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et al.
2003) or no relationship (Li
et al.
1999, Rohm and Swaminathan 2004, Hernandez
et al.
2011). Such a discrepancy in research findings might be caused by different criteria for
defining age groups in different studies. For example, the above studies used a 10-year span
(Li
et al.
1999, Stafford
et al.
2004), 15-year span (Donthu and Garcia 1999), 20-year span
(Rohm and Swaminathan 2004), respectively. Broader ranges may lessen the effect of age.
Therefore, a standard age categorization scheme should be adopted in future studies to make
cross-study comparisons feasible.
As a variable that may encourage or prevent the adoption of online shopping, income is
another characteristic that has attracted considerable research attention in the field of
technology acceptance (Allard
et al.
2009, Shin 2009). Several studies have included it as an
explanatory variable of shopping behaviour, yet the results concerning its significance are
contradictory (Miyazaki and Fernandez 2001, Raijas and Tuunainen 2001, Lu
et al.
2003, Al-
Somali
et al.
2009). Some studies showed that online shoppers tend to earn more money than
traditional store shoppers (Donthu and Garcia 1999, Korgaonkar and Wolin 1999, Li
et al.
1999, Bagchi and Mahmood 2004, Mahmood
et al.
2004, Susskind 2004), given the fact that
the most popular items purchased online, including books, CDs, holiday and leisure travel,
PC hardware, and software, are all “normal goods”—those for which demand increases as
income increases. Higher income causes internet users to perceive lower implicit risks in
undertaking online purchases and thereby affects their demand for internet products and
34
services. In contrast, other studies did not find a significant effect of income level on online
purchase intention (Raijas and Tuunainen 2001, Sin and Tse 2002, Hernandez
et al.
2011).
A large number of studies have been conducted to investigate the impact of education level
on online shopping behaviour and suggested that online shoppers are not necessarily more
educated. Whereas some studies identified a positive relationship between education and the
time and money consumers spent online (Li
et al.
1999, Liao and Cheung 2001, Burroughs
and Sabherwal 2002, Sin and Tse 2002, Susskind 2004), others did not find any significant
impact (Bellman
et al.
1999, Donthu and Garcia 1999, Bagchi and Mahmood 2004,
Mahmood
et al.
2004). This may be explained by the fact that online shopping is a relatively
easy task, which does not require a higher education level.
Scholars have paid attention to the impacts of differing cultures on online consumer
behaviour. The literature suggests that the difference in the culture between western and
eastern countries can lead to varied online shopping behaviour (O'Keefe
et al.
2000, Liu and
McClure 2001, Chau
et al.
2002, Huang 2003, Park and Jun 2003, Park
et al.
2004, Qureshi
et al.
2009, San Martín
et al.
2009, Constantinides
et al.
2010, San Martín and Camarero
2012). In an individualistic culture, for example U.S.A and Australia, where the ties between
individuals are loose, people tend to use the Internet mainly for personal purposes such as e-
commerce and information searching (O'Keefe
et al.
2000, Chau
et al.
2002, Park and Jun
2003, Smith
et al.
2013). In a collectivistic culture, for example China, Singapore, and
Mexico, people are integrated into strong and cohesive groups (Minkov and Hofstede 2011).
They use the Internet mainly for social communication and hobbies, such as
sending/receiving e-mails, accessing/ downloading software, and conducting work-related
research (Wee and Ramachandra 2000). In addition, a society with more masculinity, for
35
example Britain, tends to have a greater gender divide and predominantly male shoppers than
a less masculine society, for example Taiwan (Shiu and Dawson 2002). Stafford et al. (2004)
compared the online shopping behaviour of consumers in the U.S.A, Turkey, and Finland.
The masculinity scores, according to Hofstede’s (1980, 2010) index, were high for the U.S.A,
low for Turkey, and Finland had the lowest of the three countries. The results showed that
consumers from less masculine societies were less involved in online shopping than those
from more masculine societies, which was consistent with the findings of gender pattern in
online shopping (Zayer and Coleman 2012).
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