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

Fakhar Shahzad, Guoyi Xiu, Muhammad Aamir Shafique Khan and Muhammad Shahbaz

Technology in Society, 2020, vol. 62, issue C

Abstract: 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.

Keywords: M-government; Technology adoption; Security services; ANN (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:62:y:2020:i:c:s0160791x19302581

DOI: 10.1016/j.techsoc.2020.101278

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