Identifying factors affecting the acceptance of government to government system in developing nations – empirical evidence from Nepal

Abstract

PurposeThis paper aims to examine the factors that might influence the acceptance of government-to-government (G2G) systems in the Government of Nepal (GoN), to enhance the communication for coordination among government agencies.Design/methodology/approachAfter reviewing the Unified Model for E-Government Acceptance (UMEGA), interviews, focus group discussions with government officials and interviews with the retired senior government officials, a conceptual model has been proposed. The model is empirically tested with 234 responses collected from the government officials working in the central ministries of GoN using the structural equation modeling technique.FindingsThe result showed that factors considered from UMEGA such as performance expectancy, effort expectancy, facilitating conditions and attitude have a significant influence on the behavioral intention to use the system in the GoN. Also, the identified factors such as a commitment from leadership, awareness among leadership and transparency have a significant influence on the behavioral intention of the users to accept the system.Research limitations/implicationsThe low sample size is one of the major limitations of this research.Practical implicationsThe findings show that the identified factors have a significant influence on the acceptance model and provide useful insights to policymakers, government officials and system developers to achieve the successful implementation of the e-government system in Nepal. The findings can be used by the academicians and e-government practitioners to extend it to other developing nations.Originality/valueThis research work explores the factors affecting the acceptance of a G2G system in GoN through the modification of the UMEGA model. To the best of the authors’ knowledge, this is a novel research in the context of Nepal, where the implementation of e-government has been analyzed from the perspectives of acceptance models to support the better implementation of e-governance systems.