21
relationships (Chau and Hu 2001b,
Townsend
et al.
2001). Researchers suggested belief
factors such as PU, enjoyment, trust, and performance may influence one's attitude toward
using a technology more strongly than by PEOU (Van der Heijden and Verhagen 2004).
While some researchers favour TAM because it is a parsimonious model (Tong 2010) (Porter
and Donthu 2006), others argue that this parsimony represents a major drawback (Venkatesh
et al.
2012). According to social psychology theories, an individual’s behaviour is not just
driven by evaluative beliefs and attitudes, but also by subjective norms,
perceived
behavioural control, and habits (Burton-Jones and Hubona 2006). Thus, a significant body of
studies suggest improving or extending TAM constructs (Wixom and Todd 2005, Porter and
Donthu 2006, Srite and Karahanna 2006, Cyr
et al.
2007, Aggelidis and Chatzoglou 2009,
Chiu
et al.
2009b, Kim and Garrison 2009, Li and Huang 2009, Chung
et al.
2010, Pan and
Jordan-Marsh 2010, Belanche
et al.
2012a, Chyou
et al.
2012, Lee
et al.
2012a, Teh and
Ahmed 2012, Cheema
et al.
2013, Hiramatsu and Nose 2013, Park
et al.
2014)
.
One
of the extensions of TAM, TAM2, was proposed by Venkatesh and Davis (2000). In
TAM2, social influence (subjective norm, voluntariness, and image), cognitive instrumental
processes (job relevance, output quality, and result demonstrability) and experience were
included and found to have a significant influence on PU. The new model was tested in both
voluntary and mandatory settings. The results strongly supported TAM2 and explained 60
percent of user adoption using the update version of TAM (Venkatesh and Davis 2000).
Hsu
and Lu (2004) and
Park (2009)
provided similar empirical evidence that supported the effect
of social influence on user’s belief of a new technology.
22
In
a web-based environment, many researchers found that there were a broader range of
additional factors that were needed to investigate users’ adoption behaviour. For example,
Venkatesh (2000) suggested that TAM could be further enhanced by adding control, intrinsic
motivation, and emotion as variables within the PEOU dimension. Cai and Xu (2007)
extended the original TAM to encompass perceived enjoyment as an additional motivational
determinant of acceptance. Gefen and Straub (2003), Kim (2012), Pavlou (2003) and Shih
(2004) integrated previous work by incorporating trust into TAM and
found positive effect of
trust on behavioural intention. Ha and Stoel (2009) integrated enjoyment and trust into TAM
to understand consumer acceptance of e-shopping.
In addition, social influence was incorporated into TAM and further showed a significant
effect on consumer’s intention toward technologies according to Hsu and Lu (2004). Chen et
at. (2002) added compatibility to PU and PEOU in predicting an online consumer’s attitude.
The model showed that compatibility was positively related to a consumer’s attitude about
using technology along with PU and PEOU. Li and Huang (2009), Van der Heijden et al.
(2003) and Pavlou (2003) augmented the TAM with the perceived risk in e-stores. Chen and
Tan (2004) further expanded TAM by adding a link from perceived service
quality to attitude
toward using. Porter and Donthu (2006), in their work to study the attitude towards Internet
usage used access barrier along with PU and PEOU as the additional construct based on the
TAM.
In summary, a large number of empirical studies have applied TAM to examine online
consumer behaviour. PU and PEOU together can routinely explain up to 40 per cent of usage
intentions and 30 per cent of systems usage (Meister and Compeau 2002). However, the
literature notes TAM's parsimony as a key limitation (Venkatesh 2000, Vijayasarathy 2004).
23
TAM has been criticized for only explaining consumer behaviour on the Internet based on a
technological point of view. Since the online environment is quite complex and full of
uncertainties, there
are many potential factors, such as concerns about security and privacy,
product quality, and e-service quality, site design, product return, consumers’ Internet skills,
etc. that can affect online consumer purchase and post-purchase decision. Only focusing on
two dimensions (PU and PEOU) in the TAM seems too simple
in such a complex online
environment. Moreover, the variables in TAM are better suited to decisions involving few
technology usage choices than to situations involving users' voluntary choices (e.g., online
shopping) (Vijayasarathy 2004). Therefore, the original TAM variables may not adequately
capture key beliefs influencing consumers' attitudes toward online shopping.
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