Resource Planning and Management in Interorganizational Systems in the Oil, Gas, and Petrochemical Industries

The oil, gas, and petrochemical industries constitute as a complex system characterized by extensive interdependencies among multiple actors and a wide variety of resource flows. Effective management of these flows is the foundamental to the stability of the industries concerned. This study examines resource planning in interorganizational systems involving business entities operating in the oil, gas, and petrochemical industries. The study aimed to conceptualized the existing problems and develop a model for effective resource planning within such systems. The methods employed included observation, systems analysis, hypothetical-deductive reasoning, generalization, economic and mathematical modeling, and optimization. Based on the technological principles and the current operating conditions of oil, gas, and petrochemical production, the specific characteristics of resource flows within interorganizational systems were identified, and the available resource planning and management tools were analyzed accordingly. Barriers to effective resource planning in interorganizational systems of interaction in the Russian oil, gas, and petrochemical industries were identified. A conceptual economic and mathematical model of resource planning efficiency was developed. The model can be used to determing the optimal volumes and routes of resource flows within an interorganizational system. An approach to measuring the entropy of resource flows within systems comprising interacting business entities was also proposed. The developed model can serve as an component of an adaptive resource flow management framework used when establishing industrial clusters and other forms of interorganizational cooperation in the oil, gas, and petrochemical industries. The causal relationships identified in the study should be considered both in strategy development and operational management by industry participants and in the formulation and implemention of government policies regulating the development and operation of these industries.

1. Bratskikh D.S., Romasheva N.V., Konopelko A.Yu. (2024). A Digital Supply Chain Management Model for the Oil and Gas Industry. Oil Industry, 7: 120-125. (In Russ.)

2. Bunkovsky D.V. (2024). Digitalization of Management in Organizational Systems of Interaction between Business Entities in the Petrochemical Complex. Bulletin of Tver State University. Series: Economics and Management, 2: 84-92. (In Russ.)

3. Gubanova E.V., Samoshenkova K.A. (2024). Reserves of Automation and Digital Transformation of the Organization’s Business Processes in the Context of Lean Manufacturing. Bulletin of the Altai Academy of Economics and Law, 3-3: 367-373. (In Russ.)

4. Gary D.H., Handwerk G.E., Kaiser M.D. (2013). Refining Technology and Economics. St. Petersburg, Professiya. (In Russ.)

5. Egorov V.I., Zlotnikova L.G. (1989). Refining and Petrochemical Enterprises: Organization, Planning, Management. Moscow, Khimiya. (In Russ.)

6. Kon M.Ya. (1986). Oil Refining and Petrochemical Industry Abroad. Moscow, Khimiya. (In Russ.)

7. Malysheva T.V. (2019). The Use of Information Systems in Managing the Environmental Sustainability of Petrochemical Industries. Sustainability Management, 6 (25): 27-31. (In Russ.)

8. Adebayo Y., Ikevuje A.H., Kwakye J., Esiri A. (2024). Circular Economy Practices in the Oil and Gas Industry: A Business Perspective on Sustainable Resource Management. GSC Advanced Research and Reviews, 20: 267-285.

9. Chamani Foomani Dana A., Tamannaei M. (2021) A Game-Theoretic Approach for Transportation of Oil Products in a Duopolistic Supply Chain. AUT Journal of Civil Engineerin, 5(1): 115-128.

10. Dey P.K., Clegg B., Cheffi W. (2011). Risk Management in Enterprise Resource Planning Implementation: A New Risk Assessment Framework. Production Planning & Control, 24: 1-14.

11. Florescu M., Ceptureanu E., Cruceru A., Ceptureanu S. (2019). Sustainable Supply Chain Management Strategy Influence on Supply Chain Management Functions in the Oil and Gas Distribution Industry. Energies, 12: 1632.

12. Jiang X. (2024). Optimization of Logistics Inventory Management in Enterprises from the Supply Chain Perspective. International Journal of Global Economics and Management, 3: 309-314.

13. Jusoh A., Mahmood R., Ahmad Z., Mohd Z.A. (2024). Digital Supply Chain and Business Performance: The Case of the Oil and Gas Industry. Information Management and Business Review, 3: 1133-1145.

14. Koyeda V. (2025). Single Point of Integration to Enterprise Resource Planning Systems. Global Journal of Computer Science and Technology, 25: 1-7.

15. Min H. (2010) Artificial Intelligence in Supply Chain Management: Theory and Applications. International Journal of Logistics-Research and Applications, 13: 13-39.

16. Musa A. (2023). Review Paper Revolutionizing Oil and Gas Industries with Artificial Intelligence Technology. International Journal of Computer Sciences and Engineering, 5: 20-30.

17. Okeke A. (2024). An Exploration of Sustainability and Supply Chain Management Practises in the Oil and Gas Industry: A Systematic Review of Practises and Implications. Environmental and Sustainability Indicators, 23: 100462.

18. Ukato P., Esiri A., Sofoluwe O. (2024). Digital Twin Technology in Oil and Gas Infrastructure: Policy Requirements and Implementation Strategies. Engineering Science & Technology Journal, 6: 2039-2049.

19. Ullah I., Ilyas M., Jin Z., Almujibah H. (2024). A Fuzzy Logic-Based Risk Assessment Framework for the Crude Oil Transportation Supply Chain. Ocean Engineering, 311: 118997.

20. Wang S., Wang Y., Lai C. (2024). Connectivity Reliability Evaluation and Most Reliable Shipping Route Choice in a Seaborne Crude Oil Network. Heliyon, 10: 36295.