Are government employees adopting local e-government transformation?

Enrique Batara, Achmad Nurmandi, Tulus Warsito, Ulung Pribadi
  • Transforming Government People Process and Policy, October 2017, Emerald
  • DOI: 10.1108/tg-09-2017-0056

Factors why government employees adopt changes in e-government

What is it about?

This study aims to examine the association of technology acceptance variables with the intention of adopting e-government transformation, as defined by four dimensions, namely, using new technology systems, redesigning of governmental processes, restructuring of governmental organization and changing the organizational culture and behavior, from the perspective of city government employees in Indonesia and the Philippines. We have found out that the right attitude, facilitating conditions, and performance expectations are determinants of the intention to adopt changes in e-government.

Why is it important?

Findings suggest that attitude is a pivotal predictor of intention to adopt e-government transformation across all four dimensions, while performance expectancy, social influence and facilitating conditions also positively influence the intention to adopt process redesign, organizational structuring and cultural and behavioral change in the city government. Respondents’ length of work experience appears as a significant moderating variable. These are important in transforming government: the right mindset and support systems should be present if city governments want to improve delivery of public services through e-government.


Professor Achmad Nurmandi
JK School of Government Universitas Muhammadiyah Yogyakarta

This study reports only on the findings from two cities in two countries, Surabaya in Indonesia and Davao in the Philippines. The determination of the sample size was done through purposive sampling, so the application of results should be done with prudence. The constructs used for the research model were chosen because of their prominence in the literature. This study made use of a simple linear regression model in hypothesizing the relationships of the constructs

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The following have contributed to this page: Professor Achmad Nurmandi and Dr. Enrique Batara