Digital transformation management in oil supply chains using scenario analysis

UDK: 681.518:622:276

DOI: 10.24887/0028-2448-2026-2-77-82

Key words: oil supply chains, integrated index, digital maturity, efficiency, resilience, scenario analysis, investment prioritization, IPC, digital transformation

Authors: D.S. Bratskikh (Empress Catherine II Saint Petersburg Mining University, RF, Saint Petersburg); N.V. Romasheva (Empress Catherine II Saint Petersburg Mining University, RF, Saint Petersburg)

The article focuses on developing an approach to managing the digital transformation of oil supply chains using scenario analysis. An integral index is used as the core analytical tool, enabling a quantitative assessment of the efficiency and resilience of oil supply chain segments. Previous studies confirmed the dependence of index values on the digital maturity level of supply chain segments. Digital transformation management is examined through scenario analysis applied to a four-stage supply chain: extraction – transportation – storage – distribution. The calculation results revealed significant disparities in the integral index across the supply chain stages, from 41,5 (extraction) to 76,3 (storage). These findings highlight the need for targeted digitalization of the most vulnerable segments. Scenario modeling enabled to analyze the dynamics of the index under different digital transformation strategies. Under the inertial scenario, the index reached 52,1, under the moderate transformation scenario - 67,3, under the aggressive digitalization scenario - 81,9. To support investment decision-making, the approach incorporates an indicator of integrated performance per unit of capital (IPC). Its values increased from less than 3 % to 13 % when moving from a low to a high level of digital maturity. The study demonstrates that the integral index in scenario analysis can be used as a managerial tool for diagnosing supply chain conditions, prioritizing digitalization initiatives, forming investment portfolios. A network effect was identified: digitalization of individual supply chain stages enhances the performance of adjacent stages, confirming the necessity of a comprehensive approach to managing the digital transformation of oil supply chains.

References

1. Ulanov V., Skorobogatko O., Impact of EU carbon border adjustment mechanism on the economic efficiency of Russian oil refining, Zapiski Gornogo instituta = Journal of Mining Institute, 2022, Online first, DOI: https://doi.org/10.31897/PMI.2022.83

2. Skobelev D.O., Cherepovitsyna A.A., Guseva T.V., Carbon capture and storage: net zero contribution and cost estimation approaches (In Russ.), Zapiski Gornogo instituta = Journal of Mining Institute, 2023, V. 259, pp. 125–140, DOI: https://doi.org/10.31897/PMI.2023.10

3. Carter C.R., Rogers D.S., A framework of sustainable supply chain management: moving toward new theory, International Journal of Physical Distribution & Logistics Management, 2008, V. 38, no. 5, pp. 360–387, DOI: https://doi.org/10.1108/09600030810882816

4. Ivanov D., Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability, International Journal of Production Economics, 2023, V. 263,

DOI: https://doi.org/10.1016/j.ijpe.2023.108938

5. Gökalp E., Martinez V., Digital transformation maturity assessment: development of the digital transformation capability maturity model, International Journal of Production Research, 2022, V. 60, no. 20, pp. 6282–6302, DOI: https://doi.org/10.1080/00207543.2021.1991020

6. Büyüközkan G., Göçer F., Digital supply chain: literature review and a proposed framework for future research, Computers in Industry, 2018, V. 97, pp. 157–177,

DOI: https://doi.org/10.1016/j.compind.2018.02.010

7. Hui Fang, Fei Fang, Qiang Hu, Yuehua Wan, Supply chain management: a review and bibliometric analysis, Processes, 2022, V. 10, no. 9,

DOI: https://doi.org/10.3390/pr10091681

8. Ahmed H., Bashar M.A., Rahman M.A.T., Innovative approaches to sustainable supply chain management in the manufacturing industry: a systematic literature review, Global Mainstream Journal of Innovation, Engineering & Emerging Technology, 2024, V. 3, no. 2, DOI: https://doi.org/10.62304/jieet.v3i02.81

9. Hanelt A., Bohnsack R., Marz D., Marante C.A., A systematic review of the literature on digital transformation: insights and implications for strategy and organizational change, Journal of Management Studies, 2021, V. 58, no. 5, pp. 1159–1197, DOI: https://doi.org/10.1111/joms.12639

10. Saaty T.L., Decision making with the analytic hierarchy process, International Journal of Services Sciences, 2008, V. 1, no. 1, pp. 83–98,

DOI: https://doi.org/10.1504/IJSSCI.2008.017590

11. Pournader M., Ghaderi H., Hassanzadegan A., Fahimnia B., Artificial intelligence applications in supply chain management, International Journal of Production Economics, 2021, V. 241, DOI: https://doi.org/10.1016/j.ijpe.2021.108250

12. Andaloussi M.B., A bibliometric literature review of digital supply chain: trends, insights, and future directions, SAGE Open, 2024, V. 14, no. 2,

DOI: https://doi.org/10.1177/21582440241240340

13. Bratskikh D.S., Romasheva N.V., Konopelko A.Yu., Nikolaychuk L.A., Model of supply chain management in the oil and gas industry using digital technologies

(In Russ.), Neftyanoye khozyaystvo = Oil Industry, 2024, no. 7, pp. 120–125, DOI: https://doi.org/10.24887/0028-2448-2024-7-120-125.technologies

14. Tiwari M.K., Bidanda B., Geunes J. et al., Supply chain digitisation and management, International Journal of Production Research, 2024, V. 62, no. 8, pp. 2918–2926, DOI: https://doi.org/10.1080/00207543.2024.2316476

15. Matrokhina K., Trofimets V., Mazakov E. et al., Development of methodology for scenario analysis of investment projects of enterprises of the mineral resource complex (In Russ.), Zapiski Gornogo instituta = Journal of Mining Institute, 2023, V. 259, pp. 112–124, DOI: https://doi.org/10.31897/PMI.2023.3