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

• Published in: Data in brief Vol. 30; p. 105588
• Main Authors: Kautsarina, Hidayanto, Achmad Nizar, Anggorojati, Bayu, Abidin, Zaenal, Phusavat, Kongkiti
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.06.2020; Elsevier
• Subjects: Computer Science; End-user; Indonesia; positive security behavior; smart devices; structural equation modeling; End-user; smart devices; positive security behavior; structural equation modeling; Indonesia
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2020.105588

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.