Journal article
A two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoption
Journal of Systems and Information Technology, Vol.21(4), pp.419-438
11/11/2019
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Abstract
Purpose: Despite the widespread use of mobile government (m-government) services in developed countries, the adoption and acceptance of m-government services among citizens in developing countries is relatively low. The purpose of this study is to explore the most critical determinants of acceptance and use of m-government services in a developing country context.
Design/methodology/approach: The unified theory of acceptance and use of technology (UTAUT) extended with perceived mobility and mobile communication services (MCS) was used as the theoretical framework. Data was collected from 216 m-government users across Bangladesh and analyzed in two stages. First, structural equation modeling (SEM) was used to identify significant determinants affecting users' acceptance of m-government services. In the second stage, a neural network model was used to validate SEM results and determine the relative importance of the determinants of acceptance of m-government services.
Findings: The results show that facilitating conditions and performance expectancy are the two important precedents of behavioral intention to use m-government services, and performance expectancy mediates the relationship between MCS, mobility and the intention to use m-government services.
Research limitations/implications: Academically, this study extended and validated the underlying concept of UTAUT to capture the adoption behavior of individuals in a different cultural context. In particular, MCS might be the most critical antecedent towards mobile application studies. From a practical perspective, this study may provide valuable guidelines to government policymakers and system developers towards the development and effective implementation of m-government systems.
Originality/value: This study has contributed to the existing, but limited, literature on m-government service adoption in the context of a developing country. The predictive modeling approach is an innovative approach in the field of technology adoption.
Details
- Title
- A two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoption
- Creators
- Shamim TalukderRaymond Chiong - University of Newcastle AustraliaSandeep Dhakal - University of Newcastle AustraliaGolam Sorwar (Author) - Southern Cross University, School of Business and TourismYukun Bao
- Publication Details
- Journal of Systems and Information Technology, Vol.21(4), pp.419-438
- Identifiers
- 991012863000202368
- Academic Unit
- Faculty of Science and Engineering; School of Business and Tourism; Faculty of Business, Law and Arts; Information Technology
- Language
- English
- Resource Type
- Journal article