Presenting the Model of Internet of Things Drivers in Iran's Oil, Gas, and Electric Power Industry Supply Chain With a Fuzzy Total Interpretive Structural Modeling Approach

Document Type : Original Article

Authors

Department of Business Administration, Faculty of Financial Science, Management and Entrepreneurship, University of Kashan, Kashan, Iran

Abstract

In recent years, the Internet of Things (IoT) has emerged as a significant technology in the industrial and academic sectors, particularly in the context of the fourth-generation industry. Encouraging industries, including oil, gas, and electric power sectors to adopt IoT technology expeditiously is crucial due to its numerous advantages. This article focuses on the oil and gas and electric power industry, which is a vital sector in any country, and emphasizes the need for the accelerated implementation of IoT to unlock its potential benefits. Despite the potential of IoT to achieve important and innovative changes in oil, gas, and electric power industries, surveys indicate a slow adoption trend in Iran. Thus, this research aims to identify and model the drivers that influence the implementation of IoT in Iran's oil, gas, and electric power industry supply chain. The research consists of two stages: the identification of drivers through literature review and assessment using the Delphi method and the presentation of a model of drivers using fuzzy total interpretive structural modeling. The results, comprising 75 drivers categorized into 14 general categories, highlight "government regulations" as the most fundamental driver in Iran's oil, gas, and electric power industry supply chain.

Keywords

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References

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Energy Engineering and Management
Volume 14, Issue 1
July 2024
Pages 90-107

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