Modeling the Factors Affecting Supply Chain Optimization in the Electricity Industry: a Combined Approach to Interpretive Structural Analysis

Abstract

The purpose of this study was interpretive structural modeling of the factors affecting supply chain optimization in the electricity industry. In this study, using a mixed method, a qualitative-quantitative approach was employed to model and verify the factors affecting supply chain optimization. To this end, through content analysis and thematic analysis using Novo software to form thematic networks, a qualitative model of factors influencing supply chain optimality was designed. In order to formulate a basic pattern of the factors affecting supply chain optimality, 23 experts in the electricity industry were selected through purposeful sampling method. In the quantitative section of the study, interpretive structural modeling (ISM) approach and MICMAC analysis were used. The results showed that the initial framework of supply chain optimality model has six dimensions including supply chain performance, supply chain management, supply chain risk management, supply chain quality management, production and operation, and supply chain stability. In the ISM graph, the variables were categorized at different levels, in which the "agency" and "strategy" factors were the highest and "customer satisfaction" was the lowest factor. After MICMAC analysis, the variables were categorized in three groups of independent variables with 11 variables, with four variables and dependent variables with 10 variables. No variables were included in the PA.

Keywords

• optimization
• supply chain
• electricity industry
• ism
• micmac analysis