Designing a Deployment Model for Artificial Intelligence in Supply and Production Processes: A Case Study of a Telecommunications Equipment Manufacturer

Articles in Press

Document Type : Persian Research paper

Authors

Department of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran

10.22108/pom.2026.149216.1666

Abstract

The aim of this study is to design a context-based model for the deployment of artificial intelligence in the supply and production processes of a telecommunications equipment company in Iran. Adopting a sequential exploratory mixed-methods approach, the study first conducted an in-depth analysis of the problem using the systematic grounded theory method (Strauss and Corbin). Qualitative data were collected through in-depth semi-structured interviews with 26 expert managers and specialists. The main categories were organized within a paradigm model encompassing causal conditions, contextual conditions, intervening conditions, strategies, consequences, and behavioral intention to deploy artificial intelligence (as the core phenomenon), and the relationships between the components were identified, leading to the development of an initial model. Subsequently, the relationships of the model were tested using structural equation modeling with the partial least squares approach, whereby a 17-item Likert-scale questionnaire was completed by 100 individuals and analyzed using SmartPLS. The findings confirmed the reliability and validity of the model and revealed that causal conditions and intervening conditions have a significant effect on strategies, strategies have a significant effect on consequences, and consequences have a significant effect on behavioral intention to deploy artificial intelligence (the core phenomenon). The moderating effect of intervening conditions is also significant. This study presents a localized model and specific practical solutions.

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Main Subjects

Research in Production and Operations Management

Articles in Press, Accepted Manuscript
Available Online from 20 July 2026

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