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Repositorio Institucional de la Universidad Autónoma de Madrid https://repositorio.uam.es Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in: Information & Management 43.2 (2006): DOI: Elsevier B. V. All rights reserved. El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription What do we know about mobile Internet adopters?a cluster analysis Shintaro Okazaki Abstract Despite the increasing importance of wireless Internet use via Web enabled mobile telephony, the relationship between consumers attitude and their demographic characteristics have been only cursorily examined. The objective of our study was to fill this gap, by applying a two step cluster analysis in profiling mobile Internet adopters in Japan. The findings suggest that four clusters exist; they exhibit distinct profile patterns. Paradoxical results were found within one, affluent single youth, which was further divided into two clusters: freelance, highly educated professionals had the most negative perception of mobile Internet adoption, whereas clerical office workers had the most positive perception. Married housewives and company executives also exhibited a positive attitude toward mobile Internet usage. Keywords: Mobile; Diffusion; Innovation; Internet; i Mode; Japan; Uses and gratifications 1. Introduction In world markets, the rapid adoption of Web-enabled mobile handsets has become increasingly important to IS professionals. A recent survey in 13 countries revealed an increase in usage of 145%, reaching 79 million users in 2003, while the number of global mobile Internet adopters has been predicted to reach nearly 600 million by 2008 [19,35]. A pessimistic forecast estimated that, by the year 2005, the number of Internet-connected mobile phones would exceed the number of Internet-connected PCs [44]. Such dramatic convergence of the Internet and mobile telephony may be attributed, in particular, to activity in Asian and Scandinavian countries, where penetration growth has been meteoric. A recent survey indicated that roughly 70 million people in Japan (55% of the population) have signed up for Internet access from their cellular phones, compared with 12% of the population in the USA [13,15]. In fact, the Japanese see cell phones or Keitai as devices for surfing the Internet while Americans use their laptops. Much of this success can be traced to February 1999, when NTT DoCoMo, Japan s leading mobile operator, launched the i-mode service. This is a mobile phone service offering continuous, always-on Internet access based on packet-switching technology [6]. Through a handset, users can access a micro-browser that offers services such as , data search, instant messaging, Internet, and i-menu. is considered the most popular killer app, and 71% of i-mode users receive an newsletter [29,38]. The i-menu acts as a mobile portal resulting in approximately 4100 official and 50,000 unofficial sites offering diverse additional functions [32]. One of the unusual features of i-mode is the way it develops i-mode content. Instead of purchasing it, DoCoMo allows designated third parties to provide fee-based content and services with collection through the monthly phone bill. By October 2003, more than 40 million subscribers to 2G and 3G i-mode Internet services existed. The key to understanding this growth lies in the profiles of mobile consumer segments but little effort has addressed the fundamental question: what are the attitudinal and demographic characteristics of mobile Internet adopters? The purpose of our study was to fill this gap, by conducting a two-step cluster analysis to identify specific segments of mobile Internet adopters in Japan. Our method overcomes the limitations of traditional cluster analysis by: (1) considering both continuous and categorical variables and (2) automatically determining the number of clusters or segments on the basis of objective statistical criteria. 2. Significance of the study This study contributes to electronic commerce literature in two ways. First, research on mobile Internet adopters has primarily focused on the area of direct marketing; user profiles have rarely been considered. The majority of the studies result from sporadic industry reports that leave an important question unanswered: in developing effective business-to-consumer m-commerce strategies, how do information managers identify mobile Internet adopters? And: what kind of demographic and psychographic segments do they have? An effort to classify mobile Internet adopters based on specific attributes may therefore help in driving the development and execution of customer strategy and targeting of customers. Second, despite obvious cultural differences, an empirical investigation of consumers can serve as a useful case study for other markets. DoCoMo s i-mode, for example, has expanded to European countries; the adopters include E-Plus (Germany), KPN Mobile (Netherlands), BASE (Belgium), Bouygues Telecom (France), Telefonica Moviles (Spain), Wind (Italy), and COSMOTE (Greece), and total subscribers reached 1.5 million by the end of 2003, from 270,000 at the end of 2002 [1]. The software platform and its content have been converted into added value resulting from the solution and partner network, possibly providing wider implications [28]. Therefore, it is important to establish a theoretical basis of the attitudes and demographics of mobile Internet adopters. 3. Mobile content creation in the m-commerce value chain A chain of value-adding activities in mobilecommerce involves two global perspectives: content and infrastructure-and-services [5]. The current moves by global mobile players, however, place more strategic emphasis on content, the value chain of content aggregation, its management, and access [25]. DoCoMo s i-mode, for example, is a semi-walled garden controlled by its packet network and server system; in this many different contents may be structured into official (approved) and unofficial (nonapproved) providers (Fig. 1). However, only official providers can charge for content through DoCoMo s subscription billing system, which offers multiple incentives for active content creation. The mobile portals play a key role in adding value to mobile market-making [5]. For instance, when users select i-mode, they are presented with i-menu with links to personal information management applications, offering users a one-stop shop solution. The increasing sophistication of mobile handsets has accommodated diverse killer apps, such as built-in GPS, music downloads, videos, e-coupons for discounts, bill payment, and even karaoke machines. Strategically, this portal imposes no additional infrastructure costs, because the content creation can be arranged with a number of third-party content providers and aggregators. As a result, in 2004 DoCoMo s group net profits more than tripled to 650 billion yen [2] and its Fig. 1. Functions of i mode Internet service. Source: Reprinted by permission of Ref. [28]. Table 1 Mobile Internet services in Japan i Mode Vodafone live EZweb Operator group NTT DoCoMo Vodafone Au (KDDI) Market share 60.5% 19.5% 20.1% Number of subscribers a Markup language chtml MML HDML 3G/2.5G network b W cdma W cdma Cdma2000 1X Maximum capacity (packet) b 384 kbps 384 kbps 144 kbps Number of official sites c 2000 Charge d 1000 yen monthly charge yen per packet 300 yen monthly charge yen per packet 300 yen monthly charge yen per packet a In million [43]. Ref. [41]. Refs. [17,32]. Refs. [3,31,46]. competitors, Vodafone and au (KDDI), implemented similar mobile Internet services, albeit using different underlying technologies [17] (Table 1). 4. Profiling mobile Internet adopters In pursuing this study, it was necessary to establish a conceptual framework for assessing the structure of the mobile Internet market. In general, markets consist of a number of segments, each of which is made up of natural groupings of customers [14]. Consumers can be split into different segments or clusters, within which customers have similar characteristics and needs [27]. The combined benefits were sought by adopting a two-step cluster analysis Demographic profiling Demographic profiling is the process of splitting the market by considering personal similarities and differences, such as gender, age, marital status, occupation, monthly allowance, and household structure. Such descriptive attributes have been used in most industry surveys. Earlier industry reports have indicated that mobile Internet penetration was highest among young affluent males [42]. Most of them (83%) were found to use the mobile Internet for personal purposes, but a substantial portion (49%) also used it for work. WAP adopters in Taiwan were predominantly young single males (21 40 years old) with middle income [18]. A recent US industry report also indicated that a typical user was male, between 18 and 34 years old, with a household income of US$ 60,000 or more. Such findings suggest that the likelihood of adopting mobile IT innovations is dependent on age and income, while the effect of gender on mobile Internet service adoption remains uncertain. For example, a survey of mobile text messaging by 500 British young adults found hardly any differences due to age or gender [7]. In addition, a survey of mobile banking adoption in South Africa found that the majority (67%) of the respondents were young, educated groups, either employed or studying or both, with the gender distribution approximately equal [9] Attitudinal profiling While many industry surveys have focused on descriptive characteristics, little diagnostic information has been provided on mobile Internet adopters, where similar demographic data may be differentiated by the adopters psychological motives. We therefore attempted to uncover profiles on the basis of: (1) the uses and gratifications of adopters with the new media and (2) the diffusion of the mobile Internet as an innovation. The uses and gratifications theory is axiomatic; it argues that psychological needs shape an audiences adoption of the media [23]. This theory is primarily grounded on three basic tenets: media adopters are goal-directed, active media-users, and aware of their needs. Because the mobile Internet service has been characterized as being highly personal, interactive, and immediate [10], important attributes can be found by profiling individuals according to the degree to which they spontaneously perceive the medium to be irritating, informative, or entertaining. These have been identified as principal motivations in wired Internet service adoption [11,22,24], while prior research on the mobile Internet has made similar suggestions [4,21]. Rogers [36] defines the diffusion as the process by which an innovation is communicated through certain channels over time among the members of a social system. Therefore, it is a communication of new ideas, in which participants create and share information with one another in order to reach a mutual understanding. Thus, the mobile Internet seems to satisfy the five principal characteristics of innovation: (1) relative advantage over the idea it supersedes; (2) compatibility with existing technology; (3) perceived complexity of its understanding and use; (4) trialability; (5) observability to others. These variables collectively result in user attitude toward the mobile Internet, which in turn affects consumers behavioral intent to use it. Furthermore, prior research on Japanese i-mode adoption suggested that the credibility of a new communication channel was key to the choice of access. This was important, because more than 20% of Japanese mobile Internet adopters accessed news and city guides, which often acted as a trusted information source in their daily lives. Also, with logo branding and sponsorship campaigns increasingly popular in mobile sites, users may also have wanted to be sure of the trustworthiness of such paid-publicity. By choosing the i-menu, users could access a content-based platform, Tokusuru Menu (menu to your advantage, in Japanese), which featured text banner ads from sponsoring companies. By clicking, consumers could browse further detailed information pages that offered discounts, coupons, free-samples, sweepstakes, and ring-tone downloads, etc. Therefore, in forming basic attitudes toward and intention to access the mobile Internet, individuals may have been reminded of the underlying information credibility and trustworthiness. 5. Methodology 5.1. The questionnaire Our study was part of an omnibus research project conducted by an advertising research foundation in Tokyo. The survey instrument included face, common, and specific questions. The face questions covered general demographic information, such as gender, occupation, marital status, monthly allowance, and hours spent outside home. The common questions were related to general perceptions of media selection, leisure activity, consumption attitude, etc. Finally, the specific questions addressed attitudinal dimensions with respect to i-mode platforms, including content and source credibility, informativeness, entertainment, irritation, general liking, and willingness to access. It seemed reasonable to assume that usage of messaging and access to mobile portals were two key indicators of mobile Internet adopters. Therefore, photographic images of i-menu portal sites were inserted in the questionnaire in asking respondents for their general opinions on the use of such services. With regard to usage, the questionnaire included a filtering question: did respondents use e- mail messaging via mobile telephony? 5.2. Sample The sample involved stratified random sampling according to age and gender distribution. The population was based on the Citizens Registry Book of the Tokyo Metropolitan District. Questionnaires were distributed to 1623 residents in the greater Tokyo area. A professional marketing organization was employed for this task, and researchers visited each respondent to leave the questionnaire. A total of 786 responses were collected in the next month, giving an effective response rate of 48.4%. However, only 612 responses were included in the data analysis: those who regularly used the message service via the mobile phone. 6. Statistical treatment 6.1. The two-step cluster analysis Traditionally, cluster analysis has been used for empirical classification of objects [16]. It is an exploratory technique that has been widely applied in diverse disciplines for its partitioning ability; e.g., Bhatnager and Ghose [8] applied a latent class modeling approach to segment Web shoppers based on demographics and benefit sought while Jih and Lee [20] attempted to segment cellular phone users according to their retail shopping motives. Thus, this technique was deemed appropriate in forming groups according to the similarity of their demographic and attitudinal variables. Our study used a statistical program, TwoStep Cluster in SPSS 12.0; this had been suggested as appropriate in clustering large data sets with mixed attributes [30]. The method is based on a distance measure that enables data with both continuous and categorical attributes to be clustered. This is derived from a probabilistic model in which the distance between two clusters is equivalent to the decrease in log-likelihood function as a result of merging [12]. In the first step, original cases are grouped into preclusters that are then used in place of the raw data in the hierarchical clustering. Based upon its similarity to existing preclusters, each successive case is added to form a new precluster, using a likelihood distance measure as the similarity criterion. Cases are assigned to the precluster that maximizes a log-likelihood function. In the second step, the preclusters are grouped using the standard agglomerative clustering algorithm, producing a range of solutions, which is then reduced to the best number of clusters on the basis of Schwarz s Bayesian inference criterion (BIC), which is known as one of the most useful and objective selection criteria, because it essentially avoids the arbitrariness in traditional clustering techniques. In addition, both background noise and outliers can be identified and screened out Categorical and continuous variables The categorical and continuous variables are shown in Tables 2 and 3, respectively. The categorical variables involve gender, age, marital status, occupation, monthly allowance, and household structure. Monthly allowance was chosen over monthly income, on the assumption that the level of mobile usage expenditure is a function of disposable allowance rather than of total income. Each variable was assessed on a categorical scale with no multiple responses allowed. The continuous variables were associated with general perceptions of the mobile platform: content credibility, source credibility, informativeness, entertainment, irritation, general liking, and willingness to access. Each measure consisted of a multiple-item scale, as indicated in Table 3. To ensure the adequacy of the selected variables, two preliminary analyses were conducted in an attempt to identify significant differences between mobile users and non-users. This was needed because, if there were no significant differences between the two groups, then profiling made little sense. First, the Pearson chisquare test was performed for each of the categorical variables across the two groups. The expected values in each cell were greater than 1 and most cells had expected values greater than 5. Significant differences were detected at P for all variables between e- mail users and non-users. Second, a MANOVA was conducted with type of use or non-use as independent Table 2 Categorical variables used for the cluster analysis Variables Categories Gender (1) Male; (2) female Age (years) (1) 15 19; (2) 20 29; (3) 30 39; (4) 40 49; (5) 50 59; (6) Marital status (1) Married; (2) single Occupation (1) Executive; (2) managerial; (3) clerical; (4) administrative staff; (5) self employed; (6) freelance professional; (7) part time worker; (8) housewife; (9) student; (10) unemployed; (11) others Monthly allowance (yen) (1) 10,000; (2) 10,000 19,999; (3) 20,000 29,999; (4) 30,000 49,999; (5) 50,000 69,999; (6) 70,000 99,999; (7) 100, ,999; (8) 150,000; (9) unknown Household structure (1) Single; (2) married couple; (3) married couple and children; (4) extended family; (5) others 100 JPY US$ EUR. variable and all continuous variables as dependent variables. Using Wilks criterion, the continuous variables were significantly affected by use or non-use, F(6, 721) = 2.45, P Test of assumptions, reliability, and validity Before starting the cluster analysis, the missing values were replaced with their means by using SPSS 12.0; this was because the missing values seriously distorted the multivariate analysis results. According to the recommendations of Hair et al., the following were examined: (1) the representativeness of the sample and (2) the absence of multicollinearity. First, the sample was considered to be representative, given that our study employed a sufficiently large random sampling procedure, which meant that the results were generalizable to the population of interest. Second, the level of multicollinearity was examined through the tolerance value. The tolerance was found to be within an acceptable range, with all scores between 0.70 and 0.96, indicating low collinearity among variables. Next, the specific assumptions of the two-step clustering algorithm were assessed. First, the independence of the respondents was ensured by the random sampling plan. Second, to assess the normality of each continuous variable, both skewness and kurtosis tests were determined: in neither test did any of the calculated z-values exc
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