Analyzing the Role of the Network Economy in Optimizing the Oil Industry Supply Chain and Its Implications for Business Performance: A Data Mining Approach
Keywords:
Network economy, Oil industry supply chain, Business performance, Data mining, Panel data analysis, SPSS, Predictive modelingAbstract
Objective: This study aimed to analyze the role of the network economy in optimizing the oil industry supply chain and to examine its implications for business performance by integrating panel statistical analyses with data mining methods.
Methodology: This applied, quantitative, ex post facto study used firm-year data from 20 publicly listed U.S. oil and gas companies over 2020-2024, yielding an initial panel of 100 firm-year observations. Network economy was measured by the unique number of named partnerships, joint ventures, and disclosed corporate investment relationships. The operating expense-to-revenue ratio represented supply chain cost optimization, while return on assets and net profit margin represented business performance. Data were analyzed using hierarchical regression, generalized linear models with firm-clustered robust standard errors, Mundlak decomposition, and data mining algorithms including linear regression, regression trees, random forests, neural networks, and automated numerical modeling.
Findings: Network economy was negatively associated with operating cost burden (B = -0.0064, p < 0.05) and positively associated with return on assets (B = 0.0042, p < 0.05) and net profit margin (B = 0.0061, p < 0.05). Operating cost burden was negatively related to return on assets (B = -0.278, p < 0.001) and net profit margin (B = -0.624, p < 0.001). Final R2 values were 0.401 for operating cost burden, 0.526 for return on assets, and 0.603 for net profit margin. Mundlak decomposition showed that between-firm network effects were generally significant. Automated numerical modeling provided the best predictive performance for operating cost burden (R2 = 0.618) and return on assets (R2 = 0.557).
Conclusion: The findings indicate that broader network relationships in oil companies are associated with lower operating cost burden and stronger financial performance, and that combining explanatory and predictive approaches provides a useful framework for evaluating the role of the network economy in supply chain optimization.
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