Causative Factors for Continuous Usage of M-government Services Among Users of Smart City


  • Safiah Sidek
  • Saqr Khalfan Ali Alkaabi


Causative factor, M-government services


This paper presents a quantitative study on assessing causative factors that contributing to continuous usage of M-government services among users using questionnaire survey. The survey was conducted through purposive sampling techniques of selecting the respondents of smart city that are users of M-government of Abu Dhabi police department. The collected data from 379 valid responses of the survey was analysed for its reliability and normality and found that the data was reliable and achieved normality criteria. The data was further used for ranking of the factors based on its importance toward the continuous usage of M-government. It was found that that for Quality of M-Government group, the most significant factor is QG3 which is M-government system provides up-to-date information. In Public Value group, the most influence factor is PV9 which is Using the M-government increases the government accountability; In Trust group the most influence factor is T5 which is feel comfortable interacting with the M-government system since it generally fulfils its duties efficiently; In User Satisfaction group the most influence factor is US7 which is satisfied with the service received from the M-government; In Continuous Intention to Use group the most influence factor is CIU9 which is recommend others to use in the future. In term of group ranking, it was found that user satisfaction group leads other groups then followed by public value then trust group, continuous intention to use and finally the quality of M-government groups. This indicates that for M-government services to enhance its usage of the services the main priority should be given to user satisfaction.


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How to Cite

Safiah Sidek, & Saqr Khalfan Ali Alkaabi. (2022). Causative Factors for Continuous Usage of M-government Services Among Users of Smart City. International Journal of Sustainable Construction Engineering and Technology, 13(2), 213–219. Retrieved from



Special Issue 2022: Knowledge Management