Success of government e-service delivery: Does satisfaction matter?

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Abstract

For measuring e-government success a well-founded theory is important which can help governments to improve their services and identify how effectively public money is spent. We propose using citizen satisfaction as a measure of e-government success, as well as explore its relationships with e-government service quality. Three hypotheses have been formulated to test the model. For empirical estimation, the data used in this study was collected form Sweden. An online survey was conducted using systematic sampling among the municipalities in Sweden, 425 valid responses were received. The measures of each variables selected in this article were mainly adapted from related previous studies. Efficiency, privacy, responsiveness and web assistance were selected as e-service quality dimensions. Actual usages were measured by three items- Frequency of usage, Diversity of usages and Dependency. Confirmatory factor analyses were conducted to confirm the factor structures. The analysis shows that 43% of the variance among the factors of e-service quality, and usage is explained by citizen satisfaction. We found e-service quality has a relation with citizen satisfaction considering four dimensions of service quality. Efficiency, responsiveness and web assistance were found to be of more importance compared to privacy in determining e-service quality. Use was found to be positively and significantly related to citizen satisfaction. The results should contribute towards understanding of the key issues that influence citizens' needs and level of satisfaction with the tax services and help improve the service delivery process. Further research is suggested to explore other quality dimensions such as system and information quality. © 2010 Springer-Verlag Berlin Heidelberg.

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APA

Saha, P., Nath, A., & Salehi-Sangari, E. (2010). Success of government e-service delivery: Does satisfaction matter? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6228 LNCS, pp. 204–215). https://doi.org/10.1007/978-3-642-14799-9_18

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