Abstract
Today, the majority of the world's population owns mobile devices that allow individuals to access the Internet at any time and at any place. However, owning an Internet-enabling mobile device does not necessarily mean that an individual uses the mobile Internet. This article reviews the state of the art on the theory-guided drivers and barriers of consumer acceptance of the mobile Internet. The author describes models that help explain and predict consumer acceptance, including the Technology Acceptance Model, Motivational models, Perceived Value models, The Unified Theory of Acceptance and Use of Technology, and Diffusion of Innovation theories. The article also presents empirical research that applies and extends these models in the context of mobile Internet usage, and summarizes the most important findings of these empirical studies. Finally, this article also discusses challenges in acceptance research, as well as implications for future research.
TopOverview
Dr. Davis (Davis, 1989) at University of Arkansas is among the earliest researchers in acceptance of technology. Dr. Venkatesh (Venkatesh, Morris, Davis, & Davis, 2003) at University of Arkansas contributed to theory testing in the field and has proposed recent acceptance models that have been applied to consumer contexts of mobile Internet usage (Venkatesh, Tong, & Xu, 2012). Dr. Kleijnen (Kleijnen, de Ruyter, & Wetzels, 2007) at VU University Amsterdam, Dr. Pura (born Pihlström) (Pura, 2005) at Hanken School of Economics, as well as Dr. Nysveen, Dr. Pedersen, and Dr. Thorbjørnsen (Nysveen, Pedersen, & Thorbjørnsen, 2005) at NHH Norwegian School of Economics are among the leading experts in the area of mobile Internet consumer acceptance. In their research on consumer acceptance, they take into account the peculiarities of mobile Internet services (as described in the next paragraphs).
Most empirical research into the acceptance of mobile Internet services is based on existing theories and models of technology acceptance, such as the Technology Acceptance Model (Davis, 1989). User acceptance of PCs in work place settings was central to the early research fields in the 1980’s and 90’s: “„Understanding why people accept or reject computers has proven to be one of the most challenging issues in IS [information systems; the author] research” (Davis, Bagozzi, & Warshaw, 1989, p. 987).
Key Terms in this Chapter
Mobile commerce: The use of the mobile Internet to make commercial transactions.
Consumer Decision-Making: The process by which individuals make product and service purchase choices, use choices, and end-of-use choices. Emotional and cognitive factors as well as unconscious and conscious factors (evoked internally in individuals or externally by context) guide the choices of whether individuals adopt, use, or end the use of certain products or services.
Adoption: The decision of an individual to acquire a certain object (here, mobile phone) that is new to her or him. The opposite of adoption is rejection, that is, the decision to refrain from acquiring an object that is new to an individual.
Mobile Internet Services: Internet-based services that can be used on (or delivered to) handheld devices via mobile network technology. This covers a range of services, such as information services, entertainment services, and financial services.
Acceptance: The positive perception of the decision-making process with respect to a certain object that is new to an individual, potentially leading to adoption and usage. Acceptance includes both the attitudinal component (as part of consumer decision-making) and the behavioral intention component (as part of adoption and usage). The opposite of acceptance is resistance, that is, the negative perception of the decision-making process, leading to attitudinal and behavioral intention barriers.
Usage: In the context of mobile phone behavior, individuals do not only adopt a device, but also use the device (e.g., to make calls, to access the Internet, to use location-based services). Usage behavior differs with respect to intensity and variety and depends on contextual factors (e.g., time pressure, mobility needs).
Ubiquity: In the context of mobile phone behavior, individuals can access mobile network technology at any time and at any place using handheld devices (i.e., they are omnipresent).