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Perceptions Towards the Adoption and Utilization of M-Government Services: A Study from the Citizens’ Perspective in Saudi Arabia

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Information Technology for Management: Current Research and Future Directions (AITM 2019, ISM 2019)

Abstract

The government of Saudi Arabia has adopted M-Government for the effective delivery of services. One advantage of adding the M-Government channel to government services is that it offers unique opportunities for real-time and personalized access to government information and services through the advantage of wireless technology. However, a low adoption rate of M-Government services by citizens is a common problem in Arabian countries, including Saudi Arabia, despite the best efforts of the Saudi government. Therefore, this paper explores the determinants of citizens’ intention to adopt and use M-Government services, in order to increase the adoption rate. This study was based on the Mobile Government Adoption and Utilization Model (MGAUM) that was developed to improve adoption. Data was collected from 1,882 Saudi citizens, and the final sample consisted of 1,286 valid responses. The result of the descriptive analysis presented in this paper indicates that all the proposed factors in our MGAUM model were statistically significant factors in influencing citizens’ intention to adopt and use M-Government services, and thus help to increase the adoption rate. Perceived Usefulness, Perceived Ease of Use, Perceived Mobility, Social Influence and Perceived Compatibility were particularly influential on citizens’ intention, whereas, Perceived Trust, Culture, Awareness, Citizens Service Quality and System Quality were also influential to some degree.

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Table 5. Questionnaire items with associated codes and references [70].

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Alonazi, M., Beloff, N., White, M. (2020). Perceptions Towards the Adoption and Utilization of M-Government Services: A Study from the Citizens’ Perspective in Saudi Arabia. In: Ziemba, E. (eds) Information Technology for Management: Current Research and Future Directions. AITM ISM 2019 2019. Lecture Notes in Business Information Processing, vol 380. Springer, Cham. https://doi.org/10.1007/978-3-030-43353-6_1

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