DO YOU SEE MY EFFORT? AN INVESTIGATION OF THE RELATIONSHIP BETWEEN E-GOVERNMENT SERVICE QUALITY AND TRUST IN GOVERNMENT Hani A. Alsarraf, Salman Aljazzaf and Ahmad M. Ashkanani Primary Author mixed material bibliography ENGLAND EMERALD INSIGHT 2023 monographic en ENGLISH

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BAIK Purpose – Electronic government (e-government) has been suggested as an important tool to improve public services and enhance citizens’ trust in government. Several studies have examined the relationship between e-government service quality, satisfaction and trust in government with conflicting results. This conflict reveals the need for additional examination of the process relating e-government service quality to trust in government. This study aims to introduce a theoretical approach that considers a crucial factor, which is perceived government effort. The model proposes that perceived e-government service quality first leads to satisfaction, which in turn increases perceived effort that finally translates into trust in government. Design/methodology/approach – This study proposes and tests a conceptual model that examines the relationship between e-government service quality, satisfaction, perceived effort and trust in government. The model is tested using mediated regression analyses and Hayes’s PROCESS macro. Data were collected from an online survey of 723 individuals who interacted with e-government services in Kuwait. Findings – The results supported the proposed theoretical model and particularly confirmed the mediating role of perceived effort in the link between e-government service quality and trust in government. E-government, Service quality, User satisfaction, NONE Repository Universitas Langlangbuana Sistem Repository Elektronik Skripsi, Tesis, Desertasi dan Penelitian Dosen Universitas Langlangbuana JC301-TG-23 V17.1.5 My Library DO YOU SEE MY EFFORT? AN INVESTIGATION OF THE RELATIONSHIP BETWEEN E-GOVERNMENT SERVICE QUALITY AND TRUST IN GOVERNMENT TRANSFORMING_GOVERNMENT.png.png 2398 2023-12-19 10:28:25 2023-12-19 10:31:06 machine generated