Online service quality and perceived value in mobile government success: An empirical study of mobile police in China

Highlights

• Respecifying the updated IS success model and extending it into the m-government context.

• Service quality is divided into online and offline service quality from the perspective of service channels.

• Perceived value is used to measure net benefits from a public sector perspective.

• Offline service quality moderates the relationship between online service quality and citizen satisfaction.

Abstract

Measuring the success of mobile government (m-government) is a significant challenge faced by the public sector today, as governments are increasingly using mobile technology to provide public services to citizens and m-government endeavors have often fallen short of their potential. To address this gap, we draw on DeLone and McLean’s (2003) updated information systems (IS) success model in order to develop an m-government success model that theorizes service quality as comprising online and offline service quality and further uses perceived value to measure net benefits. The results of a survey of 286 m-government users in China indicate that information quality and online service quality, but not system quality, are positively associated with citizen satisfaction, which in turn is positively associated with perceived value. The results also show that the relationship between online service quality and citizen satisfaction is positively moderated by offline service quality, while citizen satisfaction partially mediates the relationships between information quality/online service quality (but not system quality) and perceived value. This study extends the updated IS success model by differentiating between online and offline service quality, as well as by introducing the notion of perceived value. Our results provide guidance to researchers and practitioners regarding the role of service quality and perceived value in measuring m-government system success.

Introduction

The measurement of information system (IS) success has garnered significant attention from researchers and practitioners for many years (Rana, Dwivedi, & Williams, 2013; Iannacci & Cornford, 2018; Rana, Dwivedi, & Williams, 2013; Sabherwal, Jeyaraj, & Chowa, 2006). While some authors have focused on how to form an IS success model for measuring general IS (DeLone & McLean, 1992, 2003; Seddon, 1997; Petter, DeLone, & McLean, 2008). Others have focused on how the updated IS success models are used in specific areas, such as e-commerce success (Delone & Mclean, 2004; Wang, 2008), m-commerce success (Zhou, 2013), and e-government success (Scott, DeLone, & Golden, 2016; Teo, Srivastava, & Jiang, 2009). Although various aspects related to quality have been examined in the m-government context (see review in Appendix A), this has not been done using the updated IS success model. Consequently, our study adapts the updated IS success model to the m-government context, which need not necessarily be the same as the e-commerce and e-government contexts.

Governments around the world are actively promoting m-government. M-government can be defined as the strategy utilized by a government to provide information and services to stakeholders (e.g. employees, citizens, businesses, and other organizations) via mobile technology and devices without restrictions of time and place (Ishmatova & Obi, 2009). Due to the mobility, identification and personalization advantages offered by m-government, users can overcome time and space limitations. First, it is convenient for citizens to access information from m-government services 24/7 in a timely manner. Moreover, m-government can provide users with personalized services, facilitate user participation, and enhance the interaction between the government and citizens (Trimi & Sheng, 2008). Despite this, however, the effects of m-government use have mostly fallen short of their potential in a similar way to e-government (Vincent & Harris, 2008). This problem is even more pronounced in the context of developing countries, with only about 15 % of e-government initiatives successfully achieving their key goals without any major adverse consequences (Teo et al., 2009). Therefore, measuring the effectiveness of m-government is a significant challenge for government departments.

As mentioned above, although DeLone and McLean’s (2003) updated IS success model is most commonly used to measure the success of a variety of Internet-based systems, such as e-commerce, m-commerce, and e-government, there is no empirical research measuring m-government success based on this updated model. Given that DeLone and McLean’s model (2003) is recognized as a basic framework for measuring IS success (Scott et al., 2016), and that we are examining the role of online and offline service quality in our research model, we here use the DeLone and McLean updated model (2003) rather than the DeLone and McLean model (1992). Measuring the success of an m-government system is of great significance in theory and practice. In theory, m-government is different from m/e-commerce because m-government frequently encompasses social goals (e.g., enhancing social justice, advancing public value, and promoting the sustainable development of society) (Grimsley & Meehan, 2007); moreover, it can also provide personalized and localization-based services (Wang, 2014), which may change the relevant variables (e.g., service quality related to the mobile context) and the relationships between them in the updated IS success model.

Increasingly, governments are providing public services to citizens through online and offline (O&O) channels. Correspondingly, it is important to consider both offline service quality (e.g., Lee, Kim, & Ahn, 2011) and online service quality (Rana, Dwivedi, Williams, & Weerakkody, 2016; Shareef, Archer, & Dwivedi, 2015). Only minimal research has paid attention to the role of offline service quality in citizens’ use of online public services; moreover, the emergence of O&O-based public services has also brought challenges to the updated IS success model, as the construct of service quality in the updated IS success model is a single-dimensional variable. Last but not least, the construct of ‘net benefits’ is too general and needs to be defined in terms of a specific context (Scott et al., 2016). For example, continuance intention is often used to measure IS success in the extant research (e.g., Teo et al., 2009). Although both government IS and business IS have similar goals as regards creating value for customers/citizens, there are some differences in their application goals. The former mainly focuses on the public interest (e.g., social equity, social sustainable development), while the latter focuses mainly on profit and improving output efficiency (e.g., cost reduction, market share) (Grimsley & Meehan, 2007; Perry & Rainey, 1988; Scott et al., 2016). Given that government IS and business IS encompass different strategic goals, we also need to conduct more research into whether other variables (such as the value of perceived public services) can be used as dependent variables when measuring the success of government IS. It is therefore necessary to extend and validate the updated IS success model to encompass the m-government context. In practice, government agencies around the world have embraced the digital revolution and increased investment in m-government. By evaluating m-government success, the key factors associated with usage can be identified, which will help the government to improve both the system design and the efficiency of service delivery. Hence, it is necessary to assess m-government success and extend IS success research into m-government so that we can improve m-government practices for government agencies.

The purpose of this study is to develop a contextual model based on the updated DeLone and McLean model (DeLone & McLean, 2003) in order to measure m-government success. In doing so, we make three key contributions to our understanding of the updated IS success model in the m-government context. First, although assessing m-government success is a significant challenge faced by the public sector, there has been no empirical research on m-government success to date. We accordingly offer a framework that extends IS success studies into the m-government context and test this framework using survey data. Second, although the government is increasingly inclined to provide public services to citizens through O&O channels, it is not clear how O&O service quality affects IS success. Thus, we refine the connotation of service quality from the perspective of service channels – namely, online service quality (ONQ), and offline service quality (OFQ) – and explore their effects on m-government success. Note that OFQ is used to moderate the relationship between ONQ and citizen satisfaction, thereby facilitating an understanding of why the offline service experience in O&O services is increasingly valued by service providers (Leung, Wu, Ip, & Ho, 2019). Finally, although existing research has identified the difference between a business IS (e.g., e-commerce) and a government IS (e.g., e-government), this differentiation is less important when using net benefits to measure their success. We provide new insights by using perceived value to measure net benefits in order to reflect the balance of costs and benefits in the mobile technology environment. Furthermore, perceived value (similar to public value) is measured from the public sector perspective.

The remainder of this paper is structured as follows. First, we review extant research on m-government, IS success, service quality, and perceived value, and outline our research model and hypotheses. Second, we describe our method and report our empirical results. Finally, we discuss the implications of our results and conclude the paper.