Kulkarni, P., Kirkham, R., & McNaney, R. (2022). Opportunities for Smartphone Sensing in E-Health
Research: A Narrative Review. Sensors, 22(10), 3893.

Kulkarni et al. (2022) provide an overview of smartphone-sensing literature from the past five
years to highlight the opportunities and challenges of this approach in healthcare. It predominance
of mental health studies, discusses the possibilities of using standardized sensing approaches and
machine-learning advancements, and presents the trends of smartphone sensing in healthcare over the
years. It also provides an overview of the type of health conditions studied, the types of data
collected, the tools used, and the challenges encountered in using smartphones for healthcare
studies. Smartphones have the capacity to capture a large amount of user information and are
becoming increasingly context aware. They also have the potential to track additional usage
statistics, such as screen time, application usage, and battery usage. Smartphone sensing has been
used to study physical and mental health conditions, categorized into three categories.


Kalia, P., Dwivedi, Y. K., & Acevedo-Duque, Á. (2022). Cellulographics©: A novel smartphone user
classification metrics. Journal of Innovation & Knowledge, 7(2), 100179.


Kalia et al. (2022) Investigate the Cellulographics is a concept introduced for characterization of
smartphone users, which includes behavioral classification based on user characteristics like
smartphone experience (SE), smartphone use skill (SUS), smartphone internet experience (SIE),
smartphone use periods (SUP), smart-phone screen time (SST), smartphone use frequency (SUF),
smartphone use activities (SUA), and smartphone use location (SUL). Market segmentation is the key
component of marketing, using geographic, demo-graphic, psychographic, and behavioral variables.
Cellulographics and Web-graphics are the new metrics for designing a marketing strategy, as
consumers are migrating to smartphones for their daily online activities. Smartphones are
versatile, portable, and accessible, allowing users to perform any task with ease. Mobile commerce
contributes significantly to worldwide e-commerce retail sales, but there are no classification
metrics based on smartphone usage. Cellulographics© is a novel smartphone user classification
metric. It might be expensive and time-consuming project but in a long run it will be so
beneficial.

Sahu, A., & Deshmukh, G. K. (2020). Mobile Shopping Adoption: Research Insights. Journal of
Ravishankar University, 26(1), 17-24.

Sahu, A., & Deshmukh, G. K. (2020) discuss the increasing trend of mobile shopping among consumers
and the factors influencing its adoption. They find several factors that influence mobile shopping
adoption, including perceived usefulness, ease of use, trust, perceived risk, and social influence.
However, consumers often face challenges while using mobile shopping apps, such as technical
issues, security concerns, and privacy issues. To overcome these challenges, the authors suggest
that mobile shopping app developers should focus on enhancing the usability and security features
of their apps. Additionally, retailers should focus on building trust with their customers by
providing personalized and engaging experiences. Overall, the article provides useful insights for
mobile shopping app developers and retailers seeking to understand consumer behavior and
preferences related to mobile shopping.