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Int. Journal of Business Science and Applied Management, Volume 17, Issue 3, 2022
Will shoppers adopt online group buying? Understanding
Predictors of consumers’ intention to adopt online group
buying in a typical sub-Saharan African context
Nkechi C Ojiagu
Department of Co-operative Economics & Management, Nnamdi Azikiwe University, Awka
Along Enugu-Onitsha Expressway, Awka, 420110
Tel: +2348032625656
Email: nc.ojiagu@unizik.edu.ng
Obinna Christian Ojiaku
Department of Marketing, Nnamdi Azikiwe University, Awka
Along Enugu-Onitsha Expressway, Awka, 420110
Tel: +2348062678341
Email: oc.ojiaku@unizik.edu.ng
Anayo D Nkamnebe
Department, University: Department of Marketing, Nnamdi Azikiwe University, Awka
Along Enugu-Onitsha Expressway, Awka, 420110
Tel: +234836675771
Email: ad.nkamnebe@unizik.edu.ng
Abstract
Globally, online group buying (OGB) enjoys wide acceptance within the ecosystem of electronic
commerce. Despite its popularity, it is still nascent in Nigeria and most sub-Saharan African (SSA)
economies. With increased internet and online shopping penetration in SSA, the low-price advantage of
OGB, and price sensitivity exhibited by most SSA shoppers, we argue that the adoption of OGB is
expected to be high among SSA shoppers. SSA countries have a diverse institutional and marketing
environment, which makes it unlikely to explain consumer behaviour with the same factors used in
another context. Therefore, understanding the potential predictors of OGB adoption would have far-
reaching theory and practice implications. Accordingly, this study seeks to understand the predictors of
shoppers’ intention to adopt OGB in Nigeria, a typical SSA context. The theory of planned behaviour,
social cognitive theory and empirical validations from the extant literature provide a theoretical
framework for the study. Three hundred and twenty (320) members of the social media community
were surveyed. Responses were analysed with regression analysis to test for the hypothesised
relationships. The result underscores the importance of specific self-efficacy and previous experience
as important predictors of group buying website adoption intention.
Keywords: online group buying, electronic commerce, sub-Saharan Africa, theory of planned
behaviour, social cognitive theory
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1. INTRODUCTION
The global COVID-19 pandemic and the economic crisis that followed have drastically affected
consumption habits. As a result, consumers participate in collaborative consumption and make
purchases in a group context (Li, Li, Shen, & Tang, 2022). Arguably, this is helping in product
accessibility with a concomitant improvement in quality of life. And the ubiquitous culture of the social
media is helping to advance this and is already having a wide spread impact (Zhou, Zhang, Yang &
Wang, 2017). Online group buying (OGB) has emerged as a cost-saving strategy consumer resort to,
while entrepreneurs are harnessing its potential as a business model and cashing-in on social media
traffic (Hsu, Qing, Wang, & Hsieh, 2018) to build market advantage. Also, an increasing number of
leading global online shops are adopting group buying as their core business model (Kauffman, Lai, &
Ho, 2010), while others such as Yahoo, Facebook, Taobao, and Alibaba are re-investing their existing
business model to include group buying (Li et al., 2022).
OGB refers to a type of business model that leverages on the aggregation of buyers to gain scale
and lower prices (Sun, Zhao, & Wang, 2021). The OGB model has become relatively popular,
especially in Asia, Europe, and America, and more profitable than other shopping models (Erdoğmus
& Çiçek, 2011). For instance, consumers spent more money on group-buying platforms than on online
auctions, and online group-buying is among the top three online shopping models (Chen, Yu, & Li,
2016). Undoubtedly, online group buying is on its growth trajectory with a global e-commerce sales
estimate of 6.5 trillion U.S. Dollars by 2023 (Winkler, 2020). In 2020, the global revenue for Groupon
– a leading group buying website - was around USD 1.4 billion and Pinduoduo (China) reported a total
revenue of 27.23 billion yuan ($4.29 billion) and a Gross merchandise value (GMV) of 2.4 billion yuan
as of March 2021 (Chevalier, 2022; Staff, 2022).
Following this development, researchers are intensifying their effort to understand OGB dynamics
and trends globally. Kauffman & Company pioneered research in the OGB domain and explored
consumer behaviour in online group-buying through analysis of transactional data from Mobshop and
other real-world online group-buying web sites (Kauffman & Wang, 2001; 2002; Kauffman et al.,
2010). Most of these studies are in Asia and Europe (Cao & Li, 2020; Che et al., 2015; Garcia et al.,
2020; Han & Kim, 2019, Li et al., 2022; Lim, 2020; Sharma & Klein, 2020; Sun et al., 2021; Suki &
Suki, 2017; Xia & Chae, 2021). Li et al. (2022) showed the positive effect of perceived risk on positive
eWoM communication and repurchase intention. Sun et al. (2021) report that the system quality,
information quality, service quality and interaction quality of GBW encourage consumers to have
positive economic and social satisfaction with the website. Also, Cao and Li (2020) showed that
consumers' group buying behaviour is affected by price, network externality, referral cost, social
network structure and group buying threshold. Xia and Chae (2021) found that satisfaction and
relationship commitment predict continuous intention and positive eWOM.
Despite these studies, the OGB debate is still inconclusive. An important gap in the literature is
study involving product-norm experience, and especially from the SSA context. The socio-economies
and cultural nuances of consumers from SSA warrants understanding their acceptance of the group
buying model. Developing countries, especially in SSA, operate in a different institutional and
marketing environment. Therefore, it is likely that the factors that explain OGB in another context may
differ here. For instance, the low internet penetration and internet self-efficacy in Africa compared to
other areas provides important perspectives for online group buying in this context. Arguably, OGB
promises to become the next frontier of growth in SSA, but at present the e-commerce landscape is
fairly recent. For instance, Nigeria, which represents the largest market in Africa and accounts for
about 40 per cent and over 20 percent of the West African and SSA population respectively, launched
its first OGB platform (Pricepally) in November 2019, almost two decades after Mobshop. The current
study represents one of the earliest in SSA and may also the first of its kind in Nigeria. Given these
nuances, understanding the predictors of OGB adoption in an SSA context represents a crucial
knowledge-gap that needs to be bridged.
Accordingly, this study aims to investigate the factors that predict group buying website adoption
intention in a typical SSA context, Nigeria. Specifically, the study investigates the effects of
convenience, internet and online shopping self-efficacy, online shopping experience, privacy concerns,
and internet access on GBW adoption intention. The paper adds to the literature by investigating
context specific factors such as product norm experience (i.e., online shopping experience), internet
and online shopping self-efficacy, and internet access to model OGB website adoption intention.
Following this brief introduction, the rest of this paper is structured as follows: review of the literature
and hypothesis development, methods, results, discussion and conclusion.
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
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2. REVIEW OF LITERATURE AND HYPOTHESIS DEVELOPMENT
2.1. Conceptual Clarifications - Online Group Buying
Online group buying is a model of e-commerce that aggregates the demands of consumers with
the same needs to obtain volume discounts or buy at wholesale prices. Online group buying (OGB) is
defined as when two or more people with common needs and increasing their bargaining power band
together to get a lower transaction price (Xia & Chae, 2021). In online group-buying, consumers who
share the same needs connect via the Internet to aggregate their demand and buy goods at wholesale
prices or negotiate with sellers who are willing to sell at a special discount (Cheng & Huang, 2013).
Thus, OGB as an online platform facilitates exchange between sellers and buyers and is premised on
the readiness of vendors to provide deep discounts as long as consumers will buy in volume through
the OGB and buyers achieve monetary savings by leveraging on group cohesion and their collective
bargaining power (J. Wang, Zhao, & Li, 2013; Shiau & Meiling, 2012), making it a win-win strategy in
online retailing. In OGB, value is created for consumers, sellers, and website operators. While
consumers obtain huge discounts, delivery services, and collaborate and share shopping experiences
with members of their community (Kim et al., 2014), sellers benefit from increased revenue and low
customer acquisition cost (Cao & Li, 2020). Also, website operators receive a commission or a service
charge from successful transactions (Lim, 2020).
Online group-buying has two principal classifications, namely, traditional dynamic-price group
buying and fixed-price group buying. In the dynamic price group-buying, a buyer negotiates with
sellers for volume discounts on the group's behalf, and as more buyers participate, the prices drop
(Chou, 2019; Kauffman & Wang, 2001). In other words, price changes dynamically according to the
numbers of placed orders" (Zhou, Xu, & Liao 2013, p. 79). Sharma and Klein (2016) observed that
most of the pioneer OGB such as Mercata.com and Moboshop were of the dynamic pricing model.
They failed due to the sale of products at their maturity stage and the limited assortment, uncertainties
about the deal conclusion and final price. Anand and Aron (2003) add that in the dynamic pricing
model, consumers usually hesitate to join a group before others until it reaches the final price, which
inherently causes delay and uncertainty. However, the dynamic pricing model can be better for sellers
if they face demand heterogeneity, encourage cooperation and information sharing among group-
buying participants, and are willing to become risk-takers.
Conversely, in fixed-price group-buying, an intermediary retail website operator negotiates with
sellers, who create deals for potential group buyers. Sellers quote a fixed product price, usually with a
substantial discount off the regular price based on a minimum number of buyers on the platform (Lim,
2020). Consumers can then browse the website for attractive deals, join a group or create one, and
invite other interested buyers via social messaging apps, e-mail, or social media. This activity, in turn,
creates a sense of shopping excitement and urgency to purchase the offer among online consumers
(Lim, 2020).
Furthermore, Cao and Li (2020) delineated between the traditional OGB and social e-commerce
group buying. They posit that in traditional group buying, such as Groupon, website operators negotiate
with sellers to obtain lower prices and substantial discounts as in the fixed pricing model, but that
consumer can buy individually or in a group and still enjoy the discount. Also, sellers can only place a
ceiling on orders but not a floor for the number of units for buyers. In contrast, for the social e-
commerce group-buying site in the likes of Pinduoduo, consumers have to use their social networks to
refer others and buy in a group to qualify for volume discounts, otherwise the consumers would buy at
the regular price.
2.2. Previous Studies
Online group buying has gained global acceptance and has attracted the interest of scholars. Some
authors have attempted to explain online group buying behaviour from diverse theoretical perspectives
in Europe, America and Asia (Lin, Tseng, & Shiraz. 2022; Sun et al., 2021; Xia and Chae, 2021;
Sharma & Klein 2020; Lim, 2020; Li & Yuan, 2018; Chiu, Chen, Du, and Hsu, 2018; Suki & Suki,
2017; Wang et al, 2016; Cheng & Huang, 2013). In recent research, Lin et al. (2022) showed how
buyers’ perceived value and the perceived risks of online group buying affect positive eWoM
communication and repurchase intention. Sun et al. (2021) examined how social commerce websites'
dimensions predict consumers’ economic and social satisfaction. Xia and Chae (2021) explored how
hedonic value and the utilitarian value of OGB influence eWOM continuous intention. Garcia et al.
(2020) showed that service quality, popularity and online brand image affect general satisfaction and
repurchase intention; Sharma and Klein (2020) explained how perceived value, trust, and susceptibility
to interpersonal influence predict consumer intention to participate in online group buying. Lim (2020)
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explored how the perceived benefits and perceived quality affect online group buying intentions
through perceived purchase equity in OGB.
Similarly, earlier studies by Li and Yuan (2018) elucidated on how customer experience
moderates the relationship between intermediary-related factors and vendor-related factors and
perceived risks. Chiu, Chen, Du, and Hsu (2018) found that OGB scheme value, hedonic value and
social value influence customer loyalty through affective commitment. Suki and Suki (2017) examined
how website trustworthiness, structural assurance and perceived reputation affect consumers' attitude
towards OGB. Wang et al (2016) investigated the stickiness intention of group buying websites; and
Lim and Ting (2014) showed that perceived usefulness, perceived ease of use and perceived risk affect
intention to use online group buying sites through attitudes. Cheng and Huang (2013) expanded on the
intention to participate in group buying from the potential and current customer perspectives.
Notwithstanding these studies' contribution to the online group buying literature, the discussion is still
ongoing and studies on the effect of product norm experience (ie., online shopping experience) on the
focal subject (OGB) are scarce. Accordingly, recent research has called for more research investigating
customer experience from emerging country contexts (Lin et al., 2022).
2.3. Theoretical Background and Hypothesis Development
Given the peculiarity of the sub-Saharan Africa e-commerce ecosystem, this study draws from the
theory of planned behaviour (TPB; Ajzen, 2001), social cognitive theory (Bandura, 1982) and the
literature on the concept of online shopping convenience, experience, and privacy concerns to test the
antecedents of OGB intention in a typical sub-Saharan African context. These theories are well suited
for understanding consumer behaviour and as such we adapted some of their constructs to explain
online group buying. The theory of planned behaviour postulates that intentions precede behaviour, and
subjective norm and perceived behavioural control determine intention. Subjective norm refers to the
influence of significant others on one’s behaviour; perceived behavioural control concerns an
individual's perception of the presence or absence of resources to perform a behaviour (Ajzen &
Madden, 1986). According to Cheng and Huang (2013), ability, resources, and opportunity determine
behaviour, and an individual perceiving the presence of these three factors will increase their
perception of control and this heightens their behavioural intention. In this study, internet access
represents a perception of resources and opportunity that can increase the perception of control and
behavioural intention. Thus, internet access and OGB intention were extracted from the TPB.
Self-efficacy is derived from the social cognitive theory and used as an appraisal of one’s ability
and influences the decision and effort needed to undertake certain behaviours (Pappas, Pateli,
Giannakos, & Chrissikopoulos, 2014). Due to the level of computer literacy among consumers in this
context, self-efficacy sheds light on how consumers perceive their ability to use the internet and to shop
online. Furthermore, following the increased time-scarcity and the related consumers’ quest for
convenience, especially in this context where the transportation network is inadequate, we also
investigate the convenience construct. Convenience is well established in the literature as an important
antecedent of online shopping (Duarte et al., 2018; Kollmann et al., 2012). Also, we extracted privacy
concerns from the e-commerce literature. Privacy concerns hinge on the social exchange theory,
power-responsibility equilibrium, and Behavioural decision theory (Martin & Murphy, 2016). The
growing incidence of cyber and identity theft, hacking, and phishing suggests that privacy concerns are
an important antecedent of OGB intentions. The literature on internet technology and online shopping
documents privacy concerns as a factor affecting information system use (Akhter, 2014; Lutz & Tamo-
Larrieux, 2020). Online shopping experience has been explored as a moderating or mediating variable
in the unified theory of technology acceptance and use of technology (UTUAT; Pappas et al. 2014;
Venkatesh, Morris, Davis, & Davis, 2003) or TAM (McKechnie et al., 2006). We explored online
shopping experience as an antecedent of OGB intention following the increased confidence in online
shopping. The online shopping experience is based on the experience-based norm construct (Cadotte,
Woodruff, & Jenkins, 1987). The product-norm experience posits that consumers’ experience in a
product category may cause consumers to form norms or expectations that establish what a focal brand
should be able to achieve (Cadotte et al., 1987). Importantly, there is strong evidence in the literature to
suggest that past experience using the internet for purposes other than the focal subject is a major
precursor for its use for a focal subject (Citrin et al., 2000; McKechnie et al., 2006).
The TPB and SCT are relevant theoretical lenses for this study because TPB provides the basis for
understanding future behaviour such as online group buying behaviour, and the SCT helps explain the
relevant factors that can motivate such behaviour. This study proposes that convenience, online
shopping experience, self-efficacy, privacy concerns, and internet access will determine OGB
intention.
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
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2.3.1. Convenience
As consumers get increasingly busy and time-starved, saving time and effort while shopping
becomes an essential criterion for decision making with regards to how and where to shop. Usually,
consumers expend time and effort in searching for products and brands, evaluating alternatives,
comparing prices and quality, and buying, and even making payments. This shopping engagement
constitutes the search and transaction costs capable of leading to customer defection or decision
postponement (Shih & Fang, 2005; Colgate et al., 1996). Therefore, consumers would favour
consumption processes that are convenient for their shopping needs. Convenience is the ability to
reduce consumers' non-monetary costs (i.e., time, energy, and effort) when purchasing or using goods
and services (Srivastava & Kaul, 2014). Convenience is also a consumer's desire to reduce the stress
associated with purchase decision making. The advent of the Internet, more specifically online
shopping, provided the options for time, energy, and effort saving, and the opportunity to choose retail
formats with the least demand and expenditure of time (Duarte et al., 2018). Kollmann et al. (2012)
suggest that a higher convenience orientation will lead to a higher propensity to seek information
through the online channel and will also increase the propensity to purchase online. The literature
documents convenience as an essential driver for online shopping (Izogo & Jayawardhena 2018; Lee et
al. 2016; Shih & Fang, 2005).
The convenience construct is a multidimensional construct consisting of access, search,
evaluation, transaction, and possession, and post-possession convenience (Duarte et al., 2018; Trung et
al., 2018). It could also be a uni-dimensional construct with three items measuring time and effort
saving (Srivastava & Kaul, 2014). We adopt the uni-dimensional construct and argue that consumers
would participate in group buying to save time and effort when buying goods and services. The group
decision making that precedes such purchases provides consumers with the opportunity to save time
searching, evaluating, and selecting goods and services to buy. First, is that a group member may hold
an expert opinion on the product category, thereby saving other members time and effort. Second,
when consumers collectively participate in the buying process, they enjoy the convenience of group
choice. In previous studies, convenience has been an essential motive for online group participation
(Xiao, 2015), and a significant influence on satisfaction (Srivastava & Kaul, 2014), repurchase and
eWOM intention (Duarte et al., 2018). Accordingly, we hypothesise as follows:
H1: Convenience has a positive effect on consumers’ willingness to adopt OGB.
2.3.2. Internet self- efficacy
According to Bandura's (1982) social cognitive theory, the perceived ability to organise and
execute a task is a function of an individuals' judgment of their skills rather than the task's actual skill
set. In other words, the perceived skill to use the Internet to perform a shopping task is driven by one's
ability to use a computer generally, and not so much his/her ability to perform an online transaction.
Self-efficacy enables people to determine what they can do and also helps them draw from hindsight
when performing a new task (Akhter, 2009; Jeng & Tseng, 2018). People with high self-efficacy would
feel confident using a novel and less sophisticated technology, and demonstrate higher positivity in
their usage (Jeng & Tseng, 2018). General internet self-efficacy refers to ''an individual's judgment of
efficacy across multiple internet application domains’’ (Hsu & Chiu, 2004). However, scholars have
argued for measures that are specific and distinct to particular domains (Peterson & Arnn, 2005;
Thakur, 2018). Accordingly, online shopping self-efficacy in this regard is defined as a consumer’s
self-assessment of his/her capabilities to shop online (Trung et al., 2018). Online shopping self-efficacy
is concerned with one’s ability to locate online stores, browse for products and brands, compare prices,
ascertain product and service quality, make payments online, initiate delivery returns, and invoke a
warranty.
Although the ability to use the Internet is a significant precursor of internet services adoption (Hsu
& Chiu, 2004; McKechnie et al., 2006; Thakur, 2018), consumers may experience task difficulty when
processing an online shopping transaction. Often, consumers high in internet self-efficacy may be able
to browse and shop for products online, but abandon their cart when they encounter a difficulty, in, for
instance, making an online payment. In this case, the consumer requires online shopping self-efficacy
to be able to navigate around such a difficulty. Thus, while people with high internet self-efficacy can
use the Internet, for instance, for social networking, researching, and sending e-mails, et cetera, they
require a different skill set to shop online. Therefore, consumers with high online shopping self-
efficacy may be favourably disposed to adopting an OGB. In particular, consumers' ability to initiate
and execute an online shopping task may affect their willingness to adopt OGB. Previous studies show
a mixed result between internet self-efficacy and online shopping behaviour (Hsu & Chiu, 2004;
Keisidou, Sarigiannidis, & Maditinos, 2011; Jeng & Tseng, 2018; Thakur, 2018). Therefore, we
hypothesise the following:
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H2a: Internet self-efficacy has a positive effect on consumers’ willingness to adopt OGB
H2b: Online shopping self-efficacy has a positive effect on consumers’ willingness to adopt OGB
2.3.3. Online Shopping Experience
The online shopping experience refers to a whole set of complex and subjective interactions
between consumers and an online shopping environment (Trevinal & Stenger, 2014). It is consumers’
direct or indirect experience with the process and outcome of buying goods and services through the
Internet. Direct experience is the customers' internal and subjective reaction to the online environment
in the course of a purchase, use, and post-purchase evaluation of the entire shopping process and its
outcome (Klaus, 2014). It is when a consumer has personally shopped online in the past. On the other
hand, indirect experience involves unplanned encounters with representatives of a company's products,
service, or brands. It takes the form of word-of-mouth recommendations or criticisms, advertising,
news reports and reviews, among others (Bhattacharya & Srivastava, 2018). The indirect experience
could also occur when customers benefit from the direct experiences of significant others or as a result
of consumers' outcome experience with online shopping. In other words, consumers may have a friend
or an agent process an online shopping transaction on their behalf, but take delivery of the goods or
services. Both direct and indirect shopping experiences can reduce consumers' perceived risk and
increase consumers' confidence in online shopping. However, if the experiences are negative, this will
affect consumers' accumulated knowledge, thus affecting their future decisions (Cheow, Yeo, Goh, &
Rezaei, 2017).
Online shopping experience takes two forms: experience with the focal service and product-norm
experience. The focal service experience refers to consumers' consumption experience with the service
under investigation (in this case, OGB); and the product-norm experience concerns customers' previous
experience with a range of services in the category such as online shopping (Wang, Harris & Patterson,
2012). Given that online group-buying is a different e-commerce model from the conventional online
shopping model (Shi & Liao, 2017), consumers' direct or indirect experience with online shopping
would influence their willingness to adopt OGB. Prior studies have shown that past product-norm
experience influences consumers' intention to adopt a focal service or an extended service in a similar
category. For example, Ojiaku and Aihie (2018) show that consumers' prior experience with mobile
voice services positively influenced consumers' choice of a mobile data services provider. Citrin et al.
(2000) also show that higher levels of prior internet usage for purposes other than shopping (e.g., for
communication, education, and entertainment) resulted in increased levels of the use of the Internet for
shopping. Accordingly, we hypothesise that consumers' online shopping experience will positively and
significantly influence their willingness to adopt an online group-buying platform.
H3: Online shopping experience has a positive effect on consumers’ willingness to adopt OGB.
2.3.4. Privacy Concerns
Privacy concerns are security issues relating to consumers' divulgence of personal and financial
information to online service providers. In this regard, it consists of information privacy and social
privacy. Information privacy refers to one's ability to control the collection and use of one's personally
identifiable information (Inman & Nikolova, 2017). On the one hand, social privacy concerns relate to
privacy threats that are caused by other users rather than service providers or third-party institutions
such as familiar users, hackers, and criminals (Lutz & Tamò-larrieux, 2020). In particular, consumers
provide their online identity such as e-mail addresses and their more personal financial details such as
debit card information (Martin & Murphy, 2016) when transacting online. More so, e-commerce firms
now use web technologies such as cookies, WebCrawlers, and subscription requests to collect
consumers’ data. Businesses usually collect ‘big data’ about users’ privacy and security information to
build their databases and tailor marketing programmes to end-users (Akhter, 2009). Hence, this gamut
of personal information disclosure heightens consumers' concerns about the violations of their privacy.
These concerns include vulnerability to fraud, identity theft, unwanted and obtrusive marketing
communications, opportunistic, or inappropriate use of personal data and institutional surveillance
(Martin & Murphy, 2016).
Despite these concerns, consumers' information disclosure provides the benefit of personalised
product offerings and recommendations, price discounts, free services, and more relevant marketing
communications and media content to consumers (Martin & Murphy, 2016). In which case, consumers
weigh the perceived cost of disclosing personal information to marketers against the benefits of
personalised offerings (Inman & Nikolova, 2017). When they anticipate a net benefit, consumers show
a willingness to disclose personal data (Inman & Nikolova, 2017). White (2004) refers to this private
information disclosure decision as the privacy calculus (White, 2004). Research shows a mismatch
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
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between consumers' reported privacy concerns and actual privacy disclosure behaviour. This situation,
referred to as the privacy paradox, suggests that though consumers report being very concerned about
their privacy, they still freely disclose their data (Aguirre et al. 2015). Issues relating to personal data
threats have been reported in previous studies to negatively relate to shopping intentions (Liao et al.,
2012; Ahkter, 2014), acceptance of technology (Hsu & Chiu, 2004), and technology use intention (Lutz
& Tamò-larrieux, 2020). Accordingly, we hypothesise as follows:
H4: Privacy concerns have a negative effect on consumers’ willingness to adopt OGB
2.3.5. Internet Access
For the e-commerce sector to develop successfully, internet infrastructure has to be widely
deployed and readily accessible to users both at home and in their offices. The availability of adequate
internet infrastructure, such as broadband, would make the Internet accessible and affordable.
Consumers' access to the Internet enhances their experience with technology and improves their self-
efficacy. The availability of the Internet from home improves its ease of use, and consumers with
regular internet access would appreciate its usefulness for shopping transactions (Mckechnie et al.,
2006). In Nigeria, only about 42% of the population has access to the Internet at home, and more than
128 million people access the Internet via mobile GSM (National Communication Commission; NCC,
2020). Thus, the mobile is the main port of internet connection for most people in sub-Saharan Africa.
However, Correa, Pavez, and Contreras (2018) argue that internet access via a smartphone is a form of
'under-connectedness' because it limits the activity and frequency of internet use. Moreover, the
problem of sparse mobile networks, fluctuating electricity supply, and poverty affects internet access
(Wyche & Olson, 2018).
Due to high bandwidth costs and poor internet access in Nigeria, as in a number of the SSA
countries, consumers rely on paid mobile Internet to access information and entertainment. Internet
access costs about 2% equivalent of monthly minimum wage (Stears Business, 2019), averaging $2.78
for 1GB per month (Gilbert, 2020). This cost profile is relatively expensive for the middle and working
class, and definitely beyond the reach of the poor and rural dwellers (Wyche & Olson, 2018). The high
cost of mobile data services may act as a disincentive for internet access and consequently inhibit
online shopping. In other words, when internet access is available and affordable, consumers are more
likely to shop online. Sohail (2014) reports that the lack of access to the Internet negatively affects
consumers’ intention to shop online among consumers in Saudi Arabia. Also, McKechnie et al. (2006)
find a significant effect for internet access on perceived ease-of-use, and perceived usefulness of online
financial services. Accordingly, we hypothesise as follows:
H5: Internet access has a positive effect on consumers’ willingness to adopt OGB
Figure 1. Conceptual framework
Source: Author's conceptualisation
H
1
H
2a
H
3
H
4
H
5
H
2a
Convenience
Online shopping
experience
Privacy
concerns
Internet access
Willingness to
adopt online
Group Buying
(OGB)
Self-efficacy
• Internet self-efficacy
• Online shopping self-
efficacy
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3. METHODOLOGY
3.1. Sample and Data Collection
Nigeria serves as a typical SSA context due to the country’s dominant role in the region. For
instance, about one out of every two West Africans is a Nigerian; also, about one out of every five of
the SSA population is a Nigerian. Given that OGB in Nigeria is still at his early stage, we represented
adoption intention by using consumers social media participation and familiarity with online
transactions. This is consistent with the methodological appropriateness vs. methodological orthodoxy
argument. In line with this supposition, Cook and Reichardt (1979) advocate for flexibility and
adaptability in the choice of the application of methods. Patton (1990) alluded to this in arguing for a
“paradigm of choices (where the argument was made to) reject methodological orthodoxy in favour of
methodological appropriateness as the primary criterion for judging methodological quality” (p. 38).
Accordingly, data were generated from social media members in Nigeria. The research instrument was
administered to the consumers via their WhatsApp accounts and to different WhatsApp groups. We
used WhatsApp contact lists of the researchers and that of two researcher assistants for the following
reasons: First, using social networking sites makes it easier to find respondents who qualify for the
study. Second, collecting data from real social media members increases the reliability and validity of
our research results. Third, WhatsApp is the most popular instant messaging app in Nigeria, used by
more than 45% of internet users (McCrocklin, 2018). Finally, using WhatsApp to collect data during
the coronavirus pandemic makes huge sense due to the lockdown and social distancing regimes that
limit physical contacts. 258 respondents completed the survey in two weeks. Table 1 summarizes the
demographic profile of the respondents. From table 1, 53% of the respondents are female, while 57%
are male; 60 % are married, and mostly between 20 and 50 years of age (92%). The respondents have a
good education, with 47% and 50% having a Bachelors or a postgraduate degree respectively. Most of
the respondents live in households consisting of 3 to 5 persons (46%), with a monthly household
income of less than 150, 000 (US$386; 67%) naira, and between N150,001 (US$386) to N500,000
(US$1,286; 29%). The demographic data suggest that the sample is a good representative of internet
users in Nigeria (McCrocklin, 2018).
Table 1. Respondents’ profile
Frequency
Per cent
Gender
122
47.3
136
52.7
Marital Status
100
39.1
154
60.2
2
.8
Age (in years)
116
45.0
122
47.3
20
7.8
Educational qualification
6
2.3
2
.8
122
47.3
128
49.6
Household Income (in Naira per month)
170
66.9
74
29.1
4
1.6
6
2.4
Household Size (in persons)
60
23.3
118
45.7
78
30.2
2
.8
258
100.0
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
21
3.2. Survey Instrument
The survey instrument contains two sections. Section A contains questions relating to the main
variables of the study. Section B contains the demographic information about the respondents.
Accordingly, Section A of the instrument elicited respondents’ opinions on the independent variable
items relating to internet self-efficacy - 4 items, online shopping self-efficacy - 3 items, online
shopping experience - 4 items, convenience - 3 items, internet access - 3 items, and privacy concerns -
3 items. The dependent variable consists of 3-items measuring intention to adopt OGB. All items use a
5-point Likert-scale ranging from 5 = strongly agree to 1 = strongly disagree. The measures were
sourced from the literature and adapted to fit the group-buying context. Self-efficacy was adapted form
Thakur (2018) and Akhter (2009), Online shopping experience adapted the framework from Ojiaku and
Aihie (2018); the privacy concerns scale uses the scale from Akhter (2009); convenience scales are
from Cheow et al. (2017), Internet access from GSM association (2018), and adoption intention from
(Kauffman et al., 2010). The items were face validated by senior academics in the Management and
Behavioural science discipline, while the Cronbach alpha checks the reliability of the instrument.
4. RESULTS
Principal component analysis with varimax rotation and reliability analysis was used as the
validity and reliability check for the measures. Factor loadings below 0.4 serve as the benchmark and
Cronbach alpha > 0.7. All 23 - items converge on 7-factors. Factor 1 consists of 3-items measuring
online shopping self-efficacy. Factor 2 consists of items measuring online shopping experience. Items
measuring adoption intention converged on factor 3. Factor 4 consists of items measuring privacy
concerns, while factor 5 consists of items measuring convenience. Also, 3-items measuring internet
self-efficacy converged on factor 6 and labelled accordingly. Finally, factor 7 consists of items
measuring internet access. The cumulative explained variance is 69.58%. Cronbach’s alpha for the
dimensions was reliable and above the 0.7 benchmark (Nunnally & Bainstein, 1994). Table 2 shows the
summary of the factor loading, Cronbach alpha and explained variance.
Table 2. Factor Loading, Reliability test, and Explained variance
Component
1
2
3
4
5
6
7
I find it very easy to get acquainted with several
online purchasing platforms
.829
I can confidently solve most problems that arise
during online purchases
.817
I am skilled in searching for products and services on
the Internet.
.494
I have a rich online shopping experience.
.704
I have personally shopped online in the past.
.700
I have shopped online through someone in the past.
.623
I am familiar with how to shop online.
.621
How likely are you to shop on a group buying
website in the future?
.934
How willing are you to shop on a group buying
website in the future?
.934
I'm interested in shopping from a group buying
website in the future.
.822
I am concerned about the security of financial
transactions on the Internet.
.847
I am uncomfortable giving my financial information
on the Internet.
.798
I’m concerned over the security of personal
information on the web
.785
It should be easy to find products on a group buying
website (OGB)
.725
Int. Journal of Business Science and Applied Management / Business-and-Management.org
22
I will be able to shop on a OGB anytime.
.607
I will be able to complete transactions without
difficulty on a OGB.
.575
I am confident that I can solve any problems using
the Internet.
.745
I have the necessary ability to fully use the Internet to
perform any internet-based task.
.735
I feel comfortable using the Internet for performing
any web-based task.
.577
I can afford the cost of using the Internet (e.g. data
top-up, app charges, monthly bills, travel to internet
cafés)
.758
I have access to a device that can use the Internet.
.745
I mostly access the Internet at home.
-.590
Cronbach alpha
.76
.85
.93
.75
.78
.75
.75
Explained variance
29.0
9.71
9.22
5.99
5.84
5.27
4.55
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 9 iterations.
4.1. Hypothesis Testing
Multiple regression analysis was run on SPSS version 16 to test the hypothesised relationships.
Overall, the model is a good fit (F
6, 257
= 18.7, p < 0.01), and explained 31% of the variation in the
dependent variables. The variance inflation factors were all above 1, suggesting that the model is free
from the multicollinearity problem. The regression results show a significant effect for convenience on
OGB adoption intention (β = .40, p < .01) therefore supporting H1. Similarly, online shopping
experience (β = .20, p < .05) and internet access (β = .20, p < .05) were found to significantly predict
OGB adoption intention, supporting H4 and H5 respectively. However, contrary to our expectation, we
did not find support for H2a and H2b as the regression result shows a non-significant effect for internet
self-efficacy (β = -.03, p = .60) and online shopping self-efficacy (β = -.06, p = .44) on OGB adoption
intention. Finally, we also find a non-significant effect for privacy concern on OGB adoption intention
(β = .02, p =.78). The regression weight shows that convenience and internet access have the strongest
predictive power on adoption intention, respectively. Table 3 contains a summary of the results.
Table 3. Regression Results
Model
t
Sig.
Collinearity
Statistics
β
Tolerance
VIF
Internet self-efficacy
-.031
-.531
.596
.789
1.268
Online shopping experience
.195
2.843
.005**
.584
1.713
Convenience
.397
6.038
.000**
.637
1.571
Online shopping self-efficacy
-.057
-.774
.439
.511
1.955
Internet access
.199
3.608
.000**
.905
1.105
Privacy concerns
.015
.282
.778
.981
1.019
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
23
Figure 2. Research model
Source: Author's conceptualization
** p < .05
ns = not significant
5. DISCUSSION
Given the increased confidence in online retailing and the emergence of OGB in Nigeria, this
study sought to understand consumers’ intentions to adopt OGB. We tested the effects of convenience,
Internet and online shopping self-efficacy, online shopping experience, privacy concerns, and internet
access on OGB adoption intention. The findings suggest that shopping experience is an essential
predictor of OGB adoption intention. Since online group-buying is still in its early stages and
unpopular in the context of this study, consumers with prior experience shopping with traditional
online stores demonstrated a willingness to adopt OGB. This finding confirms the importance of
experience regarding customers' expectations from retailers and corroborates the findings of He (2018)
and Pappas et al. (2014). This finding further confirms that consumers' product-norm experience
predicts focal service use intention.
Furthermore, as with previous studies (see for example: Citrin et al. 2000; Mckechnie et al. 2000;
Ojiaku & Aihie, 2018), consumers with experience of using the internet technology for other purposes
rather than group buying will strongly determine its use for the group buying. In other words, the use of
the Internet for online shopping will strongly determine its use for OGB. Although the group-buying
mechanism is quite different from the traditional online retailing, the model is still an online
transaction, and consumers who have shopped online directly or indirectly from a conventional online
retailer in the past would be willing to adopt OGB. When consumers have positive online shopping
experiences, especially when it matches their expectations, it reduces their anxiety, risk perception, and
uncertainty, and increases their confidence in online shopping.
The findings also show that convenience influences OGB adoption intention. The significant
effect of convenience corroborates previous findings by Duarte et al. (2018), Cheow et al. (2017), and
Srivastava and Kaul (2014), who found a significant influence of convenience on behavioural outcomes
and customer experience, and this also confirms its importance for group buying participation (Xiao,
2015; Lee et al. 2016). The ease of shopping from anywhere at any time and without difficulty is an
essential driver for OGB adoption. Moreover, it is the most dominant predictor of behavioural
intention, confirming Izogo and Jayawardhena (2018), who report convenience as an essential driver of
the online shopping experience. Furthermore, the time and effort savings that online transactions
provide is an essential attraction for consumers, mainly as consumers are more time-starved and busy
than before. Consumers can enjoy the convenience of group choice by participating in group buying
when they join a group buying activity usually by a group leader who is more knowledgeable and
experienced with a product or when they collaboratively evaluate and select a product to buy. In both
cases, there is an opportunity to save time and effort when shopping on a group buying website. The
β= .06, ns
Convenience
Self-efficacy
Online shopping
experience
Privacy
concerns
Internet access
Intention to
Adopt Online
Group Buying
(OGB)
• Internet self-efficacy
Online shopping self-effic
β= .40**
β= .20**
β= .02, ns
β= .20**
β= .03, ns
Int. Journal of Business Science and Applied Management / Business-and-Management.org
24
possibility of receiving goods at home or other convenient locations, making payment through the
Internet or third-party payment reinforce consumers' convenience, which influences their intention to
adopt OGB.
However, while consumers' online shopping experience and convenience predict adoption
intention, their Internet and online shopping self-efficacy are not significant predictors of OGB
adoption intention. We had expected the Internet and online shopping self-efficacy to influence
adoption intention, but our findings showed otherwise. The non-significant effects of the Internet and
online shopping self-efficacy corroborate Keisidou et al. (2011) Jeng and Tseng (2018) but contradict
Hsu and Chiu (2004). A plausible explanation for the non-significant effect of self-efficacy may
include any of these: first, since self-efficacy attempts to measure one's belief, perceptions, or feelings
of efficacy in using the Internet or shopping online, our sample consists of social media users who by
extension are internet users and may also be online shoppers. In other words, our sample consists of
consumers that can execute Internet or online shopping related tasks, rather than those with the
'perception of ability' (Jeng & Tseng, 2018) to do so. For instance, about 70% of our respondents agree
that they have competencies in shopping online or using the Internet to search for products, browsing
several online shopping platforms, and solving or performing any web-related task. Second, it is
plausible that self-efficacy may indirectly influence online group-buying intention as evidenced in the
study of Jeng and Tseng (2018), which reports that self-efficacy indirectly influences group-buying
intention through perceived ease of use.
Furthermore, we expected privacy concerns, which relate to consumers' safety and security
concerns with online transactions, to affect OGB adoption intention negatively, especially in this
context where the incidence of cyber-fraud, such as identity and financial fraud, is usually in the public
domain. Surprisingly, we did not find a significant effect for privacy concerns on the intention to adopt
OGB, and more surprising is the positive co-efficient effect. Our finding is consistent with Fagih
(2016), who found both online privacy and security concerns for non-adopters' use intention to be non-
significant. However, our findings run counter to other previous findings such as Akter (2008), which
found privacy concerns on the frequency of online transactions to be negative, and Lutz and Tamò-
larrieux, (2020) who report a moderate privacy concern about social robots among respondents. The
non-significant effect for privacy concerns could be attributable to consumers' increased confidence in
online shopping and the perception of the increased security features of e-commerce. With stringent
privacy laws in place, consumers believe that online stores have to make the effort to improve the
security features on their website to safeguard customers' data online. Also, e-commerce businesses
communicate and signal the extra security features introduced on their websites as well. Another
plausible rationale is that since consumers evaluate their privacy concerns based on the net benefit from
the perception of loss from disclosing personal and financial details and the gain from the personalised
offering, it is plausible that, over time, consumers have benefitted from such disclosure. This
corroborates Martin and Murphy (2016) and Inman and Nikolova's (2017) assertions that when
consumers disclose privacy-related information, they often subscribe for additional benefits such as
more tailored offerings and recommendations, discounts and more relevant marketing communications
and media content. This net gain might explain the positive co-efficient of privacy concerns.
Given the prospects of internet penetration in the context of this study, the availability and access
to the Internet is the gateway for online transactions. As expected, we find a significant effect of
internet access on the intention to adopt OGB, thus corroborating Mckechnie et al. (2016), which finds
a significant effect for internet access on perceived enjoyment and perceived ease of use of online
financial service. The availability and access to the Internet is a facilitating condition for the intention
to adopt OGB. When consumers have a device to connect to the Internet, and can afford to pay for an
internet subscription, it becomes practical and easy to conduct online transactions. Access to the
Internet increases the time consumers spend online and improves their efficacy to use the Internet to
perform a web-based task. Also, with the recent upsurge and availability of affordable smartphones,
many consumers can now access the Internet, and consequently, e-commerce businesses are
strategically designing mobile compatible websites to improve customer experience. The findings from
this study, therefore, suggest that convenience, shopping experience, and internet access will predict
customers’ intention to adopt OGB.
6. CONCLUSION
The As more consumers seek better ways to shop and save money, especially in the face of bleak
economic realities, the group buying model promises to become the ‘Holy Grail’ for consumers to
survive difficult times. While businesses in other climes have been quick to respond to these new
realities, the OGB model is still in its infancy in Nigeria as in most SSA contexts. Therefore, this
present study represents an empirical contribution from the under-reported sub-Saharan African context
Ojiagu Nkechi C, Ojiaku Obinna Christian and Anayo D Nkamnebe
25
to the emerging literature on OGB. Specifically, this study attempts to understand the intention to adopt
OGB among a cross-section of social media users from an emerging economy in the sub-Saharan
African context. Based on the findings from this study, we conclude that convenience, prior shopping
experience, and access to the Internet predict the intention to adopt OGB. Also, neither consumers'
concerns about privacy and security issues nor their perceived ability to use the Internet or shop online
may affect OGB adoption intention. Customers' perceived convenience and online shopping experience
are the strongest predictors of OGB adoption intention.
The study has its own limitations. First, the study uses a social media community to proxy OGB;
while this makes huge methodological sense, it is recommended that future studies use actual online
group buyers to test for potential differences between intention and actual behaviour. Second, we used
a regression analysis to test for direct relationships. Further studies should extend this by examining
systems of relationships using structural equation modelling or path analysis and test indirect
relationships in the model. Also, testing for potential mediating effects could deepen the robustness of
future methodology.
7. IMPLICATIONS
7.1 Practical Implications
The findings hold some implications for theory and practice. First, convenience shows a relatively
more substantial influence on OGB adoption intention than other constructs in the research model,
implying that OGB marketers should emphasise the convenience of OGB transactions in their
marketing communications to customers. Marketers will have to communicate the ease of finding
products, offerings and deals, and the ability to shop on a group buying website without difficulty from
anywhere and at any time. Second, the finding on the positive effect of online shopping experience
implies that OGB marketers can leverage on it to gain traction. Marketers can and micro-targeting prior
online shoppers with offerings and deals following their expressed intentions to adopt OGB.
Consumers that are familiar with online shopping and that have shopped online directly or indirectly in
the past should be the focus of marketing programs and campaigns for OGB marketers.
Finally, it is important that firms target consumers with adequate internet access both at home and
in their offices, or devise strategies to reach those without internet access. While internet access is an
obvious requirement for e-commerce businesses and online shoppers alike, it would be inimical for
businesses to assume widespread availability and access to the Internet. Therefore, OGB may focus on
customer segments in geo-locations with internet access and who use the Internet frequently at home.
However, since a group buying transaction is a coordinated arrangement between a group lead buyer
and other co-buyers, OGB may provide incentives and recruit lead-buyers as ‘sales agents’ to mediate
for and provide internet access for customers without internet access. The group leaders may register
and manage sub-accounts for these groups of customers while marketers establish and communicate
with these groups via SMS using the communication platform as a service (CpaaS) plug-in on their
website.
7.2 Theoretical Implications
The present study makes several contributions to theory. First, technologies advance by
incrementally adding to how consumers deploy them to solve problems. For instance, we know that
instant messaging technology advanced from technology that supports short message services.
Likewise, online group buying extends from online retailing and social media. This underscores the
importance of specific self-efficacy and product-norm experience as important predictors of online
shopping adoption. The theoretical implication of our model is that it provides an empirical
understanding of how this domain specific construct explains the use of technology and extends
existing models. Also, our model shows the criticality of convenience in technology adoption.
Convenience is scarcely reported in the technology adoption literature due to its limited relevance in
the context. However, in online group buying, consumers regard convenience as a strong predictor of
behaviour. Our model therefore shows the importance of accounting for convenience in explaining the
use of internet-enabled consumer technologies.
Finally, the present study integrates concepts from different adoption theories to model online
group buying. Extant literature predicted OGB using equity theory, the technology acceptance model,
and transaction cost model. We use existential constructs that are specific to our domain to predict
OGB among consumers in SSA. The implication of this theory is that factors from diverse models can
be integrated to explain behaviour. For instance, we used internet access, which, more specifically,
addresses a facilitating condition that is critical to online shopping but is rarely reported as a facilitating
condition in UTAUT.
Int. Journal of Business Science and Applied Management / Business-and-Management.org
26
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