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Data modeling positive security behavior implementation among smart device users in Indonesia: A partial least squares structural equation modeling approach (PLS-SEM)

机译:在印度尼西亚智能设备用户之间的数据建模正面安全行为实现:一种偏最小二乘结构方程建模方法(PLS-SEM)

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The article presents raw inferential statistical data related to understanding the positive security behaviors of smart device users in Indonesia, which was used to determine whether the studied variables were direct or mediating factors. The factors explored include government efforts, technology provider support, privacy concerns, trust, perceived behavioral control, attitudes, and subjective norms. The theory of planned behavior was adopted to develop the proposed model for implementing positive security behaviors. Structured questionnaires were distributed via an online survey to consumers currently using a smartphone or using a smartphone and some other smart device. Furthermore, the respondents were from 19 provinces in Indonesia. The quantitative research method was used to analyze the data. Reliability and validity were confirmed. Structural equation modeling (SEM) using the Smart PLS software version 3 was used to present data. SEM path analysis identified estimates of the relationships of the primary constructs in the data. The outcomes obtained from this dataset demonstrate a direct influence between government efforts, privacy, and perceived behavioral control and performing positive security behaviors. Other variables had positive and significant influences on implementing positive security behaviors, indicating their roles as mediation variables. This data is useful for reference and consideration in the improvement of smart device users’ security behaviors. This data can also provide valuable insights to countries with characteristics that are similar to those of Indonesia.
机译:本文介绍了与理解印度尼西亚智能设备用户的积极安全行为相关的原始推理统计数据,该数据用于确定所研究的变量是否直接或介导因子。探讨的因素包括政府努力,技术提供商支持,隐私问题,信任,感知行为控制,态度和主观规范。采用计划行为理论制定实施肯定安全行为的拟议模型。结构化问卷通过对目前使用智能手机或使用智能手机和其他一些智能设备的消费者分发。此外,受访者来自印度尼西亚的19个省份。定量研究方法用于分析数据。确认可靠性和有效性。使用智能PLS软件版本3的结构方程建模(SEM)用于呈现数据。 SEM路径分析确定了数据中主要构造的关系的估计。从该数据集获得的结果表明,政府努力,隐私和感知行为控制和执行积极的安全行为之间的直接影响。其他变量对实现积极的安全行为有积极而重大影响,表明其角色作为中介变量。在改进智能设备用户的安全行为方面,该数据对于参考和考虑非常有用。该数据还可以为具有与印度尼西亚类似的特征的国家提供有价值的见解。

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