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A two-stage structural equation modeling-neural network approach for understanding and predicting the determinants of m-government service adoption

机译:理解和预测移动政府服务采用决定因素的两阶段结构方程建模-神经网络方法

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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.
机译:目的-尽管发达国家广泛使用移动政府服务,但发展中国家公民对移动政府服务的采用和接受程度相对较低。这项研究的目的是探讨发展中国家背景下接受和使用移动政府服务的最关键决定因素。设计/方法论/方法-将技术的接受和使用(UTAUT)的统一理论扩展到感知的移动性和移动通信服务(MCS)作为理论框架。从孟加拉国的216个m-政府用户收集数据,并分两个阶段进行分析。首先,使用结构方程模型(SEM)来确定影响用户接受移动政府服务的重要决定因素。在第二阶段,使用神经网络模型来验证SEM结果并确定接受m政府服务的决定因素的相对重要性。研究结果-结果表明,便利条件和绩效期望是使用移动政府服务的行为意图的两个重要先例,而绩效预期介导了MCS,移动性和使用移动政府服务的意图之间的关系。研究的局限性/含义-从理论上讲,该研究扩展并验证了UTAUT的基本概念,以捕获不同文化背景下个人的收养行为。特别是,MCS可能是移动应用程序研究中最关键的前提。从实践的角度来看,该研究可以为政府决策者和系统开发人员提供有关移动政府系统开发和有效实施的有价值的指导。原创性/价值-这项研究为在发展中国家背景下采用移动政府服务的现有文献(但数量有限)做出了贡献。预测建模方法是技术采用领域中的一种创新方法。

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