et al.
1999, Jarvenpaa
et al.
2000, Limayem
et al.
2000,
Vijayasarathy and Jones 2000, Kimery and McCord 2002, Van der Heijden
et al.
2003)
revealed that risk perception has a significantly negative influence on the attitude towards
online shopping. As attitude towards online shopping has been regarded as the precursor of
shopping intention, risk perception was further confirmed to indirectly affect intention or
usage through attitude (Lee 2009b).
For the perception of specific risk, studies by Bhatnagar et al. (2000b), Dabholkar and Sheng
(2012), Hong and Cha (2013) and Lee (2009a) summarized that risks associated with credit
card problems (i.e., financial risk) could negatively affect online shopping intention.
Researchers (Liang and Huang 1998, Jarvenpaa
et al.
1999, Bhatnagar
et al.
2000b,
Featherman and Pavlou 2003, Joines
et al.
2003, Pavlou 2003, Kolsaker
et al.
2004, Park
et
al.
2004) provided empirical evidence that supports the negative relationship between product
quality risk and online shopping adoption, suggesting that online purchase intention is
negatively related to product quality risk. In addition, a large number of studies showed the
negative effects of privacy risk (Ranganathan and Ganapathy 2002, Van Slyke
et al.
2006,
Wirtz
et al.
2007, Lian and Lin 2008, Lee 2009a) and security risk (Liao and Cheung 2001,
Burroughs and Sabherwal 2002, Ranganathan and Ganapathy 2002, Sin and Tse 2002, Lian
and Lin 2008, Lee 2009a, Hong and Cha 2013) on online purchase intention.
For example, Lian and Lin (2008) reported that personal privacy concerns and perceived web
security concerns play a negative role in predicting consumer acceptance of online shopping,
but their influence varies according to product types. Lee (2009a) tested such effect in the
56
online banking context and confirmed the negative relationship. In contrast to previous
findings, the study conducted by Miyazaki and Fernandez (2001) demonstrated that privacy
infringement, system security, and fraudulent behaviour of the merchants do not have
significant influence on online purchase intention or actual purchase behaviour. The
inconsistent results could be attributable to a narrow definition of the risk and, therefore,
reserachers (Jarvenpaa
et al.
2000, Miyazaki and Fernandez 2001) called for specific
measures of individual risk dimensions.
Given the fact that the distribution and impersonal nature of e-commerce leads to greater
information asymmetry and higher uncertainties than the traditional shopping environment,
previous studies have emphasized the important role of perceived uncertainty as a chief
barrier to online adoption behaviour and examined the influence of uncertainty in different
online environments. Pavlou et al. (2007) calimed that uncertainty has a greater impact on
people’s purchasing intention in online bookstores than in online pharmacies. Ruiz-Mafé et al.
(2009) indicated that poor performance and loss of privacy are perceived as the predominant
risk dimensions in purchasing airline tickets online. As perceived uncertainty is an
expectation of an ambiguous potential loss, it was also shown to influence attitudes toward a
behaviour (Quintal
et al.
2010). As an example, the higher the perceived uncertainty about
the potential for financial loss associated with a purchase, the more negative attitudes will be
toward the purchase. Higher levels of ambiguity about the outcomes of a decision are likely
to lead to less favourable attitudes toward the online purchase decision (Quintal
et al.
2010).
Obviously, if buyers are worried about the outcome of online transactions due to numerous
uncertainties, risks or possible loss, they are less likely to participate in online exchange
relationships (Yeh
et al.
2012b, Kim and Lennon 2013).
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