Tools for Assessing the Potential Aggressiveness of Energy Companies' Market Strategies by Using Selective Indicators from Their Financial Statements

Mikhail V. Rodchenkov

Lomonosov Moscow State University, Moscow, Russia

Abstract

One of the consequences of the negative impact of political turbulence in the energy sector and on the global hydrocarbon market is changes in established strategies and behavior of participants, including the desire for inorganic growth at the expense of competitors. This highlights the urgency of revising indicators and applied predictive models for identifying market threats. The purpose of the study is to create a toolkit for assessing the aggressiveness potential of a company's market strategy (an applied indicative model of market threats) based on selective indicators of corporate financial reporting. The hypothesis assumes that the potential for aggressiveness of a company's market strategy is characterized by the values of a stable set of reporting indicators, the targeted change of which affects the assessment of the potential ability and readiness of a business to act as a source of market threats. The methodological framework includes regression and multivariate analysis using nonparametric testing, including single-factor analysis of variance (ANOVA) by rank. Based on the results of testing the empirical model based on primary data collected by the author from 20 leading public companies in the energy sector of four economies, reporting indicators with confirmed indicative properties were identified. The results obtained indicate that for a reliable gradation of participants in the market environment according to the degree of their potential danger to other companies, three reporting indicators are sufficient: the intensity of use of fixed assets, market activity and the enterprise value. The indicative model of market threats formed on their basis has been successfully tested. The results of the study equip managers with a stable set of reporting indicators, determined by the study of potential aggressiveness indicators of the company's market strategy; the proposed methodological approaches have the ability to adapt to solving the problems of increasing the stability and efficiency of corporate risk management systems without significant additional costs and can be used in the future for developing machine learning protocols. In addition, the results of this study may be useful for analysts and auditors when evaluating corporate market strategies and market risk management systems.

Keywords

market risks; market environment; indicative model; potential for aggressiveness; corporate management; information-significant reporting indicators; IFRS

JEL classification

References

1. Adner, R., Puranam, P., Zhu, F. (2019). What is different about digital strategy? From quantitative to qualitative change. Strategy Science, Vol. 4, No. 4, 253–261. https://doi.org/10.1287/stsc.2019.0099

            2. Vikhansky, O.S., Katalevsky, D.Y. (2022). Competitive advantage in the era of digitalization. Russian Management Journal, Vol. 20, No. 1, 5–27. (In Russ.). https://doi.org/10.21638/spbu18.2022.101

            3. Adner, R. (2021). Winning the Right Game: How to Disrupt, Defend, and Deliver in a Changing World. Cambridge, MA, MIT Press, 278 p. Available at: https://mitpress.mit.edu/9780262546003/winning-the-right-game/

            4. Porter, M. (1980). Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York, The Free Press, 396 p. Available at: https://www.hbs.edu/faculty/Pages/item.aspx?num=195

            5. Porter, M. (1985). Competitive Advantage: Creating and Sustaining Superior Performance. New York, The Free Press, 557 p. Available at: https://www.hbs.edu/faculty/Pages/item.aspx?num=193

            6. Sarasvathy, S.D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, Vol. 26, No. 2, 243–263. https://doi.org/10.5465/AMR.2001.4378020

            7. Read, S., Dew, N., Sarasvathy, S.D., Song, M. (2009). Marketing under uncertainty: The logic of an effectual approach. Journal of Marketing, Vol. 73, Issue 3, 1–18. https://doi.org/10.1509/jmkg.73.3.1

            8. Tsujimoto, M., Kajikawa, Y., Tomita, J., Matsumoto, Y. (2018). A review of the ecosystem concept. Towards coherent Ecosystem Design. Technological Forecasting and Social Change, Vol. 136, 49–58. https://doi.org/10.1016/j.techfore.2017.06.032

            9. Bogers, M., Sims, J., West, J. (2019). What is an ecosystem? Incorporating 25 years of ecosystem research. Academy of Management Proceedings, No. 1, 1–29. https://doi.org/10.5465/AMBPP.2019.11080abstract

            10. Kamynin, V.A. (2019). Assessment of the sustainability of the company's market leadership: an industry approach. Vestnik of Saint Petersburg University. Management, Vol. 18, No. 1, 3–38. (In Russ.). https://doi.org/10.21638/11701/spbu08.2019.101

            11. Kleiner, G.B. (2008). Enterprise Strategy. Moscow, Delo, 586 p. (In Russ.). Available at: https://kleiner.ru/wp-content/uploads/2014/10/strag_pr.pdf

            12. Kobylko, A.A. (2022). Crisis-Resilient Enterprise Strategy: Lessons from the Pandemic. Vestnik of Saint Petersburg University. Management, Vol. 21, No. 1, 3–18. (In Russ.). https://doi.org/10.21638/11701/spbu08.2022.101

            13. Kachalov, R.M. (2012). Economic Risk Management: Theoretical Foundations and Applications. Moscow, St. Petersburg, Nestor-Istoriia, 286 p. (In Russ.). Available at: https://elibrary.ru/item.asp?id=23008776

            14. Kachalov, R.M., Sleptsova, Y.A. (2022). Business Ecosystems in Crisis Conditions: Identification of Risk Factors. Russian Management Journal, Vol. 20, No. 2, 155–171. (In Russ.). https://doi.org/10.21638/spbu18.2022.201

            15. Trysyachny, V.I., Melnikov, A.B., Kotenev, A.D. (2017). Features of modeling the economic security of an industrial complex. St. Petersburg State Polytechnical University Journal. Economics, Vol. 10, No. 6, 96–105. (In Russ.). https://doi.org/10.18721/JE.10609

            16. Russian Business Response to the COVID-19 Pandemic (Case Study of Six Industry Cases) (2021). Edited by T.G. Dolgopyatova, N.V. Akindinova, Y.V. Simachev, A.A. Yakovlev. Moscow, Publishing House of the Higher School of Economics, 446 p. (In Russ.). Available at: https://publications.hse.ru/books/552371623

            17. Kleiner, G.B. (2013). System Economics as a Platform for the Development of Modern Economic Theory. Voprosy Ekonomiki, No. 6, 4–28. (In Russ.). https://doi.org/10.32609/0042-8736-2013-6-4-28

            18. Meuer, J., Koelbel, J., Hoffmann, H. (2020). On the nature of corporate sustainability. Organization & Environment, Vol. 33, Issue 3, 319–341. https://doi.org/10.1177/1086026619850180

            19. Kim, A., Bansal, P., Haugh, H. (2019). No time like the present: How time perspective can foster sustainable development. Academy of Management Journal, Vol. 62, No. 2, 607–632. https://doi.org/10.5465/amj.2015.1295

            20. Verenikin, A.O., Makhankova, N.A., Verenikina, A.Yu. (2021). Measuring the sustainability of the development of large Russian companies. Russian Management Journal, Vol. 19, No. 3, 237–287. (In Russ.). https://doi.org/10.21638/spbu18.2021.301

            21. Farooque O. (2016). Sustainable financial reporting practice in Australian companies – Does quality matter? Journal of Developing Areas, Vol. 50, No. 6, 175–189. https://doi.org/10.2307/26415660

            22. Plaskova, N.S., Polyanskaya, T.A., Prodanova, N.A. (2020). Methodology of Accounting and Analytical Support of the Innovation Management System: Monograph. Moscow, INFRA-M, 180 p. (In Russ.). https://doi.org/10.12737/monography_5d412b2b4888f3.52574547

            23. Turmanov, M.T., Rogulenko, T.M. (2022). The Impact of Digital Technologies on the Information Potential of Accounting (Financial) Reporting. Part 1: The concept of assessing the information content of corporate reporting, models of digitalization of assets, liabilities and their impact on the information potential of reporting. Vestnik Universiteta, No. 7, 129–137. (In Russ.). https://doi.org/10.26425/1816-4277-2022-7-129-137

            24. Lev, B. (2018). The deteriorating usefulness of financial report information and how to reverse it. Accounting and Business Research, Vol. 48, Issue 5, 465–493. https://doi.org/10.1080/00014788.2018.1470138

            25. Lo, K., Ramos, F., Rogo, R. (2017). Earnings management and annual report readability. Journal of Accounting and Economics, Vol. 63, Issue 1, 1–25. https://doi.org/10.1016/j.jacceco.2016.09.002

            26. Druzhilovskaya, T.Y., Druzhilovskaya, E.S. (2022). Problematic aspects of the draft of the new IAS 1 on the preparation of financial statements. Accounting. Analysis. Auditing, Vol. 9, No. 4, 35–44. (In Russ.). https://doi.org/10.26794/2408-9303-2022-9-4-35-44

            27. Rodchenkov, M.V. (2022). Problems of users’ perception of financial statements according to international standards. Russian Management Journal, Vol. 20, No. 3, 319–341. (In Russ.). https://doi.org/10.21638/spbu18.2022.301

            28. Rodchenkov, M.V. (2023). Assessment of the Satisfaction of the Russian Investment Community with the Quality of Financial Statements according to International Standards. Journal of Applied Economic Research, Vol. 22, No. 1, 165–189. (In Russ.). https://doi.org/10.15826/vestnik.2023.22.1.008

            29. Puchkova, S.I., Voronova, E.Y. (2023). Integrated Reporting as a Basis for Socially Responsible Investment. Accounting and Reporting, Vol. 9, No. 4, 18–24. (In Russ.). https://doi.org/10.12737/1998-0701-2023-9-4-18-24

            30. Kuleshov, D., Viljainen, S., Annala, S., Gore, O. (2012). Russian electricity sector reform: Challenges to retail competition. Utilities Policy, Vol. 23, 40–49. https://doi.org/10.1016/j.jup.2012.05.001

            31. Kornukov, I.I., Domnikov, A.Yu. (2023). Comparative Evaluation of the Performance of Commercial Banks in Russia Based on a Multidimensional Analysis of Financial Indicators. Journal of Applied Economic Research, Vol. 22, No. 1, 142–164. (In Russ.). https://doi.org/10.15826/vestnik.2023.22.1.007

            32. Yang, C.C., Ou, S.L., Hsu, L.C. (2019). A Hybrid Multi-Criteria Decision-Making Model for Evaluating Companies’ Green Credit Rating. Sustainability, Vol. 11, Issue 6, 1506. https://doi.org/10.3390/su11061506

            33. Chistyakov, V.V. (2014). On the superposition of the Borda and threshold preference orders for three-graded rankings. Procedia Computer Science, Vol. 31, 1032–1035. https://doi.org/10.1016/j.procs.2014.05.356

            34. Vazhenina, L.V., Magaril, E.R., Mayburov, I.A. (2022). Comprehensive Assessment of Resource Efficiency of Russian Gas Industry Companies. Journal of Applied Economic Research, Vol. 21, No. 3, 454–485. (In Russ.). https://doi.org/10.15826/vestnik.2022.21.3.016

            35. Sueyoshi, T., Wang, D. (2014). Sustainability development for supply chain management in US petroleum industry by DEA environmental assessment. Energy Economics, Vol. 46, 295–307. https://doi.org/10.1016/j.eneco.2014.09.022

            36. Göcs, L., Johanyák, Z.C. (2023). Feature Selection with Weighted Ensemble Ranking for Improved Classification Performance on the CSE-CIC-IDS2018 Dataset. Computers, Vol. 12, Issue 8, 147. https://doi.org/10.3390/computers12080147

            37. Avazyan, A.S., Mkhitaryan, V.S. (2001). Applied Statistics and Fundamentals of Econometrics. In 2 Vols. 2nd ed. Vol. 1. Probability Theory and Applied Statistics. Moscow, UNITY-DANA, 1000 p.. (In Russ.). Available at: https://institutiones.com/download/books/3045-prikladnaya-statistika-osnovy-ekonometriki.html

            38. Dhal, P., Azad, C. (2022). A comprehensive survey on feature selection in the various fields of machine learning. Applied Intelligence, Vol. 52, 4543–4581. https://doi.org/10.1007/s10489-021-02550-9

            39. Aggarwal, N., Shukla, U., Saxena, G., Rawat, M., Bafila, A., Singh, S., Pundir, A. (2023). Mean based relief: An improved feature selection method based on ReliefF. Applied Intelligence, Vol. 53, 23004–23028. https://doi.org/10.1007/s10489-023-04662-w

            40. Arif1, S., Marsoem, B.S. (2021). The Analysis of a company’s financial performance before and after implementing the initial public offering (a study on the company listing in the IDX Of 2018). Dinasti International Journal of Education Management and Social Science (DIJEMSS), Vol. 2, No. 4, 1045–1058. https://doi.org/10.31933/dijemss.v2i6.996

            41. Mozgovaya, O.O. (2018). Analysis of foreign experience of development of competition at retail electricity markets: UK and Northern Europe countries experience. Vestnik Universiteta, No. 10, 108–116. (In Russ.). https://doi.org/10.26425/1816-4277-2018-10-108-116

            42. Wilcoxon, F. (1945). Individual Comparisons by Ranking Methods. Biometrics Bulletin, Vol. 1, No. 6, 80–83. https://doi.org/10.2307/3001968

            43. Mann, H.B., Whitney, D.R. (1947). On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other. The Annals of Mathematical Statistics, Vol. 18, Issue 1, 50–60. https://doi.org/10.1214/aoms/1177730491

            44. Kruskal, W.H., Wallis, W.A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, Vol. 47, 583–621. https://doi.org/10.2307/2280779

            45. Conover, W.J. (1999). Practical Nonparametric Statistics. 3rd ed. New York, Wiley, 608 p. Available at: https://www.wiley.com/en-cn/Practical+Nonparametric+Statistics,+3rd+Edition-p-9780471160687

Acknowledgements

The author expresses gratitude to Viktor P. Suits, Doctor of Economics, Distinguished Professor of the Lomonosov Moscow State University for scientific and methodological guidance and useful recommendations during the preparation of the article.

About Authors

Mikhail Viktorovich Rodchenkov

Candidate of Economic Sciences, Department of Accounting, Analysis and Audit, Faculty of Economics, Lomonosov Moscow State University, Moscow, Russia (119991, Moscow, GSP-1, Leninskie Gory, 1, building, 46); ORCID https://orcid.org/0000-0002-6938-2313 e-mail: M.Rodchenkov@gmail.com

For citation

Rodchenkov, M.V. Tools for Assessing the Potential Aggressiveness of Energy Companies' Market Strategies by Using Selective Indicators from Their Financial Statements. Journal of Applied Economic Research, Vol. 23, No. 4, 1182-1210. https://doi.org/10.15826/vestnik.2024.23.4.046

Article info

Received July 22, 2024; Revised August 20, 2024; Accepted September 2, 2024.

DOI: https://doi.org/10.15826/vestnik.2024.23.4.046

Download full text article: