The mobile phone is a multipurpose device. In addition to transmitting voice communication it can provide a number of other functions and services. A good example of the differentiation from voice services is the Short text Messages Service (SMS). Other examples of more advanced use include mobile banking, taking and sharing pictures and videos, and using the Internet. This transformation process is similar to the evolution of computers: what originally was a number-crunching machine is now a multimedia information and communication device.
During the last decade we have experienced the proclaimed failure of Wireless Application Protocol (WAP), consecutive revisions of third-generation (3G) mobile technology's diffusion forecasts, and a slow actual 3G uptake in Western markets. Consequently, both academics and practitioners emphasize that technological advances and service availability do not automatically lead to widespread adoption and use [1, 3, 4]. Besides, in the roadmaps of future research on mobile market there are repeated calls for investigating factors that predict or explain adoption, acceptance, and use of mobile services [2, 7, 9]. Interestingly, the geographic areas in which these calls have mainly originated are Europe and the U.S., suggesting these foci are of particular significance in markets that have not kept pace with mobile service revolutions occurring in other national settings such as Japan and South Korea.
Vis-à-vis traditional diffusion-curve research, which operates under the stringent assumptions of an invariant unit of innovation and a definable population of potential adopters [8, 10], the mobile services market presents different scenarios [5]. Multiple mobile services with different scaling properties can be diffused as a result of the deployment of several devices and other services, thus vivid reinvention can be present.
Diffusion of innovation theory seeks to explain and predict the rate of adoption in a user population. Factors that have been found to influence adoption rate include: adopter characteristics, social networks, communication process, promoters' strategies, and innovation attributes such as triability, relative advantage, compatibility, observability, and complexity [8]. Additionally, this theory is based on the assumption that an innovation is superior to old products/services and thus it will eventually replace them (similar to the transition from the use of horses to tractors in farming). Mobile services are different. Adoption of a new mobile service does not automatically lead to abandonment of the previous ones. Instead, new mobile services are adopted in addition to existing ones due to complementarities. Furthermore, many mobile services are not valuable if used in isolation due to network effects [6] (for example, SMS is a service that only has value if others use it too, but it represents little value to the first adopters). However, for most innovations, adopters can be classified into distinct categories that relate to demographics. This enables technology providers to focus development and marketing efforts on particular segments.
In this article, we utilize a reverse approach, and use espoused behavior to identify groups that are distinct, yet in the same dimension. We suggest it is critical not only to identify core characteristics among different adopter types in terms of their degree of innovativeness, but also to determine user categories based on their behavior and how differences in technology and service use yield variations in their requirements and attitudes. We take a learning perspective based on the assumptions that: technology and service use is not completely random but evolves over time as people learn and technology matures; technology and service adoption requires and instantiates behavioral change in incremental steps; technology and service requirements provide indications on behavioral change paths; and a multiplicity of behaviors may coexist in relation to a mobile product-service offering.
This article presents results from a survey conducted in the Danish mobile communications market.1 Demark is among the most advanced European countries in mobile communications (Denmark maintains the top ranking of e-readiness, a measure developed by the Economist Intelligence Unit2) and represents a very competitive market (for example, nine mobile operators resulting in extensive price wars on contracts for SMS and voice services). Thus, we believe this is a useful example of a country in which we can investigate emerging trends in mobile services and usage patterns that may be prominent and repeated in other Western markets.
We conducted statistical analysis to identify: mobile user categories; key characteristics in technology and service use that differentiate the categories; and differences among the categories in terms of end-user requirements. We propose a categorization of mobile users exploring congruencies and differences in demographics, technology and service use, and technology-service requirements. This is expected to reduce the problems of the individual-blame bias [8] as it opens for categorizing users based on behavioral-requirements differences and not only on their predispositions whether to adopt.
Our study contributes to academic and practical research on mobile services adoption and use on two separate accounts. The survey data can be utilized beyond categorization of user segments based on demographic variables and assessing degrees of innovativeness: by exploring current use among a sample of mobile users in Denmark, we can also identify migration paths within the overall diffusion of mobile communications. In addition, we demonstrate a connection between the user as a user of technology and as a user of mobile services and that this connection can be of significant importance for understanding the adoption of mobile services.
In most European countries, a mobile user must subscribe to GPRS network services in order to utilize Multimedia Message Service (MMS) or new mobile services (such as those offered through mobile portals). Thus, mobile users can be broadly divided into GPRS and non-GPRS subscribers. These two groups can be further distinguished in terms of mobile communications services use. The non-GPRS subscribers can be subdivided into those using only voice services and those using SMS in addition to voice services. For the GPRS-enabled subscribers, a similar distinction is made between one group that uses only MMS but no other data-based services and another group using such services in addition to MMS. Both of the latter groups also use voice and SMS. Accordingly, four categories are delineated (see Figure 1).
Under the categorization scheme shown in Figure 1, "talkers" have taken one primary learning step related to mobile communications use, "writers," "photographers" and "surfers" have experienced one, two, and three additional transformations in their behavior respectively. Mobile users advance one step at a time and migration evolves in stages.
The demographics of the four categories are presented in Table 1. Talkers are mainly middle-aged men with at least a high school education, working in the private sector; writers and photographers are mainly students; and surfers are mainly men in their early thirties working in the private sector.
The proposed categorization is based on the use of mobile communications services and we investigate the groups' behavior according to the survey data. There is a significant difference in daily use of voice services between the groups: for talkers and writers it is less than five minutes, whereas for photographers and surfers it ranges between five and 10 minutes. Writers and surfers send less than 20 SMS, while photographers send more than 20 SMS weekly. In addition, photographers use MMS occasionally, while the majority of surfers use it less than five times weekly. It seems that SMS remains a prominent communication means and MMS has not taken over yet. Moreover, proposed categorization is supported by the significant differences among groups on self-assessment of innovativeness, perceived usefulness, and intention to use mobile services (see Figure 2).
The most important perceived benefit from mobile communications for all groups is improvement of personal relationships with peers. If we combine this observation with findings on relatively low voice service and rather high SMS uses, it appears the mobile device is perceived as a contact-enabling tool that allows connectivity and communications anywhere and anytime. This is also supported by the second most important benefit, which is "services make me accessible anywhere and anytime." Furthermore, the monthly payment for talkers and writers is less than 10 euros whereas for photographers and surfers the range is between 15 and 30 euros, while the main reason for choosing a mobile operator is low price.
Experience with mobile devices may affect adoption and use of specific services. There is significant difference in years of experience with mobile devices since talkers and surfers have more than six years, whereas writers and photographers have less than six years of experience. This result may relate to the observation that the latter two groups mainly include younger people (such as students). With respect to the current device used for both talkers and writers is more than one but less than two years old, whereas for the other two groups less than one year.
Technology-service features of mobile devices may enable or impede service use. For example, in the case of photographs the color display can vividly affect service use [3]. The users' requirements can be broadly distinguished in terms of device features such as color display, camera, and properties such as messenger, broadband Internet, mobile email, and other attributes. The most important requirements for all groups are color display and email and the least important ones are messenger and games (see Table 2). Email has a rather high rating among all groups indicating a generally required service.
Moreover, PC synchronization is also ranked high among all groups. Better integration between the Internet, email, and PCs may be an important path toward more advanced mobile service use. Photographers and surfers do not significantly differ in most of their requirements. However, there are significant differences in enabling services such as broadband Internet access, email, and map/positioning. This result supports the argument that surfers have taken an extra behavioral change step and that once taken, it is reflected in their future requirements. The distinction between GPRS and non-GPRS subscribers is further indicated by the significant differences between writers and photographers on all requirements. Besides, talkers and writers do not have significantly different requirements in terms of color display, camera, video, and messenger.
Categorization of mobile users based on technology and service use offers insights beyond those provided by aggregate diffusion models and criteria purely based on innovativeness. As adoption of mobile devices does not imply homogenous use, we have identified specific areas in which congruencies can be found or where significant differences exist (see Table 3).
Due to extensive subsidies on mobile devices in the Danish market, most of the respondents have relatively new devices. In particular, talkers, the least advanced group, have mobile devices that are typically less than two years old. Thus, a talker may potentially possess the same advanced services as a surfer, but has never used them. Besides, talkers have no specific technology or service requirements and seem to be stagnated in their perception of a mobile phone simply as a communication tool used anywhere and anytime. Hence, we suggest that middle-aged managers, to whom mobile operators' marketing efforts on advanced mobile services are mainly focused, may not be the optimal target group.
Moreover, the two large categories of writers and photographers significantly differ in technology and service use as well as their requirements. Writers seem quite satisfied with the features of their current mobile devices. These indications highlight the difference between the two groups that also relates to their decision whether to activate their GPRS accounts. This may explain the difficulties encountered by 3G operators trying to convert talkers and writers to surfers since the gap is difficult to be bridged with one step alone. Thus, we propose the key players in the mobile market should develop different marketing strategies focusing on photographers needs that are one step behind adoption of advanced mobile services and at the same time promoting a slower migration path for writers that seem satisfied with the use of commodity services such as voice and SMS.
The two most advanced categories, photographers and surfers, significantly differ in technology and service use. Their main requirement is better color display but the second one for surfers is email, while for photographers PC synchronization is most important. Moreover, the members of the most advanced categories have significantly different perceptions of key attributes of mobile services. Photographers attach higher importance to ease of use, security, customer service, personalization, and comfort of the device than surfers, but they both consider services pricing the most important attribute. These observations may explain why photographers have not yet adopted advanced mobile services.
There are strong indications that the usage trajectory moves from voice and SMS to also include MMS and advanced data services. However, there are significant differences among all categories of users concerning their use of mobile services in the future, as shown in Figure 1. This also underscores our initial observation that a mobile phone is not a static technology. Its usage is learning-intensive and services must be embraced by users. There appears to be many untapped functionalities in mobile devices that only mobile operators have the power to release to the users.
We argue that the thrust of utilizing the proposed categorization lies not only in identifying differences, but also opening avenues to discover areas where congruencies exist. These can form the basis for catalyzing usage paths and enabling migration of users within a category to one of more advanced use. In turn, this migration implies a departure from commodity services such as voice and SMS to more specialized services that may generate higher revenues to the key players. The proposed categorization offers insights to key players that can be used while launching new services or segmenting their market. In order for mobile operators or service providers to facilitate the trajectory movement it is useful to address the specific areas where there are congruencies in terms of technology, service use, and service requirements.
1. Baldi, S. and Thaung, H.P.-P. The entertaining way to m-commerce: Japan's approach to the mobile InternetA model for Europe. Electronic Markets 12, 1 (Dec. 2003), 613.
2. Blechar, J., Constantiou, I.D., and Damsgaard, J. Exploring the influence of reference situations and reference pricing on mobile service user behavior. European Journal of Information Systems 15, 3 (Mar. 2006), 285291.
3. Bruner, G.I. and Kumar, A. Explaining consumer acceptance of handheld Internet devices. Journal of Business Research 58, 5 (May 2005), 553558.
4. Constantiou, I.D., Damsgaard, J., and Knutsen, L. Exploring perceptions and use of mobile services: User differences in an advancing market. International Journal of Mobile Communications 4, 3 (Mar. 2003), 231247.
5. Jarvenpaa, S.L., Lang, K.R., Takeda, Y. and Tuunainen, V.K. Mobile commerce at crossroads: An international focus group study of users of mobile handheld devices and services. Commun. ACM 46, 12 (Dec. 2003), 4144.
6. Katz, M.L. and Shapiro, C. Product introduction with network externalities. Journal of Industrial Economics 40, 1 (Jan. 1992), 55-83.
7. Lyytinen, K. and Yoo, Y. Research commentary: The next wave of nomadic computing. Information Systems Research 13, 4 (Apr. 2004), 377388.
8. Rogers, E.M. Diffusion of Innovations. The Free Press, New York, 2003.
9. Sarker, S. and Wells, J.P. Understanding mobile handheld device use and adoption. Commun. ACM 46, 12 (Dec. 2003), 3540.
10. Wolfe, R.A. Organizational innovation: Review, critique and suggested research directions. Journal of Management Studies 31, 3 (Mar. 1994), 405432.
1The survey instrument included 43 questions organized in different categories including mobile services adoption diffusion and use, technology use, and demographics. The sample consisted of 1,103 respondents that completed the survey. The survey instrument is available at the Mobiconomy Web site under Activities: www.mobiconomy.dk.
2Economist Intelligence Unit (EIU), The 2006 Rankings. A white paper from the Economist Intelligence Unit (2006); http://graphics.eiu.com/files/ad_pdfs/ 2006Ereadiness_Ranking_WP.pdf.
Figure 1. Categories of mobile users according to the survey data.
Figure 2. Mobile users' self-assessments of innovativeness (means of items rated on a scale: 1 = completely disagree to 5 = completely agree).
Table 1. Demographics of mobile users.
Table 2. Mobile users' requirements on device (means of items rated on a scale: 1 = completely unimportant to 5 = very important; merged cells indicate no significant difference).
Table 3. Trends on technology and service use among categories.
©2007 ACM 0001-0782/07/0600 $5.00
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
The Digital Library is published by the Association for Computing Machinery. Copyright © 2007 ACM, Inc.
No entries found