以信任为中介构建提升公众对智慧政府模式的接受度

IF 0.6 Q4 CONSTRUCTION & BUILDING TECHNOLOGY
Hamdan Hasan Mohammed Thaiban, Safiah Sidek
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引用次数: 0

摘要

本研究的主要目的是制定一个信任模型,旨在提高公众对阿联酋智能政府服务的接受程度。该研究共确定了31个因素,分为7个不同的组或结构。该模型由口碑、知识和经验、IT质量、隐私和安全五个独立结构组成。然后,信任作为中介构念,接受作为依赖构念。采用方便抽样的方法,对400名受访者进行问卷调查。收集的数据被用于使用SmartPLS软件创建和完善模型。对模型进行了全面的分析,包括收敛信度和效度评估、判别效度评估和假设检验。研究结果揭示了所有六个假设的显著性,表明五个独立构念对中介构念(信任)的显著影响,而中介构念又显著影响依赖构念(接受)。就其对现有知识的贡献而言,本研究显著丰富了公民中心模型和智慧政府的文献。此外,在实践方面,研究结果为政策制定者和聪明的政府官员提供了宝贵的见解,可以从战略上优化方法,从而促进更快、更有效地采用智能政府服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging Trust as an Intermediary Construct for Enhancing Public Acceptance of Smart Government Model
The primary aim of this study was to formulate a trust model aimed at augmenting public acceptance of UAE's smart government services. The study identified a total of 31 factors categorized into seven distinct groups or constructs. The model comprises five independent constructs which are Word of Mouth, Knowledge and Experience, IT Quality, Privacy, and Security. Then, Trust as an intermediary construct while Acceptance as a dependent construct. Through a convenience sampling approach, data was collected from 400 respondents via a questionnaire survey. The data collected was utilized to create and refine the model using SmartPLS software. The model underwent thorough analysis, including assessments of convergent reliability and validity, discriminant validity, and hypothesis testing. The study results revealed the significance of all six hypotheses, indicating the noteworthy impact of the five independent constructs on the intermediary construct (Trust), which in turn significantly influences the dependent construct (Acceptance). In terms of its contribution to existing knowledge, this study significantly enriches the literature on citizen-centric models and smart government. Moreover, in practical terms, the findings provide valuable insights for policy makers and smart government officials to strategically optimize approaches, thereby facilitating the expedited and more effective adoption of smart government services.
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来源期刊
CiteScore
0.90
自引率
20.00%
发文量
25
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