Intelligent Predictive Model of Purchase Intention and Behavior in the Refurbished Electronics Market Using Neural Networks: Evidence from Iran

Soltani, Marzieh; Khadivar, Ameneh

doi:10.48311/mri.2026.28271

Intelligent Predictive Model of Purchase Intention and Behavior in the Refurbished Electronics Market Using Neural Networks: Evidence from Iran

Document Type : Original Article

Authors

marzieh soltani ¹

Ameneh Khadivar ²

¹ Ph.D. Candidate of Business Administration, Faculty of Social Sciences and Economics, AlZahra University, Tehran, Iran.

² Associate Professor, Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

10.48311/mri.2026.28271

Abstract

Refurbished electronics such as smartphones and laptops are increasingly positioned as sustainable and affordable options amid rising e-waste and resource constraints, yet consumer acceptance in Iran remains insufficiently understood. This study integrates Ajzen’s Theory of Planned Behavior and Schwartz’s Norm Activation framework to propose a prediction-oriented model based on artificial neural networks (ANN) for estimating purchase intention and behavior and for quantifying the relative contribution of theoretical constructs. The research is descriptive–applied, survey-based, and cross-sectional; data were collected from 400 Iranian consumers of smartphones and laptops in Fall–Winter 2024 using convenience sampling and a five-point questionnaire. After data cleaning, reverse-coding of negatively worded items, and min–max normalization, multilayer ANNs were trained in MATLAB with a 70/15/15 split for training/validation/testing. Beyond prediction, variable importance was derived via sensitivity analysis. Results indicate that the ANN provides reliable out-of-sample prediction for both intention and behavior. In the ranking of drivers, perceived behavioral control and attitude toward the behavior contribute most to explaining purchase behavior, while purchase intention remains an effective bridge from cognitive constructs to actual behavior. Subjective norms, personal norms (morality), and awareness of consequences exert positive but more modest effects. The learning-based approach offers a finer-grained picture of latent patterns than linear explanations and yields a more dependable estimate of purchase likelihood in the Iranian context. Managerially, effective policies should jointly strengthen perceived capability and ease of action (e.g., simpler purchase processes and lower after-sales risk) and build favorable attitudes grounded in economic and environmental benefits to increase acceptance of

Keywords

Refurbished electronic products

Purchase intention and behavior

Artificial neural networks

Theory of Planned Behavior

Norm Activation Model

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