Current trends and future prospects in business management analysis integration

Tetiana Portovaras; Nadiia Kovalenko; Anastasiia Kaplina; Natalia Kyrychenko; Zinoviia Zaloha

doi:10.31893/multirev.2024spe005

Keywords:

big data analytics

artificial intelligence

machine learning

digital transformation

business management

strategic planning

Abstract

The study examines the importance of implementing modern analytical methods to enhance competitiveness and efficiency in the digital age. The relevance of the research topic is driven by the dynamic development of technologies and the increasing volume of data, which requires organisations to adapt to a rapidly changing information environment. Big data analytics, artificial intelligence, machine learning, and other innovative tools are now essential for data-driven decision-making and creating new strategic advantages. The integration of analytical methods is crucial in improving the effectiveness of managerial processes. Modern approaches, such as big data analytics, artificial intelligence, and machine learning, provide more in-depth insights into market processes. It enables the identification of new opportunities and minimises risks. These approaches facilitate the identification of trends and patterns that may only sometimes be apparent when using traditional methods. In the context of globalisation and rapid changes in the economic environment, the ability to adapt quickly and make informed managerial decisions becomes a competitive advantage. Success in the digital age requires organisations to adopt innovative technologies and develop flexible strategic approaches that enable quick adaptation to changes and the implementation of innovations. The findings of this section suggest that businesses that incorporate analytics into their management processes can achieve substantial benefits, such as enhanced flexibility, operational efficiency, and innovation capabilities.
References
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31. Pamucar, D., Žižović, M., Biswas, S., & Božanić, D. (2021). A new logarithm methodology of additive weights (LMAW) for multi-criteria decision-making: Application in logistics.
32. Podolchak, N., Tsygylyk, N., Martyniuk, V., & Sokil, O. (2021). Predicting Human Resource Losses due to the COVID-19 Pandemic in the Context of Personnel Security of Organizations. 11th International Conference on Advanced Computer Information Technologies, ACIT 2021 - Proceedings, 333-336.
33. Popescu, G. H., Valaskova, K., & Horak, J. (2022). Augmented reality shopping experiences, retail business analytics, and machine vision algorithms in the virtual economy of the metaverse. Journal of Self-Governance and Management Economics, 10(2), 67-81.
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35. Sahoo, S. (2022). Big data analytics in manufacturing: a bibliometric analysis of research in the field of business management. International Journal of Production Research, 60(22), 6793-6821.
36. Shair, F., Shaorong, S., Kamran, H. W., Hussain, M. S., Nawaz, M. A., & Nguyen, V. C. (2021). Assessing the efficiency and total factor productivity growth of the banking industry: do environmental concerns matters? Environmental Science and Pollution Research, 28, 20822-20838.
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43. Tseng, M. L., Tran, T. P. T., Ha, H. M., Bui, T. D., & Lim, M. K. (2021). Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: A data driven analysis. Journal of Industrial and Production Engineering, 38(8), 581-598.
44. Yalcin, A. S., Kilic, H. S., & Delen, D. (2022). The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review. Technological forecasting and social change, 174, 121193.
45. Yang, J., Xiu, P., Sun, L., Ying, L., & Muthu, B. (2022). Social media data analytics for business decision making system to competitive analysis. Information Processing & Management, 59(1), 102751.
46. Yu, W., Zhao, G., Liu, Q., & Song, Y. (2021). Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organisational information processing theory perspective. Technological Forecasting and Social Change, 163, 120417.
47. Zhang, H., Xiao, H., Wang, Y., Shareef, M. A., Akram, M. S., & Goraya, M. A. S. (2021). An integration of antecedents and outcomes of business model innovation: A meta-analytic review. Journal of Business Research, 131, 803-814.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Portovaras, T., Kovalenko, N., Kaplina, A., Kyrychenko, N., & Zaloha, Z. (2024). Current trends and future prospects in business management analysis integration. Multidisciplinary Reviews, 7, 2024spe005. https://doi.org/10.31893/multirev.2024spe005

[1] Alekseieva, K., Maletych, M., Ptashchenko, O., Baranova O., & Buryk, Z. (2023). State business support programs in wartime conditions. Economic Affairs, New Delhi, 68(1s), 231-242. https://doi.org/10.46852/0424-2513.1s.2023.26

[2] Anh, D. B. H., & Tien, N. H. (2021). Using Hoffer matrix in strategic business analysis for Nguyen Hoang Group in Vietnam. International journal multidisciplinary research and growth evaluation, 2(4), 61-66.

[3] Bapat, G., Mahindru, R., Kumar, A., Rroy, AD, Bhoyar, S., & Vaz, S. (2024). Leveraging ChatGPT for Empowering MSMEs: A Paradigm Shift in Problem Solving. Engineering Proceedings, 59(1), 197-207. https://doi.org/10.3390/engproc2023059197

[4] Bayev, V. V., Bakhov, I. S., Mirzodaieva, T. V., Rozmetova, O., & Boretskaya, N. (2022). Theoretical and methodological fundamentals of the modern paradigm of quality management in the field of tourism. Journal of Environmental Management and Tourism, 13(2), 338-345. https://doi.org/10.14505/jemt.v13.2(58).04

[5] Benzaghta, M. A., Elwalda, A., Mousa M. M., Erkan, I., & Rahman, M. (2021). SWOT analysis applications: An integrative literature review. Journal of Global Business Insights, 6(1), 55-73.

[6] Büyüközkan, G., Mukul, E., & Kongar, E. (2021). Health tourism strategy selection via SWOT analysis and integrated hesitant fuzzy linguistic AHP-MABAC approach. Socio-Economic Planning Sciences, 74, 100929.

[7] Chatterjee, S., Rana, N. P., & Dwivedi, Y. K. (2021). How does business analytics contribute to organisational performance and business value? A resource-based view. Information Technology & People.

[8] Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296.

[9] Duan, L., & Da Xu, L. (2021). Data analytics in industry 4.0: A survey. Information Systems Frontiers, 1-17.

[10] Dzhyhora, O., Gasimov, A. (2022). Implementation of Energy Efficient Technologies and Systems in Housing Construction. Lecture Notes in Civil Engineering, 181, 625-637.

[11] Feng, G., Kong, G., & Wang, Z. (2021). We are on the way: Analysis of on-demand ride-hailing systems. Manufacturing & Service Operations Management, 23(5), 1237-1256.

[12] Fosso Wamba, S., Queiroz, M. M., Wu, L., & Sivarajah, U. (2024). Big data analytics-enabled sensing capability and organisational outcomes: assessing the mediating effects of business analytics culture. Annals of Operations Research, 333(2), 559-578.

[13] Grant, R. M. (2021). Contemporary strategy analysis. John Wiley & Sons.

[14] Hallikas, J., Immonen, M., & Brax, S. (2021). Digitalising procurement: the impact of data analytics on supply chain performance. Supply Chain Management: An International Journal, 26(5), 629-646.

[15] Halushko, O., & Batmanhlich, K. (2023). Ethical and practical aspects of the use of artificial intelligence in the educational process. Philosophy, Economics and Law Review, 3(2), 47-52. https://doi.org/10.31733/2786-491X-2023-2-47-52

[16] Henry, A. (2021). Understanding strategic management. Oxford University Press.

[17] Kachula, S., Zhytar, M., Sidelnykova, L., Perchuk, O., & Novosolova, O. (2022). The Relationship between Economic Growth and Banking Sector Development in Ukraine. WSEAS Transactions on Business and Economics, 19, 222-230. https://doi.org/10.37394/23207.2022.19.21

[18] Kalina, I., Khurdei, V., Shevchuk, V., Vlasiuk, T., & Leonidov, I. (2022). Introduction of a corporate security risk management system: The experience of poland. Journal of Risk and Financial Management, 15(8). https://doi.org/10.3390/jrfm15080335

[19] Khraisat, A., & Alazab, A. (2021). A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges. Cybersecurity, 4, 1-27.

[20] Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025.

[21] Kotsur, V., Kovtun, O. (2021). Ideology and controversity of the return of pereiaslav-khmelnytskyi historical name pereiaslav: management aspect. East European Historical Bulletin, 21, 230-243. https://doi.org/10.24919/2519-058X.21.246901

[22] Kraus, S., Schiavone, F., Pluzhnikova, A., & Invernizzi, A. C. (2021). Digital transformation in healthcare: Analysing the current state-of-research. Journal of Business Research, 123, 557-567.

[23] Kravchuk, O. I., Varis, I. O., & Pierkova, M. V. (2023). Modern practices of using artificial intelligence for the digitalization of recruiting. Problems of modern transformations. Series: Economics and Management, 8, 1-8. https://doi.org/10.54929/2786-5738-2023-8-04-06

[24] Kristoffersen, E., Mikalef, P., Blomsma, F., & Li, J. (2021). Towards a business analytics capability for the circular economy. Technological Forecasting and Social Change, 171, 120957.

[25] Kumar, S., Sureka, R., Lim, W. M., Kumar Mangla, S., & Goyal, N. (2021). What do we know about business strategy and environmental research? Insights from Business Strategy and the Environment. Business Strategy and the Environment, 30(8), 3454-3469.

[26] Lee, C. S., Cheang, P. Y. S., & Moslehpour, M. (2022). Predictive analytics in business analytics: decision tree. Advances in Decision Sciences, 26(1), 1-29.

[27] Lim, M. K., Li, Y., Wang, C., & Tseng, M. L. (2021). A literature review of blockchain technology applications in supply chains: A comprehensive analysis of themes, methodologies and industries. Computers & industrial engineering, 154, 107133.

[28] Lopatynskyi, Belei, S., Kapelista, I., & Pavlyshyn, M. (2023). The Effectiveness of the Management System in the Conditions of War and its Influence on the Development of Agribusiness. Review of Economics and Finance, 21, 932-940.

[29] Manogaran, G., Thota, C., & Lopez, D. (2022). Human-computer interaction with big data analytics. In Research Anthology on Big Data Analytics, Architectures, and Applications, 1578-1596.

[30] Margherita, A. (2022). Human resources analytics: A systematisation of research topics and directions for future research. Human Resource Management Review, 32(2), 100795.

[31] Pamucar, D., Žižović, M., Biswas, S., & Božanić, D. (2021). A new logarithm methodology of additive weights (LMAW) for multi-criteria decision-making: Application in logistics.

[32] Podolchak, N., Tsygylyk, N., Martyniuk, V., & Sokil, O. (2021). Predicting Human Resource Losses due to the COVID-19 Pandemic in the Context of Personnel Security of Organizations. 11th International Conference on Advanced Computer Information Technologies, ACIT 2021 - Proceedings, 333-336.

[33] Popescu, G. H., Valaskova, K., & Horak, J. (2022). Augmented reality shopping experiences, retail business analytics, and machine vision algorithms in the virtual economy of the metaverse. Journal of Self-Governance and Management Economics, 10(2), 67-81.

[34] Rana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2022). Understanding the dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364-387.

[35] Sahoo, S. (2022). Big data analytics in manufacturing: a bibliometric analysis of research in the field of business management. International Journal of Production Research, 60(22), 6793-6821.

[36] Shair, F., Shaorong, S., Kamran, H. W., Hussain, M. S., Nawaz, M. A., & Nguyen, V. C. (2021). Assessing the efficiency and total factor productivity growth of the banking industry: do environmental concerns matters? Environmental Science and Pollution Research, 28, 20822-20838.

[37] Shet, S. V., Poddar, T., Samuel, F. W., & Dwivedi, Y. K. (2021). Examining the determinants of successful adoption of data analytics in human resource management – A framework for implications. Journal of Business Research, 131, 311-326.

[38] Silva, A. J., Cortez, P., Pereira, C., & Pilastri, A. (2021). Business analytics in Industry 4.0: A systematic review. Expert systems, 38(7), e12741.

[39] Soeffker, N., Ulmer, M. W., & Mattfeld, D. C. (2022). Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review. European Journal of Operational Research, 298(3), 801-820.

[40] Sugiarti, E., Finatariani, E., & Rahman, Y. T. (2021). Earning Cultural Values as A Strategic Step to Improve Employee Performance. Scientific Journal of Reflection: Economic, Accounting, Management and Business, 4(1), 221-230.

[41] Sumets, A., Tyrkalo, Popovych, N., Poliakova, J., & Krupin, V. (2022). Modeling of the environmental risk management system of agroholdings considering the sustainable development values. Agricultural and Resource Economics, 8(4), 244-265. https://doi.org/10.51599/are.2022.08.04.11

[42] Tavera Romero, C., Ortiz, J. H., Khalaf, O. I., & Ríos Prado, A. (2021). Business intelligence: business evolution after industry 4.0. Sustainability, 13(18), 10026.

[43] Tseng, M. L., Tran, T. P. T., Ha, H. M., Bui, T. D., & Lim, M. K. (2021). Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: A data driven analysis. Journal of Industrial and Production Engineering, 38(8), 581-598.

[44] Yalcin, A. S., Kilic, H. S., & Delen, D. (2022). The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review. Technological forecasting and social change, 174, 121193.

[45] Yang, J., Xiu, P., Sun, L., Ying, L., & Muthu, B. (2022). Social media data analytics for business decision making system to competitive analysis. Information Processing & Management, 59(1), 102751.

[46] Yu, W., Zhao, G., Liu, Q., & Song, Y. (2021). Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organisational information processing theory perspective. Technological Forecasting and Social Change, 163, 120417.

[47] Zhang, H., Xiao, H., Wang, Y., Shareef, M. A., Akram, M. S., & Goraya, M. A. S. (2021). An integration of antecedents and outcomes of business model innovation: A meta-analytic review. Journal of Business Research, 131, 803-814.

Abstract

References

How to cite