Inf Syst Front (2012) 14:409–421 DOI 10.1007/s10796-010-9267-8
A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives Dan J. Kim & Yujong Hwang
Published online: 7 September 2010 # Springer Science+Business Media, LLC 2010
Abstract Although a few studies have focused on mobile value from the distinctive feature of a mobile technology perspective, limited attempts have been made from a mobile user’s value tendency perspective. In this study, building upon prior research on productivity-oriented and pleasure-oriented nature of systems, we categorize mobile values as having utilitarian and hedonic use. Based on these two values, we conceptualize types of tendency of mobile users’ application use namely utilitarian tendency and hedonic tendency. The goal of this study is to examine the relationships between mobile consumers’ value tendency and their perceptions of mobile Internet service quality in terms of three different mobile quality dimensions (i.e., connection quality, design quality, and information quality). In addition, drawing upon the “digital divide” literature, the relationships between mobile users’ personal dispositions (i.e., maturity and socio-economic status) and their mobile value tendency are also tested. The empirical results of the study, the interpretation of the results, research contributions, and limitations are discussed. Keywords Mobile internet . Mobile values . Utilitarian tendency . Hedonic tendency . Mobile internet service quality dimensions D. J. Kim (*) University of Houston Clear-Lake, 2700 Bay Area Boulevard, Delta, 169, Houston, TX 77058-1098, USA e-mail:
[email protected] Y. Hwang School of Accountancy and MIS, DePaul University, Chicago, IL, USA e-mail:
[email protected] Y. Hwang College of International Studies, Kyung Hee University, Seoul, South Korea
1 Introduction The Internet and mobile technology, the two most dynamic technological forces in modern information and communication technologies are converging into one ubiquitous mobile Internet service,1 which will change our way of both doing business and dealing with our daily routine activities. There is no doubt that the mobile Internet service is moving toward the new generation on which enables mobile users to enjoy a variety of new and upgraded multimedia mobile services. Mobile Internet technology has some distinctive features. Among the features, the most unique one is mobility, which refers to the ability to communicate, inform, transact and entertain at any place at anytime on the move without fixed Internet access (Clarke 2001). Another unique feature is personalization; the mobile device is personal in that it is always available on a person and retains its personal identity (Kannan et al. 2001). These two unique features of mobile technology endow mobile Internet applications’ compelling values. These values differentiate them from those of wired Internet applications. Thus, mobile consumers obtain ‘mobile values’ through the access of mobile Internet applications 1
Even though mobile Internet service and wireless Internet service are used interchangeably in many cases, they are different. Wireless Internet service can be defined to a Radio Frequency (RF)-based Internet service. Some of wireless Internet services such as Wi-Fi, Local Multipoint Distribution Service (LMDS), Multi-point Multichannel Distribution Service (MMDS), and fixed wireless LAN, have limited or low mobility—i.e., they are mobile stationary services within a restricted area (e.g., a building). In this study, mobile Internet service is defined as the narrow wireless Internet service provides high mobility in a wide area (e.g., a city-wide) through portable mobile devices such as a cell phone, a PDA, and a handheld computer. The mobile Internet service provides connectivity to the Internet while moving (i.e., mobile connectivity), whereas fixed types of wireless Internet service have a limited mobile connectivity.
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using mobile devices. In other words, the mobile Internet applications provide mobile values not only for work related but also for entertainment and pleasure (Anckar and D’Incau 2002). While mobile internet technology provides mobile values, there are resource-based limitations of mobile technology (Siau and Shen 2003), which include restricted computing power (i.e., relatively low CPU clock speed), limited memory size, small screen, low-resolution display, tiny multifunction keypad, battery life, unfriendly user interface, low bandwidth, unstable network connection, relatively high usage cost, vulnerability of wireless data transmission, and others. Because of these limitations and the high expectations due to the “better” previous experiences with high speed broadband Internet technology the quality of mobile Internet service is especially important. According to the previous studies (Hong et al. 2006; Koivisto and Urbaczewski 2004) on mobile Internet service, mobile Internet users’ service satisfaction is the major determinant of continued mobile Internet usage and the success of mobile Internet service; and the acceptance and/or continuous use of mobile Internet service are heavily based on the quality of service experienced by mobile Internet consumers. Although the importance of mobile Internet service quality, only few studies (Cheong and Park 2005; Koivisto and Urbaczewski 2004) have focused on this issue. Even the discussion of the mobile Internet service quality has been limited to technology- or network-performance centric topics such as bandwidth, latency, jitter, packet loss, and usability of information architecture (Kim et al. 2005; Wood and Chatterjee 2002). Thus, the quality of mobile Internet service should be discussed from the mobile Internet consumers’ perspective, because prospective users of the mobile Internet service are customers rather than simply technology geeks. Moreover, it is acceptable argument that mobile Internet consumers may have different value tendencies of mobile Internet applications and different perceptions of mobile Internet service quality. Thus, it is an interesting and important research topic to explore how users’ mobile application value tendency is associated with their perceptions of mobile Internet service quality. In this study, therefore, building upon prior research on productivity-oriented and pleasure-oriented nature of systems, we categorize mobile values as utilitarian and hedonic. Accordingly, we conceptualize two types of tendency on mobile consumers’ application use: utilitarian tendency and hedonic tendency. The goal of this study, therefore, is to examine the relationships between mobile consumers’ value tendency and their perceptions of mobile Internet service quality in terms of three different mobile quality dimensions (i.e., connection quality, design quality,
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and information quality). In addition, drawing from the “Digital Divide” literature (e.g., (Barzilai-Nahon 2006; Ching et al. 2005; Cho et al. 2003; Rice and Katz 2003)), the relationships between mobile users’ personal dispositions (i.e., maturity and socio-economic status) and their mobile value tendency are also tested. The remainder of the paper is organized as follows. Section two presents literature on mobile values, service quality, and digital divide as theoretical background of this study. The third section proposes a research model (namely a mobile value tendency model) and hypotheses with discussions of the research constructs of the model. The fourth section discusses research methodology and data collection. The results of the data analysis of study follow in the fifth section. The final section concludes with a discussion of the findings, as well as the limitations and implications of the study.
2 Theoritical background and litreature review As theoretical background of this study, we conduct literature review on mobile values, service quality, and digital divide.2 2.1 Mobile value—utilitarian and hedonic value of mobile applications Value has been studied in many different disciplines (e.g., psychology, economics, finance, marketing, information systems, and e-commerce) and many different terminologies are used to describe value: customer value (Woodruff 1997), transaction value (Dyer 1997; Grewal et al. 1998), acquisition value (Grewal et al. 1998), service value (Cronin et al. 1997; Heinonen and Strandvik 2005), system value (King and Epstein 1983; Mookerjee and Dos Santos 1993; Pienaar et al. 1986; Young 1984), and hedonic price (Rao and Lynch 1993). Although a large volume of literature is available on value, due to the relative novelty of mobile technologies and mobile Internet services, studies concerning mobile values are limited. Kim et al. (2007) developed the Value-based Adoption Model and explained customers’ mobile Internet adoption from the value perspective. The findings of their study show value perception to be a key determinant of mobile Internet adoption. Based on the distinctive features of mobile devices (i.e., any-time, any-place, always-on, and personal devices), several studies identified the following 2
Please note that in this study we are not proposing any theories that address the causal relationship between mobile value tendency and users’ perceptions on service quality. In this study, what we are proposing is the association between mobile value tendency and perceptions on service quality.
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mobile values: ubiquity, time-criticality, spontaneity/immediacy, accessibility, convenience, personalization, location discovery, etc. These mobile values are not uniform across all the literature; some of them are strongly associated with each other. Always-on mobile devices allow users to get time-critical information in an urgent situation (Anckar and D’Incau 2002). The “omnipresence” characteristic of mobile devices also enables mobile users to access mobile services at anytime from anyplace (Anckar and D’Incau 2002; Booz-Allen&Hamilton 2000; Kannan et al. 2001; Siau et al. 2001). The mobile values are conceptualized as ubiquity (Clarke 2001; Siau et al. 2001), time-criticality (Anckar and D’Incau 2002), spontaneity/immediacy (Anckar and D’Incau 2002), and accessibility (Clarke 2001). Ubiquity is the ability to allow mobile users to obtain information and conduct mobile transactions anyplace through Internet-enabled mobile devices. Timecriticality refers to the ability of mobile devices to satisfy time-critical needs that require prompt and to-the-point interactions (Sadeh 2002). Spontaneity/immediacy, a similar value to time-criticality, refers to the mobile capability for mobile users to get information and complete transactions in real-time. Since mobile devices provide continuous and immediate access to the Internet, mobile users have high accessibility to the Internet in niche time or in a “dead spot” as when waiting in line or moving in traffic (Baldi and Thaung 2002; Clarke 2001). The ubiquities feature of mobile service provides the mobile value which is related to convenience. For example, the mobile technology with basic health monitoring applications provides a convenient way of checking an individual patient’s health conditions. Efficiency refers to reducing costs, encompassing not only monetary but also search costs, selection range, simplicity, and speed, through the use of the mobile technology. The seamless domain roaming feature of mobile technology allows mobile users to monitor time-sensitive information (e.g., stock trading) in real-time and to make decisions right away, which increases the productivity of time-pressured users in everyday activities (Anckar and D’Incau 2002). These unique features of mobile devices provide values to mobile service providers. Since a mobile device is a personal belonging, it contains personal information as well as individual preferences. With knowledge of users’ behaviors and their preferences, mobile service providers can offer more personalized services to mobile users (Sadeh 2002). This characteristic also provides an opportunity to mobile service providers for individual-based target marketing (Baldi and Thaung 2002; Clarke 2001; Siau et al. 2001). Another mobile value is location discovery. Since mobile devices are always on and carry user identity, the location of the mobile user can be tracked (Anckar and D’Incau 2002; Booz-Allen&Hamilton 2000; Kannan et al.
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2001; Siau et al. 2001). This allows mobile service providers to do location-based marketing and to deliver promotional offerings based on a user’s current geographic position (Clarke 2001). By combining personalization and location discovery features, it would be possible to provide “infotainment” service, i.e., location-based entertainment services based on the users’ preference (Baldi and Thaung 2002; Booz-Allen&Hamilton 2000). As discussed, most studies on mobile value focused on the unique feature of mobile technology (i.e., any-time, any-place, always-on, and personal devices). However, some values depend on the type of mobile Internet applications. In line with the consumer behavior literature that distinguishes between utilitarian and hedonic value of products (Hirschman and Holbrook 1982; Holbrook 1999), several studies (Holsapple 2007; Van Der Heijden 2004; Wakefield and Whitten 2006) identify two types of system values: utilitarian and hedonic. Utilitarian systems provide instrumental and productivity-oriented value to users, whereas hedonic systems provide entertainment and pleasure-oriented value. In people’s information seeking process, Atkin (1973) finds two types of purpose. One is a utilitarian purpose that is achieved when an individual considers message content as a mean towards solving his or her practical problems, and the other is a non-instrumental, entertainment purpose that serves personal interest in a subject matter. The former, termed as instrumental utility of the media, is sought when people use messages that provide information necessary for adapting to practical environmental and psychological problems. The latter is a hedonic purpose that is sought when an individual exposes himself or herself to mass media content to provide a pleasurable sensation. The utilitarian values, which are derived from an economic concept in the information-processing paradigm are the result of useful, economically efficient and productive experiences, while hedonic values are the outcome of fun, pleasurable and enjoyable experiences (Carpenter et al. 2005; Rao and Lynch 1993). Van der Heijden (Van Der Heijden 2004) empirically finds that perceived enjoyment and perceived ease of use are strong determinates of intentions to use a hedonic information system. Manipulating the hedonic and utilitarian purpose of the mobile devices, Wakefield and Whitten (Wakefield and Whitten 2006) examine the effect of cognitive absorption and playfulness on user beliefs including perceived enjoyment and perceived usefulness of mobile devices. The results show that cognitive absorption and user playfulness significantly impact beliefs, and that the hedonic or utilitarian orientation of the technology has implications for maximizing use. Some gratification factors such as mobility, immediacy, instrumentality, sociability, relaxation, entertainment, fash-
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ion, acquisition, reassurance, and status are identified as the important motives in predicting the use of mobile devices such as mobile phones (Leung and Wei 1998; Leung and Wei 2000). Since mobile devices can be used for utilitarian/ instrumental purpose (e.g., business scheduling, stock trading, online backing, etc) and hedonic/entertainment purpose (e.g., picture/music downloading, gamming, charting, etc), both are identified as important mobile values in this study. 2.2 Service quality Quality can be defined from both consumer and provider perspectives (Laudon and Laudon 2005). International Telecommunications Union—Telecommunication (ITU-T) defines service quality as the collective effort of the service performance, which determines the degree of satisfaction of the end user (ITU-T 1994). This definition implies that a service provider and consumers may have different views of service quality. However, since quality perceptions by consumers are considered to be the key factors influencing the acceptance/usage of a new service today (Collier and Bienstock 2006; Koivisto and Urbaczewski 2004), service quality from consumers’ perspective is being paid increasingly more attention. Service quality has been studied for a long time, and SERVQUAL has become a popular method for measuring service quality (Cronin et al. 2000; Dabolkar et al. 2000; Dyke et al. 1997; Dyke et al. 1999; Gronroos 1984; Parasuraman et al. 1985; Parasuraman et al. 1988; Pitt et al. 1995). The SERVQUAL has five key dimensions: tangibles, reliability, responsiveness, assurance, and empathy. Zeithaml et al. (2000) conceptualized service quality with eleven dimensions: reliability, responsiveness, assurance, trust, security, privacy, access, flexibility, ease of navigation, efficiency, and price knowledge. Later, this number was reduced to five dimensions: information availability and content, ease of use, privacy/security, graphic style, and reliability/fulfillment (Zeithaml et al. 2002). Other prevalent methods for measuring perceived service quality include process/technical dimension (i.e., how the service is delivered to customers) and outcome/functional dimensions (i.e., what customers get out of the service) (Gronroos 1984; Parasuraman et al. 1985). However, as pointed out by Dyke et al. (Dyke et al. 1997; Dyke et al. 1999), the number and dimensions of service quality vary depending on the context and culture involved. Although SERVQUAL is an excellent model for measuring service quality in general, we found that the dimensions of SERVQUAL and other relative methods are inadequate because they do not fully explain the criteria which are important to customers of emerging markets such as mobile Internet. Recently, Chiu and his colleagues (Chiu
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et al. 2007) identify three dimensions of quality (i.e., information quality, system quality, and service quality) that affect an individual’s satisfaction and usage of Web-based learning sites. Information quality refers to the accuracy, completeness, ease of understanding, and relevance of the online materials. System quality is the user’s belief about the performance of a Web-based learning site, which includes availability, ease of use, reliability, and response time, whereas service quality is the user’s perception of the overall support delivered by a site. In mobile Internet context, information quality is also a critical component of mobile Internet service. In addition, as parts of system quality, design quality and connection quality are especially important because of the resource limitations of mobile device (i.e., a small screen with a limited input interface) and mobile network (i.e., low bandwidth, unstable network connection, vulnerability of wireless data transmission, etc). In this study, we propose information quality, design quality, and connection quality as three dimensions of mobile Internet service quality. 2.3 Digital divide The expansion of the emerging technology such as mobile Internet has raised concerns about equitable access in user served social sectors in what is known as digital divide. When the term “digital divide” is introduced, it exclusively refers to the use of computers (Rice and Katz 2003) and Internet accessibility (Katz and Rice 2002). In recent years, the cost of home computer has been dramatically reduced. According to the early research results (Bikson and Panis 1999), minorities such as blacks and Hispanics are much less likely to possess home computers and have less access to the Internet than whites and Asians and therefore miss the opportunity to access information on the Internet. Recent studies (Howard et al. 2001; Katz and Rice 2002) report that with each year at least racial and gender gaps in Internet use are reducing after other socioeconomic variables such as incomes and education are taken into account statistically. There are now more mobile Internet users who use mobile handled devices to access the Internet. Thus, the question of “digital divide” is particularly relevant to the gap between mobile Internet “haves” and “have-nots”. The digital divide is more than an issue of access; it is a sociological phenomenon reflecting broader social economic, cultural, and learning inequalities (Cho et al. 2003). In general, demographic and individual differences apparently help to determine the appeal of the interactive features of mobile service (Mundorf and Bryant 2002). Previous research ( e.g., (Kraut et al. 1999)) on the “digital divide” find that there exists very strong relationships between Internet usage and demographics such as age, ethnicity, education, and socio-economic status. Although
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“digital divide” is still an important issue in mobile Internet context, this study attempts to expand the conception of the divide to move beyond the access issue of mobile Internet. In other words, this study moves beyond the “access gap” of mobile Internet to the “usage gap” of mobile applications. For the theory of “uses-and gratifications” perspective (Rosengren 1974), people use communication technology strategically. They use different technologies/ applications for different goals. More importantly, they select technologies/applications based on how well each helps them meet specific needs or goals (Katz et al. 1974).
3 Research model and hypotheses Based on the previous mobile values identified by previous studies, we conceptualize mobile application values as two types: utilitarian and hedonic value. Considering the mobile application values, we classify two types of tendency of mobile consumers’ application use: utilitarian tendency and hedonic tendency. Utilitarian tendency on mobile applications refers to the mobile user’s preference to use mobile services which have more functional and economically meaningful values such as mobile shopping, mobile banking, news etc. Hedonic tendency refers to the preference to use mobile services which provide the emotional or psychological worth such as mobile chatting with friends, mobile games, sports, and mp3 music play, etc. Drawing on the literature review on mobile values, service quality, and digital divide from the uses-andgratifications perceptive, we propose a research model (see Fig. 1) which includes two associational relationships: 1) the relationship between mobile users’ value tendency
Fig. 1 Research model
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and their perceptions of mobile Internet service quality in terms of three dimensions (i.e., information quality, design quality, and connection quality), and 2) the relationship between personal factors including demographics and socio-economic status and mobile users’ value tendency. This study also examines the effect of a control variable (i. e., frequent use of wireless internet) on the research model. 3.1 Consumers’ perception on mobile service quality and their value tendency In mobile Internet service, information quality and design quality of mobile service are important for mobile users, since mobile devices usually have a small screen with an unfriendly input interface. Information quality refers to how useful and valuable the content that the mobile Internet service provider’s portal site provides to their customers (Berry and Parasuraman 1997). Design quality of mobile Internet service is about the ease-of-use layout, easy-to-read screen content, easy search and navigation features of the service provider’s portal site and its interface. In addition, a high quality mobile Internet service should provide an acceptable speed for the mobile user through a variety of mobile devices. In this study, connection quality refers to mobile user’s perception of the connection quality to access a mobile service without any obstructions or connection delays. A stable and reliable connection to the Internet is an essential element for their mobile Internet usage satisfaction. Thus, connection quality is important for mobile users. Mobile Internet users prefer using mobile Internet services because of the utilitarian values (i.e., functional incentives) of the service. Along with the utilitarian/ instrumental values of mobile Internet service, hedonic/ entertainment motivations for the use of mobile Internet are also grounded by the personalization of mobile devices and applications. Within the mobile Internet applications, a utilitarian tendency is relevant for task-specific use of mobile Internet, such as, online shopping, stocks trading, mobile banking, and shopping. Hedonic tendency is related to the use of mobile Internet for entertainment/sociability purposes such as gaming, and chatting. Apparently, the two mobile value tendencies are not mutually exclusive. For example, e-mail and SMS (short messaging service) have both utilitarian and hedonic values to use. Due to the unique gratification factors of mobile technology (i.e., anytime, any-place, always-on, and personal device) which are the important motives for using mobile Internet service for special purposes, individual mobile consumers may have different usage tendencies. They may have different expectations and perceptions of mobile Internet service quality. When mobile users have a strong utilitarian and/or hedonic tendency to use mobile Internet applications, they
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are more demanding and expect certain levels of quality such as fast initial connection, stable connection, easy navigation, etc. However, the current limited capacity of mobile technology does not make mobile users satisfied with the service (Siau and Shen 2003). Thus, they are more likely to perceive low quality of mobile Internet service. Thus, we propose that: H1: Mobile users who have a relatively higher level of utilitarian tendency are more likely to perceive relatively lower levels of information quality (H1a), design quality (H1b), and connection quality (H1c) of mobile Internet service than those who have a relatively lower level of utilitarian tendency. H2: Mobile users who have a relatively higher level of hedonic tendency are more likely to perceive relatively lower levels of information quality (H2a), design quality (H2b), and connection quality (H2c) of mobile Internet service than those who have a relatively lower level of hedonic tendency. 3.2 Personal factors and mobile application value tendency A variety of empirical studies confirm that the individual predisposition factors such as maturity and socio-economic status (i.e., the average standard of living and occupations) are strongly related to the usage of Internet (Chen et al. 2002; Chinn and Fairlie 2004). In the context of mobile Internet, we expect that the personal factors may have different effects on the level of usage of mobile Internet service, since the mobile Internet service is relatively expensive service. First, we expect that maturity level is related to the mobile users’ mobile value tendency of mobile applications. The level of maturity is measured by age and education in this study. In general, it is accepted that adults with a high education are considered as having a higher maturity standing than youth with a low education (or still at school). Thus, we predict that less mature users will show relatively higher hedonic usage tendency than more mature users who alternatively show relatively higher utilitarian usage tendency of mobile Internet applications. These views lead to the following: H3a: Mobile users who have a relatively higher level of maturity are more likely to have a higher utilitarian tendency of mobile Internet use than those who have a relatively lower level of maturity. H3b: Mobile users who have a relatively higher level of maturity are less likely to have a higher hedonic tendency of mobile Internet use than those who have a relatively lower level of maturity. Although previous research (e.g., (Kraut et al. 1999)) report the strong relationships between socio-economic
status and Internet usage, in this study, we do not expect that people differ in the extent to which they use mobile Internet applications in terms of socio-economic status. Mobile devices may be used actively for both functional and hedonic purposes (Wakefield and Whitten 2006). Therefore, we argue that there are no significant differences in mobile application value tendencies (i.e., utilitarian tendency and hedonic tendency) among mobile Internet uses in terms of socio-economic status. H4a: High/Low social-economic status does not result in significant differences in utilitarian value tendency of mobile Internet application among mobile users. H4b: High/Low social-economic status does not result in significant differences in hedonic value tendency of mobile Internet application among mobile users. In addition to investigating the relationships between mobile user’s personal factors and their value tendency and between their value tendency and their perceptions of mobile Internet service quality, we include a control variable, the mobile users’ frequent use of wireless Internet, to check the relationship between the degree of usage and their value tendency across the model.
4 Research methods and data collection The research utilizes the secondary data that was collected by the Korean Network Information Center (KRNIC), an institution equivalent to the InterNIC in the USA. KRNIC represents a non-profit organization founded in 1999 for the purpose of developing a stable policy regarding the assignment of domain names and IP addresses in South Korea (hereafter Korea). A nationwide-scale survey was conducted of mobile Internet users in Korea using a stratified sampling method by region, gender, and age. A structured questionnaire was used to collect broad information about overall demographic data, mobile phone use patterns, mobile applications, satisfaction levels, and landline Internet usage. All survey questionnaires were filled out on a paper-and-pencil basis while a data collector was present to help respondents to better understand the questions. Among a total of 3,000 respondents, 881 responded that they had a mobile Internet experience in the past 6 months. After eliminating incomplete and missing responses of mobile Internet users, a total of 719 usable responses were included for this study. Table 1 summarizes the key characteristics of respondents. 4.1 Measures As recommended by Bentler and Chou (1987), each construct was measured by multiple items. Multiple
Inf Syst Front (2012) 14:409–421 Table 1 Key Demographic characteristics of respondents
415 Characteristics
Frequency –
Age Gender
%
Mean
S.D.
–
25.63
8.01
446 273
62.0 38.0
–
–
High School Students (including Junior High) College Students (including 2 year and graduate school) Adult—High School Graduate
106 182 229
14.74 25.31 31.85
–
–
Adult—College Graduate
196
27.26
6
0.83
Under 500,000 Won Between 500,000 and 1,000,000 Won
5 23
0.7 3.2
–
–
Between 1,010,000 and 1,500,000 Won
44
6.1
Between 1,510,000 and 2,000,000 Won
76
10.6
Between 2,010,000 and 2,500,000 Won
204
28.4
Between 2,510,000 and 3,000,000 Won
130
18.1
Between 3,010,000 and 3,500,000 Won Between 3,510,000 and 4,000,000 Won Between 4,010,000 and 4,500,000 Won
68 82 27
9.5 11.4 3.8
More than 4,510,000 Won
60
8.3
76 160 209 78
10.6 22.3 29.1 10.8
–
–
108 88
15.0 12.2
Male Female Education
Adult—Beyond Graduate School Average monthly household income (unit Won*)
1) Missing data are not counted in frequency. 2) * 1,000,000 won is approximately equivalent to $1,000 U.S. Dollars.
How often use the mobile Internet service Everyday 3–4 times a week 1–2 times a week 3–4 times a month 1–2 times a month Less than 1 time a month
measures for each construct provide more accurate representation of the concept of construct, which are typically downward-based by measurement error when multipleregression analysis is applied (Chin 1998). Information quality is measured by three items: comprehensiveness of information, diversity in information source, and timeliness information. Design quality is measured by three items: the perceived ease-of-use layout, easy information search and menu navigation, and as easy-to-read mobile screen content of mobile Internet service. Mobile users’ perception of connection quality is also measured by three items: mobile Internet initial connection speed, data transferring speed, and stability of connection. The items were written in the form of statements or questions. Most of the scales were anchored as 5-point Likert-type scales with end points such as very dissatisfied/very satisfied, and strongly disagree/ strongly agree. Socio-economic status was measured by occupation and household income level and maturity level was measured by age and education. Contrast to the 5-point Likert-type scales measurement of three service quality constructs, the mobile tendency variables were measured by two rank-items that asked:
“What are the three main mobile Internet contents you currently use?” and “What are the three main mobile Internet contents that you wish to use in the future?” Respondents were asked to rank three applications as first, second and third choice. The list of contents included fourteen choices3: e-mail, character/melody (bell) tone/ picture download, game, coupon/lottery, stock exchange/ banking/investing, shopping/ticket reservation, chatting, sports scores/entertainment news variety, location/travel services, news, surfing internet portal sites, adult entertainment, studying, and other applications. Among those contents we considered game, character/melody (bell) tone/picture download, chatting, sports scores or variety, and adult entertainment as hedonic applications, while all others were labeled as utilitarian applications (Sheehan 2002). For the first choice, depending on it being either a utilitarian or hedonic application, three points were assigned to the corresponding tendency. By the same token, for the second and third choice, two and one points were 3
The fourteen choices were available mobile applications at that time the survey was conducted.
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allotted respectively to either utilitarian or hedonic use tendencies. Therefore, a respondent could receive any scale from zero to six for hedonic and utilitarian use tendencies. Among the fourteen mobile applications, the frequency analysis shows that character/melody (bell) tone/picture download (30.7% of usage), game (20.5%), an sports scores/entertainment news variety (6.3%) are the top three most popular hedonic applications, and e-mail (14.6%), location/travel services (5.2%), and stock exchange/banking/investing (4.1%) are the top three most used utilitarian applications. Controversies might arise about the method of distinction between hedonic and utilitarian use in this study, especially regarding e-mails as a functional application. It should be noted that scholars have been labeling e-mail as interpersonal communication (Kraut et al. 1999), and there exist enjoyment-oriented uses of e-mail, such as expressive communication. However, those types of e-mail uses entail certain purposes, primarily to sustain or enhance relationships with peers. Moreover, as instant messaging and chat rooms are growing in popularity, e-mails, alternatively, are becoming less likely to be used for entertaining purposes (Boneva et al. 2001). Therefore, in this study we categorize e-mail as a utilitarian application.
of each AVE value are higher than the off-diagonal correlation elements (Chin 1998; Fornell and Larcker 1981). Table 2 shows the summarized reliability indices. Most behavioral researchers agree that common method bias4 is a potential problem in behavioral research when the assessment of both dependent and independent variables depends on the perceptual responses from a single source (Podsakoff et al. 2003). To control common method bias in this study, we follow the recommendations of Podsakoff et al. (2003) of how to control common method biases. The four techniques from the recommendation of Podsakoff et al. (2003) were applied: protecting respondent anonymity, reducing evaluation apprehension, counter balancing question order, improving scale items, and separation of measurement. The respondents answered to be anonymous, and they were assured that there is no right or wrong answer. This kept the respondents answers to the questions as honest as possible. We also utilize two different types of measurements. Two rank-items were used for the measurement of mobile users’ application tendency. For the measurement of three service quality constructs, 5-point Likerty-type scales were used. These procedures reduce their evaluation apprehension. All latent variables were counterbalanced the order of the measurement of the dependent and independent variables.
5 Data analyses and results
5.1 Structural model test and results
The present research used both AMOS 7.0 and Partial Least Squares (PLS-Graph version 3.0.1060) to test the measurement model and structure model because PLS-Graph and AMOS can be regarded as complementary. Based on covariance analysis, like LISREL, AMOS is more confirmatory in nature and it provides various overall goodnessof-fit indices to assess model fit for convergent validity (Byrne 2001) while PLS-Graph requires minimal demands on measurement scales, sample size, and residual distributions (Chin 1998). PLS-Graph reports composite reliability (CR) and average variance extracted (AVE) for content validity and discriminant validity. The reliability was gauged via the Cronbach’s Alpha coefficient that was suggested by (Nunnally 1967) and (Churchill 1979). All reliable Alpha coefficients exceeded 0.7, the minimum cutoff score (Nunnally 1978; Nunnally and Bernstein 1994) except for the hedonic tendency (Alpha=.694) which is very close to the threshold value. Composite reliability is also used to check the internal consistency, which should be greater than the benchmark of 0.7 to be considered adequate (Fornell and Larcker 1981). All composite reliabilities of constructs have a value higher than 0.7. To evaluate discriminant validity, the average variance extracted (AVE) is used. All constructs have an AVE of at least 0.5 (Fornell and Larcker 1981) and all the square roots
To verify the structure model, we conducted a Structural Equation Modeling analysis using AMOS 7.0. The results are presented in Fig. 2. All model fit indices of the model are satisfying the suggested values (See Table 3 in detail). There are very interesting results regarding the relationships between mobile value tendency and mobile users’ perceptions of mobile Internet service quality. As we expected, mobile users’ utilitarian tendency is strongly and negatively associated with mobile users Internet service quality perceptions; H1a, H1b, and H1c are supported. However, unlike our expectation, hedonic tendency is strongly but positively associated with all three mobile Internet service quality dimensions; H2a, H2b, and H2c are not supported. As expected, socio-economic status is not strongly correlated with utilitarian tendency and hedonic tendency; H3a and H3b are supported. Maturity has strong positive relationship with mobile users’ utilitarian tendency and strong negative relationship with hedonic tendency; H4a and H4b are supported. Another interesting result is that the control variable, the frequency of wireless internet 4
Common method bias refers to error that is attributable to the measurement method rather than to the construct of interest. It is one of the main sources of measurement error which threatens the validity of the conclusions about the relationships between measures.
Inf Syst Front (2012) 14:409–421
417
Table 2 Descriptive statistics and correlation for the measured variables Variables
No. Items
Alpha
Composite Reliability
AVE
1. Socio-Economic Status (SES) 2. Maturity
2
.755
.776
.689
.830
2
.803
.900
.718
.462
3. Utilitarian Tendency
2
.732
.844
.671
.301
.369
.819
4. Hedonic Tendency 5. Connection Quality
2 3
.694 .801
.842 .815
.727 .596
−.305 .047
−.374 .119
6. Design Quality
3
.759
.866
.684
.071
7. Information Quality
3
.774
.772
.545
.028
use, does not show any significant effects across the constructs of the research model.
6 Discussion and conclusion 6.1 Findings of the study The empirical results of the study show that mobile users’ utilitarian tendency has strong negative relationships with mobile users’ mobile Internet service quality perceptions. In other words, the higher level of utilitarian tendency a mobile user has, the less likely he or she is to have higher perceptions of connection quality, design quality, and information quality of mobile Internet service. A possible interpretation of this result is that utilitarian/functional mobile applications require more speed and a more stable network connection to satisfy mobile users’ time-critical, immediate, and efficient task needs. However, the technical
Fig. 2 Results
1
2
3
4
5
6
−.499 −.142
.853 .153
.772
.095
−.089
.100
.587
.827
.050
−.059
.066
.491
.495
7
.847
.738
limitations of current mobile technology (e.g., smaller display size, lower resolution, less powerful onboard hardware and input peripherals, and slower connectivity) may constrain the effective use of mobile applications for those mobile users who have a utilitarian tendency. Thus, mobile users who are more utilitarian/functional tendency may have negative perceptions of connection quality, design quality, and information quality. Inconsistent with our expectation, interestingly, the hedonic tendency has strong positive relationships with users’ mobile Internet service quality perceptions. In other words, the higher level of hedonic tendency a mobile user has, the more likely he or she is to show higher perceptions of connection quality, design quality, and information quality of mobile Internet service. Since this unexpected result did not provide any straightforward interpretation, we investigated the data in detail. After careful examination of the mobile applications, we recognize that the two most popular hedonic applications (i.e., character/melody (bell) tone/picture download, mobile game) are pre-download based services. Compared to utilitarian/functional mobile applications, they are not time-critical applications; the limited capabilities of current mobile technology such as relatively low connection speed, and unstable network connection, are not a serious problem for these applications. However, even if we now understand the non-negative relationships between hedonic tendency and perceptions of mobile service quality, we cannot interpret the positive relationships. Could it be possible some other mediating or moderating variables are related to these relationships? Further investigation on these relationships is needed. The results also show the personal factors have different effects on the usage of mobile Internet service. Socioeconomic status is not related, but the level of maturity is related to mobile application tendencies. These results imply that since the mobile devices are generally considered as a personal stuff, mobile service providers provide personalized services to mobile users based on their personal preferences. Despite socio-economic status, mo-
418 Table 3 Model fit indices of the structure model
a
Inf Syst Front (2012) 14:409–421 Statistic
Suggested value (Sources)
Value
Chi-square Chi-square significance Chi-square/d.f. RMSEA NFI TLI CFI GFI AGFI
P = 0.96 (Hu and Bentler 1999) >= 0.90 (Bentler 1990) > 0.80 (Joreskog and Sorbom 1988) > 0.80 (Joreskog and Sorbom 1988)
261.125 0.000a 2.535a .046a .969a .975a .960a .860a .841a
satisfy the suggested value
bile users are likely to use functional mobile applications (e. g., e-mail, search, etc) as well as hedonic mobile applications (e.g., bell tone download, mobile game, etc). Thus, a mobile user’s socio-economic status does not provide any significant difference in mobile application value tendencies. However, maturity shows different effects on mobile application value tendencies. The younger and less educated mobile users have more hedonic tendency, whereas the older and more educated users have more utilitarian tendency. 6.2 Contributions This study provides several theoretical contributions in the research areas of mobile value and mobile service quality. First, two distinctive mobile values (i.e., utilitarian value and hedonic value) are identified and distinguished from each other. Based on the two values, two types of mobile application value tendencies are conceptualized from a mobile user’s perspective. Since limited attempts have been made to study mobile value from a mobile consumer’s perspective, we hope that this study provides an initial impact on this area. Second, even though service quality has been studied for a long time, to our best knowledge, there is no empirical study examining the association between mobile users’ value tendencies and their perceptions of mobile Internet service quality. Third, to control common method bias this study applies four techniques from the recommendation of Podsakoff et al. (2003) and also utilizes two different types of measurements (i.e., Likert scale and rank-item scale). In addition, this study expands the research area on the “digital divide” beyond the view of the “access gap” of mobile Internet to the “usage gap” of mobile applications. The results of the study show that mobile Internet is not just an exclusive service for specific groups such as younger generations, higher income families, etc. The study also has practical implications for managers of mobile Internet service. First, since mobile users who
have different maturity levels have different mobile application tendencies, practitioners may use maturity (e. g., age) levels rather than socio-economic status to segment their mobile consumers for target marketing and/or product promotion purposes. For example, when mobile Internet application or content providers develop a market strategy to target the younger generations, entertainment/hedonic features of the mobile Internet applications could be highlighted more than functional/utilitarian ones. Second, since mobile users who have utilitarian tendency show negative mobile Internet service quality perceptions, mobile Internet service providers should develop and provide an enhanced mobile Internet service in order to retain the mobile users. To make mobile Internet users be satisfied, obviously, the mobile Internet service should have following service qualities at least: faster and more reliable connection, more convenient interface, and higher quality of information. 6.3 Limitations and future research There are several limitations associated with this study, which offer future research opportunities. We recognize that the survey data has a limitation. The empirical data used for this study was collected in South Korea, a fast growing mobile technology market which may have a different environment from some other countries in terms of culture and technology. Therefore, such focused data may limit the generalizability of the results. Future research may replicate this study in other countries. In addition, this study proposes only three quality dimensions (connection quality, design quality, and information quality) which are directly related to mobile Internet services. There are some other important quality dimensions, which are directly or indirectly related to the service, such as technical service and support, and consumer service related to bills or fees. These quality dimensions will be possibly considered to extend the quality dimensions of mobile Internet service. Thus, it is
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our hope that this study initiates interest in this area to develop full mobile Internet service quality dimensions.
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Dan J. Kim is an Associate Professor of Computer Information Systems at University of Houston-Clear Lake (UHCL). He earned his Ph.D. in MIS from SUNY at Buffalo. He also holds a MBA degree and MS degree in computer science. His research interests are in multidisciplinary areas such as electronic commerce, mobile commerce, information security and assurance. Recently he has focused on trust in electronic commerce, wireless and mobile commerce, and information security and assurance. His research work has been published or in forthcoming more than 80 papers in refereed journals and conference proceedings including Information Systems Research, Journal of Management Information Systems, Communications of ACM, Communications of AIS, Decision Support Systems, International Journal of Human-Computer Interaction, Journal of Organizational and End User Computing, IEEE Transactions on Professional Communication, Electronic Market, IEEE IT Professional, and so on. He received an Emerald Literati Network 2009— Outstanding Paper Award, the best-paper runner-up award at the International Conference on Information Systems (ICIS) 2003 and the best research paper award at Americas Conference on Information Systems (AMCIS) 2005. He was ranked top 22nd worldwide in terms of research productivity in the area of information systems from year 2007 to 2009 based on top three leading IS journals: ISR, MISQ and JMIS Yujong Hwang is Associate Professor of Management Information Systems in the School of Accountancy and MIS at DePaul University in Chicago. He is also Professor as International Scholar at Kyung
Inf Syst Front (2012) 14:409–421 Hee University in Korea. He was Visiting Professor in the Kellogg School at Northwestern University and received his Ph.D. in MIS from the University of South Carolina. His research focuses on ecommerce, knowledge management, and human-computer interaction. His research was published in Journal of MIS, European Journal of Information Systems, Communications of the ACM, IEEE Transactions, Decision Support Systems, International Journal of Electronic
421 Commerce, International Journal of Human-Computer Studies, Behaviour & IT, Computers in Human Behavior, Communications of AIS, Electronic Markets, Journal of Organizational and End User Computing, IEEE IT Pro, Journal of IS Education, and others. He is Associate Editor of European Journal of Information Systems, Behaviour & IT, Journal of Electronic Commerce Research, and serves on the editorial board for two major journals.
