Human Factors and E-Government Service Capability: A Path Analysis

Human Factors and E-Government Service Capability: A Path Analysis

Wenwen Pan (School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China and School of Information Management, Nanjing University, Nanjing China, China), Guangwei Hu (School of Information Management, Nanjing University, Nanjing, China) and Yixin Ma (Human Resource and Social Security Bureau of Wuxi, Wuxi, China)
Copyright: © 2016 |Pages: 15
DOI: 10.4018/JECO.2016040104
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Abstract

The capability of e-government service (EGS) is affected by different organizational factors, including internal and external. Human factor is the most critical internal factor. However, few studies providing minimal anecdotal evidence have examined the relationships between human factors and EGSC. To fill the gap, this paper attempts to conceive and develop confirmatory factor analysis (CFA) models, along with structural equation modeling (SEM), from the perspective of the role, desire, skill, and learning ability of leader, team, and faculty in the process of building and applying e-Gov to investigate the relationships between them. These models explored the mechanism of how human factors affect EGSC and its components. And several valuable findings are concluded based on the empirical data analysis. It is believed that the abovementioned facets are significant for the Chinese local government sectors in designing an effective EGS delivery mechanism and improving their EGSC.
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1. Introduction

The application of e-Government (e-Gov) improves government e-services delivery efficiency. However, the service level of e-Gov in China lags behind those of other nations (according to the report of United Nations e-Government Survey 2014), and rank 55th among UN member countries, far behind Singapore, Korea, and Japan even in Asia (UNDESA, 2014). Empirical research in the past five years also showed that the willingness of the public and enterprise to accept e-Gov service (EGS) depends on its service capability (Hu et al., 2012; Hu et al., 2014).

The current discussion on e-Gov service capability (EGSC) is mainly based on two perspectives. One is the experience of external users on the quality of the EGS. It mainly focuses on the effect of e-service provided by government, including service efficiency, service quality, user satisfaction, and the effects of social environmental factors (e.g., public demands, technology development, international circumstance, etc.) (Hung, Chang, & Yu, 2006; Burroughs, 2009; Webb & Webb, 2004; Wang and Liao, 2008; Papadomichelaki & Mentzas, 2012). The other is the internal perspective, which mainly focuses on how the government uses, manages, and invests e-service resources and the role of internal environmental factors such as leadership, policy, and system (Papadomichelaki & Mentzas, 2012; Anthopoulos, Siozosa, & Tsoukalas, 2007; Hu, Pan, & Wang, 2011). Overall, many studies on EGSC were from the external perspective, but little research focuses on the internal.

From the capability management perspective, anchoring the impact factors (IF) of EGSC is the first step to efficiently manage EGSC (McDaniel, 2005; Hu et al., 2014; Hu, Shi, Wen, & Wang, 2012). Among the factors that affect EGSC, the human factor is the most critical (McDaniel, 2005; Luk, 2009). However, few studies providing minimal anecdotal evidence have examined the relationships between human factors and EGSC. To fill the gap, this paper attempts to conceive and develop confirmatory factor analysis (CFA) models, along with structural equation modeling (SEM), from the perspective of the role, desire, skill, and learning ability of leader, team, and faculty in the process of building and applying e-Gov to investigate the relationships between them.

In what follows, we first review the existing research to evaluate EGSC and related human factors, leading to the development of models to measure EGSC and content service capability (CSC). Then, we present the research models and hypotheses to describe the potential relationships between human factors and EGSC. Thereafter, research design is reported followed by a comprehensive analysis of data collected, leading to the validation and testing of the proposed models. Finally, we present a discussion of the research findings, their implications, and limitations.

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