals (n = 72) and non-professional listeners (n = 374). Following this, a 2 x 2 laboratory experiment was conducted, where 86 participants listened to songs composed by AI but were presented different narratives regarding the composition process (human versus AI). Findings - Overall, results from the online survey indicated a rather negative perception, low purchase intention for AI music and a negative credibility perception of musicians using AI. Findings from the experiment indicated no significant differences between the groups, suggesting that the awareness of the use of automation did not influence the perception towards the music. Originality/value - This paper contributes by highlighting the current perception of both listeners and music professionals towards the application of artificial creativity in music composition. Furthermore, it contributes to the existing literature on artificial creativity applied in music, by providing evidence of its impact on listeners' perception. Results reveal the importance of further investigation on the topic.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Moura, FT (Corresponding Author), IUBH Univ Appl Sci, Dept Mkt, Munich, Germany. Tigre Moura, Francisco, IUBH Univ Appl Sci, Dept Mkt, Munich, Germany. Maw, Charlotte, IUBH Univ Appl Sci, Munich, Germany.}, DOI = {10.1108/JCM-02-2020-3671}, EarlyAccessDate = {FEB 2021}, ISSN = {0736-3761}, EISSN = {2052-1200}, Keywords = {Automation; Artificial intelligence; Music; Artificial creativity; Music composition}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {f.tigre-moura@iubh.de charlotte.maw@iubh.de}, ResearcherID-Numbers = {Tigre Moura, Francisco/HJH-6195-2023 Tigre, Francisco/HJH-6256-2023}, ORCID-Numbers = {Tigre Moura, Francisco/0000-0003-4699-7582 }, Cited-References = {Aaker JL, 1997, J CONSUM RES, V24, P315, DOI 10.1086/209513. An M, 2017, ARTIFICIAL INTELLIGE. {[}Anonymous], 2016, 4 IND REVOLUTION WHA. {[}Anonymous], 2008, EMOTION MEANING MUSI. {[}Anonymous], 2004, CREATIVE MIND MYTHS. {[}Anonymous], 2018, OXFORD HDB ALGORITHM. {[}Anonymous], 1994, MUSIC GROOVES ESSAYS. {[}Anonymous], 2017, DISCOVERING STAT USI. {[}Anonymous], 1974, STIMULATING CREATIVI. Areni C. 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Yalch Richard F., 1990, J CONSUMER MARKETING, V7, P55, DOI DOI 10.1108/EUM0000000002577.}, Number-of-Cited-References = {64}, Times-Cited = {8}, Usage-Count-Last-180-days = {15}, Usage-Count-Since-2013 = {65}, Journal-ISO = {J. Consum. Mark.}, Doc-Delivery-Number = {QR2OF}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000614164800001}, DA = {2023-10-04}, } @article{ WOS:000848284300001, Author = {Simay, Attila Endre and Wei, Yuling and Gyulavari, Tamas and Syahrivar, Jhanghiz and Gaczek, Piotr and Hofmeister-Toth, Agnes}, Title = {The e-WOM intention of artificial intelligence (AI) color cosmetics among Chinese social media influencers}, Journal = {ASIA PACIFIC JOURNAL OF MARKETING AND LOGISTICS}, Year = {2023}, Volume = {35}, Number = {7}, Pages = {1569-1598}, Month = {JUN 27}, Abstract = {Purpose The recent advancements in smartphone technology and social media platforms have increased the popularity of artificial intelligence (AI) color cosmetics. Meanwhile, China is a lucrative market for various foreign beauty products and technological innovations. This research aims to investigate the adoption of AI color cosmetics applications and their electronic word-of-mouth (e-WOM) intention among Chinese social media influencers. Several key concepts have been proposed in this research, namely body esteem, price sensitivity, social media addiction and actual purchase. Design/methodology/approach An online questionnaire design was used in this research. A combination of purposive sampling and snowball sampling of AI color cosmetics users who are also social media influencers in China yields 221 respondents. To analyze the data, this research employs Structural Equation Modelling (SEM) method via SPSS and AMOS software. A 2-step approach, Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), is implemented to prove the hypotheses and generate the results. Findings 1) Social media addiction is a positive predictor of AI color cosmetics usage, (2) AI color cosmetics usage is a positive predictor of actual purchase, (3) actual purchase is a positive predictor of e-WOM intention and lastly, (4) there is a full mediation effect of actual purchase. Originality/value This research draws on the uses and gratification (U\&G) theory to investigate how specific user characteristics affect Chinese social media influencers' adoption of AI color cosmetics, as well as how this may affect their decision to purchase branded color cosmetics and their e-WOM.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Simay, AE (Corresponding Author), Corvinus Univ Budapest, Inst Mkt \& Commun Sci, Budapest, Hungary. Simay, Attila Endre; Wei, Yuling; Gyulavari, Tamas; Syahrivar, Jhanghiz; Hofmeister-Toth, Agnes, Corvinus Univ Budapest, Inst Mkt \& Commun Sci, Budapest, Hungary. Syahrivar, Jhanghiz, President Univ, Fac Business, Bekasi, Indonesia. Gaczek, Piotr, Poznan Univ Econ \& Business, Dept Mkt Strategies, Poznan, Poland.}, DOI = {10.1108/APJML-04-2022-0352}, EarlyAccessDate = {SEP 2022}, ISSN = {1355-5855}, EISSN = {1758-4248}, Keywords = {Artificial intelligence; Cosmetics; e-WOM intention; Social media influencers; Social media addiction; China}, Keywords-Plus = {AUGMENTED REALITY; PURCHASE INTENTION; SELF-ESTEEM; CONTINUANCE INTENTION; FACEBOOK ADDICTION; BODY-ESTEEM; GRATIFICATIONS; PRODUCT; PRICE; SCALE}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {attila.simay@uni-corvinus.hu}, Affiliations = {Corvinus University Budapest; Poznan University of Economics \& Business}, ResearcherID-Numbers = {Syahrivar, Jhanghiz/P-7234-2017 Hofmeister, Agnes/AEK-1276-2022 Wei, Yuling/GRJ-4677-2022 Gyulavari, Tamas/K-2503-2014}, ORCID-Numbers = {Syahrivar, Jhanghiz/0000-0002-4563-3413 Wei, Yuling/0000-0003-0955-0909 Simay, Attila Endre/0000-0001-5114-8791 Gyulavari, Tamas/0000-0003-1358-786X}, Cited-References = {Abed SS, 2022, INT J ORGAN ANAL, V30, P1045, DOI 10.1108/IJOA-11-2020-2501. 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Zhang M, 2021, J RETAIL CONSUM SERV, V58, DOI 10.1016/j.jretconser.2020.102342.}, Number-of-Cited-References = {121}, Times-Cited = {2}, Usage-Count-Last-180-days = {26}, Usage-Count-Since-2013 = {77}, Journal-ISO = {Asia Pac. J. Market. Logist.}, Doc-Delivery-Number = {K0CM8}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000848284300001}, DA = {2023-10-04}, } @article{ WOS:000655004000001, Author = {Ala'raj, Maher and Abbod, Maysam F. and Majdalawieh, Munir}, Title = {Modelling customers credit card behaviour using bidirectional LSTM neural networks}, Journal = {JOURNAL OF BIG DATA}, Year = {2021}, Volume = {8}, Number = {1}, Month = {MAY 19}, Abstract = {With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI) techniques to help banks and financial institutions to support their financial decisions. Neural networks are considered as a mostly wide used technique in finance and business applications. Thus, the main aim of this paper is to help bank management in scoring credit card clients using machine learning by modelling and predicting the consumer behaviour with respect to two aspects: the probability of single and consecutive missed payments for credit card customers. The proposed model is based on the bidirectional Long-Short Term Memory (LSTM) model to give the probability of a missed payment during the next month for each customer. The model was trained on a real credit card dataset and the customer behavioural scores are analysed using classical measures such as accuracy, Area Under the Curve, Brier score, Kolmogorov-Smirnov test, and H-measure. Calibration analysis of the LSTM model scores showed that they can be considered as probabilities of missed payments. The LSTM model was compared to four traditional machine learning algorithms: support vector machine, random forest, multi-layer perceptron neural network, and logistic regression. Experimental results show that, compared with traditional methods, the consumer credit scoring method based on the LSTM neural network has significantly improved consumer credit scoring.}, Publisher = {SPRINGERNATURE}, Address = {CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Ala'raj, M (Corresponding Author), Zayed Univ, Coll Technol Innovat, Dept Informat Syst, Dubai 19282, U Arab Emirates. Ala'raj, Maher; Majdalawieh, Munir, Zayed Univ, Coll Technol Innovat, Dept Informat Syst, Dubai 19282, U Arab Emirates. Abbod, Maysam F., Brunel Univ London, Coll Engn Design \& Phys Sci, Dept Elect \& Comp Engn, Kingston Lane, Uxbridge UB8 3PH, Middx, England.}, DOI = {10.1186/s40537-021-00461-7}, Article-Number = {69}, EISSN = {2196-1115}, Keywords = {Behavioural scoring; Neural networks; Bidirectional LSTM; Classification}, Keywords-Plus = {RISK; ALGORITHMS; DEFAULT}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Theory \& Methods}, Author-Email = {maher.alaraj@zu.ac.ae}, Affiliations = {Zayed University; Brunel University}, ORCID-Numbers = {Abbod, Maysam/0000-0002-8515-7933 Alaraj, Maher/0000-0001-9315-0670}, Funding-Acknowledgement = {Office of Research, Zayed University {[}R20053]}, Funding-Text = {This work was supported by the Office of Research, Zayed University under Grant Number R20053.}, Cited-References = {Addo PM, 2018, RISKS, V6, DOI 10.3390/risks6020038. Adeodato P, 2016, EQUIVALENCE KOLMOGOR. 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Big Data}, Doc-Delivery-Number = {SI7JO}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000655004000001}, OA = {gold, Green Published}, DA = {2023-10-04}, } @article{ WOS:000271334200003, Author = {Martinez-Lopez, Francisco J. and Casillas, Jorge}, Title = {Marketing Intelligent Systems for consumer behaviour modelling by a descriptive induction approach based on Genetic Fuzzy Systems}, Journal = {INDUSTRIAL MARKETING MANAGEMENT}, Year = {2009}, Volume = {38}, Number = {7}, Pages = {714-731}, Month = {OCT}, Abstract = {In its introduction this paper discusses why marketing professionals do not make satisfactory use of the marketing models posed by academics in their studies. The main body of this research is characterised by the proposal of a brand new and complete methodology for knowledge discovery in databases (KDD), to be applied in marketing causal modelling and with utilities to be used as a marketing management decision support tool. Such methodology is based on Genetic Fuzzy Systems, a specific hybridization of artificial intelligence methods, highly suited to the research problem we face. The use of KDD methodologies based on intelligent systems like this can be considered as an avant-garde evolution, exponent nowadays of the so-called knowledge-based Marketing Management Support Systems; we name them as Marketing Intelligent Systems. The most important questions to the KDD process-i.e. pre-processing; machine learning and post-processing-are discussed in depth and solved. After its theoretical presentation, we empirically experiment with it, using a consumer behaviour model of reference. In this part of the paper, we try to offer an overall perspective of how it works. The valuation of its performance and utility is very positive. (C) 2008 Elsevier Inc. All rights reserved.}, Publisher = {ELSEVIER SCIENCE INC}, Address = {STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA}, Type = {Article}, Language = {English}, Affiliation = {Martinez-Lopez, FJ (Corresponding Author), Univ Granada, Fac Business, Dept Mkt, E-18071 Granada, Spain. Martinez-Lopez, Francisco J., Univ Granada, Fac Business, Dept Mkt, E-18071 Granada, Spain. Casillas, Jorge, Univ Granada, Comp \& Telecommun Engn Sch, Dept Comp Sci \& Artificial Intelligence, E-18071 Granada, Spain.}, DOI = {10.1016/j.indmarman.2008.02.003}, ISSN = {0019-8501}, EISSN = {1873-2062}, Keywords = {Marketing modelling; Management support; Analytical method; Knowledge discovery; Genetic Fuzzy Systems; Methodology}, Keywords-Plus = {DECISION-SUPPORT; DISCOVERY; ALGORITHM}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, Author-Email = {fjmlopez@ugr.es casillas@decsai.ugr.es}, Affiliations = {University of Granada; University of Granada}, ResearcherID-Numbers = {Casillas, Jorge/H-4922-2011 Casillas, Jorge/HZJ-9469-2023}, ORCID-Numbers = {Casillas, Jorge/0000-0002-5887-3977 }, Cited-References = {Agarwal A, 2007, IND MARKET MANAG, V36, P443, DOI 10.1016/j.indmarman.2005.12.004. {[}Anonymous], 2001, EUROPEAN J MARKETING, DOI DOI 10.1108/EUM0000000005734. {[}Anonymous], 2003, ACCURACY IMPROVEMENT. {[}Anonymous], 1959, MEASUREMENT DEFINITI. {[}Anonymous], 2000, EUR J MARKETING, DOI DOI 10.1108/03090560010321938. {[}Anonymous], 2002, MARK INTELL PLAN, DOI DOI 10.1108/02634500210441521. {[}Anonymous], 2003, INTERPRETABILITY ISS. {[}Anonymous], MARKETING MANAGEMENT. {[}Anonymous], 2002, NAT COMP SER. {[}Anonymous], EUR J MARKETING. 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Manage.}, Doc-Delivery-Number = {513PE}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000271334200003}, DA = {2023-10-04}, } @article{ WOS:000605608800027, Author = {McLean, Graeme and Osei-Frimpong, Kofi and Barhorst, Jennifer}, Title = {Alexa, do voice assistants influence consumer brand engagement? - Examining the role of AI powered voice assistants in influencing consumer brand engagement}, Journal = {JOURNAL OF BUSINESS RESEARCH}, Year = {2021}, Volume = {124}, Pages = {312-328}, Month = {JAN}, Abstract = {Artificially Intelligent (AI) voice assistants (VAs) are continuing to grow in popularity amongst consumers. While in their infancy, several brands are now utilising VAs such as the Amazon Echo to deliver brand-related information and services. However, despite the increasing use of VAs, we have little understanding of what motivates consumers to use such devices for brand-related information. Focusing on the Amazon Echo in-home VA, and its associated Alexa Skills, this research uncovers the key drivers of consumer brand engagement through VAs. In study 1, through a set of in-depth exploratory interviews with 21 respondents, we established three factors as key drivers of why consumers use VAs to engage with brands: AI attributes, technology attributes, and situational attributes. Study 2 examines these specific drivers via a questionnaire with 724 respondents. The findings outline the VA as an actor in the engagement process and affirm the importance of the VA's AI attributes of social presence, perceived intelligence, and social attraction in influencing consumer brand engagement. Additionally, technology attributes influence consumer brand engagement, along with the utilitarian benefits derived from interactions with brand-related information. Hedonic benefits do not influence consumer brand engagement via VA technology, while trust concerns play a negative role in brand engagement behaviour. Lastly, the results convey that consumer brand engagement via a VA influences brand usage intention, but in contrast to previous research, does not directly influence future purchase intention.}, Publisher = {ELSEVIER SCIENCE INC}, Address = {STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA}, Type = {Article}, Language = {English}, Affiliation = {McLean, G (Corresponding Author), Univ Strathclyde, Business Sch, Stenhouse Wing, Glasgow G4 0QU, Lanark, Scotland. McLean, Graeme, Univ Strathclyde, Business Sch, Stenhouse Wing, Glasgow G4 0QU, Lanark, Scotland. Osei-Frimpong, Kofi, Univ Profess Studies, Accra, Ghana. Barhorst, Jennifer, Coll Charleston, 66 George St, Charleston, SC 29424 USA.}, DOI = {10.1016/j.jbusres.2020.11.045}, ISSN = {0148-2963}, EISSN = {1873-7978}, Keywords = {Artificial Intelligence (AI); Voice assistants; Consumer brand engagement; Automated technology}, Keywords-Plus = {CUSTOMER ENGAGEMENT; SOCIAL PRESENCE; ACTOR ENGAGEMENT; SERVICE; TRUST; COMPUTERS; RESPONSES; ROBOTS; MODEL; PERSONALITY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {graeme.mclean@strath.ac.uk kofi.osei-frimpong@upsamail.edu.gh barhorstj@cofc.edu}, Affiliations = {University of Strathclyde; College of Charleston}, ResearcherID-Numbers = {Osei-Frimpong, Kofi/JCR-4418-2023 Barhorst, Jennifer/AAR-8603-2021}, ORCID-Numbers = {Osei-Frimpong, Kofi/0000-0002-3956-2495 }, Cited-References = {Accenture, 2018, MAN VOIC ASS US HAV. Ahluwalia R, 2001, J MARKETING RES, V38, P458, DOI 10.1509/jmkr.38.4.458.18903. 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Res.}, Doc-Delivery-Number = {PP1DI}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000605608800027}, OA = {Green Accepted}, ESI-Highly-Cited-Paper = {Y}, ESI-Hot-Paper = {N}, DA = {2023-10-04}, } @article{ WOS:000637811700001, Author = {Shumanov, Michael and Cooper, Holly and Ewing, Mike}, Title = {Using AI predicted personality to enhance advertising effectiveness}, Journal = {EUROPEAN JOURNAL OF MARKETING}, Year = {2022}, Volume = {56}, Number = {6, SI}, Pages = {1590-1609}, Month = {JUN 7}, Abstract = {Purpose The purpose of this study is twofold: first to demonstrate the application of an algorithm using contextual data to ascertain consumer personality traits; and second to explore the factors impacting the relationship between personality traits and advertisement persuasiveness. Design/methodology/approach A mixed-method approach that comprises two distinct yet complementary studies. The first uses quantitative methods and is based on a sample of 35,264 retail banking customers. Study 2 explores the findings that emerge from Study 1 using qualitative methods. Findings This paper finds that matching consumer personality with congruent advertising messages can lead to more effective consumer persuasion for most personality types. For consumers who exhibit neurotic personality traits, ameliorating perceived risks during purchasing and providing cues for social acceptance and goal attainment are important factors for advertising effectiveness. These factors also had a positive impact on the purchasing behaviour of extroverted consumers. Research limitations/implications This research focusses on understanding purchasing behaviour based on the most dominant personality trait. However, people are likely to exhibit a combination of most or even all of the Big Five personality traits. Practical implications Building on advances in natural language processing, enabling the identification of personality from language, this study demonstrates the possibility of influencing consumer behaviour by matching machine inferred personality to congruent persuasive advertising. It is one of the few studies to use contextual instead of social media data to capture individual personality. Such data serves to capture an authentic rather than contrived persona. Further, the study identifies the factors that may moderate this relationship and thereby provides an explanation of why some personality traits exhibit differences in purchasing behaviour from those that are anticipated by existing theory. Originality/value Although the idea that people are more likely to be responsive to advertising messages that are congruent with their personality type has already been successfully applied by advertising practitioners and documented by advertising scholars, this study extends existing research by identifying the factors that may moderate this relationship and thereby provides an explanation why some personality traits may exhibit differences in purchasing behaviour from those that are anticipated by existing theory.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Shumanov, M (Corresponding Author), Swinburne Univ Technol, Dept Business Technol \& Entrepreneurship, Melbourne, Vic, Australia. Shumanov, Michael, Swinburne Univ Technol, Dept Business Technol \& Entrepreneurship, Melbourne, Vic, Australia. Cooper, Holly; Ewing, Mike, Deakin Univ, Dept Mkt, Geelong, Vic, Australia.}, DOI = {10.1108/EJM-12-2019-0941}, EarlyAccessDate = {APR 2021}, ISSN = {0309-0566}, EISSN = {1758-7123}, Keywords = {Personality; Advertising; Artificial intelligence; Machine learning; Personality traits}, Keywords-Plus = {CROSS-CULTURAL GENERALIZABILITY; ALTERNATIVE 5-FACTOR MODEL; ORGANIZATIONAL COMMITMENT; ARTIFICIAL-INTELLIGENCE; GENDER-DIFFERENCES; MEDIATING ROLE; TRAITS; DIMENSIONS; WORK; SIMILARITY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {mshumanov@swin.edu.au h.cooper@deakin.edu.au michael.ewing@deakin.edu.au}, Affiliations = {Swinburne University of Technology; Deakin University}, ORCID-Numbers = {Cooper, Holly/0000-0003-0608-5239}, Cited-References = {Aaker D. A., 1992, PSYCHOL MARKET, V9, P237, DOI DOI 10.1002/MAR.4220090306. Aaker JL, 1997, J MARKETING RES, V34, P347, DOI 10.2307/3151897. 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Yang YM, 2018, J BUS RES, V85, P155, DOI 10.1016/j.jbusres.2017.12.036. Yarkoni T, 2010, J RES PERS, V44, P363, DOI 10.1016/j.jrp.2010.04.001. Young HR, 2018, J ORGAN BEHAV, V39, P1330, DOI 10.1002/job.2303.}, Number-of-Cited-References = {84}, Times-Cited = {9}, Usage-Count-Last-180-days = {12}, Usage-Count-Since-2013 = {91}, Journal-ISO = {Eur. J. Market.}, Doc-Delivery-Number = {1U5IM}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000637811700001}, DA = {2023-10-04}, } @article{ WOS:000984501500008, Author = {de Oliveira, Leticia Jesus and Pereira, Sueli Essado}, Title = {Development and sensory analysis of a vegan dessert from chickpea by-product}, Journal = {RBONE-REVISTA BRASILEIRA DE OBESIDADE NUTRICAO E EMAGRECIMENTO}, Year = {2021}, Volume = {15}, Number = {96}, Pages = {830-840}, Month = {SEP-OCT}, Abstract = {Introduction: people are vegan for countless reasons: respect for animals, sustainability, and concern for health. Studies show that 14\% of the country's population in 2018 were vegetarians and research points Brazil in the ranking of the ten countries with the largest increase in vegans. With this growth, alternative products have emerged, such as aquafaba, which is the water from cooking legumes. Objective: To develop a vegan dessert using meringue from aquafaba. Materials and Methods: The recipe was developed in the dietetic technique laboratory, in three samples with distinct flavors (A, B and C), and for sensory analysis to be performed the project was sent to the Ethics Committee (opinion 4.008.403 of 05/05/20), applying Term of Consent to random tasters (vegan, vegetarian and omnivore). Results: After compilation and statistical analysis, the mean sensory attributes, and their acceptability indices (AI) were calculated. Although there was no significant difference between the acceptance results of the samples, sample A was the best accepted (mean 92\%), compared to B (mean 90.8\%) and C (mean 89.6\%). In the purchase intention there was an approval rate of 64\% saying they would certainly buy, 28\% would buy and 8\% would maybe buy. Conclusion: the recipe developed had a good acceptance in all samples, considering the attributes evaluated as well as the positive correlation with the purchase intention of the tasters and their frequency of candy consumption. Thus, the preparation is contributing to a compilation of new products for the public in question.}, Publisher = {INST BRASILEIRO PESQUISA \& ENSINO FISIOLOGIA EXERCICIO-IBPEFEX}, Address = {INST BRASILEIRO PESQUISA \& ENSINO FISIOLOGIA EXERCICIO-IBPEFEX, SAO PAULO, 00000, BRAZIL}, Type = {Article}, Language = {Portuguese}, Affiliation = {de Oliveira, LJ (Corresponding Author), Rua 15,Numero 352,Setor Cent, BR-74030030 Goiania, Go, Brazil. de Oliveira, Leticia Jesus, Pontificia Univ Catolica Goias, PUC Goias, Acad Nutr, Goiania, Go, Brazil. Pereira, Sueli Essado, PUC Goias, Escola Ciencias Sociais \& Saude ECISS, Goiania, Go, Brazil.}, ISSN = {1981-9919}, Keywords = {Vegans; Cicer arietinum; Sensory function}, Research-Areas = {Nutrition \& Dietetics}, Web-of-Science-Categories = {Nutrition \& Dietetics}, Author-Email = {oliveirajleticia@gmail.com suganutrir@gmail.com}, Affiliations = {Pontificia Universidade Catolica de Goias}, Cited-References = {Alles B, 2017, NUTRIENTS, V9, DOI 10.3390/nu9091023. Amaral F.M., 2018, REV BRASILEIRA GASTR, V1, P34. Bento R.A., 2013, TECNICO ALIMENTOS AN, P142. Brasil. Ministerio da Saude, 2014, GUIA AL POP BRAS. Dever Z, 2016, AQUAFABA SWEET SAVOR, P295. Dutcosky S. D., 2013, ANALISE SENSORIAL AL, P531. Goncalves N.A., 2015, NUTR BRASIL, V14, P197. IBGE. Instituto Brasileiro de Geografia e Estatistica, 2011, PESQ ORC FAM 2008 20. INSA. Instituto Nacional de Saude Doutor Ricardo Jorge SNS-Servico Nacional de Saude., 2019, AL NUTR. 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Wadhera D, 2014, EAT BEHAV, V15, P132, DOI 10.1016/j.eatbeh.2013.11.003.}, Number-of-Cited-References = {25}, Times-Cited = {0}, Usage-Count-Last-180-days = {2}, Usage-Count-Since-2013 = {2}, Journal-ISO = {RBONE-Rev. Bras. Obes. Nutr. Emagrecimento}, Doc-Delivery-Number = {VM2PH}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000984501500008}, DA = {2023-10-04}, } @article{ WOS:000504401100087, Author = {Gao, Biao and Huang, Lin}, Title = {Understanding interactive user behavior in smart media content service: An integration of TAM and smart service belief factors}, Journal = {HELIYON}, Year = {2019}, Volume = {5}, Number = {12}, Month = {DEC}, Abstract = {Smart media combines media and artificial intelligence (AI) and can also be a user-centered content service market. However, existing research lacks an understanding of user's perceptions concerning smart services generated by different user experience types across different payment groups. Taking AI-powered Smart TV (AI TV) as a typical research object, this study (1) develops a theoretical model by integrating the technology acceptance model with users' smart service belief factors and (2) employs the user experience type as an original moderator. Using data from 585 AI TV users, the structural equation modeling analysis suggests that perceived two-way communication, perceived personalization, and perceived co-creation as three belief factors, are important antecedent constructs in the extended technology acceptance model. The analysis also suggests that the user experience type exerts positive moderating effects on two-way communication and personalization to attitude toward behavior and purchase intention. This study thus contributes to the literature on smart service by identifying and studying smart service belief factors. The addition of smart service belief factors as antecedents, as well as user experience type as a moderator, are crucial to expand the generalizability of TAM to the smart media service context. From a customer experience management perspective, this study shows how to convert ad-supported users into new paid subscribers, while keeping existing subscribers by fulfilling their smart service requirements.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Gao, B (Corresponding Author), Kobe Univ, Grad Sch Business Adm, Kobe, Hyogo, Japan. Gao, Biao; Huang, Lin, Kobe Univ, Grad Sch Business Adm, Kobe, Hyogo, Japan.}, DOI = {10.1016/j.heliyon.2019.e02983}, Article-Number = {e02983}, EISSN = {2405-8440}, Keywords = {Business; Psychology; Marketing; Smart media; Technology acceptance model; Two-way communication; Personalization; Co-creation; User experience type}, Keywords-Plus = {TECHNOLOGY ACCEPTANCE; PERCEIVED EASE; CONSUMER ACCEPTANCE; ONLINE CONSUMERS; CO-CREATION; MODEL; INTERNET; PERSONALIZATION; EXPERIENCE; ADOPTION}, Research-Areas = {Science \& Technology - Other Topics}, Web-of-Science-Categories = {Multidisciplinary Sciences}, Author-Email = {biaogao.edu@outlook.com}, Affiliations = {Kobe University}, ORCID-Numbers = {Gao, Biao/0000-0002-0263-0167}, Cited-References = {Abdullah A, 2017, INT J ADV APPL SCI, V4, P16, DOI 10.21833/ijaas.2017.012.004. Agag G, 2016, COMPUT HUM BEHAV, V60, P97, DOI 10.1016/j.chb.2016.02.038. Allmendinger G, 2005, HARVARD BUS REV, V83, P131. 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Xu DJ, 2008, DECIS SUPPORT SYST, V44, P710, DOI 10.1016/j.dss.2007.10.002. Xu J.A, 2006, INT MULT MOD C. Yoon SB, 2016, COMPUT HUM BEHAV, V60, P500, DOI 10.1016/j.chb.2016.02.082. Zweig D, 2003, COMPUT HUM BEHAV, V19, P479, DOI 10.1016/S0747-5632(02)00075-4.}, Number-of-Cited-References = {128}, Times-Cited = {12}, Usage-Count-Last-180-days = {19}, Usage-Count-Since-2013 = {55}, Journal-ISO = {Heliyon}, Doc-Delivery-Number = {JY4QK}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000504401100087}, OA = {Green Published, gold}, DA = {2023-10-04}, } @article{ WOS:001035646400001, Author = {Pawar, Sanjay Krishnapratap and Vispute, Swati Amit}, Title = {Exploring international students' adoption of AI-enabled voice assistants in enrolment decision making: a grounded theory approach}, Journal = {JOURNAL OF MARKETING FOR HIGHER EDUCATION}, Year = {2023}, Month = {2023 JUL 25}, Abstract = {The proliferation and increasing significance of AI-enabled voice assistants (AIVAs) for consumer purchase decisions imply the need for a better understanding of their acceptance in the higher education (HE) enrollment context. Using the Grounded Theory (GT) research method and a consumer value perspective, we examine the enrolment decision-making of international students in the presence of AIVAs to propose a conceptual model linking value to adoption. Findings highlight the influence of the key antecedents of hedonic and functional value in AIVA adoption. The findings also indicate that the student and the AIVA can co-create novel experiences during information search and evaluation of enrollment alternatives. Some participants proactively suggest a larger role for the AIVA to aid their enrollment decision-making. Points of attention for university marketing managers are suggested based on the proposed core concept and the resulting tentative hypotheses.}, Publisher = {ROUTLEDGE JOURNALS, TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Pawar, SK (Corresponding Author), Symbiosis Int Deemed Univ, Symbiosis Inst Management Studies, Pune, India. Pawar, Sanjay Krishnapratap, Symbiosis Int Deemed Univ, Symbiosis Inst Management Studies, Pune, India. Vispute, Swati Amit, MIT World Peace Univ, MIT Sch Management, Pune, India.}, DOI = {10.1080/08841241.2023.2239720}, EarlyAccessDate = {JUL 2023}, ISSN = {0884-1241}, EISSN = {1540-7144}, Keywords = {AI-enabled voice assistants; international marketing of higher education; university marketing strategy; consumer behaviour; international students; enrollment decision-making; >}, Keywords-Plus = {QUALITATIVE RESEARCH; PERCEIVED VALUE; RECRUITMENT; ACCEPTANCE; HOME; UNIVERSITIES; TECHNOLOGIES; PERCEPTIONS; ENGAGEMENT; ALEXA}, Research-Areas = {Business \& Economics; Education \& Educational Research}, Web-of-Science-Categories = {Business; Education \& Educational Research}, Author-Email = {sanjay.pawar@sims.edu}, Affiliations = {Symbiosis International University; Symbiosis Institute of Management Studies (SIMS); Dr. Vishwanath Karad MIT World Peace University}, ResearcherID-Numbers = {Vispute, Swati Amit/I-1601-2016 Pawar, Sanjay Krishnapratap/AAM-8780-2021}, ORCID-Numbers = {Vispute, Swati Amit/0000-0003-1596-2598 Pawar, Sanjay Krishnapratap/0000-0001-8497-7553}, Cited-References = {Al Shamsi JH, 2022, EDUC INF TECHNOL, V27, P8071, DOI 10.1007/s10639-022-10947-3. 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Zwakman Dilawar Shah, 2021, SN Comput Sci, V2, P28, DOI 10.1007/s42979-020-00424-4.}, Number-of-Cited-References = {65}, Times-Cited = {0}, Usage-Count-Last-180-days = {0}, Usage-Count-Since-2013 = {0}, Journal-ISO = {J. Mark. High. Educ.}, Doc-Delivery-Number = {N2VG9}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:001035646400001}, DA = {2023-10-04}, } @article{ WOS:000405210600003, Author = {Catal, Cagatay and Guldan, Suat}, Title = {Product review management software based on multiple classifiers}, Journal = {IET SOFTWARE}, Year = {2017}, Volume = {11}, Number = {3}, Pages = {89-92}, Month = {JUN}, Abstract = {In recent years, due to significant developments in online shopping and the widespread use of e-commerce, competition among companies has increased considerably. As a result, product reviews have become a primary factor in consumers' decision making, which has given rise to a market for fraudulent reviews about real products and services. In this study, the authors propose a model using a multiple classifier system to identify deceptive negative customer reviews, which they validated with a dataset of hotel reviews from TripAdvisor. The proposed model used five classifiers by following the majority voting combination rule - namely, libLinear, libSVM, sequential minimal optimisation, random forest, and J48 - the first two of which represent different implementations of support vector machines. Ultimately, the model provided remarkable results that demonstrate improvement upon approaches reported in the literature.}, Publisher = {INST ENGINEERING TECHNOLOGY-IET}, Address = {MICHAEL FARADAY HOUSE SIX HILLS WAY STEVENAGE, HERTFORD SG1 2AY, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Catal, C (Corresponding Author), Istanbul Kultur Univ, Dept Comp Engn, TR-34156 Istanbul, Turkey. Catal, Cagatay, Istanbul Kultur Univ, Dept Comp Engn, TR-34156 Istanbul, Turkey. Guldan, Suat, ATU, Int Ataturk Airport, Informat Technol, TR-34830 Istanbul, Turkey.}, DOI = {10.1049/iet-sen.2016.0137}, ISSN = {1751-8806}, EISSN = {1751-8814}, Keywords = {consumer behaviour; customer satisfaction; pattern classification; Internet; decision making; support vector machines; optimisation; learning (artificial intelligence); data mining; software engineering; product review management software; online shopping; e-commerce; consumer decision making; fraudulent reviews; multiple classifier system; deceptive negative customer review identification; hotel review dataset; TripAdvisor; majority voting combination rule; libLinear; libSVM; sequential minimal optimisation; random forest; J48; support vector machines}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Software Engineering}, Author-Email = {catal@iku.edu.tr}, Affiliations = {Istanbul Kultur University}, ResearcherID-Numbers = {Catal, Cagatay/AAF-3929-2019}, ORCID-Numbers = {Catal, Cagatay/0000-0003-0959-2930}, Cited-References = {{[}Anonymous], 2012, ACM T MANAGEMENT INF. {[}Anonymous], 2011, 49 ANN M ASS COMPUTA. {[}Anonymous], 2000, INT WORKSH MULT CLAS. 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Sun H, 2013, 19TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (KDD'13), P1088. Xie S., 2012, KDD, DOI DOI 10.1145/2339530.2339662.}, Number-of-Cited-References = {20}, Times-Cited = {8}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {16}, Journal-ISO = {IET Softw.}, Doc-Delivery-Number = {FA1OZ}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000405210600003}, DA = {2023-10-04}, } @article{ WOS:000632432900006, Author = {Silva, Emmanuel Sirimal and Bonetti, Francesca}, Title = {Digital humans in fashion: Will consumers interact?}, Journal = {JOURNAL OF RETAILING AND CONSUMER SERVICES}, Year = {2021}, Volume = {60}, Month = {MAY}, Abstract = {The ongoing COVID-19 pandemic is disrupting the fashion industry and forcing fashion businesses to accelerate their digital transformation. The increased need for more sustainable fashion business operations, when coupled with the prospect that business might never be as usual again, calls for innovative e-commerce led practices. Recently, stakeholders have been experimenting with the idea of introducing digital humans for a more active role in fashion through the developments in artificial intelligence, virtual, augmented and mixed reality. As there is a lack of all-important empirical evidence on the consumer's propensity to interact with digital humans, we aim to quantitatively analyse consumer attitudes towards the propensity to interact with digital humans to uncover insights to help fashion businesses seeking to diversify their operations. The results reveal interesting, and statistically significant insights which can be useful for fashion business stakeholders for designing, developing, testing, and marketing digital human-based solutions. Besides, our findings contribute current insights to the existing literature on how consumers interact with digital humans, where research tends to be scarce.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Silva, ES (Corresponding Author), Univ Arts London, London Coll Fash, Fash Business Res Ctr, Fash Business Sch, 272 High Holborn, London WC1V 7EY, England. Silva, Emmanuel Sirimal; Bonetti, Francesca, Univ Arts London, London Coll Fash, Fash Business Res Ctr, Fash Business Sch, 272 High Holborn, London WC1V 7EY, England.}, DOI = {10.1016/j.jretconser.2020.102430}, EarlyAccessDate = {JAN 2021}, Article-Number = {102430}, ISSN = {0969-6989}, EISSN = {1873-1384}, Keywords = {Digital humans; Interaction; Consumer behaviour; Fashion business; E-commerce; Innovative technologies}, Keywords-Plus = {AUGMENTED-REALITY; RETAIL; COVID-19; BEHAVIOR; TECHNOLOGY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {e.silva@fashion.arts.ac.uk f.bonetti@fashion.arts.ac.uk}, Affiliations = {University of Arts London}, ResearcherID-Numbers = {Bonetti, Francesca/ITW-1544-2023 }, ORCID-Numbers = {Silva, Emmanuel Sirimal/0000-0003-3851-9230}, Cited-References = {Accenture, 2020, HUM EXP ORG SHOULD. 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Serv.}, Doc-Delivery-Number = {RB9NZ}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000632432900006}, DA = {2023-10-04}, } @article{ WOS:000723029400001, Author = {Butt, Asad and Ahmad, Hassan and Muzaffar, Asif and Ali, Fayaz and Shafique, Nouman}, Title = {WOW, the make-up AR app is impressive: a comparative study between China and South Korea}, Journal = {JOURNAL OF SERVICES MARKETING}, Year = {2022}, Volume = {36}, Number = {1, SI}, Pages = {73-88}, Month = {JAN 13}, Abstract = {Purpose Consumers today actively participate in online purchasing experiences. As a result, it is critical to comprehend the behavioral aspects of novel technology usage, such as augmented reality (AR). AR apps enable beauty companies to create and design more immersive experience services. This study aims to highlight consumers' perspectives on their continued desire to use AR app services. Design/methodology/approach A comparative study between China and South Korea was conducted with sample sizes of 458 and 315, respectively. Smart PLS was used for analysis. Findings The findings suggest that AR apps influence innovative consumers in China and South Korea to be satisfied with and continue to use such services. Previous research on technology acceptance model, information system success, AR and artificial intelligence (AI)-context-specific variables supported the findings. Practical implications This study contributes to the development of AR apps for beauty brands, as such technology revolutionizes how beauty brands work and grow. As a result, AR apps can pave the way for brands to provide an immersive experience to their customers. Originality/value The current study contributes to AR and AI drivers in the context of beauty brands by using novel technologies such as AR. AR integration with AI-context-specific variables indicates that consumers in China and South Korea are innovative and accept such technologies when purchasing beauty products online.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Ahmad, H (Corresponding Author), Univ Okara, Okara, Pakistan. Butt, Asad, Univ Cent Punjab, Fac Management Studies, Lahore, Pakistan. Ahmad, Hassan, Univ Okara, Okara, Pakistan. Muzaffar, Asif, Birmingham City Univ, Birmingham City Business Sch, Birmingham, W Midlands, England. Ali, Fayaz, Shenzhen Univ, Coll Management, Res Inst Business Analyt \& Supply Chain Managemen, Shenzhen, Peoples R China. Shafique, Nouman, Gomal Univ, Dera Ismail Khan, Pakistan.}, DOI = {10.1108/JSM-12-2020-0508}, EarlyAccessDate = {NOV 2021}, ISSN = {0887-6045}, Keywords = {AR content quality; AR environment embedding; AR satisfaction; AR interactivity; AR enjoyment; AR customization; ISS; TAM; E-commerce; Digitalization; Customer experience; Artificial intelligence; Technology and service; Behavioral insight}, Keywords-Plus = {AUGMENTED REALITY; VIRTUAL-REALITY; SERVICE QUALITY; CUSTOMER SATISFACTION; PERCEIVED ENJOYMENT; PURCHASE INTENTION; SOCIAL-INTERACTION; MOBILE INTERNET; SYSTEMS SUCCESS; TECHNOLOGY}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {hassaan1214@hotmail.com}, Affiliations = {University of Central Punjab; Birmingham City University; Shenzhen University; Gomal University}, ResearcherID-Numbers = {Butt, Asad Hassan/ABB-5692-2020 }, ORCID-Numbers = {Butt, Asad Hassan/0000-0003-4718-4508 Ahmad, Hassan/0000-0003-3925-3956}, Cited-References = {Abdullah F, 2016, COMPUT HUM BEHAV, V63, P75, DOI 10.1016/j.chb.2016.05.014. 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Zhou V., 2019, 3 TRENDS COSMETICS A. Ziaullah M, 2017, BEHAV INFORM TECHNOL, V36, P85, DOI 10.1080/0144929X.2016.1196503.}, Number-of-Cited-References = {138}, Times-Cited = {12}, Usage-Count-Last-180-days = {24}, Usage-Count-Since-2013 = {87}, Journal-ISO = {J. Serv. Mark.}, Doc-Delivery-Number = {YM3NX}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000723029400001}, OA = {Green Accepted}, DA = {2023-10-04}, } @article{ WOS:000553834400001, Author = {Hamilton, Kristy A. and Lee, Seo Yoon and Chung, Un Chae and Liu, Weizi and Duff, Brittany R. L.}, Title = {Putting the ``Me{''} in endorsement: Understanding and conceptualizing dimensions of self-endorsement using intelligent personal assistants}, Journal = {NEW MEDIA \& SOCIETY}, Year = {2021}, Volume = {23}, Number = {6}, Pages = {1506-1526}, Month = {JUN}, Abstract = {Self-endorsement-depicting the ``self{''} as an endorser of a brand-represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one's own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommendations from a typical, but not self-tailored, intelligent personal assistant. Because endorsement is a well-known and highly effective advertising strategy, this is a high bar. We present evidence for self-referencing as an underlying mechanism, and perceived interactivity and identification as boundary conditions of self-endorsing. Consumers may show skepticism toward advertising but may not know how to be skeptical of themselves. As consumers outsource their tasks and decisions to new artificial intelligence (AI)-driven devices, they will need to be attentive to new media biases that threaten productive use of these devices.}, Publisher = {SAGE PUBLICATIONS LTD}, Address = {1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Hamilton, KA (Corresponding Author), Univ Illinois, Inst Commun Res, Urbana, IL 61801 USA. Hamilton, Kristy A.; Lee, Seo Yoon; Chung, Un Chae; Liu, Weizi, Univ Illinois, Inst Commun Res, Urbana, IL 61801 USA. Duff, Brittany R. L., Univ Illinois, Charles H Sandage Dept Advertising, Advertising, Urbana, IL USA.}, DOI = {10.1177/1461444820912197}, EarlyAccessDate = {JUL 2020}, Article-Number = {1461444820912197}, ISSN = {1461-4448}, EISSN = {1461-7315}, Keywords = {Artificial intelligence; consumer behavior; empirical research; endorsement; intelligent personal assistants; self-endorsement}, Keywords-Plus = {PERSUASION KNOWLEDGE; BIG DATA; ONLINE; INTERNET; ATTITUDE}, Research-Areas = {Communication}, Web-of-Science-Categories = {Communication}, Author-Email = {kristyh2@illinois.edu}, Affiliations = {University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign}, ORCID-Numbers = {Hamilton, Kristy/0000-0001-6567-8427 Liu, Weizi/0000-0003-2071-1603}, Cited-References = {Ahn SJ, 2011, J ADVERTISING, V40, P93, DOI 10.2753/JOA0091-3367400207. {[}Anonymous], 2013, ADVERTISING UNEASY P. {[}Anonymous], 1960, 2 TREATISES GOVT CRI. {[}Anonymous], 1979, LEVELS PROCESSING HU. {[}Anonymous], 2012, INT J EC FINANCE, DOI DOI 10.5539/IJEF.V4N3P105. {[}Anonymous], 2007, INTERNET SOCIAL INEQ. 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White TB, 2008, MARKET LETT, V19, P39, DOI 10.1007/s11002-007-9027-9.}, Number-of-Cited-References = {45}, Times-Cited = {6}, Usage-Count-Last-180-days = {9}, Usage-Count-Since-2013 = {48}, Journal-ISO = {New Media Soc.}, Doc-Delivery-Number = {SP2RB}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000553834400001}, DA = {2023-10-04}, } @inproceedings{ WOS:001008773300048, Author = {Dominique-Ferreira, Sergio and Gomes, Helena and Brito, Pedro Quelhas and Prentice, Catherine}, Editor = {Mesquita, A and Abreu, A and Carvalho, JV and deMello, CHP}, Title = {Exploring the Role of Emotional Intelligence and Artificial Intelligence on Luxury Value and Customer-Based Outcomes}, Booktitle = {PERSPECTIVES AND TRENDS IN EDUCATION AND TECHNOLOGY, ICITED 2022}, Series = {Smart Innovation Systems and Technologies}, Year = {2023}, Volume = {320}, Pages = {543-554}, Note = {International Conference on Information Technology and Education (ICITED), Rio de Janeiro, BRAZIL, JUL 14-16, 2022}, Organization = {KES Int}, Abstract = {To strengthen theoretical and practical understanding of consumers' perceptions of luxury brands, previous literature has scrutinized the financial, functional, individual, and social dimensions of the luxury value construct. However, few authors have focused on linking the antecedent dimensions of luxury value to further attitudinal outcomes, besides purchase intention. Also, the few studies considering both dimensions focused on age or culture as moderator dimensions between such constructs. The gap identified in the literature constitutes the originality of the present study. As a result, the main goal of the present work is to measure the impact of luxury value perceptions in customer-based outcomes, as well as the possible moderator effect of Artificial Intelligence and Emotional Intelligence in the relationship between Owner Based Luxury Value and customer-based outcomes. Therefore, a quantitative methodological approach will be employed, through the development of a questionnaire.}, Publisher = {SPRINGER-VERLAG SINGAPORE PTE LTD}, Address = {152 BEACH ROAD, \#21-01/04 GATEWAY EAST, SINGAPORE, 189721, SINGAPORE}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Dominique-Ferreira, S (Corresponding Author), Polytech Inst Cavado \& Ave UNIAG, Appl Management Res Unit UNIAG, Dept Mkt \& Tourism, Barcelos, Portugal. Dominique-Ferreira, Sergio, Polytech Inst Cavado \& Ave UNIAG, Appl Management Res Unit UNIAG, Dept Mkt \& Tourism, Barcelos, Portugal. Gomes, Helena, Univ Porto, Fac Econ, Porto, Portugal. Brito, Pedro Quelhas, Univ Porto, Dept Mkt, Porto, Portugal. Prentice, Catherine, Univ Southern Queensland, Dept Mkt, Springfield, Australia.}, DOI = {10.1007/978-981-19-6585-2\_48}, ISSN = {2190-3018}, EISSN = {2190-3026}, ISBN = {978-981-19-6587-6; 978-981-19-6585-2; 978-981-19-6584-5}, Keywords = {Luxury; Owner Based Luxury Value (OBLV); Service encounter; Service quality; Artificial Intelligence (AI); Emotional Intelligence (EI); Customer engagement; Customer satisfaction; Customer loyalty}, Keywords-Plus = {SATISFACTION INDEX; PERCEPTIONS; ENGAGEMENT; LOYALTY; BRANDS; TECHNOLOGY; PURCHASE; QUALITY; MODEL}, Research-Areas = {Education \& Educational Research}, Web-of-Science-Categories = {Education \& Educational Research; Education, Special}, Author-Email = {sergio.dominique@gmail.com pbrito@fep.up.pt cathyjournalarticles@gmail.com}, Affiliations = {Instituto Politecnico do Porto; Universidade do Porto; Universidade do Porto; University of Southern Queensland}, Funding-Acknowledgement = {FCT - Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher Education {[}UIDB/04752/2020]}, Funding-Text = {UNIAG, R\&D unit funded by the FCT - Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher Education. ``Project Code Reference: UIDB/04752/2020{''}.}, Cited-References = {Alexander MJ, 2018, J SERV MANAGE, V29, P333, DOI 10.1108/JOSM-08-2016-0237. 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Vigneron F, 2017, J BRAND MANAG ADV CO, P199, DOI 10.1007/978-3-319-51127-6\_10. Wiedmann KP, 2009, PSYCHOL MARKET, V26, P625, DOI 10.1002/mar.20292. Wixom BH, 2005, INFORM SYST RES, V16, P85, DOI 10.1287/isre.1050.0042. Xiang Z, 2015, INT J HOSP MANAG, V44, P120, DOI 10.1016/j.ijhm.2014.10.013. Yuan JX, 2008, J TRAVEL RES, V46, P279, DOI 10.1177/0047287507308322. Yuksel A, 2010, TOURISM MANAGE, V31, P274, DOI 10.1016/j.tourman.2009.03.007.}, Number-of-Cited-References = {46}, Times-Cited = {0}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {1}, Doc-Delivery-Number = {BV2OU}, Web-of-Science-Index = {Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH)}, Unique-ID = {WOS:001008773300048}, DA = {2023-10-04}, } @article{ WOS:001022364800001, Author = {Li, Huajun and Lei, Yueqiu and Zhou, Qi and Yuan, Hong}, Title = {Can you sense without being human? Comparing virtual and human influencers endorsement effectiveness}, Journal = {JOURNAL OF RETAILING AND CONSUMER SERVICES}, Year = {2023}, Volume = {75}, Month = {NOV}, Abstract = {As AI increasingly permeates digital spaces, virtual influencers are operating in similar ways as human influ-encers. However, given their recent introduction, the effectiveness of virtual influencers is unclear, and there is limited managerial guidance regarding when and how they should be used. Across four studies, including an empirical investigation using secondary data analysis and three scenario-based experiments spanning two cul-tural contexts, we find that virtual influencers are less effective than human influencers as endorsers in terms of brand attitude and purchase intention. Furthermore, we identify perceived sensory capability and credibility as the serial mechanism. Lastly, we introduce the salience of sensory cues within the ad as a theoretically important and managerially relevant moderator, which attenuates the negative effect of virtual influencers. This research extends virtual influencer literature by focusing on business-related outcomes. Our theoretical model highlights essential differences in advertising outcomes between human and virtual influencers and provides important managerial implications.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Zhou, Q (Corresponding Author), Huazhong Univ Sci \& Technol, Sch Journalism \& Informat Commun, 1037 Luoyu Rd, Wuhan 430074, Peoples R China. Li, Huajun; Lei, Yueqiu; Zhou, Qi, Huazhong Univ Sci \& Technol, Sch Journalism \& Informat Commun, 1037 Luoyu Rd, Wuhan 430074, Peoples R China. Yuan, Hong, Univ Oregon, Lundquist Coll Business, 1208 Univ Oregon, Eugene, OR 97403 USA.}, DOI = {10.1016/j.jretconser.2023.103456}, EarlyAccessDate = {JUN 2023}, Article-Number = {103456}, ISSN = {0969-6989}, EISSN = {1873-1384}, Keywords = {Virtual influencer; Endorsement effectiveness; Mind perception theory; Perceived credibility; Sensory cue}, Keywords-Plus = {CELEBRITY CREDIBILITY; MIND PERCEPTION; ROBOTS; IMPACT}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {jennyzq1020@gmail.com}, Affiliations = {Huazhong University of Science \& Technology; University of Oregon}, ResearcherID-Numbers = {yuan, lin/JDW-7387-2023 wu, p/JDW-5015-2023 yang, peng/JEZ-8452-2023 zhou, yang/JED-3951-2023 Yang, Jie/JDM-6213-2023 zhang, chen/JES-0371-2023 Liu, Jie/JCP-1070-2023 li, xiang/JCN-9316-2023 Yang, Jing/JFK-4046-2023}, ORCID-Numbers = {Yang, Jie/0000-0002-3941-0053 Yang, Jing/0009-0004-8274-9863}, Funding-Acknowledgement = {China Science Foundation of Ministry of Education {[}22YJCZH264]; China Postdoctoral Science Foundation {[}2021M701324]}, Funding-Text = {Acknowledgments This project is financially supported by the China Science Foundation of Ministry of Education (Grant No. 22YJCZH264) , China Postdoctoral Science Foundation (Grant No. 2021M701324) .}, Cited-References = {Adtraction, 2020, WHAT IS VIRT INFL. 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VirtualHumans, 2022, INST HAS VER 35 VIRT. Voorveld HAM, 2019, J ADVERTISING, V48, P14, DOI 10.1080/00913367.2019.1588808. Wang S.W., 2017, J ADVERTISING RES, V63, P1. Wiedmann KP, 2021, J PROD BRAND MANAG, V30, P707, DOI 10.1108/JPBM-06-2019-2442. Wirtz J, 2018, J SERV MANAGE, V29, P907, DOI 10.1108/JOSM-04-2018-0119. Yang G., 2022, INT J ADVERT, V41, P1.}, Number-of-Cited-References = {76}, Times-Cited = {1}, Usage-Count-Last-180-days = {71}, Usage-Count-Since-2013 = {71}, Journal-ISO = {J. Retail. Consum. Serv.}, Doc-Delivery-Number = {L3NQ6}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:001022364800001}, DA = {2023-10-04}, } @article{ WOS:000851928500001, Author = {Jajic, Ivan and Herceg, Tomislav and Pejic Bach, Mirjana}, Title = {Deployment of the Microeconomic Consumer Theory in the Artificial Neural Networks Modelling: Case of Organic Food Consumption}, Journal = {MATHEMATICS}, Year = {2022}, Volume = {10}, Number = {17}, Month = {SEP}, Abstract = {Organic food consumption has become a significant trend in consumer behaviour, determined by various motives, among which the price does not play a major role, thus reflecting the Lancaster approach to the microeconomic consumer theory. Additionally, artificial neural networks (ANNs) have proven to have significant potential in providing accurate and efficient models for predicting consumer behaviour. Considering these two trends, this study aims to deploy the Lancaster approach in the emerging area of artificial intelligence. The paper aims to develop the ANN-based predictive model to investigate the relationship between organic food consumption, demographic characteristics, and health awareness attitudes. Survey research has been conducted on a sample of Croatian inhabitants, and ANN models have been used to assess the importance of various determinants for organic food consumption. A Three-layer Multilayer Perceptron Neural Networks (MLPNN) structure has been constructed and validated to select the optimal number of neurons and transfer functions. One layer is used as the first input, while the other two are hidden layers (the first covers the radially symmetrical input, sigmoid function; the second covers the output, softmax function). Three versions of the testing, training, and holdout data structures were used to develop ANNs. The highest accuracy was achieved with a 7-2-1 partition. The best ANN model was determined as the model that was showing the smallest percent of incorrect predictions in the holdout stage, the second-lowest cross-entropy error, the correct classification rate, and the area under the ROC curve. The research results show that the availability of healthy food shops and consumer awareness of these shops strongly impacts organic food consumption. Using the ANN methodology, this analysis confirmed the validity of the Lancaster approach, stating that the characteristics or attributes of goods are defined by the consumer and not by the product itself.}, Publisher = {MDPI}, Address = {ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Bach, MP (Corresponding Author), Univ Zagreb, Fac Econom \& Business, Zagreb 10000, Croatia. Jajic, Ivan; Herceg, Tomislav; Pejic Bach, Mirjana, Univ Zagreb, Fac Econom \& Business, Zagreb 10000, Croatia.}, DOI = {10.3390/math10173215}, Article-Number = {3215}, EISSN = {2227-7390}, Keywords = {microeconomic theory; artificial neural networks; Lancaster approach; organic food; healthy eating}, Keywords-Plus = {PURCHASE; WILLINGNESS; LABELS; SHOP}, Research-Areas = {Mathematics}, Web-of-Science-Categories = {Mathematics}, Author-Email = {mpejic@net.efzg.hr}, Affiliations = {University of Zagreb}, ResearcherID-Numbers = {Pejic Bach, Mirjana/E-7313-2012}, ORCID-Numbers = {Jajic, Ivan/0000-0002-5081-3531 Pejic Bach, Mirjana/0000-0003-3899-6707}, Cited-References = {Abiodun OI, 2018, HELIYON, V4, DOI 10.1016/j.heliyon.2018.e00938. Albersmeier F, 2009, SUSTAIN DEV, V17, P311, DOI 10.1002/sd.426. {[}Anonymous], 1999, J CONSUM POLICY. {[}Anonymous], COMMUNICATION COMMIS, DOI DOI 10.31249/ESPR/2021.03.04. Antoun C, 2016, FIELD METHOD, V28, P231, DOI 10.1177/1525822X15603149. 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Zander K, 2010, FOOD QUAL PREFER, V21, P495, DOI 10.1016/j.foodqual.2010.01.006.}, Number-of-Cited-References = {72}, Times-Cited = {0}, Usage-Count-Last-180-days = {3}, Usage-Count-Since-2013 = {8}, Journal-ISO = {Mathematics}, Doc-Delivery-Number = {4K4NL}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000851928500001}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000748377200017, Author = {Chatterjee, Sweety and Kulkarni, Prasanna}, Title = {Healthcare consumer behaviour: the impact of digital transformation of healthcare on consumer}, Journal = {CARDIOMETRY}, Year = {2021}, Number = {20}, Pages = {134-143}, Month = {NOV}, Abstract = {Healthcare consumer behavior is influenced by the cumulative impact of internal/external factors. Individual considerations, and interplay amongst determinants, are both crucial. Today, customers demand more information, greater options, and real-time interactions. Customer engagement has become crucial. Digital Transformation with emerging technologies like AI, Blockchain, Telemedicine, etc., helps physicians, optimizes systems, improves patient experience, and reduces human errors. This paper discusses factors influencing healthcare consumers' behavior and provides insights into digital technologies to enhance the consumer experience. The qualitative method is used by engaging a closed consumer group in discussion and through in-depth interviews. The analysis provides an insight into the behavior of healthcare consumers. The study finds that the new breed of consumers is well informed about healthcare providers' digital readiness. The factors influencing consumers to select healthcare providers include digital readiness of the healthcare provider, good customer experience, word of mouth, and brand image.}, Publisher = {RUSSIAN NEW UNIV}, Address = {UL RADIO, 22, MOSCOW, 105005, RUSSIA}, Type = {Article}, Language = {English}, Affiliation = {Kulkarni, P (Corresponding Author), Symbiosis Int Deemed Univ, Symbiosis Inst Digital \& Telecom Management, Pune, Maharashtra, India. Chatterjee, Sweety; Kulkarni, Prasanna, Symbiosis Int Deemed Univ, Symbiosis Inst Digital \& Telecom Management, Pune, Maharashtra, India.}, DOI = {10.18137/cardiometry.2021.20.134143}, ISSN = {2304-7232}, Keywords = {Digital Transformation; Healthcare services; Consumer behavior; Impact}, Research-Areas = {Medical Laboratory Technology}, Web-of-Science-Categories = {Medical Laboratory Technology}, Author-Email = {pkulkarni@sidtm.edu.in}, Affiliations = {Symbiosis International University; Symbiosis Institute of Digital \& Telecom Management (SIDTM)}, ResearcherID-Numbers = {KULKARNI, PRASANNA/HLX-6520-2023}, ORCID-Numbers = {KULKARNI, PRASANNA/0000-0003-1620-6380}, Cited-References = {{[}Anonymous], 2015, INT J INNOVATIVE RES. Chetana MR., FACTORS CAUSING TRAN. Gardan D, 2015, EC SERIES. Gingis Dan., 2019, HEALTHCARE GOES DIGI. Hahn H., 2019, E HLTH, P311. Jahankhani H., 2019, BLOCKCHAIN CLIN TRIA, P31. 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Tresp V, 2016, P IEEE, V104, P2180, DOI 10.1109/JPROC.2016.2615052.}, Number-of-Cited-References = {14}, Times-Cited = {0}, Usage-Count-Last-180-days = {13}, Usage-Count-Since-2013 = {46}, Journal-ISO = {Cardiometry}, Doc-Delivery-Number = {YP1GR}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000748377200017}, OA = {Bronze}, DA = {2023-10-04}, } @article{ WOS:000797218400015, Author = {Kasza, Gyula and Csenki, Eszter and Szakos, David and Izso, Tekla}, Title = {The evolution of food safety risk communication: Models and trends in the past and the future}, Journal = {FOOD CONTROL}, Year = {2022}, Volume = {138}, Month = {AUG}, Abstract = {Management of risks and uncertainty played an important role in the rise of human cultures from the beginning. Long journey has been taken from deciphering spiritual signs to the usage of artificial intelligence. Communication about risks also went through an evolutionary path and became highly specialised. During previous decades, food safety risk communication developed to be a distinguishable and well-grounded profession. Based on literature of the last 40 years, the evolution of food safety risk communication is presented from the perspectives of consumer involvement, methodological approach, and challenges. Expected future trends are also unfolded during the analysis. The paper identifies 5 + 1 stages in the evolution of food safety risk communication: Pre-risk communication era, Deficit model, Dialogue model, Partnership model, and Behavioural insight model. Expected future trends are summarised as a 6th stage, called Controlled risk environment model. The models are separated by level of consumer involvement and methodological approach. Consumer science played a crucial role in the evolutionary procedure. Despite the observed advancement between the stages, the application of each communication model might have justification under certain circumstances. In practice, the different stages have no clear boundaries, and the models can overlap. An organisation can even move on to the next phase by skipping a previous evolutionary step.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Kasza, G (Corresponding Author), Natl Food Chain Safety Off, Dept Risk Prevent \& Educ, Kelet Karoly u 24, H-1024 Budapest, Hungary. Kasza, Gyula; Csenki, Eszter; Izso, Tekla, Natl Food Chain Safety Off, Dept Risk Prevent \& Educ, Kelet Karoly u 24, H-1024 Budapest, Hungary. Szakos, David, Univ Vet Med, Istvan u 2, H-1078 Budapest, Hungary.}, DOI = {10.1016/j.foodcont.2022.109025}, EarlyAccessDate = {APR 2022}, Article-Number = {109025}, ISSN = {0956-7135}, EISSN = {1873-7129}, Keywords = {Food safety; Risk communication; Risk analysis; Consumer behaviour; Risk perception}, Keywords-Plus = {PULSED-ELECTRIC-FIELD; SCIENCE COMMUNICATION; PERCEPTION; ATTITUDES; DEFICIT; PARTICIPATION; INFORMATION; CHALLENGES; MANAGEMENT; HEALTH}, Research-Areas = {Food Science \& Technology}, Web-of-Science-Categories = {Food Science \& Technology}, Author-Email = {kaszagy@nebih.gov.hu}, Affiliations = {University of Veterinary Medicine Budapest}, ORCID-Numbers = {Kasza, Gyula/0000-0003-3120-2820}, Funding-Acknowledgement = {Horizon 2020 project entitled SafeConsume {[}727580]; Bolyai Janos Research Fellowship of the Hungarian Academy of Sciences; Bolyai + Fellowship of the New National Excellence Program of the Ministry of Innovation and Technology {[}UNKP-21-5]; H2020 Societal Challenges Programme {[}727580] Funding Source: H2020 Societal Challenges Programme}, Funding-Text = {This work was supported by the Horizon 2020 project entitled SafeConsume (Grant Agreement No. 727580) and the Bolyai Janos Research Fellowship of the Hungarian Academy of Sciences and the Bolyai + Fellowship (UNKP-21-5) of the New National Excellence Program of the Ministry of Innovation and Technology.}, Cited-References = {Ahteensuu M, 2012, J AGR ENVIRON ETHIC, V25, P295, DOI 10.1007/s10806-011-9311-9. {[}Anonymous], 2009, HDB RISK CRISIS COMM. {[}Anonymous], 2011, GEOLOGICAL SOC AM TO. {[}Anonymous], 2003, SCI PUBL POLICY. {[}Anonymous], 2010, HDB RISK CRISIS COMM. {[}Anonymous], 1992, SOCIAL THEORIES RISK. {[}Anonymous], SOLUTIONS ENV PERIL. 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Wogalter MS, 2006, HUM FAC ER, P783.}, Number-of-Cited-References = {81}, Times-Cited = {8}, Usage-Count-Last-180-days = {5}, Usage-Count-Since-2013 = {34}, Journal-ISO = {Food Control}, Doc-Delivery-Number = {1I4RY}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000797218400015}, OA = {hybrid, Green Published}, DA = {2023-10-04}, } @article{ WOS:000697186700001, Author = {Srivastava, Abhishek and Dasgupta, Shilpee A. and Ray, Arghya and Bala, Pradip Kumar and Chakraborty, Shibashish}, Title = {Relationships between the ``Big Five{''} personality types and consumer attitudes in Indian students toward augmented reality advertising}, Journal = {ASLIB JOURNAL OF INFORMATION MANAGEMENT}, Year = {2021}, Volume = {73}, Number = {6}, Pages = {967-991}, Month = {OCT 13}, Abstract = {Purpose The purpose of this paper is to investigate the role of the ``Big Five{''} personality traits (extraversion, openness, agreeableness, conscientiousness and neuroticism) on the adoption of augmented reality (AR), with a particular focus on the role AR may play in interactive marketing. Design/methodology/approach A quantitative-based approach was followed by a questionnaire survey, which was completed by 230 respondents comprising graduate and postgraduate students, using structural equation modelling. Findings While the trait of openness was positively associated with the perceived ease of use of AR, the usefulness of AR and subjective norms, the trait of neuroticism was negatively associated with the perceived ease of use of AR. Extraversion was positively associated with subjective norms. Perceived ease of use of AR, the usefulness of AR and subjective norms were positively associated with attitudes toward AR. Practical implications The data gathered will add a valuable contribution to the currently limited data available on empirical consumer behaviour research, particularly in relation to the adoption of AR for interactive marketing. Originality/value The findings of this study will benefit academics working on the adoption of technology in rapidly developing fields such as automation and artificial intelligence; the study also contributes to the emerging interdisciplinary domain of psychology, information systems, marketing and human behaviour.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Ray, A (Corresponding Author), FORE Sch Management, Informat Technol, New Delhi, India. Srivastava, Abhishek, Indian Inst Management Jammu, Jammu, India. Dasgupta, Shilpee A., Indian Inst Management Ranchi, Gen Management Area, Ranchi, Bihar, India. Ray, Arghya, FORE Sch Management, Informat Technol, New Delhi, India. Bala, Pradip Kumar; Chakraborty, Shibashish, Indian Inst Management Ranchi, Ranchi, Bihar, India.}, DOI = {10.1108/AJIM-02-2021-0046}, EarlyAccessDate = {SEP 2021}, ISSN = {2050-3806}, EISSN = {1758-3748}, Keywords = {Augmented reality; Big five personality traits; Consumer attitude; Generation Z; Wearable devices; Technology acceptance factors}, Keywords-Plus = {TECHNOLOGY ACCEPTANCE; USER ACCEPTANCE; SMART GLASSES; ADOPTION; IMPACT; USAGE; DIMENSIONS; MODEL}, Research-Areas = {Computer Science; Information Science \& Library Science}, Web-of-Science-Categories = {Computer Science, Information Systems; Information Science \& Library Science}, Author-Email = {arghya.ray16fpm@iimranchi.ac.in}, Affiliations = {Indian Institute of Management (IIM System); Indian Institute of Management Jammu; Indian Institute of Management (IIM System); Indian Institute of Management Ranchi; FORE School of Management; Indian Institute of Management (IIM System); Indian Institute of Management Ranchi}, ResearcherID-Numbers = {Ray, Arghya/GXH-3304-2022 }, ORCID-Numbers = {RAY, ARGHYA/0000-0001-5836-0621 Dasgupta, Shilpee/0000-0002-2298-1570 Chakraborty, Shibashish/0000-0002-6958-6762}, Cited-References = {AJZEN I, 1991, ORGAN BEHAV HUM DEC, V50, P179, DOI 10.1016/0749-5978(91)90020-T. 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However, many studies face the challenges of lacking a clear definition of emotional attachment that is overarching to cover emotional attachment to different entities and of differentiating these types of attachment phenomena. After reviewing the classic and contemporary research on human emotional attachment to people, pets, and possessions, we propose a novel, generalized definition and model of attachment across a person's lifespan that describes the mechanism of human emotional attachment. Our literature review revealed two distinct but overlapping broad categories of research on human attachment: human-human attachments and human-nonhuman attachments. Our model integrates psychological principles and mechanisms from both classic infant-mother attachment theory and contemporary consumer behaviour research on emotional attachment to nonhuman objects. Emphasis is placed on the central role ofthe self-conceptin all forms of human emotional attachments. We define human emotional attachment as a psychological phenomenon characterized by (a) perceiving the attributes of the attachment object as congruent with the self (supporting the self-concept and self-worth), (b) eliciting emotional reactions, and (c) evoking attachment behaviours. More specifically, the new model may lead to a series of new research on human emotional attachment to technologies and on its relationship to individuals' self-concept development and well-being.}, Publisher = {TAYLOR \& FRANCIS LTD}, Address = {2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Huang, LX (Corresponding Author), Arizona State Univ, Mesa, AZ 85212 USA. Huang, Lixiao, Arizona State Univ, Ctr Human Artificial Intelligence \& Robot Teaming, Gilbert, AZ USA. Picart, Jose, North Carolina State Univ, Dept Educ, Raleigh, NC 27695 USA. 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Sci.}, Doc-Delivery-Number = {QP2CO}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000558168300001}, DA = {2023-10-04}, } @inproceedings{ WOS:000661127403048, Author = {Niedbal, Rafal and Sokolowski, Adam and Wrzalik, Artur}, Editor = {Soliman, KS}, Title = {Selected Aspects of Internet Marketing Processes Automation in Enterprise Management}, Booktitle = {EDUCATION EXCELLENCE AND INNOVATION MANAGEMENT: A 2025 VISION TO SUSTAIN ECONOMIC DEVELOPMENT DURING GLOBAL CHALLENGES}, Year = {2020}, Pages = {3147-3156}, Note = {35th International-Business-Information-Management-Association Conference (IBIMA), Seville, SPAIN, APR 01-02, 2020}, Organization = {Int Business Informat Management Assoc}, Abstract = {The paper presents the issues related to automation of selected internet marketing processes. A vital aspect of contemporary enterprises functioning is a properly defined and selected marketing theory implemented within the virtual information space. This is a component of communication between potential customers and the enterprise. This space requires that marketing processes are automated. This is carried out based on the mechanisms available in such solutions as: Marketing Automation and Programmatic Marketing. An important role here play: artificial intelligence, machine learning and software bots. The underlying objective of the paper is the investigate the interest of commercial enterprises that operate based on the traditional-internet business model in implementing solutions in the scope of e-marketing processes automation. The pilot research was conducted with the use of a survey questionnaire and additional phone conversations as a free-form interviews among the enterprises of the gardening industry in the selected EU countries. Within the research the authors have distinguished three components of solutions applied in optimising marketing processes: Marketing Automation, Programmatic Marketing and chat bots. The results demonstrate a significant interest in the discussed solutions, in particular in implementing them on social media portals, communication with clients as well as customer behaviour analysis and monitoring. The results of the research also include opinions of entreprenuers, which indicted the potential benefits of the presented solutions pertaining to marketing processes optimisation, such as: reduced cost of service, a possibility of acquiring additional data indispensable to segment and analyse loyalty of customers.}, Publisher = {INT BUSINESS INFORMATION MANAGEMENT ASSOC-IBIMA}, Address = {34 E GERMANTOWN PIKE, NO. 327, NORRISTOWN, PA 19401 USA}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Niedbal, R (Corresponding Author), Czestochowa Tech Univ, Fac Management, Czestochowa, Poland. Niedbal, Rafal; Sokolowski, Adam; Wrzalik, Artur, Czestochowa Tech Univ, Fac Management, Czestochowa, Poland.}, ISBN = {978-0-9998551-4-0}, Keywords = {Marketing Automation; Programmatic Marketing; Online Marketing; Chat Bots}, Keywords-Plus = {AGENTS}, Research-Areas = {Business \& Economics; Science \& Technology - Other Topics}, Web-of-Science-Categories = {Business; Green \& Sustainable Science \& Technology; Economics; Management}, Author-Email = {rafal.niedbal@pcz.pl adam.sokolowski@pcz.pl artur.wrzalik@pcz.pl}, Affiliations = {Technical University Czestochowa}, Cited-References = {{[}Anonymous], STAT MARK AUT SURV R. {[}Anonymous], 2019, MARKETING AUTOMATION. {[}Anonymous], 2020, WHAT IS PROGRAMMATIC. {[}Anonymous], 2014, PROGRAMMATIC BUYING. Araujo T, 2018, COMPUT HUM BEHAV, V85, P183, DOI 10.1016/j.chb.2018.03.051. Bakhshi N., 2018, CHATBOTS POINT VIEW. Ben Mimoun MS, 2015, J RETAIL CONSUM SERV, V26, P70, DOI 10.1016/j.jretconser.2015.05.008. 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Zarouali B., 2018, BEHAV SOCIAL NETWORK, V21, P1.}, Number-of-Cited-References = {28}, Times-Cited = {0}, Usage-Count-Last-180-days = {0}, Usage-Count-Since-2013 = {2}, Doc-Delivery-Number = {BR6GF}, Web-of-Science-Index = {Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH)}, Unique-ID = {WOS:000661127403048}, DA = {2023-10-04}, } @article{ WOS:000760268900001, Author = {Liu, Yishu and Chen, Chen}, Title = {Improved RFM Model for Customer Segmentation Using Hybrid Meta-heuristic Algorithm in Medical IoT Applications}, Journal = {INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS}, Year = {2022}, Volume = {31}, Number = {01}, Month = {FEB}, Abstract = {In Internet of Things (IoT) business applications, healthcare records and medical web service management have emerging technologies tremendous amount of data in daily transactions. The cloud service providers have attracted the attention of a huge number of user requests based on different Quality of Service (QoS) factors. The data gained researchers attention to predict user behavior through the production of IoT applications. Artificial Intelligence (AI)-based techniques have a great impact on analyzing and detection of web service segmentation and user behavior in selecting and allocating online services and online stores with wireless communications and smart devices. This research improves the Redundancy, Frequency, and Maintenance value (RFM) model to evaluate healthcare records using a hybrid Grouping Genetic Algorithm (GGA) and Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithms. In this hybrid method, using the GGA algorithm, the features selection is applied to find the optimal features for healthcare records of customer segmentation. After that, by applying the RFM model on the data output of the genetic algorithm, the data are clustered. Finally, by applying the DBSCAN algorithm, the most suitable case for clustering will be selected. The simulation results show that the accuracy of the genetic algorithm is 97\% and the final clustering accuracy is 92\%.}, Publisher = {WORLD SCIENTIFIC PUBL CO PTE LTD}, Address = {5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE}, Type = {Article}, Language = {English}, Affiliation = {Chen, C (Corresponding Author), Nanchang Normal Coll Appl Technol, Sch Econ \& Management, Nanchang 330108, Jiangxi, Peoples R China. Liu, Yishu; Chen, Chen, Nanchang Normal Coll Appl Technol, Sch Econ \& Management, Nanchang 330108, Jiangxi, Peoples R China.}, DOI = {10.1142/S0218213022500099}, Article-Number = {2250009}, ISSN = {0218-2130}, EISSN = {1793-6349}, Keywords = {IoT; healthcare records; customer segmentation; feature selection; RFM model; DBSCAN; GGA}, Keywords-Plus = {PURCHASE INTENTION; PREDICTION; INTERNET; ATTITUDE}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications}, Author-Email = {pim\_lau@163.com cool-16@163.com}, Cited-References = {Al Bazi A, 2021, INT J ARTIF INTELL T, V30, DOI 10.1142/S0218213021500032. Anitha, 2019, J KING SAUD U INF SC. {[}Anonymous], 2014, INT J INF THEORY. Arora N, 2019, DECISION-INDIA, V46, P179, DOI 10.1007/s40622-019-00208-7. Blaszczynski J, 2021, EXPERT SYST APPL, V163, DOI 10.1016/j.eswa.2020.113740. 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Tools}, Doc-Delivery-Number = {ZG4ZW}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000760268900001}, DA = {2023-10-04}, } @article{ WOS:000405783400067, Author = {Bezerra, Valeria S. and Freitas-Silva, Otniel and Damasceno, Leandro Fernandes and Goulart Nunes Mamede, Alexandra Mara and Cabral, Lourdes M. C.}, Title = {SENSORY ANALYSIS AND CONSUMERS STUDIES OF ACAI BEVERAGE AFTER THERMAL, CHLORINE AND OZONE TREATMENTS OF THE FRUITS}, Journal = {JOURNAL OF FOOD PROCESSING AND PRESERVATION}, Year = {2017}, Volume = {41}, Number = {3}, Month = {JUN}, Abstract = {Acai is a fruit of the Amazon region consumed as beverage, pulp, and other products, being exported to many countries because of its peculiar characteristic flavor and antioxidant power potential. For Acai there is still a need for improving sanitizing processes, making it more effective, reducing the microbiological contamination without affecting either the physicochemical and sensory characteristics of final product. Thermal (blanching at 80 and 90C) and nonthermal treatments (150 mg/L-1 chlorination and 4 mg/L-1 aqueous ozonation) were applied to fruits in order to evaluated their anthocyanins content and also processed beverages for coloring, sensory characteristics, and their purchase intentions. Ozonated fruits exhibited less anthocyanins content and beverage originated from this process showed higher color difference from the traditional beverage. Consumers could not distinguish among beverages processed thermally and sanitized by chlorination. Beverage from blanched fruits in both temperatures obtained good notes and positive purchase intention. PRACTICAL APPLICATIONS The Acai fruit has naturally high microbial load and sanitization processes of fruit were studied. Thermal (blanching at 80 and 90C) and nonthermal treatments (150 mg/L-1 chlorination and 4 mg/L-1 aqueous ozonation) were applied to fruits in order to evaluated possible changes the anthocyanins content on Acai fruits and color and sensory characteristics of the beverage. Practical results were obtained since aqueous ozonation process promoted changes in total anthocyanins content of Ac, ai fruits and the difference of the color beverage over traditional sample. Thermal and nonthermal treatments for Ac, ai fruits did not affect the quality and sensory characteristics of beverages, and beverages from fruits thermally treated obtained good purchase intentions by traditional regional consumers. The thermal treatment of Acai fruit at 90C can be considered a new parameter for the sanitization of Acai processors.}, Publisher = {WILEY}, Address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, Type = {Article}, Language = {English}, Affiliation = {Bezerra, VS (Corresponding Author), Univ Fed Rio de Janeiro, PPGCAL Inst Chem, Av Athos da Silveira Ramos,149 Bloco A-5 Andar, BR-21941909 Rio De Janeiro, RJ, Brazil. Bezerra, Valeria S., Univ Fed Rio de Janeiro, PPGCAL Inst Chem, Av Athos da Silveira Ramos,149 Bloco A-5 Andar, BR-21941909 Rio De Janeiro, RJ, Brazil. Bezerra, Valeria S.; Damasceno, Leandro Fernandes, Embrapa Amapa, Rodovia Juscelino Kubitscheck 2-600, BR-68903419 Macapa, AP, Brazil. Freitas-Silva, Otniel; Goulart Nunes Mamede, Alexandra Mara; Cabral, Lourdes M. C., Embrapa Food Technol, Av Amer 29501, BR-23020470 Rio De Janeiro, RJ, Brazil.}, DOI = {10.1111/jfpp.12961}, Article-Number = {e12961}, ISSN = {0145-8892}, EISSN = {1745-4549}, Keywords-Plus = {EUTERPE-OLERACEA; LISTERIA-MONOCYTOGENES; ANTHOCYANINS; QUALITY; COLOR; FOOD; DEGRADATION; STABILITY; COPIGMENTATION; OPTIMIZATION}, Research-Areas = {Food Science \& Technology}, Web-of-Science-Categories = {Food Science \& Technology}, Author-Email = {valeria.bezerra@embrapa.br}, Affiliations = {Universidade Federal do Rio de Janeiro; Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA); Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA)}, ResearcherID-Numbers = {Freitas-Silva, Otniel/S-4765-2018}, ORCID-Numbers = {Freitas-Silva, Otniel/0000-0002-7658-8010}, Funding-Acknowledgement = {Government of the State of Amapa, Brazil through the Secretary of State for Science and Technology-SETEC; Foundation for the Amapa State Research-Foundation Tumucumaque; FAPERJ}, Funding-Text = {This research project has financial support from the Government of the State of Amapa, Brazil. through the Secretary of State for Science and Technology-SETEC and the Foundation for the Amapa State Research-Foundation Tumucumaque and FAPERJ.}, Cited-References = {ALBARICI T.R., 2002, EFEITO TEMPERATURA N, P2. 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Min and Kim, Min Je and Lee, Mi Young and Baik, Sung Wook}, Title = {Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting}, Journal = {ENERGY AND BUILDINGS}, Year = {2023}, Volume = {279}, Month = {JAN 15}, Abstract = {Due to global warming and climate changes, buildings including residential and commercial are significant contributors to energy consumption. To this end, net zero energy building (NZEB) has become a progressively popular concept where the annual sum of power generation and consumption is zero. However, occasionally, there exists a mismatching between demand and supply in NZEB due to consumer behaviour and weather conditions disturbing the overall management of the smart grid. To overcome such hurdles, precise prediction of energy usage is a key strategy among others. Therefore, in this study, an efficient hybrid AI-based framework is proposed for accurate forecasting of power consumption and generation that is mainly composed of three steps. Initially, the optimal pre-processing procedure is applied for data refinement. Next, for the spatiotemporal features, a convolutional long short-term memory (ConvLSTM) is used that learns discriminative patterns from the past power knowledge, followed by a bidirectional gated recurrent unit (BDGRU) that extracts on temporal aspects. Eventually, feature descriptors are then passed to multilayer perceptron layers to perform the forecasting. After extensive experiments over the household and photovoltaic energy data, we concluded that our model substantially reduced the errors of 0.012 and 0.045 in terms of mean square error (MSE) on hourly data as compared to the recent state-of-the-art techniques (SOTA).(c) 2022 Elsevier B.V. All rights reserved.}, Publisher = {ELSEVIER SCIENCE SA}, Address = {PO BOX 564, 1001 LAUSANNE, SWITZERLAND}, Type = {Article}, Language = {English}, Affiliation = {Baik, SW (Corresponding Author), Sejong Univ, Seoul, South Korea. Khan, Samee Ullah; Khan, Noman; Ullah, Fath U. Min; Kim, Min Je; Lee, Mi Young; Baik, Sung Wook, Sejong Univ, Seoul, South Korea.}, DOI = {10.1016/j.enbuild.2022.112705}, EarlyAccessDate = {DEC 2022}, Article-Number = {112705}, ISSN = {0378-7788}, EISSN = {1872-6178}, Keywords = {Building energy; Smart grid; Forecasting; Deep learning; Solar power; Power consumption; Time series}, Keywords-Plus = {NEURAL-NETWORKS; PREDICTION; MODEL; CNN}, Research-Areas = {Construction \& Building Technology; Energy \& Fuels; Engineering}, Web-of-Science-Categories = {Construction \& Building Technology; Energy \& Fuels; Engineering, Civil}, Author-Email = {sbaik@sejong.ac.kr}, Affiliations = {Sejong University}, ResearcherID-Numbers = {KHAN, SAMEE ULLAH/AAU-2504-2020 Khan, Noman/ABI-3725-2020}, ORCID-Numbers = {KHAN, SAMEE ULLAH/0000-0001-5640-4942 Khan, Noman/0000-0001-7531-3827}, Funding-Acknowledgement = {National Research Foundation of Korea (NRF) - Korean government (MSIT); {[}2019M3F2A1073179]}, Funding-Text = {This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019M3F2A1073179) .}, Cited-References = {Ahmed A, 2019, RENEW SUST ENERG REV, V100, P9, DOI 10.1016/j.rser.2018.09.046. 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Zou W, 2019, IEEE T IND INFORM, V15, P4934, DOI 10.1109/TII.2019.2910606.}, Number-of-Cited-References = {57}, Times-Cited = {9}, Usage-Count-Last-180-days = {8}, Usage-Count-Since-2013 = {10}, Journal-ISO = {Energy Build.}, Doc-Delivery-Number = {7R4WG}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000910073700001}, DA = {2023-10-04}, } @inproceedings{ WOS:000866475000019, Author = {Bhavana, Puppala Bala and Kondaveeti, Hari Kishan and Dalai, Asish Kumar}, Editor = {Noor, A and Sen, A and Trivedi, G}, Title = {Zomato Review Analysis Using NLP}, Booktitle = {PROCEEDINGS OF EMERGING TRENDS AND TECHNOLOGIES ON INTELLIGENT SYSTEMS (ETTIS 2021)}, Series = {Advances in Intelligent Systems and Computing}, Year = {2022}, Volume = {1371}, Pages = {235-242}, Note = {International Conference on Emerging Trends and Technologies on Intelligent Systems (ETTIS), ELECTR NETWORK, MAR 04-05, 2021}, Organization = {Ctr Dev Adv Comp; Petr Gas Univ Ploiesti, Fac Mech \& Elect Engn, Automat Control Comp \& Elect Dept}, Abstract = {Natural language processing is generally used to understand the interactions between humans and machine, and it is also a subpart of artificial intelligence. Sentimental analysis is a subpart of AI and used to differentiate the words by the patterns that are given by people like good, bad, or average. Sentiment analysis is used to knowabout user's likes and dislikes toward a product. Zomato is an app which is used for ordering foods from different restaurants and allows user to drop their reviews and ratings of respective food that they ordered. These reviews given by the customers will be taken for sentimental analysis. The buying decision of a customer is also depending on the reviews and ratings. So, reviews have a lot more important. It is estimated that 79\% of unstructured data is producing every day. A lot of textual data are generating through social media, healthcare, e-commerce applications. We as humans cannot analyze these huge volumes of data. Sentiment analysis will help us to do this task very easily. In this project, we can train with millions of data and predict new data as positive, negative, and neutral. We use artificial neural networks (ANNs) to train the model and to predict the reviews as positive, negative, or neutral. Artificial neural networks use feedforward networks and work as biological neural networks.}, Publisher = {SPRINGER INTERNATIONAL PUBLISHING AG}, Address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Dalai, AK (Corresponding Author), VIT AP Univ, Sch Comp Sci Engn, Near Vijayawada, Amaravati, Andhra Pradesh, India. Bhavana, Puppala Bala; Kondaveeti, Hari Kishan; Dalai, Asish Kumar, VIT AP Univ, Sch Comp Sci Engn, Near Vijayawada, Amaravati, Andhra Pradesh, India.}, DOI = {10.1007/978-981-16-3097-2\_19}, ISSN = {2194-5357}, EISSN = {2194-5365}, ISBN = {978-981-16-3097-2; 978-981-16-3096-5}, Keywords = {Natural language processing; Artificial neural networks; Sentimental analysis; Feedforward network}, Research-Areas = {Computer Science}, Web-of-Science-Categories = {Computer Science, Artificial Intelligence}, Author-Email = {balabhavana.puppala@vitap.ac.in kishan.kondaveeti@vitap.ac.in asish.d@vitap.ac.in}, Affiliations = {VIT Bhopal University}, ResearcherID-Numbers = {Kondaveeti, Hari Kishan/K-4827-2017}, ORCID-Numbers = {Kondaveeti, Hari Kishan/0000-0002-3379-720X}, Cited-References = {cheatsheet, LOSS FUNCTIONS. monkeylearn, SENTIMENT ANAL. Munoz R, EVOL COMMUN. Patrikar S, 2019, GRADIENT DESCENT. Sharma A.V, 2017, ACTIVATION FUNCTIONS.}, Number-of-Cited-References = {5}, Times-Cited = {0}, Usage-Count-Last-180-days = {0}, Usage-Count-Since-2013 = {2}, Doc-Delivery-Number = {BU0AS}, Web-of-Science-Index = {Conference Proceedings Citation Index - Science (CPCI-S)}, Unique-ID = {WOS:000866475000019}, DA = {2023-10-04}, } @article{ WOS:000911284400001, Author = {Lin, Jhih-Syuan (Elaine) and Wu, Linwan}, Title = {Examining the psychological process of developing consumer-brand relationships through strategic use of social media brand chatbots}, Journal = {COMPUTERS IN HUMAN BEHAVIOR}, Year = {2023}, Volume = {140}, Month = {MAR}, Abstract = {As brands increasingly integrate artificial intelligence (AI)-enabled automation as part of their communication efforts, marketers have employed social media brand chatbots to provide personalized responses to consumers and facilitate relationship building. However, how specific facets of consumer-brand relationships may be manifested in the process of consumer-brand interaction via social media brand chatbots warrants further investigation. Hence, the current research develops a conceptual model to examine how perceived contingency, a defining psychological determinant of social media brand chatbots, determines consumer brand relationship outcomes via different motivational experiences and consumer engagement. Based on the survey conducted in the U.S. (N = 491), the findings reveal that perceived contingency is positively related to gratifications of information seeking, social interaction, and entertainment, while information seeking and social interaction lead to enhanced consumer engagement. In addition, consumer engagement helps deepen brand intimacy, strengthen affective commitment, and increase chatbot-related behavioral intention and purchase intention. The findings further show that social-interaction gratification and consumer engagement are crucial components that underline how consumers' perception of contingency can foster strong, affect-laden brand relationships when marketers capitalize on the conversational capabilities of social media brand chatbots. Theoretical and practical implications, as well as limitations and directions for future research, are discussed.}, Publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Lin, JS (Corresponding Author), Natl Chengchi Univ, Taiwan Inst Governance \& Commun Res, Coll Commun, Dept Advertising, 64,Sect 2,Zhinan Rd, Taipei, Taiwan. Lin, Jhih-Syuan (Elaine), Natl Chengchi Univ, Taiwan Inst Governance \& Commun Res, Coll Commun, Dept Advertising, 64,Sect 2,Zhinan Rd, Taipei, Taiwan. Wu, Linwan, Univ South Carolina, Coll Informat \& Commun, Sch Journalism \& Mass Commun, 800 Sumter St,Room 329, Columbia, SC USA.}, DOI = {10.1016/j.chb.2022.107488}, EarlyAccessDate = {DEC 2022}, Article-Number = {107488}, ISSN = {0747-5632}, EISSN = {1873-7692}, Keywords = {Social media brand chatbots; Perceived contingency; Uses and gratifications; Consumer engagement; consumer-brand relationships}, Keywords-Plus = {ARTIFICIAL-INTELLIGENCE; CONVERSATIONAL AGENT; CUSTOMER ENGAGEMENT; SELF-DISCLOSURE; WEB SITE; INTERACTIVITY; COMMITMENT; METHODOLOGY; EXPERIENCE; TRUST}, Research-Areas = {Psychology}, Web-of-Science-Categories = {Psychology, Multidisciplinary; Psychology, Experimental}, Author-Email = {jslin@nccu.edu.tw linwanwu@mailbox.sc.edu}, Affiliations = {National Chengchi University; University of South Carolina System; University of South Carolina Columbia}, Funding-Acknowledgement = {Ministry of Science and Technology under grant MOST {[}108-2410-H-004 -183 -MY2]}, Funding-Text = {This study was supported by the Ministry of Science and Technology under grant MOST \#108-2410-H-004 -183 -MY2.}, Cited-References = {Aaker JL, 1997, J MARKETING RES, V34, P347, DOI 10.2307/3151897. 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Xu AB, 2017, PROCEEDINGS OF THE 2017 ACM SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'17), P3506, DOI 10.1145/3025453.3025496. Youn S, 2021, COMPUT HUM BEHAV, V119, DOI 10.1016/j.chb.2021.106721. Yuen M., 2022, CHATBOT MARKET 2022. Zarouali B, 2021, EUR J COMMUN, V36, P53, DOI 10.1177/0267323120940908. Zarouali B, 2018, CYBERPSYCH BEH SOC N, V21, P491, DOI 10.1089/cyber.2017.0518.}, Number-of-Cited-References = {149}, Times-Cited = {3}, Usage-Count-Last-180-days = {43}, Usage-Count-Since-2013 = {71}, Journal-ISO = {Comput. Hum. Behav.}, Doc-Delivery-Number = {7T2NU}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000911284400001}, DA = {2023-10-04}, } @article{ WOS:000528193700028, Author = {Koehn, Dennis and Lessmann, Stefan and Schaal, Markus}, Title = {Predicting online shopping behaviour from clickstream data using deep learning}, Journal = {EXPERT SYSTEMS WITH APPLICATIONS}, Year = {2020}, Volume = {150}, Month = {JUL 15}, Abstract = {Clickstream data is an important source to enhance user experience and pursue business objectives in e-commerce. The paper uses clickstream data to predict online shopping behavior and target marketing interventions in real-time. Such AI-driven targeting has proven to save huge amounts of marketing costs and raise shop revenue. Previous user behavior prediction models rely on supervised machine learning (SML). Conceptually, SML is less suitable because it cannot account for the sequential structure of clickstream data. The paper proposes a methodology capable of unlocking the full potential of clickstream data using the framework of recurrent neural networks (RNNs). An empirical evaluation based on real-world e-commerce data systematically assesses multiple RNN classifiers and compares them to SML benchmarks. To this end, the paper proposes an approach to measure the revenue impact of a targeting model. Estimates of revenue impact together with results of standard classifier performance metrics evidence the viability of RNN-based clickstream modeling and guide employing deep recurrent learners for campaign targeting. Given that the empirical analysis shows RNN-based and conventional classifiers to capture different patterns in clickstream data, a specific recommendation is to combine sequence and conventional classifiers in an ensemble. The paper shows such an ensemble to consistently outperform the alternative models considered in the study. (C) 2020 Elsevier Ltd. All rights reserved.}, Publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Lessmann, S (Corresponding Author), Humboldt Univ, Chair Informat Syst, Spandauer Str 1, D-10178 Berlin, Germany. Koehn, Dennis; Lessmann, Stefan, Humboldt Univ, Chair Informat Syst, Spandauer Str 1, D-10178 Berlin, Germany. Schaal, Markus, Webtrekk GmbH, Robert Koch Pl 4, D-10115 Berlin, Germany.}, DOI = {10.1016/j.eswa.2020.113342}, Article-Number = {113342}, ISSN = {0957-4174}, EISSN = {1873-6793}, Keywords = {Deep learning; e-commerce; Recurrent neural networks; Digital marketing}, Keywords-Plus = {CONVERSION; MODELS; TIME}, Research-Areas = {Computer Science; Engineering; Operations Research \& Management Science}, Web-of-Science-Categories = {Computer Science, Artificial Intelligence; Engineering, Electrical \& Electronic; Operations Research \& Management Science}, Author-Email = {dkoehn@hotmail.de stefan.lessmann@hu-berlin.de markus.schaal@webtrekk.com}, Affiliations = {Humboldt University of Berlin}, ResearcherID-Numbers = {Lessmann, Stefan/AEG-7736-2022}, ORCID-Numbers = {Lessmann, Stefan/0000-0001-7685-262X}, Cited-References = {Abadi M, 2016, TENSORFLOW LARGE SCA, V16, P265. Abelian J, 2017, EXPERT SYST APPL, V73, P1, DOI 10.1016/j.eswa.2016.12.020. Arora S., 2016, KDD WORKSH MACH LEAR. 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Appl.}, Doc-Delivery-Number = {LG6FG}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000528193700028}, DA = {2023-10-04}, } @article{ WOS:000664448800004, Author = {Oancea, Octavian}, Title = {The implications of behavioural economics for pricing in a world of offer optimisation}, Journal = {JOURNAL OF REVENUE AND PRICING MANAGEMENT}, Year = {2021}, Volume = {20}, Number = {6, SI}, Pages = {626-633}, Month = {DEC}, Abstract = {The impact of the COVID-19 on the industry has highlighted once again the need to create new ways of addressing consumers that would be less reliant on historic data, and more adjusted to recent observations of consumer behaviour, real time experiments and competitive context. This article addresses the implications of consumer behavioural economics in the design of offers and the way airlines will have to rethink the way they price in a New Distribution Capability (NDC) world, as defined by IATA. In a pandemic impacted era, this investment will show its fruits not only after, but also during the recovery phase, where travel behaviour is exceptionally different, capacity fluctuates and the competitive landscape is equally difficult to predict. We will discuss what challenges a pricing department is facing in this new world of offers, as well as how to overcome them in order to provide relevant and personalised offers to each consumer and price them according to the value that these offers bring. In the COVID-19 context as well as post-pandemic, airlines will need to not only respond quicker with capacity adjustments, but also to better understand human behaviour relative to a purchase decision and address each consumer with an optimised offer in real-time, as they request it. Some of the questions for which new artificial intelligence experimentation techniques and behavioural economics models will require significant development are: What drives a person to choose or not to choose a certain offer? How many choices should they see? What trip purpose segment do they belong to? What is their willingness to pay? What attributes of an offer are people considering and what value do they associate to these offers?}, Publisher = {PALGRAVE MACMILLAN LTD}, Address = {BRUNEL RD BLDG, HOUNDMILLS, BASINGSTOKE RG21 6XS, HANTS, ENGLAND}, Type = {Article}, Language = {English}, DOI = {10.1057/s41272-021-00348-5}, EarlyAccessDate = {JUN 2021}, ISSN = {1476-6930}, EISSN = {1477-657X}, Keywords = {Pricing; Behavioural economics; Revenue management; Innovation; Offer optimisation}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business, Finance}, Author-Email = {omifam@yahoo.com}, Cited-References = {Bockelie A, 2017, J REVENUE PRICING MA, V16, P553, DOI 10.1057/s41272-017-0100-6. Cheng YY, 2012, BRIT J PSYCHOL, V103, P129, DOI 10.1111/j.2044-8295.2011.02067.x. Lu Y, 2019, IMPACTS ANCILLARY SE. Nammir D. S. S., 2012, EUR J BUS MANAGE, V4, P27. Oancea O, 2020, J REVENUE PRICING MA, V19, P230, DOI 10.1057/s41272-020-00248-0. 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Revenue Pricing Manag.}, Doc-Delivery-Number = {WS1DT}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000664448800004}, OA = {Bronze}, DA = {2023-10-04}, } @article{ WOS:001052247600001, Author = {Leong, Lai-Ying and Hew, Teck Soon and Ooi, Keng-Boon and Hajli, Nick and Tan, Garry Wei-Han}, Title = {Revisiting the social commerce paradigm: the social commerce (SC) framework and a research agenda}, Journal = {INTERNET RESEARCH}, Year = {2023}, Month = {2023 AUG 24}, Abstract = {PurposeSocial commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).Design/methodology/approachIn the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.FindingsFrom 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.Practical implicationsThe SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.Originality/valueThe authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article; Early Access}, Language = {English}, Affiliation = {Tan, GWH (Corresponding Author), UCSI Univ, UCSI Grad Business Sch, Kuala Lumpur, Malaysia. Tan, GWH (Corresponding Author), Nanchang Inst Technol, Sch Finance \& Econ, Nanjing, Peoples R China. Tan, GWH (Corresponding Author), Yunnan Normal Univ, Sch Econ \& Management, Nanjing, Peoples R China. Tan, GWH (Corresponding Author), Asia e Univ, Subang Jaya, Malaysia. Leong, Lai-Ying, Univ Tunku Abdul Rahman, Fac Business \& Finance, Dept Commerce \& Accountancy, Perak, Malaysia. Hew, Teck Soon, Univ Malaya, Fac Business \& Econom, Dept Operat \& Management Informat Syst, Kuala Lumpur, Malaysia. Ooi, Keng-Boon; Tan, Garry Wei-Han, UCSI Univ, UCSI Grad Business Sch, Kuala Lumpur, Malaysia. Ooi, Keng-Boon; Tan, Garry Wei-Han, Nanchang Inst Technol, Sch Finance \& Econ, Nanjing, Peoples R China. Ooi, Keng-Boon, Chang Jung Christian Univ, Coll Management, Tainan, Taiwan. Hajli, Nick, Swansea Univ, Sch Management, Swansea, Wales. Tan, Garry Wei-Han, Yunnan Normal Univ, Sch Econ \& Management, Nanjing, Peoples R China. Tan, Garry Wei-Han, Asia e Univ, Subang Jaya, Malaysia.}, DOI = {10.1108/INTR-08-2022-0657}, EarlyAccessDate = {AUG 2023}, ISSN = {1066-2243}, Keywords = {Social commerce framework; research agenda; science mapping; evolution map; scoping review; bibliometric analysis; performance analysis}, Keywords-Plus = {BEHAVIOR; SUPPORT}, Research-Areas = {Business \& Economics; Computer Science; Telecommunications}, Web-of-Science-Categories = {Business; Computer Science, Information Systems; Telecommunications}, Author-Email = {lyennlly@gmail.com hewtecksoon@gmail.com Ooikengboon@gmail.com n.hajli@lboro.ac.uk garrytanweihan@gmail.com}, Affiliations = {Universiti Tunku Abdul Rahman (UTAR); Universiti Malaya; UCSI University; Nanchang Institute Technology; Chang Jung Christian University; Swansea University; Yunnan Normal University}, ResearcherID-Numbers = {OOI, Keng-Boon/I-4143-2019 Lai-Ying, Leong/S-5659-2017}, ORCID-Numbers = {OOI, Keng-Boon/0000-0002-3384-1207 Hajli, Professor Nick/0000-0002-9818-181X Tan Wei Han, Garry/0000-0003-2974-2270 Lai-Ying, Leong/0000-0001-7283-0300}, Funding-Acknowledgement = {UCSI University {[}T2S-2023/003]}, Funding-Text = {This work was supported by the UCSI University under the UCSI World's Top 2\% Scientist Research Grant under the project number T2S-2023/003.}, Cited-References = {Abdelsalam S, 2020, IEEE ACCESS, V8, P89041, DOI 10.1109/ACCESS.2020.2993671. 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Zvarikova K., 2022, REV CONT PHILOS, V21, P171.}, Number-of-Cited-References = {76}, Times-Cited = {0}, Usage-Count-Last-180-days = {7}, Usage-Count-Since-2013 = {7}, Journal-ISO = {Internet Res.}, Doc-Delivery-Number = {P7DR8}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:001052247600001}, DA = {2023-10-04}, } @inproceedings{ WOS:000290114100006, Author = {Gan, C. and Limsombunchai, V. and Clemes, M. and Weng, A.}, Editor = {Zerger, A and Argent, RM}, Title = {Consumer Choice Prediction: Artificial Neural Networks versus Logistic Model}, Booktitle = {MODSIM 2005: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING}, Year = {2005}, Pages = {51-57}, Note = {International Congress on Modelling and Simulation (MODSIM05), Melbourne, AUSTRALIA, DEC 12-15, 2005}, Abstract = {Quantitative analysis for forecasting in business and marketing, especially in consumer behaviour and consumer decision-making process (consumer choice modelling), has become more poplar in business practices. The ability to understand and to accurately predict the consumer decision can lead to more effectively target the products (and/or services), cost effectiveness in marketing strategies, increasing in sale and result in substantial improvement in the overall profitability of the firm. Conventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choices. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. Neural networks are considered as a field of artificial intelligence. The development of the models was inspired by the neural architecture of human brain. Neural networks have been generally applied to two different categories of problems recognition problems and generalisation problems. Recognition problems include visual applications such as learning to recognize particular words and speak them. Generalization problems include classification and prediction problems. ANN have been applied in many disciplines, including biology, psychology, statistics, mathematics, medical science, and computer science. Recently ANNs have been applied to a variety of business areas such as accounting, finance, management and decision making, marketing, and production. However, the technique has been sparsely used in modelling consumer choices. For example, Dasgupta et al. (1994) compared the performance of discriminant analysis and logistic regression models against an ANN model with respect to their ability to identify consumer segment based upon their willingness to take financial risks and to purchase a non-traditional investment product. The purpose of this paper is to empirically compare the predictive power of the probability neural network (PNN), a special class of neural networks, and the MLFN with the logistic model on consumers' banking choices between electronic banking and non-electronic banking. Data for this analysis was obtained through a mail survey sent to 1,960 household in New Zealand. The questionnaire gathered information on consumers' decision to use electronic banking versus non-electronic banking. The factors include service quality dimensions, perceived risk factors, user input factors, price factors, service product characteristics, and individual factors. In addition, demographic variables including age, gender, marital status, ethnic background, educational qualification, employment, income, and area of residence are considered. Empirical results showed that both ANN models (MLFN and PNN) exhibit a higher overall percentage correct on consumer choice predictions than the logistic model. Furthermore, the PNN demonstrates to be the best predictive model since it has the highest overall percentage correct and a very low percentage error on both Type I and Type II errors.}, Publisher = {MODELLING \& SIMULATION SOC AUSTRALIA \& NEW ZEALAND INC}, Address = {MSSANZ, CHRISTCHURCH, 00000, NEW ZEALAND}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Gan, C (Corresponding Author), Lincoln Univ, Commerce Div, Lincoln, New Zealand. Gan, C.; Limsombunchai, V.; Clemes, M.; Weng, A., Lincoln Univ, Commerce Div, Lincoln, New Zealand.}, ISBN = {978-0-9758400-2-3}, Keywords = {Electronic Banking; Artificial Neural Networks; Logistic Regression}, Keywords-Plus = {SEGMENTATION; DENSITY}, Research-Areas = {Computer Science; Operations Research \& Management Science; Mathematics}, Web-of-Science-Categories = {Computer Science, Interdisciplinary Applications; Operations Research \& Management Science; Mathematics, Applied; Mathematics, Interdisciplinary Applications}, Author-Email = {Ganc1@lincoln.ac.nz}, Affiliations = {Lincoln University - New Zealand}, ResearcherID-Numbers = {Gan, Christopher/D-6635-2018 Clemes, Michael/X-2205-2018}, ORCID-Numbers = {Gan, Christopher/0000-0002-5618-1651 Clemes, Michael/0000-0002-0438-8693}, Cited-References = {Al-Ashban A. A., 2001, INT J BANK MARK, V19, P191. Albanis G. A., 1999, P 5 ANN C INF SYST A. {[}Anonymous], J MARKETING MANAGEME. Ben-Akiva M.E., 1985, DISCRETE CHOICE ANAL. 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West PM, 1997, MARKET SCI, V16, P370, DOI 10.1287/mksc.16.4.370.}, Number-of-Cited-References = {22}, Times-Cited = {0}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {9}, Doc-Delivery-Number = {BUQ81}, Web-of-Science-Index = {Conference Proceedings Citation Index - Science (CPCI-S)}, Unique-ID = {WOS:000290114100006}, DA = {2023-10-04}, } @article{ WOS:000937168000003, Author = {Cuesta-Valino, Pedro and Kazakov, Sergey and Gutierrez-Rodriguez, Pablo and Rua, Orlando Lima}, Title = {The effects of the aesthetics and composition of hotels' digital photo images on online booking decisions}, Journal = {HUMANITIES \& SOCIAL SCIENCES COMMUNICATIONS}, Year = {2023}, Volume = {10}, Number = {1}, Month = {FEB 15}, Abstract = {Photographic images help customers perceive product information more accurately and clearly. A customer's perception of a particular product also influences their decision to purchase it. In the context of a hotel, guests evaluate digital hotel photos online during their booking decision process. While a large body of research has contributed to the understanding of how hotel online digital images shape hotel customer behaviour, little is known about the aesthetics, content, and composition of hotel images and their effects on booking decisions. In addition, previous research has routinely been criticised for having methodological limitations. These studies have routinely used surveys and experiments to explore how hotel pictures affect customer perception of the hotel and his/her booking intentions. Unlike prior studies, this research scopes a determination of the `selling' properties pertinent to the hotel's digital images placed online on the hotel-themed websites with the application of the latest technologies pursuant to visual data mining, processing and analysis. This study employed Google's Inception v3 neural network as an AI solution for embedding and classifying hotel photo images with the further application of logistic regression and fuzzy cognitive mapping method. The results of the present study determined the hotel picture properties that may engender positive customer perception of the hotel and sequentially can precipitate hotel booking. The revealed `selling' hotel image properties comprise (a) light and time of the photo shooting, (b) image colour scheme, (c) human presence, and (d) shooting angle. This study suggests a set of practical recommendations to hotel marketers to develop `selling' photo images that generate hotel bookings online. The completed research is one of the first in the nascent literature stream in AI-powered computer vision solutions studies to determine the effects of photo aesthetics on online hotel bookings.}, Publisher = {SPRINGERNATURE}, Address = {CAMPUS, 4 CRINAN ST, LONDON, N1 9XW, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Cuesta-Valino, P (Corresponding Author), Univ Alcala, Alcala De Henares, Spain. Cuesta-Valino, Pedro; Kazakov, Sergey, Univ Alcala, Alcala De Henares, Spain. Gutierrez-Rodriguez, Pablo, Univ Leon, Leon, Spain. Rua, Orlando Lima, Polytech Porto, Ctr Org \& Social Studies, Porto, Portugal.}, DOI = {10.1057/s41599-023-01529-w}, Article-Number = {59}, EISSN = {2662-9992}, Keywords-Plus = {INFORMATION; PERFORMANCE; INSIGHTS; TOURISM}, Research-Areas = {Arts \& Humanities - Other Topics; Social Sciences - Other Topics}, Web-of-Science-Categories = {Humanities, Multidisciplinary; Social Sciences, Interdisciplinary}, Author-Email = {pedro.cuesta@uah.es}, Affiliations = {Universidad de Alcala; Universidad de Leon; Instituto Politecnico do Porto}, ResearcherID-Numbers = {Cuesta-Valiño, Pedro/J-2809-2018 Kazakov, Sergey/AEY-5424-2022 Gutiérrez-Rodríguez, Pablo/ITT-3959-2023}, ORCID-Numbers = {Cuesta-Valiño, Pedro/0000-0001-9521-333X Kazakov, Sergey/0000-0001-5532-5791 Gutiérrez-Rodríguez, Pablo/0000-0001-5407-4265}, Funding-Acknowledgement = {Telefonica and its Telefonica Chair on Smart Cities of the Universitat Rovira i Virgili; Universitatde Barcelona {[}42, DB.00.18.00]}, Funding-Text = {This research was supported by Telefonica and its Telefonica Chair on Smart Cities of the Universitat Rovira i Virgili and the Universitatde Barcelona (project number 42.DB.00.18.00).}, Cited-References = {Aksoy S, 2017, TOUR MANAG PERSPECT, V22, P73, DOI 10.1016/j.tmp.2017.02.001. 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Wang Weining, 2014, Journal of Computer Aided Design \& Computer Graphics, V26, P1075. Weber L., 2019, J SOC MEDIA MARK, V6, P332. Yang S, 2022, J BUS RES, V152, P447, DOI 10.1016/j.jbusres.2022.07.058. Yeh CH, 2014, ACM T MULTIM COMPUT, V10, DOI 10.1145/2584105. Zhang QF, 2020, J DESTIN MARK MANAGE, V16, DOI 10.1016/j.jdmm.2020.100429.}, Number-of-Cited-References = {74}, Times-Cited = {1}, Usage-Count-Last-180-days = {8}, Usage-Count-Since-2013 = {8}, Journal-ISO = {Hum. Soc. Sci. Commun.}, Doc-Delivery-Number = {9F0LK}, Web-of-Science-Index = {Social Science Citation Index (SSCI); Arts & Humanities Citation Index (A&HCI)}, Unique-ID = {WOS:000937168000003}, OA = {gold}, DA = {2023-10-04}, } @article{ WOS:000574447900001, Author = {Cheung, Man Lai and Leung, Ka Shing Wilson and Chan, Hak Sin}, Title = {Driving healthcare wearable technology adoption for Generation Z consumers in Hong Kong}, Journal = {YOUNG CONSUMERS}, Year = {2021}, Volume = {22}, Number = {1, SI}, Pages = {10-27}, Month = {JUL 30}, Abstract = {Purpose Young consumers have increasingly adopted wearable health-care technology to improve their well-being. Drawing on generation cohort theory (GCT) and the technology acceptance model (TAM), this study aims to illuminate the major factors that drive the adoption of health-care wearable technology products by Generation Z (Gen-Z) consumers in Hong Kong. Design/methodology/approach A self-administrated online survey was used to collect data from a sample of Gen-Z consumers in Hong Kong with experience in using health-care wearable technology. Data analysis was performed using partial least-squares-structural equation modeling to verify four hypotheses. Findings The results reveal that consumer innovativeness (CI) and electronic word-of-mouth referral (EWOM) are significant predictors of perceived credibility, perceived ease of use and perceived usefulness, which subsequently drive online engagement intention and adoption intention (AI). Practical implications This research provides practical guidance for marketers of health-care wearable technology products. In particular, CI and EWOM hold the key to young consumers' product perceptions (and thereby their online engagement and AIs). Originality/value This research leverages the insights of GCT to enrich the TAM, specifically by including CI and EWOM as antecedents and online engagement as a consequence in the context of health-care wearable technology. The results of an empirical study enhance theoretical understanding of Gen-Z consumers' perceptions and behavioral intentions toward health-care wearable technology. They also point to actionable recommendations for marketing this new technology to young consumers.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Cheung, ML (Corresponding Author), Hang Seng Univ Hong Kong, Dept Mkt, Shatin, Hong Kong, Peoples R China. Cheung, ML (Corresponding Author), Univ Newcastle, Newcastle Business Sch, Newcastle, NSW, Australia. Cheung, Man Lai; Chan, Hak Sin, Hang Seng Univ Hong Kong, Dept Mkt, Shatin, Hong Kong, Peoples R China. Cheung, Man Lai, Univ Newcastle, Newcastle Business Sch, Newcastle, NSW, Australia. Leung, Ka Shing Wilson, Polytech Univ Hong Kong, Coll Profess \& Continuing Educ, Hong Kong, Peoples R China.}, DOI = {10.1108/YC-04-2020-1123}, EarlyAccessDate = {SEP 2020}, ISSN = {1758-7212}, EISSN = {1747-3616}, Keywords = {Generation cohort theory; Generation Z; Technology acceptance model; Health-care wearable technology; Adoption intention}, Keywords-Plus = {WORD-OF-MOUTH; BEHAVIORAL INTENTION; SOCIAL-MEDIA; ACCEPTANCE MODEL; USER ACCEPTANCE; DISCRIMINANT VALIDITY; PURCHASE INTENTION; PERCEIVED EASE; ENGAGEMENT; ANTECEDENTS}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business}, Author-Email = {manlaiicheung@gmail.com wilsonks.leung@cpce-polyu.edu.hk hschan@hsu.edu.hk}, Affiliations = {Hang Seng University of Hong Kong; University of Newcastle; Hong Kong Polytechnic University}, ResearcherID-Numbers = {KS, Wilson/ADE-2061-2022 }, ORCID-Numbers = {KS, Wilson/0000-0002-0345-5508 Cheung, Man Lai/0000-0003-0320-1134}, Cited-References = {Abbott, 2019, GEN IS AF HEALTHC IN. 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Zhang T., 2019, TOUR REV, V75, P56.}, Number-of-Cited-References = {102}, Times-Cited = {33}, Usage-Count-Last-180-days = {10}, Usage-Count-Since-2013 = {40}, Journal-ISO = {Young Consum.}, Doc-Delivery-Number = {TS1AC}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000574447900001}, DA = {2023-10-04}, } @article{ WOS:000822838600005, Author = {Zatonatska, Tetiana and Hubska, Maryna and Shpyrko, Viktor}, Title = {MARKETING STRATEGIES IN THE BANKING SERVICES SECTOR WITH THE HELP OF DATA SCIENCE}, Journal = {MARKETING AND MANAGEMENT OF INNOVATIONS}, Year = {2022}, Number = {2}, Pages = {121-127}, Abstract = {Competition between marketing strategies of enterprises shifts to the use of artificial intelligence and begins to be considered in the context of competition between Data Science projects. Therefore, the issue of developing methodology and building a model in a particular area is relevant, which will make the project quite effective and ensure the achievement of goals for the company. The banking services market has a certain specificity of consumer behaviour, so forming marketing strategies is a somewhat complex process. Thus, banks face the task of maintaining the loyalty of their existing customers and attracting new ones. This article aims to build a marketing strategy to attract new customers in the banking sector using Data Science tools. The result of the study is the construction of two econometric models of the different bank's credit products: cash loans and credit cards, which determine the influence of various factors on this process and helps to distribute the advertising budget between different types of advertising. Using the built model, it was determined that advertising campaigns directly affect the increase in the number of new customers in the bank and the overall growth of brand knowledge about the banking institution in society. In addition, the determined weights of each influencing factor helped form an advertising budget, which increased customer inflows by 12\%, with an average ROI of 3.18. Taking all into account, the model had shown its effectiveness in organising the bank's advertising campaign when decisions were made using Data Science technologies. The results obtained based on the models give a fairly clear understanding of the factors influencing the inflow of new customers in the bank, which will model the distribution of the budget for advertising campaigns in future periods and predict their effectiveness. Competition in the country's financial sector is forcing banking institutions to use data science in their marketing activities.}, Publisher = {SUMY STATE UNIV, DEPT MARKETING \& MANAGEMENT INNOVATIVE ACTIVITY}, Address = {RYMSKIY-KORSAKOV ST 2, SUMY, 40007, UKRAINE}, Type = {Article}, Language = {English}, Affiliation = {Zatonatska, T (Corresponding Author), Taras Shevchenko Natl Univ Kyiv, Kiev, Ukraine. Zatonatska, Tetiana; Hubska, Maryna; Shpyrko, Viktor, Taras Shevchenko Natl Univ Kyiv, Kiev, Ukraine.}, DOI = {10.21272/mmi.2022.2-11}, ISSN = {2218-4511}, Keywords = {bank; marketing activity; advertising; regression; involvement of new clients; Data Science}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Management}, Author-Email = {tzatonat@ukr.net maryna.hubska@gmail.com viktor.shpyrko@gmail.com}, Affiliations = {Ministry of Education \& Science of Ukraine; Taras Shevchenko National University Kiev}, ResearcherID-Numbers = {Shpyrko, Viktor/HZK-4921-2023}, Cited-References = {Alalwan AA, 2018, INT J INFORM MANAGE, V42, P65, DOI 10.1016/j.ijinfomgt.2018.06.001. Chernyak O., 2020, ICTERI WORKSHOPS, P282. Dolega L, 2021, J RETAIL CONSUM SERV, V60, DOI 10.1016/j.jretconser.2021.102501. Fedirko O., 2021, EUR RES STUD J, V24, P3, DOI {[}10.35808/ersj/2187, DOI 10.35808/ERSJ/2187]. Financial Conduct Authority, 2022, STRATEGIC REV RETAIL. Kelesidou F, 2021, MODERN BANK MARKETIN. Kuznyetsova A, 2018, MARK MANAG INNOV, P316, DOI 10.21272/mmi.2018.4-27. Lin YS, 2021, COMPUT INTEL NEUROSC, V2021, DOI 10.1155/2021/5995008. Mykhalchuk T, 2021, INT WORKSH INT DATA, P527, DOI 10.1109/IDAACS53288.2021.9660854. Rodriguez M, 2015, IDEAS IN MARKETING: FINDING THE NEW AND POLISHING THE OLD, P636. Shapiro B., 2020, GENERALISABLE ROBUST. Zhou Y., 2021, COMPUT INTEL NEUROSC, V2021.}, Number-of-Cited-References = {12}, Times-Cited = {1}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {8}, Journal-ISO = {Mark. Manag. Innov.}, Doc-Delivery-Number = {2U0ET}, Web-of-Science-Index = {Emerging Sources Citation Index (ESCI)}, Unique-ID = {WOS:000822838600005}, OA = {Green Published}, DA = {2023-10-04}, } @article{ WOS:000729878100007, Author = {Pyka, A. and Cardellini, G. and van Meijl, H. and Verkerk, P. J.}, Title = {Modelling the bioeconomy: Emerging approaches to address policy needs}, Journal = {JOURNAL OF CLEANER PRODUCTION}, Year = {2022}, Volume = {330}, Month = {JAN 1}, Abstract = {With its update of the Bioeconomy Strategy and the Green Deal, the European Commission committed itself to a transformation towards a sustainable and climate-neutral European Union. This process is characterised with an enormous complexity, which policymaking needs to acknowledge for designing transition pathways. Modelling can support policymaking in dealing with uncertainty and complexity. This article reviews emerging and new developments and approaches to model the development of the bioeconomy. We focused our review on how bioeconomy modelling addresses key enabling factors related to (i) climate change, (ii) biodiversity, (iii) circular use of biomass, (iv) consumer behaviour related to biomass and bioproducts use, and (v) innovation and technological change. We find that existing modelling frameworks offer large possibilities for extensions and considerations for analysing short-run impacts related to climate change and circularity, and to lesser degree for biodiversity, and we identify possibilities for developing further the existing bioeconomy models. However, addressing key processes related to societal and technological changes is more challenging with existing/conventional modelling approaches, as they specifically relate to how innovations transform economic structures and how consumers learn and change their preferences and what kind of dynamics are to be expected. We indicate how emerging modelling techniques such as Agent-Based Modelling could improve and complement existing bioeconomy modelling efforts by allowing for the consideration of structural change and, more generally, transformation of the economic metabolism. This modelling approach eclecticism asks for a better description of modelling targets, a sound reflection on the meaning of time horizons and a closer cooperation between the different research communities. Furthermore, it will benefit from the developments in big data and artificial intelligence from which we expect valuable guideposts for designing future modelling strategies.}, Publisher = {ELSEVIER SCI LTD}, Address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {Pyka, A (Corresponding Author), Univ Hohenheim, Inst Econ, Hohenheim, Germany. Pyka, A., Univ Hohenheim, Inst Econ, Hohenheim, Germany. Cardellini, G., Energyville VITO, Boeretang 200, B-2400 Mol, Belgium. van Meijl, H., Wageningen Univ \& Res, Wageningen Econ Res, Wageningen, Netherlands. van Meijl, H., Wageningen Univ, Agr Econ \& Rural Policy Grp, Wageningen, Netherlands. Verkerk, P. J., European Forest Inst, Yliopistokatu 6B, Joensuu 80100, Finland.}, DOI = {10.1016/j.jclepro.2021.129801}, EarlyAccessDate = {NOV 2021}, Article-Number = {129801}, ISSN = {0959-6526}, EISSN = {1879-1786}, Keywords = {Bioeconomy; Complexity; Modelling; Policy}, Keywords-Plus = {CLIMATE-CHANGE MITIGATION; HUMAN DECISION-MAKING; LAND-USE; EUROPEAN FORESTS; BIODIVERSITY; INNOVATION; SUSTAINABILITY; BEHAVIOR; HETEROGENEITY; UNCERTAINTIES}, Research-Areas = {Science \& Technology - Other Topics; Engineering; Environmental Sciences \& Ecology}, Web-of-Science-Categories = {Green \& Sustainable Science \& Technology; Engineering, Environmental; Environmental Sciences}, Author-Email = {a.pyka@uni-hohenheim.de}, Affiliations = {University Hohenheim; VITO; Wageningen University \& Research; Wageningen University \& Research}, ResearcherID-Numbers = {van Meijl, Hans/G-6223-2015 Pyka, Andreas/IST-6329-2023}, ORCID-Numbers = {van Meijl, Hans/0000-0002-2455-6869 }, Funding-Acknowledgement = {Directorate-General for Research and Innovation; Joint Research Centre of the European Commission}, Funding-Text = {This work has received funding from the Directorate-General for Research and Innovation and the Joint Research Centre of the European Commission. 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Clean Prod.}, Doc-Delivery-Number = {XO0IC}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000729878100007}, OA = {hybrid}, DA = {2023-10-04}, } @article{ WOS:000416122000008, Author = {Fiore, Mariantonietta and Gallo, Crescenzio and Tsoukatos, Evangelos and La Sala, Piermichele}, Title = {Predicting consumer healthy choices regarding type 1 wheat flour}, Journal = {BRITISH FOOD JOURNAL}, Year = {2017}, Volume = {119}, Number = {11, SI}, Pages = {2388-2405}, Abstract = {Purpose - Healthy and safety food issues are more and more becoming the purchasing process core of conscious consumer. ``Type 1{''} wheat flour means higher protein and ash content. The purpose of this paper is to investigate the attributes usually referred to the characteristics of wheat flour known to consumers and at implementing a predictive model of purchasing that allows to make correct decisions without the necessary experience of a real human expert. Design/methodology/approach - In order to investigate the research aims of the paper, an online survey was carried out and conducted by means of the Google Forms in the detection time January-April 2016. The online survey collected responses from 467 Italian respondents asked to give feedback about their buying habits of various types of flour. The responses were analyzed through a data mining approach. This paper implements predictive analytics to create a statistical model of future behavior by means of a machine learning algorithms. Findings - In line with recent healthy and dynamic trends in the food industry, conscious consumer seems to be willing to pay a price for ``type 1{''} wheat flour that is four times higher than the price related to the basic types of wheat flour. Social implications - Consumer seems not to know well the ``type 1{''} wheat flour and its healthy characteristics; then, it should be crucial to implement promotional strategies and marketing hand in hand. Promotion can be a key element in putting across the health benefits of special kinds of wheat flour. Originality/value - Highlighting health issues about the ``type 1{''} wheat flour gives insights and sheds some light on the crucial need of changing eating and purchasing behavior. Then, originality of this paper can be found in the used predictive algorithm of the artificial intelligence.}, Publisher = {EMERALD GROUP PUBLISHING LTD}, Address = {HOWARD HOUSE, WAGON LANE, BINGLEY BD16 1WA, W YORKSHIRE, ENGLAND}, Type = {Article}, Language = {English}, Affiliation = {La Sala, P (Corresponding Author), Univ Foggia, Dept Econ, Foggia, Italy. Fiore, Mariantonietta; La Sala, Piermichele, Univ Foggia, Dept Econ, Foggia, Italy. Gallo, Crescenzio, Univ Foggia, Dept Clin \& Expt Med, Foggia, Italy. Tsoukatos, Evangelos, TEI Crete, Gazi Malevyziou, Greece.}, DOI = {10.1108/BFJ-04-2017-0200}, ISSN = {0007-070X}, EISSN = {1758-4108}, Keywords = {Consumer behaviour; Healthy food; Basis types of wheat flour; Machine learning algorithms}, Keywords-Plus = {FOOD CHOICE; CONSCIOUSNESS; INFORMATION; ATTRIBUTES; BEHAVIOR; OBESITY; SAMPLE}, Research-Areas = {Agriculture; Food Science \& Technology}, Web-of-Science-Categories = {Agricultural Economics \& Policy; Food Science \& Technology}, Author-Email = {piermichele.lasala@unifg.it}, Affiliations = {University of Foggia; University of Foggia; Hellenic Mediterranean University}, ResearcherID-Numbers = {fiore, mariantonietta/L-3559-2019 La Sala, Piermichele/U-2214-2017 Gallo, Crescenzio/AAC-1482-2019 }, ORCID-Numbers = {La Sala, Piermichele/0000-0003-2081-8013 Gallo, Crescenzio/0000-0002-3929-462X fiore, mariantonietta/0000-0002-9244-6776 Tsoukatos, Evangelos/0000-0002-2670-8555}, Cited-References = {Akhtar S, 2011, FLOUR AND BREADS AND THEIR FORTIFICATION IN HEALTH AND DISEASE PREVENTION, P263, DOI 10.1016/B978-0-12-380886-8.10024-8. 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Roselli L, 2016, AGRIBUSINESS, V32, P329, DOI 10.1002/agr.21454. Simeone M, 2012, J FOOD AGRIC ENVIRON, V10, P162. Sun YHC, 2008, APPETITE, V51, P42, DOI 10.1016/j.appet.2007.11.004. Taccari M, 2016, J FOOD SCI, V81, pM1996, DOI 10.1111/1750-3841.13372. Williams B., 2010, AUSTRALASIAN J PARAM, V8, P1, DOI DOI 10.33151/AJP.8.3.93. Witten IH, 2011, MOR KAUF D, P1.}, Number-of-Cited-References = {50}, Times-Cited = {14}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {17}, Journal-ISO = {Br. Food J.}, Doc-Delivery-Number = {FN6KC}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000416122000008}, DA = {2023-10-04}, } @article{ WOS:000206799700002, Author = {Heppenstall, Alison and Evans, Andrew and Birkin, Mark}, Title = {Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets}, Journal = {JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION}, Year = {2006}, Volume = {9}, Number = {3}, Month = {JUN}, Abstract = {One emerging area of agent-based modelling is retail markets; however, there are problems with modelling such systems. The vast size of such markets makes individual-level modelling, for example of customers, difficult and this is particularly true where the markets are spatially complex. There is an emerging recognition that the power of agent-based systems is enhanced when integrated with other AI-based and conventional approaches. The resulting hybrid models are powerful tools that combine the flexibility of the agent-based methodology with the strengths of more traditional modelling. Such combinations allow us to consider agent-based modelling of such large-scale and complex retail markets. In particular, this paper examines the application of a hybrid agent-based model to a retail petrol market. An agent model was constructed and experiments were conducted to determine whether the trends and patterns of the retail petrol market could be replicated. Consumer behaviour was incorporated by the inclusion of a spatial interaction (SI) model and a network component. The model is shown to reproduce the spatial patterns seen in the real market, as well as well known behaviours of the market such as the ``rocket and feathers{''} effect. In addition the model was successful at predicting the long term profitability of individual retailers. The results show that agent-based modelling has the ability to improve on existing approaches to modelling retail markets.}, Publisher = {J A S S S}, Address = {UNIV SURREY, DEPT SOCIOLOGY, GUILDFORD GU2 7XH, SURREY, ENGLAND}, Type = {Article}, Language = {English}, Article-Number = {2}, ISSN = {1460-7425}, Keywords = {Agents; Spatial Interaction Model; Retail Markets; Networks}, Keywords-Plus = {PRICE; BEHAVIOR}, Research-Areas = {Social Sciences - Other Topics}, Web-of-Science-Categories = {Social Sciences, Interdisciplinary}, ResearcherID-Numbers = {Heppenstall, Alison/N-4354-2015}, ORCID-Numbers = {Heppenstall, Alison/0000-0002-0663-3437}, Cited-References = {Abdulai A, 2000, J DEV ECON, V63, P327, DOI 10.1016/S0304-3878(00)00115-2. {*}ARG NAT LAB, EMCAS EL MARK COMPL. BACON RW, 1991, ENERG ECON, V13, P211, DOI 10.1016/0140-9883(91)90022-R. Birkin M, 2002, RETAIL GEOGRAPHY INT. BIRKIN M, 1996, INTELLIGENT GIS LOCA. 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SHIN D, 1994, OPEC REV, V18, P137, DOI DOI 10.1111/J.1468-0076.1994.TB00497.X.}, Number-of-Cited-References = {29}, Times-Cited = {29}, Usage-Count-Last-180-days = {1}, Usage-Count-Since-2013 = {8}, Journal-ISO = {JASSS}, Doc-Delivery-Number = {V00PK}, Web-of-Science-Index = {Social Science Citation Index (SSCI)}, Unique-ID = {WOS:000206799700002}, DA = {2023-10-04}, } @article{ WOS:000881891300004, Author = {Ghodhbani, Hajer and Neji, Mohamed and Qahtani, Abdulrahman M. and Almutiry, Omar and Dhahri, Habib and Alimi, Adel M.}, Title = {Dress-up: deep neural framework for image-based human appearance transfer}, Journal = {MULTIMEDIA TOOLS AND APPLICATIONS}, Year = {2023}, Volume = {82}, Number = {15}, Pages = {23151-23178}, Month = {JUN}, Abstract = {The fashion industry is at the brink of radical transformation. The emergence of Artificial Intelligence (AI) in fashion applications creates many opportunities for this industry and make fashion a better space for everyone. Interesting to this matter, we proposed a virtual try-on interface to stimulate consumers purchase intentions and facilitate their online buying decision process. Thus, we present, in this paper, our flexible person generation system for virtual try-on that aiming to treat the task of human appearance transfer across images while preserving texture details and structural coherence of the generated outfit. This challenging task has drawn increasing attention and made huge development of intelligent fashion applications. However, it requires different challenges, especially in the case of a wide divergences between the source and target images. To solve this problem, we proposed a flexible person generation framework called Dress-up to treat the 2D virtual try-on task. Dress-up is an end-to-end generation pipeline with three modules based on the task of image-to-image translation aiming to sequentially interchange garments between images, and produce dressing effects not achievable by existing works. The core idea of our solution is to explicitly encode the body pose and the target clothes by a pre-processing module based on the semantic segmentation process. Then, a conditional adversarial network is implemented to generate target segmentation feeding respectively, to the alignment and translation networks to generate the final output results. The novelty of this work lies in realizing the appearance transfer across images with high quality by reconstructing garments on a person in different orders and looks from simlpy semantic maps and 2D images without using 3D modeling. Our system can produce dressing effects and provide significant results over the state-of-the-art methods on the widely used DeepFashion dataset. Extensive evaluations show that Dress-up outperforms other recent methods in terms of output quality, and handles a wide range of editing functions for which there is no direct supervision. Different types of results were computed to verify the performance of our proposed framework and show that the robustness and effectiveness are high by utilizing our method.}, Publisher = {SPRINGER}, Address = {VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS}, Type = {Article}, Language = {English}, Affiliation = {Ghodhbani, H (Corresponding Author), Univ Sfax, Natl Engn Sch Sfax ENIS, REs Grp Intelligent Machines REGIM Lab, BP 1173, Sfax 3038, Tunisia. Ghodhbani, Hajer; Neji, Mohamed; Alimi, Adel M., Univ Sfax, Natl Engn Sch Sfax ENIS, REs Grp Intelligent Machines REGIM Lab, BP 1173, Sfax 3038, Tunisia. Neji, Mohamed, Natl Sch Elect \& Telecommun Sfax Technopk, BP 1163, Sfax 3018, Tunisia. Qahtani, Abdulrahman M., Taif Univ, Coll Comp \& Informat Technol, Dept Comp Sci, POB 11099, Taif 21944, Saudi Arabia. Almutiry, Omar; Dhahri, Habib, King Saud Univ, Coll Appl Comp Sci, Riyadh, Saudi Arabia. Alimi, Adel M., Univ Johannesburg, Fac Engn \& Built Environm, Dept Elect \& Elect Engn Sci, Johannesburg, South Africa.}, DOI = {10.1007/s11042-022-14127-w}, EarlyAccessDate = {NOV 2022}, ISSN = {1380-7501}, EISSN = {1573-7721}, Keywords = {Artificial intelligence; Outfit generation; Garment interchange; Virtual try-on; Semantic segmentation}, Keywords-Plus = {RECOMMENDATION SYSTEM}, Research-Areas = {Computer Science; Engineering}, Web-of-Science-Categories = {Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory \& Methods; Engineering, Electrical \& Electronic}, Author-Email = {hajer.ghodhbani@regim.usf.tn mohamed.neji@ieee.org amqahtani@tu.edu.sa oalmutiry@ksu.edu.sa hdhahri@ksu.edu.sa adel.alimi@regim.usf.tn}, Affiliations = {Universite de Sfax; Ecole Nationale dIngenieurs de Sfax (ENIS); Taif University; King Saud University; University of Johannesburg}, ResearcherID-Numbers = {Dhahri, Habib/L-7833-2018 Alimi, Adel M./A-5697-2012}, ORCID-Numbers = {Alimi, Adel M./0000-0002-0642-3384}, Funding-Acknowledgement = {Taif University, Taif, Saudi Arabia {[}TURSP-2020/327]; Ministry of Higher Education and Scientific Research of Tunisia {[}LR11ES48]}, Funding-Text = {We deeply acknowledge Taif University for Supporting this study through Taif University Researchers Supporting Project number (TURSP-2020/327), Taif University, Taif, Saudi Arabia. The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES48.}, Cited-References = {Arashpour M, 2021, J BUILD ENG, V33, DOI 10.1016/j.jobe.2020.101672. Bhatti UA, 2022, IEEE T GEOSCI REMOTE, V60, DOI 10.1109/TGRS.2021.3090410. Bhatti UA, 2022, CHEMOSPHERE, V288, DOI 10.1016/j.chemosphere.2021.132569. Bhatti UA, 2021, MULTIMED TOOLS APPL, V80, P13367, DOI 10.1007/s11042-020-10257-1. Bhatti UA, 2019, ENTERP INF SYST-UK, V13, P329, DOI 10.1080/17517575.2018.1557256. Bhatti UA, 2018, HUM VACC IMMUNOTHER, V14, P165, DOI 10.1080/21645515.2017.1379639. Choi S, 2021, PROC CVPR IEEE, P14126, DOI 10.1109/CVPR46437.2021.01391. Chowdhary CL, 2020, SENSORS-BASEL, V20, DOI 10.3390/s20185162. Cui A., 2021, P IEEE CVF INT C COM, P14618. DeBogota CDC, 2021, STATE FASHION 2021. Dong H, 2019, IEEE I CONF COMP VIS, P9025, DOI 10.1109/ICCV.2019.00912. 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Tools Appl.}, Doc-Delivery-Number = {I2KP1}, Web-of-Science-Index = {Science Citation Index Expanded (SCI-EXPANDED)}, Unique-ID = {WOS:000881891300004}, OA = {Green Submitted, Bronze, Green Published}, DA = {2023-10-04}, } @inproceedings{ WOS:000427297600051, Author = {Grandhi, Balakrishna and Patwa, Nitin and Saleem, Kashaf}, Editor = {Vrontis, D and Weber, Y and Tsoukatos, E}, Title = {DATA DRIVEN MARKETING FOR GROWTH AND PROFITABILITY}, Booktitle = {GLOBAL AND NATIONAL BUSINESS THEORIES AND PRACTICE: BRIDGING THE PAST WITH THE FUTURE}, Series = {EuroMed Academy of Business Conference Book of Proceedings}, Year = {2017}, Pages = {675-694}, Note = {10th Annual Conference of the EuroMed-Academy-of-Business, Rome, ITALY, SEP 13-15, 2017}, Organization = {EuroMed Acad Business; EuroMed Res Ctr; EuroMed Journal Business; EuroMed Res Business Inst}, Abstract = {Purpose: In the current business environment, more uncertain than ever before, understanding consumer behaviour is an integral part of an organization's strategic planning and execution process. It is the key driver for becoming a market leader. Therefore, it is important that all processes in business are customer centric. Capturing, categorizing, warehousing, mining, analysing and making sense of data is a real-time challenge for all marketers. Organizations embracing digitization are seeing Big Data getting bigger. Investments are being made in IT infrastructure, Internet of Things, machine learning and artificial intelligence in business decision-making. Marketers need to harness big data by engaging in Data Driven Marketing (DDM) to help organizations choose the `right' customers, to `keep' and `grow' them and to sustain `growth' and `profitability'. This research examines DDM adoption practices and how companies can aim to enhance shareholder value by bringing about `customer centricity' through better use of data. Design/Methodology/Approach: An online survey conducted in 2016 received 180 responses from junior, middle and senior executives. Of the total responses 26\% were from senior management, 39\% from middle management and the remaining 35\% from junior management. Industries represented in the survey included Retail, BFSI, Healthcare and Government, Automobile, Telecommunication, Transport \& Logistics and IT. Other industries represented were Aviation, Marketing Research \& Consulting, Hospitality, Advertising \& Media and Human resource. Among the respondents, 34\% represented companies with less than \$ 30 million in annual revenues, 15\% between \$ 30-50 million and \$ 50-100 million, 32\% between \$ 100-500 million, and the remaining 19\% with \$ 500 million and above in annual revenues. In terms of company size, 60\% were companies with 1-500 employees, 13\% with 500-1000 and 26\% with 1000 and above employees. The survey was done in Dubai which represents a blend of several global economies and hence, can be generalised. Findings: Success of DDM depends upon how well an organization embraces the practice. The first and foremost indicator of an organization's commitment is the extent of resources invested for data driven marketing. Respondents were divided into four categories; Laggards, Dabblers, Contenders, and Leaders based on their `current level of investments' and ` willingness to enhance investments' soon. `Leaders' are from Retail, Banking \& financial services, transportation \& logistics and Telecommunication sectors. The major sources of information are point-of-sales data, social media and other published sources. They use data to understand what and why customers are buying, what their consumption patterns are and what makes them satisfied or dissatisfied. `Dabblers' are players who have realized the importance of data and have just begun to incorporate it in their marketing in a limited way. `Contenders' are far more regular in using data for measuring and taking marketing decisions. `Laggards' are at the other extreme when it comes to using data for customer analysis. Practical implications: The results of the study offer interesting implications for managing the growing sea of data. An iterative and incremental approach is the need of the hour, even if it has to start with baby steps, to invest in and reap the fruits of data driven marketing. The intention to use any system is always dependent on two primary belief factors: perceived usefulness and perceived ease of use, however attitudes and social factors are equally important. Investments in the right people, infrastructure and processes early on can result in better marketing due diligence and contribute to higher return on marketing investment, necessary to sustain an organization's growth and profitability. Originality/Value: All organizations, irrespective of size and sector, need to engage in data driven marketing for customer centricity. In this era of digitalization, a marketer needs to wisely handle the volume, velocity, variety and veracity of data. Roger's diffusion of innovation theory identifies factors leading to the adoption of innovation by both individuals and organizations. The theory argues that willingness and ability to adopt depends on awareness, interest, evaluation, trial and adoption ( Rogers, 2003). There is a dearth of knowledge with regards to who is and is not adopting DDM, and how best big data can be harnessed for enhancing effectiveness and efficiency of marketing budget. It is, therefore, imperative to build a knowledge base on DDM practices, challenges and opportunities. Better use of data can help companies enhance shareholder value by bringing about `customer centricity'.}, Publisher = {EUROMED PRESS}, Address = {RUE ANTOINE BOURDELLE, DOMAINE DE LUMINY BP 921, MARSEILLE CEDEX 9, 13 288, FRANCE}, Type = {Proceedings Paper}, Language = {English}, Affiliation = {Grandhi, B (Corresponding Author), SP Jain Sch Global Management, Dubai, U Arab Emirates. Grandhi, Balakrishna; Patwa, Nitin; Saleem, Kashaf, SP Jain Sch Global Management, Dubai, U Arab Emirates.}, ISSN = {2547-8516}, ISBN = {978-9963-711-56-7}, Keywords = {Data Driven Marketing; Customer Centric; Value Proposition; Digital Data; Marketing Metrics; Marketing Analytics; Marketing Audit; Marketing Dashboard; Digital Marketing and Marketing Investment; ROMI (Return On Marketing Investment) and Diffusion of Innovation}, Keywords-Plus = {OPPORTUNITIES; MODEL}, Research-Areas = {Business \& Economics}, Web-of-Science-Categories = {Business; Management}, ResearcherID-Numbers = {Patwa, Nitin/JAZ-0219-2023}, Cited-References = {Agrawal D, 2014, J INDIAN BUS RES, V6, P332, DOI 10.1108/JIBR-09-2014-0062. 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