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Technological Forecasting & Social Change
journal homepage: www.elsevier.com/locate/techfore
Consumers’ value co-creation in sharing economy: The role of social
support, consumers’ ethical perceptions and relationship quality
Waqar Nadeema,⁎
, Mari Juntunena
, Farid Shirazib
, Nick Hajlic
a
Department of Marketing, Management and International Business, Oulu Business School, University of Oulu, Finland
b
Institute for Innovation and Technology Management, Ryerson University, Toronto, Canada
c
School of Management, Swansea University, United Kingdom
A R T I C L E I N F O
Keywords:
Sharing economy
Value co-creation
Social support
Relationship quality
Ethics
A B S T R A C T
The ancient phenomenon of ‘sharing’ has become mainstream, and transformed the traditional consumer behavior
due to proliferation of online sharing economy platforms. Millions of people participate in popular
sharing economy platforms (SEPs) such as Airbnb and Uber. Although sharing economy research has gained
interest, yet a holistic model that explains the formation of consumer value co-creation intentions on such
platforms remains absent. The purpose of this study is to develop a model of the antecedents of consumers value
co-creation intentions at SEPs and evaluate it empirically. Building on social support theory, relationship quality
theory, value co-creation and marketing ethics literature, we propose a theoretical model that explains the
formation of consumers’ value co-creation intentions. Empirical data was collected from n = 342 Generation Y
consumers and analyzed using structural equation modeling (SEM). The results reveal that social support influences
ethical perceptions, which further influences value co-creation. Ethical perceptions also influence
consumers' trust, satisfaction and commitment with the SEP. However, trust and commitment do not influence
value co-creation intentions. Our study contributes to the literature on sharing economy by providing a holistic
model of the antecedents of consumers’ value co-creation intentions. We also offer important insights for SEP
managers.
1. Introduction
The act of ‘sharing’ is not new and communal ways of life and
bartering existed long ago (Botsman and Rogers, 2010; Cheng et al.,
2018; Ertz et al., 2016; Sundararajan, 2016). However, only recently
has the term ‘sharing economy’ gained popularity in the form of a new
culture of sharing based on fee payment through online platforms,
which has now become mainstream (Bucher et al., 2016). Belk (2014)
p.1597 defines sharing economy as the “acquisition or distribution of a
source coordinated by people for a compensation or a certain fee”. The
sharing economy provides affordable and more convenient alternatives
to the established industries (Eckhardt and Bardhi, 2016). For instance,
Airbnb (accommodation), Uber (transportation and ridesharing), Lendico
(peer-to-peer lending), Taskrabbit (on demand labor, freelancing),
GwynnieBee (used clothes) and machinerylink (farming equipment) are
some of the popular sharing economy platforms (SEPs) used by millions
of people (Zervas et al., 2017). The revenues of SEPs are expected to
reach around 335 billion dollars by the year 2025 (PWC, 2015).
The essential actors in the sharing economy are the consumers who
continually co-create value with companies and other consumers. Value
co-creation refers to a process in which different parties produce valued
outcomes together (Prahalad and Ramaswamy, 2004). Unlike in traditional
online contexts, both the companies and consumers can operate
as buyers and sellers via SEPs. Although the extensive amount of the
extant literature well expands our understanding of value co-creation
both in offline and online settings (see e.g. Brodie et al., 2013;
Gronroos, 2008; Payne et al., 2008; Zwass et al., 2010) and recent research
examines brand value co-creation in social commerce settings
(Hajli et al., 2017; Tajvidi et al., 2017), there still is huge a paucity of
knowledge with regards to our understanding of value co-creation in
the context of a sharing economy. Specifically, less attention has been
paid to the notion of why consumers engage and participate in value cocreation
(Martinez-Canas et al., 2016; Nambisan and Baron, 2009) in
general and via SEPs in particular. Several authors have drawn attention
to the creation of new lines of inquiry in the domain of value cocreation
in a sharing economy (Camilleri and Neulofer, 2017;
Zhang et al., 2018), yet various researchers call for a model of the
process of value co-creation that can be used in multiple settings
https://doi.org/10.1016/j.techfore.2019.119786
Received 28 March 2019; Received in revised form 27 August 2019; Accepted 17 October 2019
⁎
Corresponding author.
E-mail address: waqar.nadeem@oulu.fi (W. Nadeem).
Technological Forecasting & Social Change 151 (2020) 119786
Available online 19 November 2019
0040-1625/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/BY/4.0/).
T
(Hajli et al., 2017; Merz et al., 2009, 2018). Even though some researchers
importantly explore consumers’ motivations to participate in
value co-creation, they recognize the importance to identify the precursors
that lead to consumers’ value co-creation intentions
(Payne et al., 2009; Roberts et al., 2014; Tajvidi et al., 2017). Consequently,
it is vitally important that we examine what the antecedents
are to consumers’ value co-creation intentions at SEPs.
Current research recognizes two central antecedents to consumers’
value co-creation intentions in online environments: social support
from other participants (Ramaswamy and Oczan, 2016) and the relationship
quality with online communities (Hajli et al., 2017;
Kamboj et al., 2018; Tajvidi et al., 2018). However, research related to
SEPs has revealed that specifically young adults, i.e. the so-called
Generation Y (GenY) age cohort, have privacy concerns with regards to
SEPs (Ranzini et al., 2017). It is widely recognized that concern about
privacy is an important aspect of consumers’ ethical perceptions in
online environments (Agag et al., 2016; Cheng et al., 2014;
Roman, 2007; Roman and Cuestas, 2008). Despite these important
contributions, no research has thus far produced a holistic model of
consumers’ value co-creation intentions that also takes consumers’
ethical perceptions into account in general or specifically in the context
of SEPs.
The purpose of this study is to develop and test a holistic model that
explains the formation of consumers’ value co-creation intentions at
SEPs. We specifically focus on the following question: What is the role
of consumers’ ethical perceptions in relation to social support and the
relationship quality as an antecedent to consumers’ value co-creation
intentions at SEPs? We theoretically build on well-documented literature
including social support theory, relationship quality theory, value
co-creation literature, and the literature on marketing and business
ethics and propose a theoretical model that explains the formation of
consumers’ value co-creation intentions. We empirically test the model
using a structural equation modeling (SEM), with the data from 342
GenY consumers on a US based online platform. We focus on Gen Y
because many researchers (e.g. Mittendorf, 2016; Ranzini et al., 2017)
urge further exploration of this cohort in sharing economy settings.
Additionally, the sharing economy is often strongly linked to GenY
because of its nature, which originates on the principles of co-consumption
and technological dependence (Belk, 2014; Godelnik, 2017;
Ranzini et al., 2017): GenY is more tech savvy than older generations
(Bolton et al., 2013), as they have lived through the emergence of SEPs,
and their consumption habits significantly differ from those of older
generations (see e.g. Klein and Smart, 2017; Nadeem et al., 2015;
Ranzini et al., 2017). For instance, GenY is more likely to choose shared
or public transportation instead of owning their own car (Klein and
Smart, 2017) and is less likely to own a house, which is in contrast with
previous generations (Xu et al., 2015). It is therefore vital to study this
cohort more deeply in order to draw contemporary findings. In answer
to our research question; our findings reveal that social support gives a
basis for ethical perceptions, which then influences relationship quality
constructs and value co-creation intentions. Our study contributes to
the literature on SEPs by providing a holistic model of the antecedents
of consumers’ value co-creation intentions. We also offer insights for
SEP managers.
The next section introduces the theoretical background of the study,
followed by a research model. The empirical section describes our data,
analyses, and results. The study concludes by discussing the results and
offering theoretical and managerial contributions, along with limitations
and further research ideas on the topic.
2. Theoretical background
2.1. Understanding the concept of sharing economy
Although there is no agreement upon the definition of sharing
economy among academics and practitioners (see e.g. Netter et al.,
2019), researchers recognize some similar characteristics regarding this
phenomenon. According to Belk (2014), a sharing economy is the
process of distributing what is ours to others for their use and the act of
receiving and taking something from others for our use.
Sundrarajan (2016) refers to sharing economy as crowd-based capitalism,
as there is on-demand access through the transfer of ownership
for a certain period of time. Further, Botsman and Rogers (2010) have
also referred to the sharing economy as the phenomenon of collaborative
consumption. Belk (2014) refers to collaborative consumption
as the acquisition or distribution of a resource coordinated by people
for a fee or compensation that can be conducted in the form of trading,
swapping, and bartering. Eckhardt and Bardhi (2016) argue that the
sharing economy is more like an access economy because the emphasis
on sharing is secondary and guided by an intermediary firm. Moreover,
Kumar et al. (2018) refer to sharing economy as monetization in the
form of the short-term rental of underutilized assets by service providers,
which can be individuals or firms. On the basis of these definitions,
the current study takes a broad standpoint for the definition of
sharing economy on the two principles that were common to all the
aforementioned definitions, namely: capitalization of underutilized resources
based on a compensation or a fee and emphasizing that SEP
service providers can either be individuals or firms.
When compared to other online platforms, such as e-ecommerce
platforms, through which firms provide offers to consumers (businessto-consumers
i.e. B2C), SEPs place consumers at the core and the
starting point of all interaction (consumer-to-consumer i.e. C2C). SEPs
operate as intermediaries and thereby let consumers contribute to solutions
that match each consumer's specific context and their purposes.
SEPs enable consumers to come up with the solution rather steering it
on their own, which, in turn, enhance consumers’ participation in the
form of finding support from other members and their peers (WeEconomy,
2015). In other words, SEPs empower consumers to participate
in a way that allows them to offer and specify solutions by
themselves, which is an important aspect of value co-creation. The next
chapter introduces the extant research on value co-creation by specifically
focusing on SEPs.
2.2. Value co-creation
For the sake of remaining competitive in the markets, value-cocreation
has recently emerged as a major strength for businesses
(Merz et al., 2018; Zwass, 2010). Prahalad and Ramaswamy (2004)
refer to value-co-creation as a holistic management strategy or initiative
that brings distinct agents/different parties together to produce
valued outcomes. The value co-creation approach is harnessed by
companies not only to gain a competitive advantage but also corporate
reputation and brand value (Cova and Dalli, 2009).
According to service dominant logic (SD-logic) (Vargo and
Lusch, 2004, 2008; Williams and Aitken, 2011), consumers are at the
forefront of co-creating value with companies. Furthermore, SD- logic
asserts that services and not goods are the unit of exchange and that the
mutual actions of consumers and service providers result in value cocreation.
This understanding has led companies to give their consumers
a more active role and, vice versa, companies increasingly engage
consumers’ processes in the development of their services and products
(Flint, 2002; Prahalad and Ramaswamy, 2004). Vargo et al. (2008)
assert that value co-creation is basically a process of relying on the joint
efforts of companies, consumers, and other agents in such a way that
mutual dependence and reciprocity are crucial to defining the interdependent
roles, which are consequently related to the production and
service of value creation. In order to ensure efficient service delivery,
tailored goods, and more personalized services, consumers must learn
to use, maintain, repair, and adapt offerings to their own usage situations,
unique needs, and behaviors (Vargo and Lusch, 2004, 2008).
Another theoretical lens, post-modernism for value co-creation,
leads to a view of companies offering consumers more tailored goods
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
2
and services in order to encourage them to participate more
(Bendapudi and Leone, 2003; Firat and Venkatesh, 1993). The view is
aligned with an understanding of the nature of sharing economy being
such that value is primarily created in networks. Accordingly, SEPs are
based on the principle of consumer involvement and consumer participation.
SEPs exist because of the social support they get through
consumers and the relationship(s) they develop with consumers. In
other words, SEPs will cease to exist if nobody participates in them. As
SEP consumers are proactive, they are able to participate in service
conceptualization, testing, designing, product/service marketing, and
support specialization (Nambisan and Nambisan, 2008; OHern and
Rindfleisch, 2010). Indeed, as so many consumers are seeking and
providing information through SEPs, we may infer that brand value is
facilitated by the tendencies and behaviors of online consumers
(Naylor et al., 2012) and that value can be co-created by harnessing the
support available through such platforms (Ramaswamy and
Oczan, 2016). Subsequently, the support obtained via SEPs, the development
of good relationships with consumers, and the creation of
successful SEPs can be major challenges for SEP service providers.
Despite the substantial importance of SEPs, little consideration has
been given to explaining consumers’ intentions for co-creating value via
SEPs. To create such a model, the current study continues by presenting
the three approaches that offer the main concepts for our research
model: social support theory, consumer's ethical perceptions, and relationship
quality theory.
2.3. Social support theory
Social support theory can trace its roots to 1980s psychology literature
(see e.g. Barrera, 1986). According to Gottileb and
Bergen (2010), social support refers to the perception individuals have
of the available social resources, or those resources that are actually
provided to them by other members in their network in the context of
both formal support groups and informal helping connections and relationships.
Several authors assert that social support examines how
individuals experience the feeling of care in terms of responsiveness and
the facilitation provided by other individuals in their networks or social
groups (Cobb, 1976; House, 1983; Tajvidi et al., 2017). Along with
psychology, social support has been given adequate attention by academics
in sociology, healthcare, and even in literature on marketing
(see e.g. Hajli et al., 2017; Liang et al., 2011; Tajvidi et al., 2018).
However, with recent advances in technology and the emergence of
SEPs, it has become more relevant than ever to understand this phenomenon
more deeply.
In the context of a sharing economy, the role of social support is
paramount, as consumers heavily rely on support from other members
while making decisions. SEPs are based on the principle of sharing
ideas, thoughts, connections, and experiences, and the starting point for
all of this is carried out in an online environment. People may have
different motivations regarding their participation in online platforms.
For example, some people share their experiences and participate more
freely when they perceive there will be an improvement in their reputation
by doing so (Wasko and Faraj, 2005). Moreover, participation
in online environments and sharing experiences exert a great deal of
influence on the shaping of other participants’ thoughts and decisionmaking
(Gruzd et al., 2011). For instance, a traveler is most likely to
look at others member's comments when selecting a host through a
sharing economy platform such as Airbnb or Homeaway.
Social support is typically considered as a multi-dimensional construct
(Cohen and Hoberman, 1983; Langford et al., 1997; Xie, 2008).
The aforementioned studies have revealed various dimensions of social
support, including emotional support, informational support, belonging
support, tangible support, instrumental support, and appraisal support.
Emotional and informational support tend to be most relevant in online
settings (Liang et al., 2011; Xie, 2008). Emotional support refers to the
provision of messages or communication that involves emotional
concerns such as empathy, caring, and understanding. Informational
support can be defined as the communication or provision of messages
that involve informational concerns, such as advice, knowledge that can
be helpful in solving problems, and recommendations (Liang et al.,
2011). Given the nature of SEPs and the interactions that take place
through them, we theorize that emotional support and informational
support are essential dimensions of social support in relation to SEPs.
When the emotional support exists in an SEP, it is likely that consumers
feel that they are being cared for and understood. Furthermore, when
informational support is enacted through the SEP, consumers may feel
that they are able to acquire the relevant information. Each of these
arrangements may encourage consumers to share information with
others in such a platform and rely on the recommendations of others as
support to their decisions, i.e. they co-create value through the SEP.
However, because the extant research has recognized that consumers
have privacy concerns with regards to the information they share
through SEPs (Ranzini et al., 2017), we move on to introduce consumers’
ethical perceptions of SEPs next.
2.4. Consumers’ ethical perceptions of SEPs
As the above discussion shows, consumers may, on the one hand,
perceive SEPs as convenient, enjoyable, and economical (Zach et al.,
2018), while on the other hand, however, potentially perceiving SEPs
as risky with regards to ethical lapses. Consumers are required to give
their personal information, which at times makes them vulnerable in
the sense of their information potentially being used for non-intended
commercial activities (Dillahunt and Malone, 2015). Even the most
historically respected and best-known companies have recently faced
ethical failures. For instance, Facebook failed to ensure consumer
privacy and data protection; Wells Fargo was accused of consumer
deception; and Uber was found to have been cheating drivers by
rounding off fees in its own favor (Newcomer, 2017). As research on
SEPs has just begun to emerge, it is of paramount importance that we
understand the ethical aspects of SEPs (Perren and Kozinets, 2018;
Sutherland and Jarrahi, 2018).
Consumers’ ethical perceptions in online settings refers to “perceptions
of consumers about a company's responsibility and integrity (behind
the online platform) in its attempt to deal with consumers in a
secure, honest, fair and confidential manner that ultimately gives protection
to the consumer's interests.” (Roman 2007, p.34). Privacy and
security have traditionally been the two main ethical concerns in online
settings (Roman and Cuestas, 2008). In the context of a sharing
economy, even these issues are underexplored (Sutherland and
Jarrahi, 2018) and other potentially important ethical marketing issues
need to be considered. Roman (2007) added non-deception and fulfillment/reliability
to the two concepts above in the context of online
retailing. More recently, research on online retailing has not only
confirmed these four dimensions but also added novel dimensions such
as sales behavior (Cheng et al., 2014), service recovery (Agag et al.
2016; Cheng et al., 2014), and shared value (Agag et al. 2016).
Building on Roman's (2007) widely cited research, we include four
dimensions in our approach to consumers’ ethical perceptions of SEPs;
privacy, security, fulfillment/reliability, and non-deception. On online
platforms, uncertainty embedded in the notion of loss and risk that
consumers personal information might be exposed to unintended individuals
or parties is referred to as privacy concern (Bart et al., 2005).
Privacy concerns are related to consumers concerns about how they
control and use their personal information. Security pertains to consumers
perceptions of uncertainty in the form of incurring monetary
losses while interacting on an online platform (Roman, 2007). Security
concerns deal with data breaches in the form of losses with regards to
financial, personal, and transactional information (see e.g.
Cadwalladr and Graham-Harrison, 2018; Smith 2016). Non-deception
relates to the concept of fraud (Roman, 2010) and has not received
much attention, specifically in the domain of sharing economy
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
3
literature. Fraud committed through SEPs can comprise the purposeful
misrepresentation of services/goods along with unreliable delivery of
services/goods. Non-deception indicates that SEP service providers will
not engage in practices that are deceptive, manipulative or fraudulent,
and leading to consumers making a transaction or a purchase
(Limbu et al., 2011). Fulfillment/reliability deals with the degree to
which consumers believes they will be able to place an order as accurately
as possible through the SEP (Parasurman et al., 2005;
Wolfinbarger and Gilly, 2003). Moreover, fulfillment/reliability necessitates
an accurate display and description of the services/goods
offered, for instance, and tracking and prompting a confirmation order.
In addition, the goods/services have to be the same as they have been
represented or displayed; e.g. an Airbnb room cannot look better in the
picture than in reality, in order to avoid misrepresentations in the
pictures.
The aforementioned aspects are essential influencers on consumers’
relationship quality with an SEP. Thus, we introduce the concept of
relationship quality next.
2.5. Relationship quality theory
Relationship quality comes under the umbrella term of relationship
marketing. The main focus of relationship marketing is the formation of
partnerships between the service providers and consumers
(Tajvidi et al., 2017) and, thus, value creation for both sellers and
buyers (Gummesson, 1987; Boulding et al., 2005). Consumers mainly
enter into relationships with firms as they expect to receive positive
value from their participation (Peterson, 1995). Relationship quality
plays a crucial role in determining consumers’ involvement and interests
with products/services. Relationship quality is described as the
intensity and tightness of a relationship (Henning-Thrau et al., 2002;
Liang et al., 2011). In addition, Smith (1998) has described relationship
quality as the overall strength of the relationship and the degree to
which this relationship meets the expectations and needs of the parties
involved. The vast majority of research related to relationship quality
has been conducted in offline settings (Athanasopoulou, 2009;
Rafiq et al., 2013; Vieria et al., 2008). Besides that, Walsh et al. (2010)
reveal that relationship quality is equally important in the online and
offline context for the sake of retaining consumers and the differences
in the impact of relationship quality dimensions are very context specific.
For instance, in online settings, consumers face several issues related
to their vulnerability when making online transactions due to the
high degree of uncertainty. Most consumers are now present online
and, therefore, it is vital that we understand and study the concepts of
relationship quality online, specifically in the context of sharing
economy.
It has become paramount for SEPs to develop good relationships
with their consumers. These days, consumers have so much to choose
from and they can easily switch from one service provider to another if,
for example, there are any issues with a specific SEP. The existing research
on social commerce settings has shown that social support positively
influences relationship quality, which in turn positively influences
continuance intentions (Liang et al., 2011). More recently, Tajvidi
et al. (2018) found in social commerce settings that social support has a
positive association with consumers’ perceived relationship quality and
value co-creation is a direct outcome of relationship quality. Previous
research has also shown that relationships are stronger when they are
built with an individual person rather than with a selling firm
(Palmatier et al., 2006). This is well in line with SEPs, where both firms
and individuals can act as sellers.
The existing empirical research related to relationship quality has
used the concept as an abstract and global construct, keeping in mind
the fact, that although the components are different, consumers still
may find it difficult to distinguish between them (Crosby et al., 1990).
In general, researchers agree that relationship quality is a multidimensional
construct (Garbarino and Johnson, 1999; Palmatier et al.,
2006). A meta-analysis conducted by Palmatier et al. (2006) revealed
that the multi-dimensional constructs of relationship quality, i.e. trust,
satisfaction, commitment, are foremost in influencing any businesses
performance. Trust is defined as the willingness to rely on an exchange
partner with whom a certain level of confidence has been built
(Moorman et al., 1993). Satisfaction refers to the consumers’ evaluation
of the comprehensive performance of a product/service provider
(Gustafsson et al., 2005). Commitment refers to the notion or desire to
keep and maintain the relationship (Moorman et al., 1993; Morgan and
Hunt, 1994). Although some researchers treat relationship quality as a
global construct (Wulf et al., 2001; Kumar et al., 1995), researchers
often disaggregate the construct and measure each of the sub-constructs
individually (see, e.g. Rafiq et al., 2013). This enables researchers to
draw an understanding and focus on the component that matters most,
rather than focusing their efforts on all the components equally
(Rafiq et al., 2013). We follow this line of thought in our research. In
building on the above discussion, we now move on to present our research
model and hypotheses.
3. Research model and hypotheses
3.1. Research model
We propose a general and encompassing theoretical model for the
antecedents to consumers’ value co-creation intentions at SEPs (Fig. 1).
The model determines the effect of social support on consumers’ ethical
perceptions, which in turn leads to relationship quality constructs and
value co-creation intentions.
The current study integrates various theoretical lenses when identifying
the main constructs of the research model and in establishing the
relationships between them. The main constructs are social support,
which is rooted in social support theory (Barrera, 1986; Cobb, 1976;
Gottileb and Bergen, 2010); consumers’ ethical perceptions, which is
rooted in marketing and business ethics literature (Bush et al., 2000;
Laczniak and Murphy, 2019; Roman, 2007; Roman and Cuestas, 2008);
relationship quality, which is developed from the literature on relationship
marketing and relationship quality theory (Henning-Thrau et al.,
2002; Liang et al., 2011; Rafiq et al., 2013); and value co-creation, which
is rooted in service dominant logic (SD-logic) (Vargo and Lusch, 2004;
2008; Vargo et al., 2008). Despite the construct value co-creation, all
constructs are multidimensional. Social support is hypothesized to be a
second-order construct comprising two sub-dimensions: emotional
support and informational support. Consumers’ ethical perceptions is
treated as a second-order construct, too, consisting of four dimensions:
privacy, security, non-deception, and fulfillment/reliability
(Roman, 2007; Roman and Cuestas, 2008). Relationship quality consists
of three disaggregated concepts: – trust, commitment and satisfaction –
used to evaluate consumers’ relationship quality.
The hypothesized relationships between the constructs are developed
on the basis of well documented theoretical foundations provided
by previous studies (Abela and Murphy; 2008; Hajli et al., 2017;
Liang et al., 2011; Tajvidi et al., 2018; Williams and Aitken, 2011). It
must be mentioned here that, although the integrations of the aforementioned
theories are broadly studied in offline settings, other online
settings, and social commerce settings; this kind of holistic model has
neither previously been established in these settings nor tested in the
context of sharing economy literature. Therefore, our study is one of the
first to further explore these relationships and add to the existing body
of knowledge. We discuss the hypotheses of the current study in the
following section.
3.2. Hypotheses development
Social support theory is derived from social psychology literature
that takes into account the notion of the experience of individuals
present in a social network in which they feel helped, loved, respected,
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
4
and cared for by other members (Barrera, 1986; Cobb 1976;
Hajli, 2018). Once this type of support system is developed in an online
platform, more people are attracted to join such networks. In addition,
when consumers find support from other members when, for example,
they encounter a problem or issue, it is more likely that they develop
positive feelings towards the platform and make better decisions in
addressing the problem or issue (Hajli, 2018). In the context of SEPs,
consumers can find informational support, as the platforms enable their
users to give recommendations, reviews, chat on their forums, and
complete profile information for the sake of making informed and
better decisions. Similarly, consumers can draw emotional support if
they encounter a problem and other consumers present in the platform
help resolve that problem (Hajli, 2018). Thus, we treat social support as
a multi-dimensional construct comprising emotional support and informational
support.
Previous research has revealed that the relationships between consumers
on online platforms and the social support available can lead to
not only satisfaction (Obst and Stafurik, 2010) but also trust of the
consumers on online platforms (Crocker and Canevello, 2008). Building
on the aforementioned theoretical discussion and empirical findings on
social support, as well as recognizing the characteristics of SEPs, it is
reasonable to assume that social support operates as an antecedent to
the consumers’ perceptions of the ethical aspects related to the SEP in
question. Hence, it is hypothesized:
H1+. Social support on SEPs positively affects consumers’ ethical
perceptions of SEPs.
Renowned companies have long been harnessing the idea of brand
value co-creation online. For instance, Ikea is a typical example of this
phenomenon, having introduced the notion of ‘co-create Ikea’ by allowing
fans and customers to develop new products online. The support
in the form of incentives and rewards available on the digital platform
provided by Ikea allows customers to come up with product ideas and
suggestions. Ikea received thousands of suggestions in this regard and
this co-creation enables them to put crowd wisdom to work in
developing better designs and products and eventually benefitting the
company and its existing and potential customers (Ikea, 2019). Prior
research on social media environments has asserted that value cocreation
can be fostered by online social support (Ramaswamy and
Oczan, 2016). Therefore, in consideration of the previous research, it
can be posited that social support received on SEPs can enable value cocreation
intentions. Hence it is postulated:
H2+. Social support on SEPs increases consumers’ value co-creation
intentions at SEPs.
According to Rotter (1971), consumer trust is developed when the
consumer feels that the seller (e.g. sharing economy service provider) is
fair, benevolent, responsible, and honest. Moreover,
Crosby et al. (1990) argue that trust develops when consumers believe
their interests would be served by the seller. Previous research has
shown that there is a positive effect of ethical construct of privacy on
trust (Bart et al., 2005). Robertson and Anderson (1993) revealed that
consumers’ trust is highly dependent on the ethical practices of the
industrial salespeople with regards to product, price, promotion, and
placement. Even in offline settings, the role of ethical sales practices has
been found to be positive in relation to trust (Roman, 2003). More recently,
in e-retail settings, Elbeltagi and Agag (2016) have revealed the
positive effect of ethical dimensions on consumers trust. Theoretically,
consumer behavior theory suggests that the marketing activities act as a
stimulus (drawing consumers’ ethical perceptions) to evoke certain
responses, and one of those responses can be trust (Elbeltagi and
Agag, 2016). In keeping the traditional e-retail perspective at the fore,
it is plausible that ethical perceptions can affect consumers’ trust within
the sharing economy context. Based on the aforementioned studies, we
hypothesize:
H3+. Consumers’ ethical perceptions of SEPs increase consumers’ trust
in SEPs.
When consumers feel content with the experience of their previous
purchase, they are referred to as satisfied consumers (Anderson and
Srinivasan, 2003; Roman, 2007). The relationship between a higher
Fig. 1. Research model.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
5
order construct of consumers’ ethical perceptions has been confirmed
before in online retail settings (Roman, 2007). From a theoretical
standpoint, the notion of consumer satisfaction is embedded in the
expectancy disconfirmation paradigm (Burke et al., 1988;
Roman, 2007). According to this paradigm, consumers make a comparison
between their expectations of a product or service and its
performance, which leads to either confirmation or disconfirmation.
Negative disconfirmation occurs when the expectations do not meet the
performances. Conversely, positive disconfirmation occurs when the
product/service performance surpasses the initial expectation and,
hence, satisfaction is an outcome of positive disconfirmation or confirmation
(Roman, 2007). In the sharing economy context, if accurate
information is provided through SEPs and SEPs are adhere to high
ethical standards, leading to realistic expectations of products/services,
then it is likely that consumers will be more inclined towards the positive
disconfirmation or confirmation side. This eventually leads to
consumer satisfaction. As prior research in e-retail settings has also
revealed the positive effect of ethics on satisfaction (Cheng, 2011;
Elbeltagi and Agag, 2016; Kurt and Hacioglu, 2010; Roman, 2007), it is
of high importance that this relationship be studied in the sharing
economy context; in terms of whether or not consumer satisfaction is
fostered by consumers’ ethical perceptions. Thus, we hypothesize:
H4+. Consumers’ ethical perceptions of SEPs increase consumers’
satisfaction with SEPs.
According to Moorman et al. (1993), relationship commitment is
the enduring desire to keep, maintain, and continue the valued relationship.
If consumers have positive ethical perceptions of sharing
economy service providers, this reduces their uncertainty (Hwanga and
Leec, 2012) and the risks associated with online platforms (Morgan and
Hunt, 1994). This eventually leads to relationship commitment
(Gundlach et al., 1995). If consumers do not feel comfortable in their
use of SEPs due to ethical issues (related to privacy, security, deception,
fulfillment), then it is likely that they might not want to continue the
relationship with the SEP in question. Studies in the e-retail context
have shed light on the positive association between consumers’ ethical
perceptions and commitment (Collier and Esteban, 2007; Elbeltagi and
Agag, 2016). More recently, Elbeltagi and Agag (2016) have shown that
consumers’ ethical perceptions can be treated as the precursor of consumer
commitment. In the sharing economy context, the relationship
between consumers’ ethical perceptions and commitment is understudied.
To ascertain this we hypothesize:
H5+. Consumers’ ethical perceptions of SEPs increase consumers’
commitment with SEPs.
According to Zach et al. (2018), SEPs have become popular because
consumers perceive participation in SEPs as more convenient, economical,
and enjoyable. Conversely, consumers also have risks associated
with such platforms and these risks can be related to privacy,
security, fulfillment/reliability and non-deception. SEPs operate on the
principle of information sharing and data input from the members, and
this involves the risk of information being used for un-wanted commercial
activities (Dillahunt and Mallone, 2015). There have been cases
of such practice; for instance Uber rounded up the fee to the nearest
dollar in its favor, by cheating the drivers (see e.g. The Guardian, 2018;
Newcomer, 2017). Such practices deter the consumers from participating
freely in SEPs. Therefore, we argue that if consumers ethical
perceptions are taken care of by the SEPs, it is likely that they will
participate freely, share information, and co-create value. Thus, it is
hypothesized:
H6+. Consumers’ ethical perceptions of SEPs increase consumers’
value co-creation intentions at SEPs.
Chen and Myagmarsuren, 2011 asserted that relationship quality is
one of the major factors affecting consumers’ decisions to build, withdraw,
keep, and maintain the relationship. Advances in technology
have led to consumers developing interactive relationships on online
platforms by being anonymous and impersonal (Wang and
Emurian, 2005). In the sharing economy context, the quality of the
relationship between consumers and service providers can be determined
when any previous interaction has generated positive outcomes
and future interactions and transactions are expected between
consumers and service providers.
Through SEPs, service providers share information on their products
and services as an input mechanism for value co-creation. From the
consumers’ point of view, they freely interact and share their experiences
and information with other consumers and, therefore, contribute
to value co-creation with the SEP. From the point of view of SEPs, the
platform they provide allows consumers to post their opinions freely,
and based on comments, reviews and suggestions from the consumers,
SEPs devise their marketing and product strategies to better serve the
needs of the consumers (see e.g. We-Economy, 2015). It can be surmised
that SEPs allow and encourage consumers to not only participate
but also co-create value. This process stems from the relationship
quality. Several authors have argued that trust, satisfaction, and commitment
tend to be the main components of relationship quality
(Hajli et al., 2017; Morgan and Hunt,1994; Palmatier et al., 2006;
Sheth and Parvatiyar, 2002). In this regard, consumers will tend to gain
more trust, satisfaction, and a sense of commitment with SEPs.
Previous studies in social commerce settings have confirmed the
relationships between the constructs of relationship quality, i.e. trust,
satisfaction, and commitment, with value co-creation intentions (see
e.g. Hajli et al., 2017; Kamboj et al., 2018; Tajvidi et al., 2018). With
regards to trust, Guenzi and Pelloni (2004) argue that trust is essential
in online environments for the sake of commercial and interpersonal
relationships. According to Pavlou (2003), trust is crucial in most social
and economic transactions, and also has been studied in social commerce
settings (Nadeem et al., 2017a) influencing behavioral outcomes.
Therefore, we expect trust to be an important component of relationship
quality, impacting on value co-creation intentions in sharing
economy settings. Thus, we hypothesize:
H7+. Consumers’ trust in SEPs increases consumers’ value co-creation
intentions at SEPs.
Satisfaction represents the overall performance evaluation a consumer
carries out in relation to a product or service after consumption
(Gustafsson et al., 2005). Satisfaction stems from consumers developing
positive attitudes towards the experience of products or services
(Boulding et al., 1993). It can be assumed that if consumers are satisfied
with SEPs, they will co-create value with the SEPs. Thus, is it hy-
pothesized:
H8+. Consumers’ satisfaction with SEPs increases consumers’ value cocreation
intentions at SEPs.
In recent research, commitment has been measured by the willingness
of consumers to participate in online platforms (see e.g.
Hajli et al., 2017). For the sake of developing successful, productive,
and long-term relationships, commitment becomes a fundamental
component of relationship quality (Dwyer et al., 1987; Hsu et al.,
2010). In sharing economy contexts, customers with high levels of
commitment are more inclined to like SEPs, which then fosters longterm
relationship stability with the brand (Fournier, 1998). Moreover,
commitment enhances value co-creation in the form of consumer involvement
and participation with the social commerce platforms
(Hajli et al., 2017). This implies that strong commitment with SEPs
leads consumers to participate and engage with SEPs, and thereby cocreate
value with the SEPs. Following this logic, we examine the impact
of commitment on value co-creation intentions. Hence, it is hypothe-
sized:
H9+. Consumers’ commitment with SEPs increases consumers’ value
co-creation intentions at SEPs.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
6
4. Data collection
An online survey was conducted with consumers who rely on
sharing economy platforms. The list was inspired by the popular
sharing economy platforms including 1) Uber, 2) Lyft, 3) Airbnb 4)
Indiegogo, 5) Homeaway, 6) Kickstarter, and 7) Zipcar. We obtained
almost 500 responses at a cost of 0.5$ each through an online US-based
website, Amazon's MTurk. Researchers have previously shown MTurk
results to be comparable in quality in relation to comparisons with data
collected from other offline and online domains (see e.g.
Buhrmester et al., 2011; Mason and Suri, 2012). Accordingly, our data
is much more reliable than, for instance, student samples, which have
often been criticized due to their inherent limitations (see e.g.
Peterson and Merunka, 2014).
We specifically focused on Generation Y (GenY) consumers who
were born between 1981 and 1999 (Bolton et al., 2013), irrespective of
other characteristics. This is because the co-consumption and technological
dependence that are typical to the sharing economy are often
strongly linked to GenY (Belk, 2014; Godelnik, 2017; Ranzini et al.,
2017), and because the consumption patterns of GenY markedly differ
from those of other generations. A total of 342 responses fulfilled the
criteria of GenY respondents. The sample profile is provided in Table 1.
4.1. Measurement
The current study adapts all measures from previous literature.
Moreover, a seven-point Likert scale was used (ranging from
1 = “Strongly disagree” to 7 = Strongly agree”). The measurement
items were further reworded to a small extent to fit in the research
context of SEPs. The independent variable – social support – was further
measured by two sub-variables – emotional support and informational
support – and the items for variables were adapted from
Tajvidi et al. (2017). Moreover, the items for four sub-variables
(privacy, security, fulfillment/reliability, non-deception) of consumer's
ethical perceptions of SEPs were adapted from the studies by
Roman (2007) and Roman and Cuestas (2008). The constructs of relationship
quality, trust, commitment, and satisfaction were adapted
from Liang et al. (2011). The items used for value co-creation intentions
at sharing economy platforms were obtained from Ramaswamy and
Ozcan (2016), Schau et al. (2009); and Tajvidi et al. (2017).
4.2. Measurement validation
The first step involved screening of the data and checking for the
unengaged responses as evidenced by giving the exact same response
for every single question. We retained n = 342 responses that met the
criteria of falling in the cohort of GenY and useable responses. As the
evidence of normal distribution, all the values were below +3 and −3,
indicating no non-normal distribution issues.
When data is collected from the same population at the same time,
the problem of common method bias may occur and influence the validity
of the study (Podsakoff et al., 2003). In order to address this issue,
we applied Harman's single factor test. More specifically, we ran an unrotated
exploratory factor analysis by constraining the number of factors
to be 1 (one). Results of this test reveal that the maximum variance
explained by a single factor is 35.599. Therefore, it can be asserted that
the current dataset does not suffer from the common method bias issue,
as the variance explained by a single factor is approximately 36%,
which is less than the threshold value of 50%. This means that no single
factor surpassed the threshold value of 50%. Furthermore,
Pavlou et al. (2007) have suggested that no correlations among the
constructs should be above 0.9. If there is an issue of common method
bias, then the correlations among the constructs would be significantly
higher (r > 0.90). Consequently, the common method bias is not a
concern in this study.
5. Data analysis and results
5.1. Factor analyses
Amos version.24 was employed to analyze the data. Exploratory
factor analysis and confirmatory factor analysis tests were conducted in
order to determine the reliability and validity of the constructs
(Anderson and Gerbing, 1988; Fornell and Larcker, 1981). After careful
analysis of the items contributing to the poor fit of the model, factors
with cross loadings and small loadings were deleted accordingly. In
addition, values were assessed through standardized residual covariance
and the items contributing to the poor fit of the model were deleted
accordingly. Moreover, modification indices were also assessed
and treated accordingly. This led us to remove one item from informational
support factor; three items from privacy factor; three items
from security factor; two items from fulfillment factor; three items from
trust factor; one item from commitment factor; and one item from satisfaction
factor. Therefore, in total, 27 items were retained out of 41
items for the purpose of further analysis. We also deleted the subconstruct
of non-deception as it came out to be negative and non-significant
in the measurement model. It is pertinent to mention here that
the main aim of the authors was to retain as many items as possible;
however, upon applying all possible solutions, the retained number of
items was 27, indicating a good statistical fit for the model. The final
items retained are presented in Table 2.
The assessment of each measurement scale turned out to be reliable.
For instance, the Cronbach's alphas ranged higher than the 0.70
threshold suggested by Nunnally (1978). Furthermore, the goodness of
fit statistics of the measurement model revealed an acceptable fit see
e.g. (Browne and Cudeck, 1993; Doll et al., 1994; Hair et al., 2009;
Kenny, 2014; Schermelleh-Engel et al., 2003) (Table 3).
5.2. Validity and reliability
We conducted comprehensive reliability and validity tests and, as
the evidence of convergent validity, all the loadings were above 0.7. In
addition, as the evidence of discriminant validity (Hu and
Bentler, 1999), there were no strong cross loadings in exploratory factor
Table 1
Sample profiles.
Variable Percentage
Gender
Male 52.3%
Female 47.7%
Age
GenY (19–37 years) 100%
(Frequency) How often do you use SEPs?
Daily 6.4%
Weekly 34.8%
Monthly 37.1%
Quarterly 15.5%
Once in six months 5.0%
Once in a year 1.2%
(Experience) How long have you been using the SEPs?
1 year 7.3%
2 years 20.5%
3 years 28.9%
4 years 23.7%
5 years 10.8%
6 years 8.8%
What is your favorite/preferred SEP?
Uber 60.17%
Airbnb 15.53%
Lyft 12.88%
KickStarter 4.07%
a
Others 7.35%
a
Others include Zipcar, Homeaway, Patreon, Snapgoods etc.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
7
analysis. We have two higher order factors in the measurement model;
i.e. social support and consumers’ ethical perceptions of SEPs. Moreover,
there were no loadings greater than 0.7 in the factor correlation
matrix and all AVE values were above 0.5 (Table 4).
5.3. Hypotheses testing and structural model with results
Structural equation modeling (SEM) through Amos version 24 was
utilized to estimate the hypothesized relationships. The analyses provided
acceptable fit indices for the structural model (Table 5) (see e.g.
Hair et al., 2009). We even checked the model by removing the two
non-significant paths and the goodness of fit indices remained the same.
Social support was found to contribute positively and significantly to
consumer's ethical perceptions of a sharing economy platform
(β = 0.624, p < 0.01) supporting H1+ (Table 6). Moreover, social
support positively influences value co-creation intentions (β = 0.287,
p < 0.01), thus H2+ is supported. Furthermore, consumers’ ethical
perceptions of sharing economy platforms positively and significantly
contribute to trust (β = 0.915, p < 0.01), satisfaction (β = 0.796,
p < 0.01), and commitment (β = 0.805, p < 0.01) in sharing economy
platforms. Hence, the hypotheses H3+, H4+ and H5+ are also supported.
Consumers’ ethical perceptions also positively and significantly
influence consumers’ value co-creation intentions (β = 0.680,
p < 0.01), supporting H6+. Moreover, commitment and trust in SEPs
do not translate into value co-creation intentions, whereas satisfaction
does (β = 0.31, p < 0.01). Therefore, H7+ and H9+ are not supported
and H8+ is supported. The R2
values denote the percentage of variance
explained for the dependent variables. These values also indicate the
predictive power of the exogenous constructs on endogenous variables.
Table 2
Constructs and measurement items table.
Constructs and measurement items Standardized loading (t-
value)
Mean a
SD a
CA
Social support
Emotional support 0.929
When faced with difficulties, some people on my favorite SEP take my side 0.815(19.42) 4.49 1.669
When faced with difficulties, some people on my favorite SEP comforted and encouraged me 0.908(23.86) 4.43 1.688
When faced with difficulties, some people on my favorite SEP listened to me talking about my private feelings 0.869(.std) 4.27 1.792
When face with difficulties, some people on my favorite SEP expressed interest in and concern about my well-being 0.914(24.11) 4.40 1.741
Informational support 0.871
On my favorite SEP, some people would offer suggestions when I needed help 0.836(19.10) 4.72 1.587
When faced with difficulties, some people on my favorite SEP would help me discover the cause and provide me with
suggestions
0.923(.std) 4.69 1.601
Consumer's ethical perceptions of sharing economy platforms
Privacy 0.868
This SEP clearly explains how information provided by consumers is used 0.804(.std) 5.04 1.543
This SEP will not use personal information for purposes other than for the original transactions without the consent of
consumers
0.791(15.73) 5.01 1.459
This SEP guarantees that the personal information of consumers will be handled in accordance with a third party's
privacy-protection regulations and has acquired authentication knowledge
0.793(15.80) 5.01 1.416
This SEP will not apply special technology to collect and analyze the internet behavior and shopping habits of consumers
without their consent
0.768(15.18) 4.74 1.571
Security 0.808
This SEP guarantees that the transmission of transactional data will be protected without any unauthorized modification
or sabotage
0.756(.std) 5.33 1.361
This SEP has a transactional security policy that consumers can understand easily 0.806(14.91) 5.15 1.448
This SEP guides consumers to correct and safe payment steps 0.726(13.34) 5.44 1.327
Fulfillment/Reliability 0.861
Consumers receive the correct products/service items and their quantities ordered online 0.765(.std) 5.45 1.287
Consumers receive products/services that are ordered online, matching the description on this SEP 0.832(15.40) 5.43 1.313
This SEP guarantees that products/services ordered online are authentic and not imitations 0.785(14.51) 5.42 1.407
The products/services pricing on this SEP are consistent with the bill 0.745(13.72) 5.37 1.397
Relationship quality
Trust 0.873
I would characterize the SEP as honest 0.882(20.04) 5.32 1.427
The SEP is trustworthy 0.879(19.94) 5.35 1.397
Commitment 0.877
I feel a sense of belonging with the SEP 0.834(18.38) 4.96 1.657
I care about the long-term success of the SEP 0.870(19.63) 5.29 1.465
I am a loyal patron of the SEP 0.820(17.92) 5.35 1.393
Satisfaction 0.802
Overall, I am satisfied with the SEP 0.872(18.46) 5.81 1.145
The last time I used the SEP, it fulfilled my expectation 0.770(15.77) 5.79 1.248
Value co-creation intentions 0.865
I am willing to provide my experiences and suggestions when my friends on my favorite SEP want my advice on buying
something from a sharing economy platform
0.793(16.86) 5.29 1.427
I am willing to buy the products/services of an SEP recommended by my friends through my favorite sharing economy
platform
0.817(17.60) 5.19 1.454
I consider the buying experiences of my friends through my favorite SEP when I want to go for a service in a sharing
economy platform
0.870(19.31) 5.25 1.415
a
Note: Scales adapted from the mentioned authors and altered in the context of sharing economy platforms SD = Standard Deviation; CA = Cronbach's Alpha.
Table 3
Goodness of fit indices of the measurement model.
SRMR NFI CFI TLI PClose Chi-Square df P-value RMSEA
0.055 0.908 0.950 0.941 0.025 645.085 304.00 0.000 0.057
SRMR = Standardized Root Mean Square Residual; NFI= Normed Fit Index;
CFI= Comparative Fit Index; TLI = Tucker-Lewis Index; Df= Degrees of
Freedom; RMSEA = Root Mean Square Error of Approximation.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
8
For instance, 39% of the variance is explained in consumer's ethical
perceptions of sharing economy platforms (Fig. 2). Moreover, 84%,
63%, and 65% of the variance is explained in trust, satisfaction, and
commitment, respectively.
6. Discussion
The purpose of this study was to create and test a holistic model that
explains the formation of consumers’ value co-creation intentions at
SEPs. Building on various bodies of literature, such as social support
theory, relationship quality theory, value co-creation literature and the
literature on marketing and business ethics we proposed a theoretical
model which explains the formation of consumers’ value co-creation
intentions. We analyzed the empirical data collected from 342
Generation Y consumers on a US-based online platform using structural
equation modeling (SEM) and confirmed the majority of the hypothesized
relationships.
In terms of the holistic model, the results reveal that social support
influences ethical perceptions, which further influences value co-creation
intentions through satisfaction. Ethical perceptions also influence
trust and commitment, but we were unable to confirm their influence
on value co-creation intentions. Moreover, social support also has a
direct influence on value co-creation intentions. Our findings are in line
with existing research in many respects, although our model and context
are novel. In essence, the relationship between social support and
value co-creation is in line with Hajli (2014), who revealed that social
support is an antecedent of social commerce intention on Facebook.
Our findings are also in line with research demonstrating that the social
support available online can lead to satisfaction (Hajli 2014; Obst and
Stafurik, 2010), commitment, and trust (Hajli 2014). The findings are in
line with previous studies in which several researchers have found the
positive effect of ethics on satisfaction (Cheng, 2011; Elbeltagi and
Agag, 2016; Kurt and Hacioglu, 2010; Roman, 2007) and in which, for
instance Williams and Aitken (2011) have proposed that when businesses
behave in accordance with values that motivate consumers, such
as ethics, consumers’ participation in co-creation activities increases.
Furthermore, our finding of the relationship between satisfaction and
co-creation intentions is partly in line with Hajli (2014), who revealed
that relationship quality, including satisfaction, trust, and commitment,
influences social commerce intentions. We were, however, unable to
confirm the relationships between trust and commitment and value cocreation
intentions. This may be due to our target respondents feeling
that SEPs are rather new, leading them to enthusiastically try many
different SEPs, yet not exerting a strong commitment to any of them.
Even if consumers potentially rely on a certain SEP, this does not necessarily
mean that they will write good reviews and give feedback or
recommendations that can be further utilized by other consumers present
there, as well as by the SEPs service providers themselves. The
second potential explanation could be that the consumers’ ethical perceptions
lead them to trust the SEPs without this trust necessarily
translating into sharing their experiences further or giving advice to
their peers. The target respondents showed a preference for using the
SEPs without necessarily contributing to the user community around
them and, as such, can be termed as so called ‘lurkers'. This is an interesting
finding as it expresses the role of individualism rather than the
more socially active role played by consumers in today's socially-focused
and connected world fueled by technology advances. Only when
consumers are satisfied with SEPs are they likely to co-create value with
the SEP.
In terms of constructs, we confirmed that social support is a multidimensional
second-order construct comprising emotional support and
informational support. The result is in line with previous research recognizing
the importance of both emotional and informational support
(Hajli, 2014, 2018) in online settings. Additionally, we confirmed that
ethical perceptions can be considered as a second-order construct
consisting of three dimensions: privacy, security, and fulfillment/reliability.
This construct is partly similar to the construct suggested by
Table 4
Validity and reliability of measures.
CR AVE MSV MaxR(H) COCRE SUPP ETHIC TRUS SATS COMT
COCRE 0.867 0.684 0.469 0.872 0.827
SUPP 0.887 0.797 0.508 0.888 0.614 0.893
ETHIC 0.914 0.781 0.558 0.994 0.665 0.509 0.884
TRUS 0.873 0.775 0.679 0.873 0.653 0.584 0.747 0.881
SATS 0.807 0.677 0.642 0.822 0.685 0.380 0.676 0.801 0.823
COMT 0.879 0.708 0.679 0.882 0.612 0.713 0.639 0.824 0.611 0.842
CR = Composite Reliability; AVE = Average Variance Extracted; MSV = Maximum Shared Variance; MaxR(H) = Maximal Reliability; ETHIC = Consumers Ethical
Perceptions of SEPs; COMT = Commitment; SATS = Satisfaction; TRUS = TRUST; COCRE = Value co-creation intentions; SUPP = Social Support.
Table 5
Goodness of fit indices of causal model.
SRMR NFI CFI TLI Chi-Square df p-value RMSEA
0.072 0.886 0.926 0.916 803.586 310.000 0.000 0.068
SRMR = Standardized Root Mean Square Residual; NFI = Normed Fit Index;
CFI = Comparative Fit Index; TLI = Tucker Lewis Index; Df = Degrees of
Freedom; RMSEA = Root Mean Square Error of Approximation.
Table 6
Path estimates.
Relationships Hypotheses Std. estimates(t-value) P- value Results
SUPP → ETHIC H1+ 0.624(9.066) 0.000 Supported
SUPP → COCRE H2+ 0.287(4.561) 0.000 Supported
ETHIC → TRUS H3+ 0.915(12.257) 0.000 Supported
ETHIC → SATS H4+ 0.796(10.077) 0.000 Supported
ETHIC → COMT H5+ 0.805(11.019) 0.000 Supported
ETHIC → COCRE H6+ 0.680(2.313) 0.018 Supported
TRUS → COCRE H7+ −0.341(−1.707) 0.088 Not-Supported
SATS → COCRE H8+ 0.309(3.144) 0.000 Supported
COMT → COCRE H9+ −0.049(−0.516) 0.616 Not-Supported
SUPP = Social Support; ETHIC = Consumer's ethical perceptions of sharing economy platforms; COMT = Commitment; TRUS = Trust; SATS = Satisfaction;
COCRE = Value co-creation intentions.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
9
Roman (2007) and clearly supports the role of the two traditional main
ethical concerns in online settings; namely privacy and security
(Roman and Cuestas, 2008). This construct has, however, fewer factors
than the five-factor construct of Cheng et al. (2014), as we intentionally
excluded service recovery from our research model due to it being
beyond the scope of this study. Our construct also differs from previous
research by conducted by Agag (2019), who has proposed more individual
factors that relate to consumers ethical perceptions.
Interestingly, although non-deception proved to be one of the subfactors
of the second-order construct in Roman's (2007) work, it provided
a an insignificant relationship with ethical perceptions when we
included the second-order construct of ethical perceptions in our
measurement model. We propose two potential explanations for this.
Firstly, even in such a novel context as the use of SEPs, consumers have
recognized that SEPs behave in an ethical way without making any false
statements about their competitors or blaming other organizations and,
thus, the meaning of potential deception becomes insignificant in its
totality. Secondly, our respondents represent a heterogeneous cohort,
consisting both of those for whom non-deception is significant and
those for whom it is insignificant. As we conducted our analyses using
SEM, we were unable to reveal this potential heterogeneity.
7. Theoretical implications
Our study contributes to literature on SEPs in several ways. Firstly,
we provide a holistic model of the antecedents to consumers’ value cocreation
intentions at SEPs. Although SEPs have gained research interest,
a holistic model explaining the formation of consumer value cocreation
intentions in such platforms has remained absent from the
existing research. To specify this further, although previous research
(Hajli, 2014) has shown that both relationship quality including satisfaction,
trust, and commitment and that social support consisting of
emotional and informational support are antecedents to social commerce
intention, ethical perceptions have been absent in the models
used thus far. Our study closes this gap by highlighting the role of
ethics, responsibility, and sustainable behavior in the context of SEPs.
Although Hajli (2014) focused on social commerce by using Facebook
data, no research has examined these aspects in the context of SEPs. Our
study is first to do so.
Additionally, we confirmed the influence of ethical perceptions not
only on trust, satisfaction, and commitment, which are central
constructs in relationship quality theory, but also on consumers’ value
co-creation intentions at SEPs. Although the underlying relationship
between social support and social commerce intentions is recognized in
the extant research (Hajli 2014), no research has considered how value
co-creation is fostered by consumers’ ethical perceptions. Additionally,
although research has shown that the GenY cohort has privacy concerns
with regards to SEPs (Ranzini et al., 2017), our study is among the first
to establish the role of ethical perceptions in relation to their value cocreation
intention through SEPs.
Furthermore, our study is the first to confirm that social support is
an antecedent to value co-creation through SEPs. Although it is widely
acknowledged by researchers that the social support available online
can lead to satisfaction (Hajli 2014; Obst and Stafurik, 2010), commitment,
and trust (Hajli 2014), as well as the recognition that ethical
practice and values have a positive effect on satisfaction (Cheng, 2011;
Elbeltagi and Agag, 2016; Kurt and Hacioglu, 2010; Roman, 2007),
these studies have mainly been conducted in e-retail or social commerce
settings. Thus, our study adds to these studies by confirming the
relationship in the context of SEPs.
In addition, we confirmed that social support is a multi-dimensional
second-order construct comprising emotional support and informational
support. Although previous research has confirmed the construct
in social commerce settings (Liang et al., 2011), our study is the first to
do so in relation to the sharing economy. Our study also shows that
consumers’ ethical perceptions also constitutes a multi-dimensional
construct comprising privacy, security, and fulfillment/reliability. Even
though various researchers have examined this construct and its subconcepts
in traditional online settings (Agag 2019; Cheng et al., 2014;
Roman, 2007; Roman and Cuestas, 2008), the current study is pioneering
in its confirmation of the construct in relation to SEPs, specifically
from the viewpoint of GenY cohort. Although our findings related
to the role of non-deception, which turned out to be nonsignificant,
differ from the existing literature in online contexts
(Roman, 2007), our study offers an important platform on which our
understanding of the ethical perceptions related to SEP can be ad-
vanced.
Finally, even though the GenY cohort is tech savvy (Bolton et al.,
2013) and closely connected to the sharing economy (Belk, 2014;
Godelnik, 2017; Ranzini et al., 2017), they have been understudied in
the sharing economy context. Our study not only answers the call by
Ranzini et al. (2017) to explore this cohort more in sharing economy
Fig. 2. Structural model with results.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
10
settings and provide a significant contribution to the relevant literature,
but also advances the field by drawing on actual consumer survey data
from this cohort.
8. Managerial implications
We offer three suggestions for SEP managers. Firstly, it is essential
that SEP managers ensure consumers feel they gain social support both
in a form of emotional and informational support while engaging with
SEPs. GenY is tech savvy and SEPs are easy to use, which means that
they probably consider technological aspects as self-evident and their
focus while using SEPs changes to include entertainment and experiential
aspects. This means that consumers are not only purchasing
consumption experiences of shared products or services but also engaged
in experiential mechanisms throughout the purchasing process
with the SEP. If they confront difficulties during this experiential process,
it is essential they feel that someone at the SEP lives this experience
with them: they need to feel that someone is interested in them,
they are heard, and their problems will be solved. This not only ensures
consumers successfully experience the SEP but also influences how they
perceive ethical aspects and create relationships with the SEP.
Secondly, it is also crucial to recognize the essential role of ethical
perceptions of consumers while they are using SEPs. At the bare
minimum, this means that consumers need to feel that the SEP takes
care of the privacy and security aspects and operates reliably. These
aspects are essential, as together they influence how willing consumers
are to participate in co-creating value with others through the SEP, and
they also influence consumers trust and satisfaction for and commitment
to the SEP.
Thirdly, it is important to remember that even though consumers
say they trust the SEP and are committed to it, neither of these increases
their intention of participating in value co-creation through the platform.
Only their satisfaction with and ethical perceptions of the SEP,
preceded by social support, are meaningful antecedents in explaining
their value co-creation intentions at SEPs.
9. Limitations and future research
As for research in general, our study also has its limitations. Firstly,
we focused on Generation Y consumers only. Although it is essential for
researchers to understand the buying and consumption behavior of this
age cohort, focusing on them gives a partial view of the whole SEP
landscape. It is important to acknowledge that the data from other
consumer segments (see e.g. Nadeem et al., 2017b) such as middle-aged
or elderly people might offer more diverse results. Additionally, our
data was from the US only. This means that the study offers quite a
narrow perspective on the global phenomenon of SEPs as it lacks, for
instance, international, cross-cultural, and global viewpoints. All these
limit the global generalization of the results. In addition, we managed
to confirm ethical perceptions as a second-order construct consisting of
three factors only. The extant research has recognized a variety of other
factors that may offer novel insights to ethical perceptions in online
environment.
We encourage researchers to further examine the role of ethical
perceptions in terms of social commerce in general and amongst SEPs
particularly. For instance, because we revealed that ethical perceptions
influence trust, satisfaction, and commitment, but were able to confirm
the relationships between trust and commitment and value co-creation
intentions, more research is needed to examine the importance of these
relationships in general and in relation to ethical perceptions particularly
in the context of social commerce. Additionally, because we
considered ethical perceptions as a second-order construct consisting of
three factors only, more research is needed to test if the construct can
include more factors. Specifically, the role of non-deception requires
further research attention: non-deception provided a significant relationship
with ethical perceptions in e-retail settings before (see e.g.
Roman, 2007) but it provided a non-significant relationship with
ethical perceptions when ethical perceptions were considered as part of
a measurement model in our context of the sharing economy. We call
for further research to close these gaps, along with novel ideas to further
examine the role of ethics, responsibility, and sustainability in
sharing economy research.
Funding source
None.
Declaration of Competing Interest
None.
Supplementary materials
Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.techfore.2019.119786.
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Waqar Nadeem is working as an Assistant Professor at the Department of Marketing,
Management and International Business at Oulu Business School, University of Oulu,
Finland. Waqar has a D.Sc. (Econ. & Bus. Adm.) with specialization in Marketing from
OBS. His research has appeared in journals such as Journal of Business Ethics,
Technological Forecasting and Social Change, Industrial Marketing Management, Journal
of Consumer Behaviour, International Journal of Information Management among others.
His research interests include sharing economy, social commerce, marketing ethics, and
consumer behavior. He is corresponding author and can be reached at: waqar.nadeem@
oulu.fi
Mari Juntunen is an Associate Professor/Senior Research Fellow at the Department of
Marketing, Management and International Business at Oulu Business School, University
of Oulu, Finland. Her research interests include corporate branding, imaginary aspects
and organizational change, which she has studied in different contexts, including small
and medium-sized enterprises (SMEs), B2B, software, logistics, and military forces. Her
work appears in outlets such as Journal of Business Ethics, Industrial Marketing
Management, Journal of Business Research, Journal of Consumer Behaviour, Journal of
Services Marketing and Journal of Brand Management, among others.
Farid Shirazi is a Senior Researcher at Institute for Innovation and Technology
Management at Ryerson University, Toronto, Canada. He is an Associate Professor of the
Ted Rogers school of Information Technology Management. Dr. Shirazi's research focuses
mainly on the impact of ICTs on the social and economic development. His main research
interests are IT-enabled sustainability and development, Cloud Computing, Bigdata
Analytics, E-government strategies, Green IS management as well as the ethical and security
perspectives associated with the introduction and use of ICTs. He has published in
several journals including: Information & Management (I&M), International Journal of
Production Economics among others.
Nick Hajli is an Associate Professor of Marketing in Swansea University, UK. Nick has a
PhD in Management from Birkbeck, University of London. His research has appeared in
the top 20 journals used in Business School Research Rankings and ABS journals such as
Journal of Business Ethics, Journal of Business Research, Industrial Marketing
Management, Annals of Tourism Research, Computers in Human Behaviours, Information
Technology & People and Technological Forecasting and Social Change. He is the author
the Handbook of Research in Integrating Social Media into Strategic Marketing.
W. Nadeem, et al. Technological Forecasting & Social Change 151 (2020) 119786
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