Development and Validation of a Causal Model for Assessing Energy Imbalance in Iran’s Gas Industry

Abstract

This study aimed to identify and explain the factors influencing the severity of the gas imbalance, examine its consequences, and develop an integrated causal model. In terms of purpose, the study was applied, and methodologically, it employed an exploratory sequential mixed-methods design. Participants in the qualitative phase consisted of experts, managers, and specialists knowledgeable about issues related to the gas and energy industries. Data were collected through semi-structured interviews until theoretical saturation was reached and were subsequently analyzed. The statistical population of the quantitative phase comprised individuals with relevant knowledge and experience in the gas and energy sectors. Data from 300 respondents were examined using a researcher-developed 40-item questionnaire. Quantitative data were analyzed using SPSS and SmartPLS software and partial least squares structural equation modeling (PLS-SEM). The qualitative findings indicated that the gas imbalance is a multidimensional and systemic phenomenon. Its determinants were classified into six principal dimensions: demand pressure and consumption patterns; the quality of energy policymaking and governance; infrastructure capacity and reliability; demand-side management, technology, and efficiency; climatic and environmental pressures; and temporal and feedback complexities. The severity of the gas imbalance was also identified as the central construct, while its economic, industrial, social, environmental, and security consequences were identified as the model’s ultimate outcomes. The quantitative results confirmed the satisfactory reliability and validity of the measurement model and demonstrated that all seven research hypotheses were statistically significant. Demand pressure and consumption patterns, with a path coefficient of 0.291; temporal and feedback complexities, with a coefficient of 0.267; and climatic and environmental pressures, with a coefficient of 0.160, had positive and significant effects on the severity of the gas imbalance. Conversely, infrastructure capacity and reliability, with a coefficient of −0.256; the quality of energy policymaking and governance, with a coefficient of −0.201; and demand-side management, technology, and efficiency, with a coefficient of −0.147, had negative and significant effects on the severity of the imbalance. Furthermore, the severity of the gas imbalance had a strong positive effect on its consequences, with a path coefficient of 0.712. Collectively, the six predictor variables explained 62.9% of the variance in the severity of the gas imbalance, while the severity of the imbalance explained 50.6% of the variance in its consequences. The predictive relevance index values for the severity of the imbalance and its consequences were 0.408 and 0.316, respectively, and the model’s overall fit was assessed as acceptable and relatively satisfactory. Overall, the findings demonstrated that the gas imbalance is not attributable to a single factor and that its sustainable reduction requires simultaneous interventions in demand management, infrastructure development and modernization, governance reform, improvements in efficiency and technology, and the management of climatic impacts and time delays.