The Digital Divide: Current and Future Research Directions - MISRC ...

creating a narrow further economically advantaged online elite. Mossberger et al. [2003]
suggest four different types of divides related to ICT: an information divide due to certain
people’s inability to gain access to online information due to demographic characteristics;
a skills divide related to computer-specific capabilities; an economic opportunity divide
related to the inability to receive training, education or employment opportunities; and a
democratic divide related to certain people’s inability to participate in e-government.
In addition to these four, we propose that there is an emerging e-commerce divide
due to certain people’s inability to make use of more advanced e-commerce online
functionalities and services. This differs from the other four in the sense that the e-
commerce divide is based on the online consumer’s ability to take advantage of powerful
e-commerce functionalities.
In the same way that diffusion of innovations theory has been applied to ICT
adoption, recent theory building work has been underway to understand the adoption of
e-commerce as an innovation [Gefen and Straub, 2000; Gefen et al., 2003; Koufaris,
2002]. While much of the work has focused on the event of purchasing products online,
it is recognized that engaging in online commerce at the individual level is a complex
behavioral task. For example, Choudhury et al. [2001] argue that online consumers
proceed through two different stages in online shopping: gathering product information
and subsequently making the purchase. Individual inequality of usage can occur with
both tasks in terms of skills employed, barriers to overcome, type of technology
employed, feelings of ease with specific online vendors, and motivation to engage in the
activity. (See Pavlou and Fygenson [2006] for recent work in this area.)
From a different theoretical perspective, Akhter [2003] develops and tests a series
of sociological hypotheses regarding the correlation of various demographic
characteristics, such as gender, age, education, and income, with intention to purchase
goods over the Internet. Using a survey questionnaire of 1,794 individuals, the results
show that these variables are significant in influencing a person’s likelihood of using the
Internet for online commerce. This is one of the first studies that look specifically at
demographics and individual e-commerce activities.
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