User acceptance of mobile e-government services: An empirical study

Government Information Quarterly 30 (2013) 33–44

Contents lists available at SciVerse ScienceDirect

Government Information Quarterly journal homepage: www.elsevier.com/locate/govinf

User acceptance of mobile e-government services: An empirical study Shin-Yuan Hung a,⁎, Chia-Ming Chang b, Shao-Rong Kuo a a b

Department of Information Management, National Chung Cheng University, 168 University Rd., Ming Hsiung, Chia-Yi, Taiwan, ROC Department of Information Management, Shih Chien University Kaohsiung Campus, 200 University Rd., Neimen Kaohsiung 845, Taiwan, ROC

a r t i c l e

i n f o

Available online 9 November 2012 Keywords: M-government services e-Government services Mobile communication perspective Theory of planned behavior Information systems acceptance

a b s t r a c t The traditional focus of e-government services research has been on non-mobile services but now with the incorporation of mobile services more people are able to access these Mobile e-government services (m-government services). In addition, such services are critical for improving user-to-government communication effectiveness and maintaining relationships. The purpose of this study is to identify the factors that determine user acceptance of these services. Based primarily on the theory of planned behavior and supplemented by the mobile communication perspective, a sample of 331 users of m-government services in Taiwan was tested. The findings show that perceived usefulness, perceived ease of use, trust, interactivity, external influence, interpersonal influence, self efficacy, and facilitating conditions are critical factors. This study has given us a better understanding of critical mobile communication factors in improving user acceptance of m-government services. Implications and recommendations for research and practice are also presented and discussed. © 2012 Elsevier Inc. All rights reserved.

1. Introduction With the increasing popularity of mobile communication devices, mobile e-government services (m-government services) have become vital for improving user-to-government mobile communication. Global mobile cellular subscriptions reached approximately 4.6 billion by the end of 2009, 370 times the 1990 number (M-Communication, 2012). Meanwhile, m-government services have also continued growing (Benlamri, Adi, Al-Qayedi, & Dawood, 2010; Kim, Yoon, Park, & Han, 2004). Despite the advantages brought about by these services, users have often had difficulty ensuring well-developed wireless networks infrastructure/software, accessing user-oriented services, and have faced a lack of well-established legislation for data and information practices (E-Government, 2010). The two distinct advantages of mobile phone or mobile communication devices are the mobility of telecommunications and the supporting of many communication services content (M-Communication, 2012). One of the most complex problems governments face is being able to communicate with their citizens anytime and anywhere. Several studies (Garnett, Marlowe, & Pandey, 2008; Melkers & Willoughby, 2005; Pandey & Garnett, 2006) have indicated that communication plays a large role in either mitigating performance problems or enhancing government performance. Despite the fact that mobile communication anytime and anywhere is crucial in improving performance, some governments face ⁎ Corresponding author. E-mail addresses: [email protected] (S.-Y. Hung), [email protected] (C.-M. Chang), [email protected] (S.-R. Kuo). 0740-624X/$ – see front matter © 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.giq.2012.07.008

difficulty in communicating continuously with their citizens. For example, remote area users, homebound, low computer-literacy, or chronic illness users have had difficulty utilizing e-government services (E-Government, 2010). In the e-government services literature, past research has focused on non-m-government services acceptance, ignoring mobile communication factors. Hence the factors studied here may be of importance in explaining user acceptance of the services. Several studies have noted that value communication plays a critical role in advancing services (Cheng, 2008; Moon, 2002; Pirog & Johnson, 2008). They may gain more of a following from mobile communication than non-mobile services' delivery. Several authors have proposed that information systems (IS) security standard (Smith, 2010), trust (Teo, Srivastava, & Jiang, 2008), or interoperability (Otjacques, Hitzelberger, & Feltz, 2007) are essential to governmental IS services' delivery. To date, research has primarily been aimed at non-mobile services' delivery. Therefore, it is insufficient for m-government services to focus only on non-mobile services' delivery factors, ignoring the mobile communication factors. In order to improve m-government services, integrating IS services acceptance and mobile communication factors should be emphasized. Mobile communication factors place much more emphasis on user acceptance of IS services. Some studies have pointed out that these services come as a result of attracting mobile users (Biocca, Owen, Tang, & Bohil, 2007; Hong & Tam, 2006) or effective communication (Dabbish & Kraut, 2008; Ngwenyama & Lee, 1997). Changes in mobile communication efficiency or mobile communication content lead to changes in user acceptance of IS services. In terms of content, several authors have proposed that usefulness (Davis, 1989), compatibility

34

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

with work style (Taylor & Todd, 1995), and trustworthiness (Gefen, 2000; Gefen, Karahanna, & Straub, 2003) are critical. Ease of use (Davis, 1989) or interactivity (Jiang, Chan, Tan, & Chua, 2010; McMillan & Hwang, 2002; Sicilia, Ruiz, & Munuera, 2005) is seen to be relevant to mobile communication efficiency. In addition, external and interpersonal influences (Bhattacherjee, 2000), self efficacy (Devaraj, Easley, & Crant, 2008; Wu & Lederer, 2009), and facilitating conditions (Gallivan, Spitler, & Koufaris, 2003; Venkatesh, Brown, Maruping, & Bala, 2008) are essential to IS services acceptance. However, there has thus far been relatively little research into the effects of mobile communication factors in the context of m-government services. Hence, the goal of this research is to identify and explain factors of improving user acceptance of these services. In theoretical respects, the theory of planned behavior (TPB) is a well-defined mode for explaining IS acceptance behavior. According to TPB, acceptance behavior is determined by behavior intentions toward a specific system, where the intentions are determined by attitude, subjective norms, and perceived behavior control (Ajzen, 1991, 2001). The critical advantage of using TPB is that it provides a framework for examining the effects of external variables on system acceptance. Several studies have pointed out that user-accepted IS services can be appropriately explained by TPB (Hsieh, Rai, & Keil, 2008; Pavlou & Fygenson, 2006; Song & Zahedi, 2005). The communication perspective is defined as “communicative messages and related media used to communicate with a market” (M-Communication, 2012). Several authors have proposed that marketing communication perspectives (Bampo, Ewing, Mather, Stewart, & Wallace, 2008; Grove, Carlson, & Dorsch, 2007; Prins & Verhoef, 2007) are applicable to services acceptance. Thus, the theoretical and practical values of this study are demonstrated through TPB as a theoretical framework and supplemented by the mobile communication perspective. The findings of this study contribute to the relevant literature in three ways. First, the importance of this work lies in exploring building and mechanisms for improving user acceptance of m-government services. Second, it is found that incorporating mobile communication factors is critical. Third, the attitude toward m-government services, subjective norms, and perceived behavior control are also critical in mediating the effects of factors on user acceptance. In addition, the practical contributions of this research are also threefold. First, for governmental policy makers, the findings provide implications for the building of performance indicators. Second, for governmental agencies, this study provides critical self-evaluation indicators. Finally, for system developers, the results of this study provide practical guidance for designing m-government services. The remainder of this paper is organized as follows. Section 2 presents a comprehensive review of the m-government literature and related studies, the theory of planned behavior, and the mobile communication perspective. Section 3 presents a description of the proposed research model and hypotheses. Section 4 presents a description of the research method. Analytical results are reported in Section 5. Section 6 provides discussion and the implications of the findings. Finally, Section 7 presents the conclusion. 2. Literature review 2.1. M-government services in Taiwan The Taiwanese m-government services plan was formulated by the Research, Development, and Evaluation Commission (RDEC), Executive Yuan of Taiwan. These services were included in the “M-Taiwan” (Mobile Taiwan Program) plan which was developed in August 2004. It includes the “Broadband Pipelines Construction Program” and the “M-Taiwan Applications Promotion Program”. After the deployments of optical fiber pipelines were completed, the wireless broadband applications were promoted. The M-Taiwan plan focuses on mobile services, the mobile life-style, and mobile

learning. It aims to integrate well-established e-government services with m-government service applications to create a high quality mobile environment (Hsieh, 2007). The construction of a wireless infrastructure was designed by the Science and Technology Advisory Group (Rustagi, King, & Kirsch, 2008) of the Executive Yuan and described in the “Taiwan WiMAX Development Blueprint”. The M-Taiwan plan provided subsidies to 17 qualified enterprises to launch 26 programs. Eight local governments in Taiwan were involved in this program and they cooperated with these enterprises to establish wireless broadband networks and services (Cheng, 2008). In recent years, many development milestones of m-government services have been achieved. Most public areas and popular tourist spots in Taiwan have had free Wi-Fi services since last October (FAQs, 2011). Several other examples include networks of improving the ubiquitous life, creating e-opportunities in a ubiquitous network society, life-enhancing applications for the society, and electronic governance of it. In the near future, the government plans to provide more high-quality and convenient m-government service applications (M-Taiwan, 2010). 2.2. M-government services and related studies M-government services are critical applications of mobile communication services in the e-government. Several studies have noted that m-government service innovations or comparisons can be of enormous value to mobile services. Several more studies (Garnett et al., 2008; Melkers & Willoughby, 2005; Pandey & Garnett, 2006) have pointed out that communication plays a large role in either mitigating performance issues or enhancing government performance. In addition, appropriate IT mechanisms place value on improving mobile interactive communication. To date, research on e-government services has primarily fitted the users' cost-benefit analysis of the IT services delivery channel. Hence, m-government services have been particularly influential in contributing insight into mobile communication effectiveness (for e-government services). M-government services are a critical prerequisite to improving the effectiveness of mobile communication. Several studies have noted that their innovations or comparisons can be of enormous value to mobile services. For example, e-government services have often had difficulty reaching remote areas users, homebound users, low computer-literacy users, or chronic illness users (E-Government, 2010) and some consumers have often had difficulty entering the mobile communication market (Grant, 2007). In addition, appropriate IT mechanisms are valuable for improving mobile interactive communication. To date, research on e-government services has primarily been on trustworthiness and fitting the user's cost–benefit analysis to the IT services' delivery channel. Thus, user acceptance of m-government services is vital to the communication effectiveness of m-government services. Previous studies have emphasized various factors for improving service delivery effectiveness. Perceived usefulness and perceived ease of use are critical factors in user acceptance. Several authors (Cheng, 2008; Moon, 2002; Pirog & Johnson, 2008) have indicated that investment values' communication plays an important role in supporting the arguments for e-government services. In addition, trust has received a great deal of emphasis. A trustworthy and useful user perceives that the cost-benefit analysis of e-government services cannot lead to effective mobile interactive IT services. With e-government shifting to m-government services, there has been a change of emphasis to integrate e-government service mechanisms and mobile communication mechanisms. Hence, it is insufficient for m-government services to focus only on non-mobile service delivery factors, ignoring the influence of mobile communication factors. Another critical distinction between m-government services and traditional e-government services is that while traditional services

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

allow more non-mobile services delivery, m-government services allow relatively more mobile communication elements. Citizens can participate more in online discussions of political issues with increasing frequency, improve mobile communication efficiency, enhance mobile communication convenience and flexibility, share the government's modern image, receive more customized services, and enjoy higher accessibility of services (E-Government, 2010). In addition, unlike traditional e-government services, modern governments need to be responsible for well-developed wireless and mobile networksrelated infrastructure and software, avoid hyper-surveillance concerns, maintain reliable citizens' privacy policy records, offer easy access to alternative forms of government services, legislate for data and information practices, and improve government transparency and accountability (E-Government, 2010). Several authors have proposed that IS security standards (Smith, 2010), trust (Teo et al., 2008), or interoperability (Otjacques et al., 2007) are essential to government IS services' delivery. In addition, several authors have also proposed that perceived usefulness and ease of use (Davis, 1989), compatibility (Taylor & Todd, 1995), trust (Gefen, 2000; Gefen et al., 2003), interactivity (Jiang et al., 2010; McMillan & Hwang, 2002; Sicilia et al., 2005), external and interpersonal influences (Bhattacherjee, 2000; Bhattacherjee & Sanford, 2006; Montoya, Massey, & Khatri, 2010), self efficacy (Devaraj et al., 2008; Wu & Lederer, 2009), and facilitating conditions (Gallivan et al., 2003; Venkatesh et al., 2008) are essential to IS services acceptance. A user's planned behavior of m-government services may place much more emphasis on appropriate mechanisms. Therefore, there is the need to explain how factors improve user acceptance of m-government services through the theory of planned behavior. 2.3. Theory of planned behavior TPB has been validated as a well-researched model of explaining user planned acceptance behavior. However, this has been neglected in the popular context of m-government services. Several studies have indicated that user-accepted IS services can be appropriately explained by TPB (Hsieh et al., 2008; Pavlou & Fygenson, 2006; Song & Zahedi, 2005). Finding suitable mechanisms to improve user acceptance of m-government services is beneficial for extending TPB to explain IT services in a specific context. For example, Taylor and Todd indicate the importance of adding more feasible mechanisms to improve the applicability of TPB. To date, the mechanisms which improve user acceptance of m-government services have not been fully investigated. Consequently, TPB is critically needed to improve the user's attitude, subjective norm and perceived behavior control regarding these services. First, from the TPB perspective, the attitude toward m-government services can be positively affected by mobile communication elements, because mobile interactive communication is beneficial for a user's belief evaluations. Second, the subjective norms of m-government services can also be positively affected by mobile communication elements, since mobile interactive opinion exchanges between users and government have a significant positive impact on users' subjective norms. Finally, perceived behavior control of m-government services can also be positively affected by mobile communication elements, because mobile interactive hardware/software resources exchanges between users and government also have a positive impact on users' perceived behavior control. In these respects, this study extends the TPB's theoretical context to the m-government services context. 2.4. Mobile communication perspective The mobile communication perspective is seen as crucial in demonstrating communication effectiveness. However, like TPB it has been neglected in the context of m-government services. Because of

35

the explanatory power of TPB, many empirical studies have been validated in the context of either public or private sectors. For example, Taylor and Todd have indicated the importance of adding more feasible mechanisms to improve TPB. Based on the mobile communication perspective, several important factors should be emphasized. Some authors have proposed that marketing communication perspectives (Bampo et al., 2008; Grove et al., 2007; Prins & Verhoef, 2007) are essential to services' acceptance. The attitude toward m-government services is affected mainly by perceived usefulness (Davis, 1989), perceived ease of use (Davis, 1989), compatibility (Taylor & Todd, 1995), trust (Gefen, 2000), and interactivity (Sicilia et al., 2005). The subjective norm is affected by external influences and interpersonal influences separately (Bhattacherjee, 2000; Hung, Chang, & Yu, 2006). To improve perceived behavior control, both self-efficacy and facilitating conditions must be emphasized (Bhattacherjee, 2000; Hung et al., 2006). Hence, the mobile communication perspective is used as a complementary perspective to explain user acceptance of m-government services.

3. Research model and hypotheses The theoretical model is presented in Fig. 1. The proposed research model includes nine external variables based on theoretical arguments from the mobile communication perspective. Two dimensions are identified communication efficiency and communication content (Bampo et al., 2008; Grove et al., 2007; Prins & Verhoef, 2007) in using mobile access to e-government services. The selection of these variables is supported by previous studies in e-government services' acceptance or mobile communication literature (Hung et al., 2006; M-Communication, 2012). Twelve hypotheses and their supporting studies are summarized in Table 1. Greater perceived usefulness and perceived ease of use will result in a more positive attitude toward m-government services. According to TPB, the attitude toward objects is affected by the users' belief evaluations toward them (m-government services, in this study) (Ajzen, 1991; Madden, Ellen, & Ajzen, 1992). Positive belief evaluations toward m-government services may result from either mobile communication efficiency or manageable mobile communication content. Based on the mobile communication perspective, integrative services' content is seen to be relevant to a user's perceived usefulness of using m-government services. Several studies have noted that service communication content is associated with perceived usefulness (Bhattacherjee, 2000; Davis, 1989; Taylor & Todd, 1995). In addition, based also on the mobile communication perspective, convenient mobile communication services are closely related to a user's perceived ease of use (for using m-government services). Numerous studies stress that service communication efficiency relates to perceived ease of use (Bhattacherjee, 2000; Davis, 1989; Taylor & Todd, 1995). Accordingly, the increasing of a user's perceived usefulness and ease of use induced by using m-government services may lead to a more positive attitude toward m-government services. Therefore, the first two hypotheses of this study are as follows. H1. A higher level of perceived usefulness leads to a more positive attitude toward m-government services. H2. A higher level of perceived ease of use leads to a more positive attitude toward m-government services. Higher compatibility will result in a more positive attitude toward m-government services. Such an attitude may result from a user's belief evaluations about useful and manageable m-government services content. Based on the mobile communication perspective, manageable m-government services content is associated with their compatibility with a user's working ways. Several studies have noted

36

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

Perceived Usefulness

Perceived Ease of Use

H1 H2

Compatibility H3 Attitude Trust

H4

H5 H10

Interactivity

External Influence

H6 Subjective Norm

H11

Intention

H7 Interpersonal Influence H12

Self Efficacy H8 Perceived Behavior

H9

Control

Facilitating Condition

Fig. 1. The Research Model.

that service communication content is associated with compatibility (Chau & Tam, 1997; Jiang & Benbasat, 2007; Taylor & Todd, 1995). Accordingly, higher compatibility induced by using m-government services may lead to a more positive attitude toward them. Therefore, the third hypothesis of this study is as follows. H3. A higher level of compatibility leads to a more positive attitude toward m-government services. Higher trust will result in a more positive attitude toward m-government services. A positive attitude may be a consequence of users' belief evaluations about sincere mobile communication. Mobile communication at anytime and anyplace is associated with mutual trust building. Numerous studies (Gefen, 2000; Gefen et al., 2003; Pavlou & Fygenson, 2006) stress that service communication

content relates mainly to trustworthy sources. Accordingly, higher trust induced by using m-government services may lead to a more positive attitude. Thus, the following hypothesis has been derived. H4. A higher level of trust leads to more positive attitude toward m-government services. Higher interactivity will result in a more positive attitude toward m-government services. A positive attitude toward m-government services may follow from a user's belief evaluations about mobile interactive communication. Mobile communication is associated with a user's perceived interactivity of m-government services. Several studies have noted that service communication is associated with interactivity (Jiang et al., 2010; McMillan & Hwang, 2002; Sicilia et al., 2005). Accordingly, higher interactivity induced by using m-government

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44 Table 1 Summary of research hypotheses. Hypothesis

Supporting studies

H1

Perceived usefulness →attitude

H2

Perceived ease of use →attitude

H3

Compatibility→ attitude

H4

Trust →attitude

H5

Interactivity → attitude

H6

H10

External influence → subjective norm Interpersonal influence → subjective norm Self efficacy → perceived behavior control Facilitating condition →perceived behavior control Attitudes → intention

H11

Subjective norm→ intention

H12

Perceived behavior control →intention

(Bhattacherjee, 2000; Davis, 1989; Taylor & Todd, 1995) (Bhattacherjee, 2000; Davis, 1989; Taylor & Todd, 1995) (Chau & Tam, 1997; Jiang & Benbasat, 2007; Taylor & Todd, 1995) (Gefen, 2000; Gefen et al., 2003; Pavlou & Fygenson, 2006) (Jiang et al., 2010; McMillan & Hwang, 2002; Sicilia et al., 2005) (Bhattacherjee, 2000; Bhattacherjee & Sanford, 2006) (Bhattacherjee, 2000; Montoya et al., 2010) (Devaraj et al., 2008; Wu & Lederer, 2009) (Gallivan et al., 2003; Venkatesh et al., 2008) (Ajzen, 1985, 1991; Bhattacherjee, 2000) (Ajzen, 1985, 1991; Bhattacherjee, 2000) (Ajzen, 1985, 1991; Bhattacherjee, 2000)

H7 H8 H9

services may lead to a more positive attitude toward them. Thus, the following hypothesis has been derived. H5. A higher level of interactivity leads to more a positive attitude toward m-government services. A user's normative beliefs will lead to subjective norms toward m-government services. According to TPB, subjective norms refer to perceptions of the preferences of significant others regarding the worth of engaging in a specific behavior (Ajzen, 1991; Madden et al., 1992). Attitude toward m-government services is affected by suggestions of both attractive spokespersons in the mass media and frequently interactive friends. Several studies have noted that both salient persons' opinions are critical for improving subjective norms (Bhattacherjee, 2000; Bhattacherjee & Sanford, 2006). From the communication perspective, immediate answers to questions and sign in at IT services for information are seen to be relevant to a user's mobile communication. Numerous studies stress that service communication relates mainly to interpersonal influence (Bhattacherjee, 2000; Montoya et al., 2010). Hence, through more external and interpersonal mobile communication, external influence and interpersonal influence can lead to a more positive attitude toward m-government services. Thus, the following hypotheses have been derived. H6. A higher level of external influence leads to a more positive subjective norm in m-government services. H7. A higher level of interpersonal influence leads to a more positive subjective norm in m-government services. A user's self-efficacy and facilitating conditions will lead to perceived behavior control toward m-government services. According to TPB, perceived behavior control is defined as the individual's perception of how easy or difficult it is to perform a specific action (Ajzen, 1991, 2001). It is seen to be relevant to a user's mobile communication, because resources, knowledge, and ability to use m-government services can be acquired from immediate answers to questions, manageable services resources, and concurrent knowledge sharing, respectively. Self efficacy, defined as the conviction that one can successfully execute a given behavior (Bandura, 1997), is seen to be relevant to effective conversation, immediate answers to questions, and attention-keeping services.

37

Numerous studies stress that the subjective norm relates mainly to the interpersonal influence of service communication (Devaraj et al., 2008; Wu & Lederer, 2009). Accordingly, through a user's mobile communication, self-efficacy can lead to perceived behavior control. In addition, the manageable resources required to use m-government services can also lead to the improving of behavior control. Numerous studies stress that the subjective norm relates mainly to interpersonal influence of service communication (Gallivan et al., 2003; Venkatesh et al., 2008). Thus, this study proposes the following hypotheses: H8. A higher level of self-efficacy leads to more positive perceived behavior control in m-government services. H9. A higher level of facilitating conditions leads to more positive perceived behavior control in m-government services. In the TPB model, attitudes toward behavior, subjective norms, and perceptions of behavior control are generally found to accurately predict individual behavior intentions (Ajzen, 1991, 2001). Prior research on TPB supports this assertion, demonstrating that they can indeed significantly affect the intention to use new IS services (Bhattacherjee, 2000; Taylor & Todd, 1995). In the field of e-government services, researchers also proposed that these factors affect user acceptance. Numerous studies stress that behavior intention relates mainly to attitude, subjective norms, and perceived behavior control of service communication (Ajzen, 1985, 1991; Bhattacherjee, 2000). Although it is now widely recognized that these factors are critical for understanding and predicting intentions and behavior, in specific contexts, clarifying the relationships of them in the context of mgovernment services has not yet happened. Furthermore, mgovernment services are the core for more interactive e-government services. Accordingly, the following hypotheses have been derived from the theoretical framework of the TPB: H10. A positive attitude leads to a more positive behavior intention to accept m-government services. H11. A higher level of subjective norm leads to a more positive behavior intention to accept m-government services. H12. A higher level of perceived behavior control leads to a more positive behavior intention to accept m-government services.

4. Research method 4.1. Data collection and sample representativeness A web-based survey was conducted with m-government services users. We posted our questionnaire on the Taiwanese e-government website with the assistance of a public affairs forum administrator. The duration of the post time was one month. To increase the response rate, the participants fulfilling all items were rewarded with lottery participation. To ensure that participants were aware of the nature of the prizes, this study encouraged careful completion of the questionnaire with the prize as the incentive. The sample for this study consisted of m-government services users. To ensure that the beliefs measured were based on direct behavioral experiences, only responses from those who had previously used m-government services were included. The total number of participants was 356; 331 were valid. No response analysis was also applied to ensure no evidence of a ‘no response bias’, a procedure recommended by Armstrong and Overton (Armstrong & Overton, 1977). All respondents were divided into two groups based on the return dates. Compared to gender, age, education, job, marriage status, and computer usage time, the two groups demonstrated no significant differences based on the independent sample t-test. In addition, compared to the means of constructs

38

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

Table 2 Demographic profile of all respondents. Variable Gender Age

Education

Annual income

Marriage status Computer usage hours per week

Male Female b20 years old 21–30 years old 31–40 years old Senior high school Undergraduate Graduate bUS$11,198 US$11,198–US$18,663 US$18,663–US$29,860 >US$29,860 Single Married b7 h 7 h–14 h 14 h–21 h 21 h–28 h >28 h

Table 3 Results of the validity and reliability analysis. Count

Percentage %

219 112 26 281 24 11 212 108 266 57 6 2 312 19 78 93 34 45 81

66.2 33.8 7.9 84.9 7.3 3.3 64.0 32.6 80.4 17.2 1.8 0.6 94.3 5.7 23.6 28.1 10.3 13.6 24.5

Perceived usefulness Perceived ease of use Compatibility Trust Interactivity External influence Interpersonal influence Self efficacy Facilitating condition Attitude Subjective norm Perceived behavior control Behavior intention

# of items

Composite reliability

Variance extracted percent

Factor loading

4 3

0.86 0.89

61 73

0.70–0.83 0.84–0.87

3 2 3 3 3

0.86 0.87 0.81 0.81 0.83

68 77 59 59 62

0.81–0.83 0.87–0.88 0.73–0.79 0.69–0.82 0.72–0.83

3 3

0.81 0.76

59 52

0.61–0.88 0.58–0.88

3 3 3

0.81 0.88 0.85

59 72 65

0.64–0.86 0.82–0.88 0.78–0.85

3

0.78

54

0.64–0.80

in this study, the two groups also showed no significant differences. Therefore, evidence of a ‘no response bias’ is demonstrated.

reliability. The structural model that best fitted the data was identified, and the hypotheses were tested between constructs using this model.

4.2. Instrument development

5. Results

For instrument construction, the items used for each investigated variable were primarily adopted from previous studies, while incorporating the necessary validation and wording changes. Specifically: items measuring perceived usefulness and perceived ease of use were adapted from (Davis, 1989). Items measuring compatibility were adapted from (Taylor & Todd, 1995). Items measuring trust were adapted from (Gefen, 2000). Items measuring interactivity were adapted from (Sicilia et al., 2005). Those measuring external influences and interpersonal influences, attitude toward m-government services, subjective norm, and intention to accept m-government services were adapted from Bhattacherjee (2000) and Taylor and Todd (1995). All items were measured using a seven-point Likert-type scale, with anchors ranging from “strongly agree” to “strongly disagree.” In the pretest, to ensure the content validity, this study had five professors and experts review the questionnaire. It was then modified in accordance with their recommendations. In the pilot study, analysis of the responses of 20 random respondents revealed no problems with the survey design. The data was also examined for completeness of responses. Subsequently, some changes were made to the questionnaires. Following this, the questionnaire was administered.

5.1. Users' profile

4.3. Statistical analysis The data were analyzed using AMOS 7.0 structural equation modeling (SEM) software. According to Hair, Anderson, Tatham, and Black (1998), the two main reasons for using SEM were: (1) to provide a straightforward method for dealing with multiple relationships simultaneously, while providing statistical efficiency and (2) to assess relationships comprehensively, while providing a transition from exploratory to confirmatory analysis. SEM is especially suitable for testing a series of relationships constituting a large-scale model or an entire theory. In fact, SEM has been identified as an appropriate covariance-based approach for studies with a strong basis on ‘a priori’ theory. This study is well suited for confirmatory testing of the fit of the proposed theoretical model to observe data using SEM. Following the approach suggested by Anderson and Gerbing (1988), the analysis of data from the 331 samples was conducted in two stages. The measurement model was estimated using a confirmatory factor analysis to test whether the constructs possessed sufficient validation and

The profile of m-government services users who completed the survey is presented in Table 2. Male users composed 66.2% of the sample and female users 33.8%. Users' ages fell predominantly between 21 and 30 (84.9%), and the educational level was primarily undergraduate or graduate degree (96.6%). The majority of marriage statuses were single (94.3). Respondents whose computer usage time exceeded 7 h per week constituted 76.5% of the sample. 5.2. Reliability and validity The psychometric properties of the scales were assessed in terms of composite reliability, discriminant validity, and factor loadings. Table 3 reports item factor loadings, average variances extracted, and composite reliability for this study. In terms of assessing the latent factors' reliabilities, the composite reliability and their reflective measurement items were calculated, along with the average variances extracted for each construct (Fornell & Larcker, 1981). The scales' reliabilities ranged from 0.76 to 0.89, with the average variance extracted ranging from 52% to 77%. The factor loadings ranged from 0.58 to 0.88. Hence, the Likert-scales were found to have good reliability. In terms of discriminated validity, two criteria were assessed (Chin, 1998). First, items should load more highly on the construct they are intended to measure than on other constructs. Second, the square root of the average variance extracted must be larger than the inter-construct correlations. The square root of the average Table 4 Results of the model goodness-of-fit. Fit index

Recommended criteria

Results in this study

Chi-square/degree of freedom GFI RMR RMSEA TLI NFI IFI CFI

b3.0 >0.9 b0.08 b0.08 >0.9 >0.9 >0.9 >0.9

1.77 0.90 0.10 0.05 0.94 0.90 0.95 0.95

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

39

Common criteria for the SEM have been previously suggested, and the results are presented in Table 4. Some common fit indices reported in the SEM are designed to identify model goodness-of-fit. Most indices exceeded their respective common acceptance levels, suggesting that the research model provided a reasonably good fit to the data. The results are shown in Fig. 2 (though the measurement model and belief correlations are omitted for clarity). Eleven of the 12 hypothesized paths are significant at the 0.1, 0.05, and 0.01 p-value levels. Fig. 2 displays all structural relationships among the studied constructs. Fig. 2 indicates that the model explains 59% of the variance of intention to accept m-government services. Perceived usefulness, perceived ease of use, trust, and interactivity are seen to explain 72% of the variance of attitude toward m-government services. External and interpersonal influences explain 69% of the variance of the

variance extracted from each construct was greater than 0.70 and was also greater than the correlations between the construct and other constructs, indicating that all constructs share more variances with their indicators than they do with other constructs. Hence, the Likert-scales were found to have discriminated validity. Finally, Anderson and Gerbing (1988) suggest that the assessment of convergent validity requires assessing the loading of each observed indicator on its latent construct. The results of the confirmatory factor analysis (CFA) found that all loadings were significant at p-value b 0.01. Thus, this strong evidence demonstrates satisfactory convergent validity. Given that the required assessments of reliability and validity in the measurement model are satisfactory, the subsequent process of identifying the structural model that best fits the data is detailed in the next section.

Perceived Usefulness

Perceived Ease of Use

0.628*** 0.163***

Compatibility

Attitude R2=0.72 Trust

0.079*

0.083** 0.532***

Interactivity

External Influence

0.121*** Subjective Norm 0.593***

0.319***

Intention R2=0.59

R2=0.69

Interpersonal Influence 0.103**

Self Efficacy 0.496*** Perceived Behavior 0.260 Facilitating Condition

Control R2=0.66

Fig. 2. Results of the research model. * denotes significance at the p b 0.1 level; ** denotes significance at the p b 0.05 level; *** denotes significance at the p b 0.01 level; and - - -> denotes not significant.

40

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

Table 5 Summary of the research findings. Hypothesis

Hypothesized direction

Critical ratio

Finding

H1: Perceived usefulness →attitude H2: Perceived ease of use → attitude H3: Compatibility →attitude H4: Trust → attitude H5: Interactivity → attitude H6: External influence →subjective norm H7: Interpersonal influence →subjective norm H8: Self efficacy → perceived behavior control H9: Facilitating condition →perceived behavior control H10: Attitude →intention H11: Subjective norm → intention H12: Perceived behavior control →intention

+

15.17⁎⁎⁎

Supported

+

3.94⁎⁎⁎

Supported

+ + + +

0.80⁎ 1.90⁎⁎ 2.02⁎⁎ 2.76⁎⁎⁎

Not Supported Supported Supported Supported

+

13.52⁎⁎⁎

Supported

+

10.87⁎⁎⁎

Supported

+

5.69⁎⁎⁎

Supported

+ + +

12.43⁎⁎⁎ 7.44⁎⁎⁎ 2.40⁎⁎

Supported Supported Supported

Note: the critical ratio (Devaraj, et al.) is defined as “Critical ratio = Estimate / Standard Errors”. The CR values greater than 1.64, 1.96 and 2.32 are statistically significant at 0.1, 0.05 and 0.01 levels, respectively. The results of structural equation modeling are standardized maximum likelihood path coefficients for the hypothesized model. ⁎ Denotes significance at the p b 0.1 level. ⁎⁎ Denotes significance at the p b 0.05 level. ⁎⁎⁎ Denotes significance at the p b 0.01 level.

subjective norm. Self-efficacy and facilitating conditions explain 66% of the variance of perceived behavior control. 5.3. Hypothesis testing Table 5 indicates that 11 hypotheses were significantly supported and 1 hypothesis was not empirically supported by the data. In summary, perceived usefulness, perceived ease of use, trust, and interactivity are identified as the main determinants of attitude toward m-government services. External and interpersonal influences are the main determinants of the subjective norm. Self-efficacy and facilitating conditions are the main determinants of perceived behavior control. Attitude toward m-government services, the subjective norm, and perceived behavior control are the main determinants of the intention to accept m-government services. Aside from the above hypotheses, the results indicate that compatibility did not significantly affect attitude toward m-government services in this study. 6. Discussion This study proposed and tested an m-government services acceptance model. Past m-government services research focused mainly on mobile services or e-government services studies. User acceptance of m-government services may contribute considerably to a more robust technological development or value realization of e-government services. In addition, as a new type of e-government services, this study is pioneering with respect to complementing the IS services acceptance study through focusing on the mobile communication aspect. In terms of communication content factors on attitude toward m-government services, significant effects of perceived usefulness and trust were observed. With respect to perceived usefulness, the finding is in line with previous IS services studies (Bhattacherjee, 2000; Bhattacherjee & Sanford, 2006; Pavlou & Fygenson, 2006). In terms of trust, the finding is also generally compatible with the results in previous studies (Lowry, Vance, Moody, Beckman, & Read, 2008; Pavlou & Fygenson, 2006; Robert, Denis, & Hung, 2009). Hence, in the context of m-government services, attitude is affected

mainly by both useful performance-related services and trustworthy question–answer services. In terms of communication efficiency factors on attitude toward m-government services, the significant effects of perceived ease of use and interactivity were demonstrated. With respect to perceived ease of use, this study emphasizes that ease of m-government services use in maintaining mobile communication has a significant effect on the attitude toward them. The finding is in line with past IS service contexts (Bhattacherjee, 2000; Sabherwal, Jeyaraj, & Chowa, 2006) and complements the specific IS service context with relatively lower ease of use (Hu, Chau, Sheng, & Tam, 1999). In terms of inter-activity, this study emphasizes m-government services' inter-activity affecting users' attitudes toward m-government services and complements online product presentations' efficacy (Jiang & Benbasat, 2007), website success (Palmer, 2013), and users' affective involvement in functional products on websites (Jiang et al., 2010). Hence, a user's attitude toward m-government services is affected mainly by the perceived ease of use and inter-activity induced by the services. The results of this study indicate that external influence and interpersonal influence are the main determinants of the subjective norm. Several studies (Bhattacherjee, 2000; Song & Zahedi, 2005) have noted that salient friends and mass media information are highly pertinent to a user's subjective norm toward IS services. Therefore, this study tends to validate the importance of external influence and interpersonal influence in understanding a users' acceptance in the context of m-government services. The results of this study also indicate that self-efficacy and facilitating conditions are the main determinants of perceived behavior control. Numerous studies (Bhattacherjee, 2000; Bock, Kankanhalli, & Sharma, 2006; Bulgurcu, Cavusoglu, & Benbasat, 2010) have noted that users' self-efficacy or hardware/software facilitating resources are highly pertinent to users' perceived behavior control or intention toward IS services. Therefore, this study tends to validate the importance of self-efficacy and facilitating conditions in understanding users' acceptance of m-government services. Consistent with our hypotheses, the results of this study indicate that attitude toward m-government services, the subjective norm, and perceived behavior control are the main determinants of intention to accept m-government services. In this context, the findings appear to be consistent with previous IS services acceptance studies (Bhattacherjee, 2000; Pavlou & Fygenson, 2006; Taylor & Todd, 1995). Therefore, this study tends to validate the importance of these factors in understanding users' intention to accept m-government services and, as such, extends the theoretical applicability of TPB. Regarding the relations between compatibility and attitude toward m-government services not being empirically supported by the data, a partial explanation for this may lie in the fact that these services (in Taiwan) are gradually developing and are not yet complete. Accordingly, this could lead to compatibility being reduced in importance as a variable in our study. 6.1. Implications for research In recent years, there has been an increased interest in studying IS services acceptance in conjunction with the marketing communication context. It is generally agreed by IS as well as marketing researchers that m-government services may be beneficial to effective communication performance. Our research contributes to related literature in the following important areas. First, appropriate mechanism factors may be critical for improving user acceptance of m-government services. The user's planned acceptance behavior may be a consequence of effective communication efficiency and communication content factors supporting mutual communication and contributions. Several previous IS planned acceptance behavior studies have explored factors supporting the user's communication performance through TPB. However, there is a very

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

limited breadth of study on user planned acceptance behavior. Hence, this study contributes to exploring mechanism factors for improving users' planned acceptance behavior and extending the TPB theoretical application to the m-government services context. Second, users' planned acceptance behavior may be affected by effective communication efficiency and communication content factors. Their behavior may be a consequence of effective communication efficiency and communication content factors. For example, several previous manageable services contents and interactive communication coexisting studies have emphasized the interplay of cognition and affect in the context of social interpersonal interaction (McAllister, 1995) or shoppers' behavior (Chea & Luo, 2008; Homburg, Koschate, & Hoyer, 2006; Shiv & Fedorikhin, 1999). Both the thought processes and emotional experiences of m-government services users may be separately affected by manageable services content and interactive communication factors. However, there is a very limited breadth of study on this. Hence, this study contributes to exploring these two factors for the improving of users' planned acceptance behavior and for extending marketing communication theoretical application to the m-government services context. Finally, attitude, the subjective norm, and perceived behavior control may mediate the effects of effective communication efficiency and communication content factors on user planned acceptance behavior of m-government services. First, concerning user acceptance behavior, the user's sum of communication content beliefs about acceptance behavior may mediate the effects of the two communication content factors (perceived usefulness and trust). Second, the user's sum of communication efficiency beliefs about acceptance behavior may mediate the effects of the communication efficiency factors (perceived ease of use and interactivity). Third, the effective communication efficiency and communication content influence of others in the user's social environment can mediate the effects of two factors (external influence and interpersonal influence) on user acceptance behavior. Finally, they can also mediate the effects of two factors (self-efficacy and facilitating condition) on user acceptance behavior. Hence, in order to explain user acceptance of m-government services, attitude, the subjective norm, and perceived behavior control play critical roles in mediating the effects of communication efficiency and communication content factors. 6.2. Implications for practice In light of the findings from this study, we provide some implications and recommendations for m-government services policy makers, government agency officials, and m-government system developers. Policy makers can enhance citizens' acceptance of m-government services (through several directions) in several ways. First, the main communication efficiency and communication content factors have been identified for policy makers responsible for the future marketing planning of m-government services. Accordingly, to carefully evaluate the effectiveness of m-government services, policy makers can improve marketing planning through monitoring these factors as effectiveness indicators. Second, important communication content determinants of attitude are perceived usefulness and trust. We suggest that the policy makers develop communication attitude improvement planning by providing useful citizens-productivity-related information and trustworthy responses to their questions. Third, important communication efficiency determinants of attitude are perceived ease of use and interactivity. We suggest that the policy makers develop communication attitude improvement planning by providing user-friendly guidance or providing real-time interactive question answers for their citizens. Fourth, interpersonal influences and external influences have a large impact on subjective norms. Accordingly, we suggest that much more emphasis is placed on both increasing peer influence and mass media advertising influence for the citizens. Fifth, self-efficacy and facilitating conditions have a large impact on perceived behavior control.

41

Accordingly, we suggest that the policy makers place much more emphasis on both increasing users' usage knowledge and hardware/ software resources. Finally, attitude, the subjective norm, and perceived behavior control are critical for developing the intention to accept m-government services. Accordingly, we suggest that intentional improvement planning is developed by increasing citizens' positive perceptions of using the services, enhancing users' influence on potential m-government services citizens, and improving their behavior control of using these services. This study also illustrates several practical directions along which government agency officials can enhance citizens' acceptance of the services. Since the main communication efficiency and communication content factors have been identified t hose responsible can evaluate and thus improve marketing planning through monitoring these factors. Second, important communication content determinants of attitude toward m-government services are: perceived usefulness and trust. We suggest that government agency officials develop communication attitude improvement planning by providing useful citizens-productivity-related information and trustworthy responses to their questions. Third, important communication efficiency determinants of attitude toward m-government services are: perceived ease of use and interactivity. We suggest that those responsible develop communication attitude improvement planning by providing user-friendly guidance or providing real-time interactive question answers. Fourth, interpersonal influences and external influences have a large impact on subjective norms concerning m-government services. Accordingly, we suggest that agency officials place much more emphasis on both increasing peer influence and mass media advertising influence for their citizens. Fifth, self-efficacy and facilitating conditions have a large impact on perceived behavior control. Accordingly, we suggest that government agency officials place much more emphasis on both increasing user's usage knowledge and hardware/ software resources for its citizens. Finally, a positive attitude, the subjective norm, and perceived behavior control are critical for developing the intention to accept m-government services. Accordingly, we suggest that intention improvement planning is developed by increasing citizens' positive perceptions of using the services, enhancing users' influence on potential m-government services citizens, and improving citizens' behavior control of using its services. For m-government system developers, some implications are as follows: First for future marketing planning for m-government services, the main communication efficiency and communication contents factors have been identified. Accordingly, to effectively evaluate the effectiveness of the services, developers can improve marketing planning through monitoring these factors. Second, important communication content determinants of attitude toward m-government services are perceived usefulness and trust. We suggest that developers develop communication attitude improvement planning by providing useful citizens-productivity-related information and trustworthy responses to citizens' questions. Third, important communication efficiency determinants of attitude are perceived ease of use and interactivity. We suggest that system developers develop communication attitude improvement planning by providing user-friendly guidance or providing real-time interactive question answers. Fourth, interpersonal influences and external influences have a large impact on subjective norms concerning m-government services. Accordingly, we suggest that developers place much more emphasis on both increasing peer influence and mass media advertising influence for citizens. Fifth, self-efficacy and facilitating conditions have a large impact on perceived behavior control. Accordingly, we suggest more emphasis on both increasing users' usage knowledge and hardware/software resources for citizens. Finally, attitude toward m-government services, subjective norms, and perceived behavior control are critical for developing the intention to accept m-government services. Accordingly, we suggest increasing citizens' positive perceptions, enhancing users' influence on potential citizens, and improving behavior control.

42

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

While this study discusses factors affecting m-government services acceptance from TPB, some factors and perspectives have not been mentioned, but they are still important issues for policy makers and system developers. First, they s should note that compared to non-mobile services, mobile services are exposed to a more dangerous environment. Because wireless networks can be accessed by everyone, hackers may intercept signals (Lu, Liu, Yu, & Wang, 2008). The protection of wireless data transmission and storage is of more concern than wired data. For example, results show that about 75% of consumers worry about security and transaction risks when using mobile payment services (Lu, Yang, Chau, & Cao, 2011). Because the m-government services generally store a lot of citizens' information, lack of information security may urge policy makers to provide useless services leading to low service acceptance (Bertot, Jaeger, & Hansen, 2012; Schaupp & Bélanger, 2005). For example, because of the absence of an information security plan, the e-government services in Africa are limited to static website information (Maumbe, Owei, & Alexander, 2008). Therefore, ensuring the security of personally identifiable information cannot be ignored by policy makers in the promoting of m-government services. Second, policy makers should consider users' affordability of m-government services. Although m-government services give users a more convenient life style, they may have to spend more money on wireless connections to get these services. For some users, these extra expenses are not affordable, especially for users in rural areas (Akca, Sayili, & Esengun, 2007). Since the goal of m-government is to serve the greatest possible number of people, policy makers should lower users' acquisition costs so that most people can access these services. Policy makers may negotiate with enterprises to provide reasonable monthly subscription fees or even offer free use of government services. For example, the government in Taiwan have provided free Wi-Fi services of 1 Mbps bandwidth in some public areas and famous tourist attractions since last October (FAQs, 2011). Third, this paper discusses the usage of mobile services from the general users' point of view. However, certain user groups' characteristics have not been considered in the paper. There are large numbers of people who are having difficulty in accessing internet services across the globe. In the U.S., about 12 million people suffer from blindness, deafness, severe vision or hearing impairment and more than 25 million in the U.S. experience some sort of vision trouble (Census, 2006; Pleis, Lucas, & Ward, 2009). In addition, the trend of societal aging also increases potential senior users, who may reach 19% of the total population in the U.S. and even 32% in Japan by 2030 (Niehaves, 2011). For these groups of users, the government should provide specific options in the mobile service. These options may include alternative texts for images and audio guides, avoiding blinking text in the web pages, default values for text and option inputs, etc. (Yu & Parmanto, 2011). These elements relate greatly to the accessibility and usability of mobile services for these user groups (Olalere & Lazar, 2011). They provide new opportunities and challenges to m-government services (Bertot et al., 2012). Policy makers should continually pay attention to these users. Fourth, the services usually want to make the user's life easier so that they are welcomed by more people. Nevertheless, some m-government services suffer from more controversies than other services. For example, the provision of public transportation information, national weather prediction, and travel documents over mobile phones accelerates the transmission of information and avoids waste paper. But for remote e-voting, the opposing candidates value the transparency of the voting process more than its convenience (Zissis & Lekkas, 2011). Most arguments regarding remote e-voting are not concerning technical feasibilities but on possible manipulations by individuals. The differences among m-government services may affect the acceptance of a particular service so policy makers should be careful. In addition to these issues, there are some limitations when policy makers and service developers apply the findings of this study. First, the rate of Taiwan's mobile phone popularization is over 100% (Cheng, 2008) and Taiwan is listed among the high access countries

in the digital access index, which measures the overall ability of individuals in a country to access and use new information communication technologies (DAI, 2012). It increases the possibility of successful m-government services. People may use m-government services when the government provides enough motivation, such as extra benefits or free trials. It is not easy for every country to ensure the same advantages. The findings in the research may not be applicable to countries with a low mobile phone popularization rate. Second, mobile wireless devices often access internet with narrower bandwidth or smaller displays, but different mobile devices have varying capabilities and interface designs, including the screen size, the screen resolution and input mechanisms. These characteristics may affect the performance of certain services and therefore user intention. For example, online content which is well-displayed on the screen of a tablet may be confusing and difficult to navigate when viewed on a smart phone. While displaying the bulk of the information on a Web site in text format is a common solution to accommodate the limitations (Fagan & Fagan, 2004), policy makers and system developers should still be cautious about applying the findings of this study to users of various mobile devices. 7. Conclusion This study contributes to theory by extending TPB to the context of m-government services. Such a perspective indicates that by examining communication efficiency and integrated communication service factors, user acceptance behavior in m-government service settings can be effectively improved. These two factors act as the critical drivers for user acceptance of m-government services. Our findings have academic implications both for IS service acceptance and integrated marketing communication literature. This study has taken a step toward implementing mechanisms to improve user acceptance of m-government services for practitioners. Such findings demonstrate the importance of implementing practically the two critical elements of effective communication and integrated communication service mechanisms. The results of this study emphasize that significant improvement in the attitude toward m-government services, subjective norms, and perceived behavior control can be obtained via effective mobile communication and integrated communication service mechanisms. Policy makers, government agency officials, and m-government system developers should take note. Future research collecting data from both m-government service users and policy makers would advance our understanding of the working of mechanisms and their effect on user acceptance of m-government services. In addition, future research could expand the subject group to include various m-government service users of the Greater China economic region. Finally, longitudinal studies are also required to observe the continuity in the use of m-government services. References Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Action control, from cognition to behavior (pp. 11–39). Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. Ajzen, I. (2001). Nature and operation of attitudes. Annual Review of Psychology, 52(1), 27–58. Akca, H., Sayili, M., & Esengun, K. (2007). Challenge of rural people to reduce digital divide in the globalized world: Theory and practice. Government Information Quarterly, 24(2), 404–413. Anderson, J., & Gerbing, D. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Armstrong, J., & Overton, T. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 396–402. Bampo, M., Ewing, M., Mather, D., Stewart, D., & Wallace, M. (2008). The effects of the social structure of digital networks on viral marketing performance. Information Systems Research, 19(3), 273–290. Bandura, A. (1997). Self-efficacy: The exercise of control. Worth Publishers. Benlamri, R., Adi, W., Al-Qayedi, A., & Dawood, A. (2010). Secure human face authentication for mobile e-government transactions. International Journal of Mobile Communications, 8(1), 71–87.

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44 Bertot, J. C., Jaeger, P. T., & Hansen, D. (2012). The impact of polices on government social media usage: Issues, challenges, and recommendations. Government Information Quarterly, 29(1), 30–40. Bhattacherjee, A. (2000). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 30(4), 411–420. Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805–825. Biocca, F., Owen, C., Tang, A., & Bohil, C. (2007). Attention issues in spatial information systems: Directing mobile users' visual attention using augmented reality. Journal of Management Information Systems, 23(4), 163–184. Bock, G., Kankanhalli, A., & Sharma, S. (2006). Are norms enough? The role of collaborative norms in promoting organizational knowledge seeking. European Journal of Information Systems, 15(4), 357–367. Bulgurcu, B., Cavusoglu, H., & Benbasat, I. (2010). Information security policy compliance: An empirical study of rationality-based beliefs and information security awareness. MIS Quarterly, 34(3), 523–548 ([Article]). Census, U. S. (2006). 2006 American community survey. (2008, from). http://factfinder. census.gov/servlet/ADPTable?_bm=y&-geo_id=01000US&-ds_name=ACS_2006_ EST_G00_&-_lang=en&-_caller=geoselect&-format= Chau, P., & Tam, K. (1997). Factors affecting the adoption of open systems: an exploratory study. MIS Quarterly, 21(1), 1–24. Chea, S., & Luo, M. (2008). Post-adoption behaviors of E-service customers: The interplay of cognition and emotion. International Journal of Electronic Commerce, 12(3), 29–56. Cheng, R. (2008). Introduction of M-Taiwan applications promotion program and development trend of global WiMAX. (2012, from). http://wimaxtaipei.tw/column_ detail.php?id=7 Chin, W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295. Dabbish, L., & Kraut, R. (2008). Awareness displays and social motivation for coordinating communication. Information Systems Research, 19(2), 221–238. DAI (2012). List of countries by digital access index. (2012, from). http://www. internetworldstats.com/list3.htm Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Devaraj, S., Easley, R., & Crant, J. (2008). How does personality matter? Relating the five-factor model to technology acceptance and use. Information Systems Research, 19(1), 93–105. E-Government (September 1). E-government. (from). http://en.wikipedia.org/wiki/ Mobile_government Fagan, J. C., & Fagan, B. (2004). An accessibility study of state legislative Web sites. Government Information Quarterly, 21(1), 65–85. FAQs (2011). Government indoor public area free WiFi access: FAQs. (2012, from). http://itaiwan.gov.tw/en/faq.php Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. Gallivan, M., Spitler, V., & Koufaris, M. (2003). Does information technology training really matter? A social information processing analysis of coworkers' influence on IT usage in the workplace. Journal of Management Information Systems, 22(1), 153–192. Garnett, J., Marlowe, J., & Pandey, S. (2008). Penetrating the performance predicament: Communication as a mediator or moderator of organizational culture's impact on public organizational performance. Public Administration Review, 68(2), 266–281. Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737. Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 51–90. Grant, I. (2007). Why young consumers are not open to mobile marketing communication. International Journal of Advertising, 26(2), 223–246. Grove, S., Carlson, L., & Dorsch, M. (2007). Comparing the application of integrated marketing communication (IMC) in magazine Ads across product type and time. Journal of Advertising, 36(1), 37–54. Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate data analysis. Homburg, C., Koschate, N., & Hoyer, W. D. (2006). The role of cognition and affect in the formation of customer satisfaction: A dynamic perspective. Journal of Marketing, 70(3), 21–31. Hong, S. J., & Tam, K. Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162–179. Hsieh, C. T. (2007). M-Taiwan program: A WiMAX ecosystem. (2012, from). http:// www.wimaxforum.org/technology/downloads/M_Taiwan_Program.pdf Hsieh, Rai, A., & Keil, M. (2008). Understanding digital inequality: Comparing continued use behavioral models of the socio-economically advantaged and disadvantaged. MIS Quarterly, 32(1), 97–126. Hu, P., Chau, P., Sheng, O., & Tam, K. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112. Hung, S., Chang, C., & Yu, T. (2006). Determinants of user acceptance of the e-government services: The case of online tax filing and payment system. Government Information Quarterly, 23(1), 97–122. Jiang, & Benbasat, I. (2007). Investigating the influence of the functional mechanisms of online product presentations. Information Systems Research, 18(4), 454–470. Jiang, Chan, J., Tan, B. C. Y., & Chua, W. S. (2010). Effects of interactivity on website involvement and purchase intention. ([Article]). Journal of the Association for Information Systems, 11(1), 34–59. Kim, Y., Yoon, J., Park, S., & Han, J. (2004). Architecture for implementing the mobile government services in Korea. Conceptual modeling for advanced application domains (pp. 601–612).

43

Lowry, P., Vance, A., Moody, G., Beckman, B., & Read, A. (2008). Explaining and predicting the impact of branding alliances and web site quality on initial consumer trust of e-commerce web sites. Journal of Management Information Systems, 24(4), 199–224. Lu, J., Liu, C., Yu, C. -S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information Management, 45(1), 52–64. Lu, Y., Yang, S., Chau, P. Y. K., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information Management, 48(8), 393–403. Madden, T., Ellen, P., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin, 18(1), 3. Maumbe, B. M., Owei, V., & Alexander, H. (2008). Questioning the pace and pathway of e-government development in Africa: A case study of South Africa's cape gateway project. Government Information Quarterly, 25(4), 757–777. McAllister, D. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. McMillan, S., & Hwang, J. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29–42. M-Communication (2012). Mobile phone. from. http://en.wikipedia.org/wiki/Mobile_ communication Melkers, J., & Willoughby, K. (2005). Models of performance-measurement use in local governments: Understanding budgeting, communication, and lasting effects. Public Administration Review, 65(2), 180–190. Montoya, M., Massey, A., & Khatri, V. (2010). Connecting IT services operations to services marketing practices. Journal of Management Information Systems, 26(4), 65–85. Moon, M. J. (2002). The evolution of e-government among municipalities: Rhetoric or reality? Public Administration Review, 62(4), 424–433. M-Taiwan (2010). Mobile Taiwan applications promotion program. http://www. mtaiwan.org.tw/cht/index.php Ngwenyama, O., & Lee, A. (1997). Communication richness in electronic mail: Critical social theory and the contextuality of meaning. MIS Quarterly, 21(2), 145–167. Niehaves, B. (2011). Iceberg ahead: On electronic government research and societal aging. Government Information Quarterly, 28(3), 310–319. Olalere, A., & Lazar, J. (2011). Accessibility of U.S. federal government home pages: Section 508 compliance and site accessibility statements. Government Information Quarterly, 28(3), 303–309. Otjacques, B., Hitzelberger, P., & Feltz, F. (2007). Interoperability of e-government information systems: Issues of identification and data sharing. Journal of Management Information Systems, 23(4), 29–51. Palmer, J. (2013). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151–167. Pandey, S., & Garnett, J. (2006). Exploring public sector communication performance: Testing a model and drawing implications. Public Administration Review, 66(1), 37–51. Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115–143. Pirog, M. A., & Johnson, C. L. (2008). Electronic funds and benefits transfers, E-government, and the winter commission. Public Administration Review, 68, S103–S114. Pleis, J. R., Lucas, J. W., & Ward, B. W. (2009). Summary health statistics for U.S. adults: National Health Interview Survey, 2008. Vital and Health Statistics, 10(242), 1–157. Prins, R., & Verhoef, P. (2007). Marketing communication drivers of adoption timing of a new e-Service among existing customers. Journal of Marketing, 71(2), 169–183. Robert, L., Denis, A., & Hung, Y. (2009). Individual swift trust and knowledge-based trust in face-to-face and virtual team members. Journal of Management Information Systems, 26(2), 241–279. Rustagi, S., King, W. R., & Kirsch, L. J. (2008). Predictors of formal control usage in IT outsourcing partnerships. Information Systems Research, 19(2), 126–143. Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006). Information system success: Individual and organizational determinants. Management Science, 52(12), 1849–1864. Schaupp, L. C., & Bélanger, F. (2005). A conjoint analysis of online consumer satisfaction. Journal of Electronic Commerce Research, 6(2), 95–111. Shiv, B., & Fedorikhin, A. (1999). Heart and mind in conflict: The interplay of affect and cognition in consumer decision making. Journal of Consumer Research, 26(3), 278–292. Sicilia, M., Ruiz, S., & Munuera, J. (2005). Effects of interactivity in a web site: The moderating effect of need for cognition. Journal of Advertising, 34(3), 31–44. Smith, S. (2010). Circuits of power: A study of mandated compliance to an information systems security de jure standard in a government organization. MIS Quarterly, 34(3), 463–486. Song, J., & Zahedi, F. (2005). A theoretical approach to web design in E-commerce: A belief reinforcement model. Management Science, 51(8), 1219–1235. Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. Teo, T., Srivastava, S., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99–132. Venkatesh, V., Brown, S., Maruping, L., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502. Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2), 419–432. Yu, D. X., & Parmanto, B. (2011). U.S. state government websites demonstrate better in terms of accessibility compared to federal government and commercial websites. Government Information Quarterly, 28(4), 484–490. Zissis, D., & Lekkas, D. (2011). Securing e-government and e-voting with an open cloud computing architecture. Government Information Quarterly, 28(2), 239–251.

44

S.-Y. Hung et al. / Government Information Quarterly 30 (2013) 33–44

Shin-Yuan Hung is Professor and Chair of Department of Information Management at National Chung Cheng University in Taiwan. He was a visiting scholar of the MIS Department at the University of Arizona during summer 2007–spring 2008. Prior to the leave, he had been the Secretary General of the same university. Dr. Hung received his bachelor degree in Statistics from the National Chung Hsing University in Taiwan and his master and doctoral degrees in Information Systems from the National Sun Yat-sen University in Taiwan. His current research interests include decision support systems, knowledge management, electronic commerce, and data mining. He has published a number of papers in Decision Support Systems, Information & Management, Electronic Commerce Research and Applications, Information Technology & People, Communications of the AIS, Journal of Organizational Change Management, Government Information Quarterly, Computer Standard and Interfaces, Pacific Asian Journal of Association for Information Systems, Journal of Chinese Information Management, among others.

Chia-Ming Chang is an Associate Professor of Department of Information Management at Shih Chien University Kaohsiung Campus. He holds a Ph.D. in Information Systems from the National Chung Cheng University. His current research interests include decision support systems, electronic government, and user interface design. He has published articles in Electronic Commerce Research and Applications, Computer Standard and Interfaces, Information Management & Computer Security, Government Information Quarterly, and so on.

Shao-Rong Kuo received his Master Degree from the Department of Information Management at National Chung Cheng University, Taiwan.