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Mobile Commerce Applications and Adoption

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The potential advantages of mobile commerce applications have been discussed extensively in the recent literature, with many industries offering mobile services. Examples from the financial sector include instant funds transfer (mobile banking) and share trading (mobile brokerage). Commuter services such as sending schedule change alerts or using a mobile phone to pay for parking have become widespread. Applications based on the location of the user (e.g., offering mobile coupons to customers in the vicinity of a shop or a restaurant) are also being trialled (Barnes, 2002; Siau, Lim, & Shen, 2001; Varshney, Vetter, & Kalakota, 2000). Despite the potential benefits (for example, improved customer service) mobile commerce applications have not been widely adopted across business sectors. Mobile banking illustrates the point: initially, seen as the “killer application” of mobile commerce (Kannan, Chang, & Whinston, 2001), it has now been termed a “dead end” (Semrau & Kraiss, 2001). It has also been classified as an application which has not yet matured (Mallat, Rooi, & Tuunainen, 2004). However, innovative applications continue to emerge, for example, breaking news alerts (CNN, n.d.), and a mobile tutoring service (Butte, 2004). It has become important therefore to identify the determinants of mobile commerce adoption and the emerging adoption patterns. A significant number of results in this area have been reported in the literature. Recent examples include studies of mobile services adoption in areas characterized by relatively high penetration of mobile devices—such as Denmark (Constantiou, Damsgaard, & Knutsen, 2004), Singapore (Samtani, Leow, Lim, & Goh, 2004), and Finland (Carlsson, Hyvonen, Repo, & Walden, 2005). The identified drivers and inhibitors of mobile commerce adoption can be broadly classified as factors related to mobile infrastructure access, and factors relating to perceived consumer value. This article proposes a mobile commerce reference model which incorporates both infrastructure access and customer value and can be used to formulate research questions related to mobile commerce adoption. The remainder of the article is organized as follows: first, mobile commerce is defined and compared to electronic commerce. The next section introduces a mobile commerce reference model and discusses mobile commerce adoption. The article continues with a review of future trends and a brief conclusion.
Title: Mobile Commerce Applications and Adoption
Description:
The potential advantages of mobile commerce applications have been discussed extensively in the recent literature, with many industries offering mobile services.
Examples from the financial sector include instant funds transfer (mobile banking) and share trading (mobile brokerage).
Commuter services such as sending schedule change alerts or using a mobile phone to pay for parking have become widespread.
Applications based on the location of the user (e.
g.
, offering mobile coupons to customers in the vicinity of a shop or a restaurant) are also being trialled (Barnes, 2002; Siau, Lim, & Shen, 2001; Varshney, Vetter, & Kalakota, 2000).
Despite the potential benefits (for example, improved customer service) mobile commerce applications have not been widely adopted across business sectors.
Mobile banking illustrates the point: initially, seen as the “killer application” of mobile commerce (Kannan, Chang, & Whinston, 2001), it has now been termed a “dead end” (Semrau & Kraiss, 2001).
It has also been classified as an application which has not yet matured (Mallat, Rooi, & Tuunainen, 2004).
However, innovative applications continue to emerge, for example, breaking news alerts (CNN, n.
d.
), and a mobile tutoring service (Butte, 2004).
It has become important therefore to identify the determinants of mobile commerce adoption and the emerging adoption patterns.
A significant number of results in this area have been reported in the literature.
Recent examples include studies of mobile services adoption in areas characterized by relatively high penetration of mobile devices—such as Denmark (Constantiou, Damsgaard, & Knutsen, 2004), Singapore (Samtani, Leow, Lim, & Goh, 2004), and Finland (Carlsson, Hyvonen, Repo, & Walden, 2005).
The identified drivers and inhibitors of mobile commerce adoption can be broadly classified as factors related to mobile infrastructure access, and factors relating to perceived consumer value.
This article proposes a mobile commerce reference model which incorporates both infrastructure access and customer value and can be used to formulate research questions related to mobile commerce adoption.
The remainder of the article is organized as follows: first, mobile commerce is defined and compared to electronic commerce.
The next section introduces a mobile commerce reference model and discusses mobile commerce adoption.
The article continues with a review of future trends and a brief conclusion.

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