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Interpretive Structural Modeling of Value Chain Productivity Base on Modularity Approach in Oil and Gas Industries
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Nima Baghersaee1   , Seyed Zabihollah Hashemi2 , Mansoreh Aligholi3 |
1- PhD Student in Industrial Management, Department of Industrial Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran , N.baghersaes@iau.ir
2- Assistant Professor, Department of Industrial Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3- Associate Professor, Department of Business Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran |
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Abstract: (3 Views) |
The oil and gas industry is one of the most important economic sectors of countries, which is improving productivity in its value chain is a very important challenge. use of new approaches such as modularity and structural-interpretive models is necessary to eliminate this effect. In this study, key factors affecting the productivity of the value chain in the oil and gas industry and relationships between them determined based on the ISM/MIC-MAC approach. The results shows that eight key elements (value chain management, improvement phenomenon, strategic management model, supply chain management, modularity approach, productivity improvement, exploration and production process, and environmental assessment) are interconnected as Interpretive Structural network.Inspired by the logic of modularity, this model enables the design of a flexible, intelligent, and adaptable with environment value chain, which is improving operational productivity, strategic decision-making and facilitated innovation in the oil and gas industry, especially Iranian exploration and production companies.
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| Keywords: Value chain management, productivity improvement, strategic model, Modularity, Interpretive Structural Modeling, exploration and production companies(E&P). |
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Full-Text [PDF 1304 kb]
(2 Downloads)
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Type of Study: Research |
Subject:
Management
Received: 2026/09/21 | Accepted: 2026/09/1 | Published: 2026/09/1
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