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Predicting the adoption of a mobile government security response system from the user's perspective: An application of the artificial neural network approach

机译:从用户的角度来看,预测移动政府安全响应系统的采用:人工神经网络方法的应用

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摘要

The core aim of this study is not only to explore the new phenomenon of mobile government (m-govt) security response systems (SRS) but also to identify some important factors from the user's perspective in order to build a strong and acceptable m-govt SRS for crisis management. In a comprehensive research model, the relationships between constructs were measured by a two-stage approach using structural equation modeling (SEM) and an artificial neural network (ANN) on data collected through a structured questionnaire from 574 valid respondents. The outcomes from the SEM and ANN analyses predicted that awareness, perceived compatibility, perceived response time, and trust are the top four major factors in adopting m-govt SRS, regardless of the factors' order of influence. This finding makes a significant contribution to the current literature on m-govt adoption and has practical significance for understanding various aspects of the development and implementation of m-govt SRS. The current study provides a broad perspective on the successful implementation of m-govt SRS by government agencies and practitioners, particularly in the provision of security services.
机译:本研究的核心目标不仅可以探索移动政府(M-GOVT)安全响应系统(SRS)的新现象,而且还要识别来自用户的角度的一些重要因素,以建立一个强大而可接受的M-GOVT危机管理的SRS。在一个综合的研究模型中,通过使用结构方程模型(SEM)和人工神经网络(ANN)通过从574个有效受访者通过结构化问卷收集的数据来测量构造之间的关系。 SEM和ANN分析的结果预测,意识,感知兼容性,感知时间和信任是采用M-GOVT SRS的前四个主要因素,无论影响因素的影响。这一发现对M-GOVT采用的目前文献产生了重大贡献,并对了解M-GOVT SRS的开发和实施的各个方面具有实际意义。目前的研究提供了政府机构和从业者的成功实施M-GOVT SRS的广泛的观点,特别是在提供安全服务方面。

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