IoT, Smart Cities, Services and Government
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Paper Number
1747
Paper Type
Completed
Description
The applications of e-government systems continue to attract the interests of both practitioners and researchers. Despite the extant literature on e-government adoption research, most of these studies have similar theories and predictors. Furthermore, many of these studies have presented e-government adoption predictors that are contradictory with each other or have inconsistent findings. The purpose of this study is to conduct a comprehensive review of existing e-government adoption research and find out the most frequently examined and best predictors of e-government adoption by users. Through the use of 75 relevant studies, we found that that service preference, perceived behavioral control, attitude, satisfaction and perceived usefulness are the best predictors of e-government adoption. Based on these results, we suggest that future researchers should consider these predictors in e-government adoption. We also provided a comprehensive e-government adoption model as well as recommended research directions for future e-government research.
Recommended Citation
Wu, Xiaohe and Chong, Alain, "A review of predictors in e-government adoption research" (2021). ICIS 2021 Proceedings. 4.
https://aisel.aisnet.org/icis2021/iot_smart/iot_smart/4
A review of predictors in e-government adoption research
The applications of e-government systems continue to attract the interests of both practitioners and researchers. Despite the extant literature on e-government adoption research, most of these studies have similar theories and predictors. Furthermore, many of these studies have presented e-government adoption predictors that are contradictory with each other or have inconsistent findings. The purpose of this study is to conduct a comprehensive review of existing e-government adoption research and find out the most frequently examined and best predictors of e-government adoption by users. Through the use of 75 relevant studies, we found that that service preference, perceived behavioral control, attitude, satisfaction and perceived usefulness are the best predictors of e-government adoption. Based on these results, we suggest that future researchers should consider these predictors in e-government adoption. We also provided a comprehensive e-government adoption model as well as recommended research directions for future e-government research.
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18-IoT