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- W4386871572 abstract "Background: This study investigates the effect of digital transformation on corruption at country level. Very few studies have empirically investigated this phenomenon. The model presented lays the relationships between socio-technical and socio-political factors and their impact on technological factors, which in turn, influence corruption. Methods: Secondary data from 139 countries collected by credible international organizations are used for the empirical analyses. The sample of 139 countries, used in this study, makes the results more robust and generalizable than those published in previous studies. PLS-SEM and multi-group analysis were used to test the hypotheses presented in the research model. Results: The results of the analysis show that digital transformation can significantly lower the corruption. The empirical analysis also demonstrates that socio-technical and socio-political factors are important in supporting the technological factors in reducing corruption. Multi-group analysis based on the GNI categorization of the World Bank revealed fine results for nations of different economic level. The significance of the relationships varies based on the development level of the country. Conclusions: This study contributes to the growing empirical base of literature on digital transformation and corruption by empirically assessing new relationships that have not been explored in the extant literature using a relatively larger sample size. The results suggest that technology plays a critical role in reducing the corruption in any country. Factors such as infrastructure, e-participation, education/human capital, laws relating to ICT, and Importance of ICT to government are found to be vital for fighting corruption." @default.
- W4386871572 created "2023-09-20" @default.
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- W4386871572 date "2022-01-01" @default.
- W4386871572 modified "2023-09-27" @default.
- W4386871572 title "The Effect of Digital Transformation on Corruption: A Global Analysis" @default.
- W4386871572 doi "https://doi.org/10.17705/1pais.14204" @default.
- W4386871572 hasPublicationYear "2022" @default.
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