ORIGINAL RESEARCH article
Front. Big Data
Sec. Machine Learning and Artificial Intelligence
Modeling Household Adoption of IoT-Based Home Security in Dhaka: A PLS–Machine Learning Framework
Provisionally accepted
- 1Daffodil International University, Dhaka, Bangladesh
- 2Multimedia University - Cyberjaya Campus, Cyberjaya, Malaysia
- 3Woosong University, Daejeon, Republic of Korea
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Despite several strategies, Bangladesh has a poor rate of internet of things (IoT) deployment. This study therefore seeks to investigate the factors shaping IoT adoption for residential security in Dhaka and to analyze their respective contributions. Hence, this study combined two important theories, namely protection motivation theory (PMT) along with attitude-social influence-self-efficacy (ASE) in which a hybrid PLS-Machine learning approach has been used to identify both linear and nonlinear correlations with high predictive accuracy. Snowball sampling method was utilized to choose 348 valid replies from a survey of household heads. Afterward, partial least squares (PLS) followed by artificial neural networks (ANN) and machine learning (ML) classifiers were the procedures that made up the complete assessment method. The variables that affected intention with a variance of 34.9% and accuracy of 74.28% were severity, vulnerability, response efficacy, response cost, and attitude. The theoretical contribution of this study lies in its novel integration of PMT and ASE models, offering new insights into their combined effect on technology adoption in emerging markets. Besides, the findings contribute to the literature by increasing the public awareness of home security that can enhance Dhaka's overall state of public order and safety. On the other hand, vulnerability was the most significant predictor, followed by response cost, attitude, response efficacy, self-efficacy, social influence, and severity. The theoretical contribution of this study lies in its novel integration of PMT and ASE models, offering new insights into their combined effect on technology adoption in emerging markets. Besides, the findings contribute to the literature by increasing the public awareness of home security that can enhance Dhaka's overall state of public order and safety. Moreover, the findings may offer valuable insights for companies and entrepreneurs, as incorporating these factors into marketing strategies and investment initiatives is likely to foster greater consumer adoption.
Keywords: Attitude-social influence-self-efficacy, Home security, Internet of Things, PLS-ML, Protection Motivation Theory
Received: 04 Oct 2025; Accepted: 13 Jan 2026.
Copyright: © 2026 Mahmud, Rahman, Farid, UDDIN and Abdul Karim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
JIA UDDIN
Hezerul Abdul Karim
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