2.2.5 Conclusion
It is acknowledged that TAM and TPB are widely applied to explain consumer behaviour.
However, the inherent weaknesses of both theories should be noted, that is, neither TAM nor
TPB have been found to provide consistently superior explanations or predictions of
consumers’ online shopping behaviour (Chen
et al.
2007a). The extant research is also
compounded by a lack of academic inquiry into a complete list of antecedents that influence
consumers’ online shopping intentions and purchase behaviour. Given that online shopping is
a complicated decision process and the online environment is complex, simply focusing on
TAM or TPB to identify the antecedents and predict the behaviour-related consequences may
have some limitations.
Firstly, consumers make a shopping decision based on their family needs, budget limitations,
and other constraints impinging on them (Bakshi and Gupta 2012). Accordingly, they are
likely to maximize the shopping benefits and minimize the costs (i.e., time and effort
expended during the shopping process) (Chiu
et al.
2014). In forming value perceptions,
consumers balance costs against benefits (Kleijnen
et al.
2007). In relation to online shopping,
many costs and benefits have been associated with online buying, such as, easy access, time
convenience, privacy and security issues, product quality concerns, and so forth. Consumers
feel particularly vulnerable to risks in the online environment because the allocation of
responsibility for a failure or loss (i.e., who is to blame) may not always be clear in this
technology-mediated environment (Bahli and Benslimane 2004). Consumers are very
sensitive with regard to services that involve monetary transactions, in which case they worry
about both money and information loss (Huang
et al.
2014). Research reveals that the
willingness to adopt online shopping depends primarily on consumers’ risk perceptions as
they increase the potential costs perceived by consumers (D'Alessandro
et al.
2012). Thus, it
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is of paramount importance to include the costs-related factors and examine their effects on
online decision making.
Secondly, online shopping behaviour is a social influence process and is affected by social
norms, mass media, word-of-mouth and third party organizations (Çelik 2011, Lee
et al.
2011c). An extensive range of research in social psychology concerns the concept of social
influence (e.g., peers, family members, superiors, colleagues) and it is considered as an
independent predictor of behavioural intention (Hong
et al.
2008). The consumer behaviour
literature also recognizes the influence of mass media (e.g., newspapers, magazines,
television) as an important factor that affects consumer purchasing decisions (Campbell and
Keller 2003, Kim and Han 2009). However, prior TAM and TPB research with its primary
focus on technology adoption among workers within a specific organization, does not
examine such social and media influence on consumers’ adoption decisions. Thus, only
focusing on constructs in TAM and TPB may limit the understanding of individual
consumer’s online shopping behaviour.
Thirdly, online shopping can be viewed as an innovation and its adoption is impacted by
consumer characteristics (e.g., involvement, innovativeness, risk-bearing propensity and
Internet expertise) as well as technology characteristics (e.g., system quality and online store
design) (Zhu
et al.
2012b). Therefore, the use of the TAM and TPB, as it is originally
conceived, is not comprehensive and convincing to fully explain online consumer behaviour.
No single theory is capable of capturing the complexities of online shopping behaviour. An
integrated theory is needed in order to provide a better explanation for online shopping
behaviour.
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