Using a multi-framework to investigate the determinants of smart government systems adoption in public service organizations in Saudi Arabia

  • Mohammed Alajmi

    Student thesis: Doctoral Thesis

    Abstract

    Due to the great changes caused by technological advances for economies, the environment and whole societies, technology is now an integral part of scientific research. The Kingdom of Saudi Arabia (KSA) has recognized the importance of smart government systems (SGS) and IT’s importance, and the country’s government began implementing national electronic government projects in 1998. Researchers and practitioners have been interested in determining what guides users' adoption of technology in the workplace. The main variables impacting smart government systems (SGS) adoption in Saudi Arabia have gotten little attention. This study's aim is to evaluate the adoption of smart government systems (SGS) in the Kingdom of Saudi Arabia (KSA) and how that has affected workplace employee behavior. As a result, this study fills the gaps in our knowledge about the elements that shape the adoption of smart government systems (SGS). This research seeks to create a comprehensive, integrated model that can explain how SGS affect public sector agencies in the KSA. The model is based on the following theories: Technology– Organization–Environment (TOE), Unified Theory of Acceptance and Use of Technology (UTAUT), and Technology Acceptance Model (TAM). It contains new and modified variables that were not considered by previous theories. Four research questions and 24 hypotheses were devised and investigated. A questionnaire for a survey was developed for data collection purposes. The study gathers and analyses information using quantitative approaches. Online surveys were given to employees working for the Saudi Arabian Ministry of Foreign Affairs, Ministry of Justice, Ministry of Education and Ministry of Health about their adoption of smart government systems (SGS) and what the outcomes were. The samples were taken from a database listing employees at Saudi ministries. Using the ministry's email system, the questionnaire was sent out to all 2150 participants. After that, interested people were invited to take part in this research. The total number of participants was 419, yielding a response rate of 22%. Structural Equation Modeling (SEM) and the Statistical Package for Social Sciences helped to analyze the data. The model was authenticated using multiple regression analysis. A variety of relevant statistical tests were employed: summary statistics, correlation analysis, validity and reliability analysis and factor analysis. Construct reliability and convergent validity for the model was determined. In addition, other indicators were also examined, for example standardized factor loadings, average variance extracted (AVE) and Cronbach's Alpha (α). It was shown in the findings that factor loadings were between the values of 0.592 to 0.947, which are appropriate values for this study. A total of 2150 participants took part in the study. Descriptive statistics were used to examine the demographic data. The assumptions were examined and the hypotheses were tested using correlations between the study variables and regression analysis. It was determined in the findings that from the seventeen variables in the first four groups, seven had a major impact on the way SGS adoption was perceived. Two out of three technological factors which are security concerns and ICT strategy. Three out of five from the organizational factors which are managerial support, staff training and incentives. Two out of five environmental factors which are external support and trust. All the four factors in the social factors were found to be not significant. The way employees perceived the SGS had a major influence on SGS adoption. It was shown that SGS adoption significantly influenced the six variables related to the impact of smart government systems adoption and what the organizational benefits were. From the twenty-four hypotheses, fourteen were supported. The results make important contributions to the Saudi government policymakers for determining what are the important factors that affect the incorporation of smart technologies. It is suggested the findings are supported and can be applicable to the relevant factors that will help in better understanding smart government systems use and implementation by employees in the Saudi public sector. Furthermore, these results revealed that the following variables were significantly having an impact on perceptions of smart government systems (SGS): security concern, ICT strategy, managerial support, staff training, incentives, external support, and trust. Also, the findings indicate all outcome variables – cost-effectiveness, organizational efficiency, automation, transparency, quality of service and accessibility - have a strong impact on and relationship to the implementation of SGS. Identifying the main factors that impact employees’ adoption of SGS would improve people’s knowledge about those factors helping or hindering the technology acceptance process. The Saudi government can use the findings of this study to formulate policies and procedures regarding SGS in various ministries and departments. Also, this study helps organizations’ leaders in identifying the expected benefits such as better services, cost-effectiveness, efficiency, and automation. The study's findings have implications for various types of organization managers and practitioners who are responsible for introducing and advancing new technologies in the workplace. This research also helps in identifying the outcomes (i.e. organizational and social benefits) of adopting the SGS by employees so that organizations’ needs and processes function better. Moreover, results will provide useful insights for reducing the costs associated with new technologies. The following outcomes are desired: improved service quality that increases users’ satisfaction, more rapid provision of services and faster access for users, transparency/full disclosure that reduces corruption and system availability that gives rise to users’ satisfaction.
    Date of Award2022
    Original languageEnglish
    SupervisorMasoud Mohammadian (Supervisor) & Majharul Talukder (Supervisor)

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