Internet of Things Adoption Model in the Supply Chain of Iran's Automotive Industry: A Grounded Theory Approach

Subject Areas :

ALi Jantarani ¹ , masoud barati ² , Arash Shahin ³ , Mohammad Talari ⁴

1 - Department of Management, Na.C., Islamic Azad University, Najafabad, Iran.
2 - Department of Management, Na.C., Islamic Azad University, Najafabad, Iran; (Corresponding Author).
3 - Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Iran.
4 - Business Department, Hazrat-e Masoumeh University, Qom, Iran.

Received: 2025-02-23 Accepted : 2025-06-27 Published : 2025-11-09

Keywords: Internet of Things (IoT), Automotive Industry, Supply Chain, Grounded Theory,

Abstract :

Abstract

Purpose: The purpose of this research is to develop a localized model for the adoption of the Internet of Things (IoT) in the automotive supply chain in Iran.

Research methodology: This study was conducted using a qualitative approach based on the grounded theory method. Data was collected through semi-structured interviews with 12 industrial and academic experts in the automotive field, and data analysis was performed in the stages of open, axial, and selective coding. To enhance the validity of the findings, member checking and constant comparison techniques were also used.

Findings: The results indicate that causal conditions—including organizational, social, managerial, industrial, and financial factors—play a significant role in the adoption of IoT in this industry. In addition, contextual conditions such as partner maturity in the supply chain, technological infrastructure, and supply chain capabilities act as either facilitators or barriers. Cultural, security, technical, and financial factors were identified as intervening conditions.

Originality/scientific added value: The innovation of this study lies in its focus on localizing the IoT adoption model in the Iranian automotive supply chain and its precise identification of specific dimensions and barriers in this field. The presented results can serve as a guide for decision-makers and researchers to facilitate and accelerate the successful implementation of this technology in the automotive industry.

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