ALGORITHMIC MANAGEMENT AS A DRIVER OF ACCELERATED GROWTH IN HIGH-GROWTH FIRMS
DOI:
https://doi.org/10.68302/std2026.vol1.178Keywords:
Algorithmic Management, Fast Growing Company, Artificial Intelligence, Accelerated GrowthAbstract
The focus of this report is on exploring the relationship between algorithmic management and the specifics of high-growth firms, emphasizing the mechanisms through which data and algorithms support the achievement of accelerated organizational development. The analysis examines the role of artificial intelligence in decision-making processes, resource optimization, and adaptation to a dynamic business environment. On this basis, the main management mechanisms through which algorithmic management can function as a growth factor are identified, as well as limitations related to data dependence, transparency, and ethical aspects of algorithmic management.
Supporting Agencies
The publication is funded by the Bulgarian Scientific Fund, under Project N KP06H55/3 (“A conceptual model for evaluation of fast-growing companies operating in innovation-intensive industries, based on Artificial Intelligence methods”)Downloads
References
[1] V. K.Nhan, T. T. Thu, Mapping the landscape of algorithmic management in gig economy: A bibliometric analysis, International Journal of Information Management Data Insights, Volume 6, Issue 1, 2026, 100402, ISSN 2667-0968, https://doi.org/10.1016/j.jjimei.2026.100402.
[2] P. Liu, L. Yuan, How algorithmic management enhances team resilience: The role of informal leadership emergence and algorithmic transparency, International Journal of Information Management, Volume 88, 2026, 103042, ISSN 0268-4012, https://doi.org/10.1016/j.ijinfomgt.2026.103042.
[3] J. M. Moritz, L. Pomrehn, H. Steinmetz, M. C. Wehner, A meta-analysis on reactions to algorithmic decision-making in human resource management, Human Resource Management Review, Volume 36, Issue 2, 2026, 101135, ISSN 1053-4822, https://doi.org/10.1016/j.hrmr.2026.101135.
[4] N. Hajiheydari, M. S. Delgosha, Staying or leaving? A person-centred view of algorithmic management and gig worker attrition, Journal of Business Research, Volume 210, 2026, 116092, ISSN 0148-2963, https://doi.org/10.1016/j.jbusres.2026.116092.
[5] J. Zhao, T. A. Syed, Making sense of algorithms: Workers' coping strategies for algorithmic management on digital platforms, Technological Forecasting and Social Change, Volume 223, 2026, 124443, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2025.124443.
[6] B. Jianu, I.P. Tussyadiah, G.Miller, The toll of resisting algorithmic management, International Journal of Contemporary Hospitality Management, Volume 37, Issue 12, 2025, Pages 4065-4083, ISSN 0959-6119, https://doi.org/10.1108/IJCHM-12-2024-1821.
[7] W. Liu, H. Yang, S. Liu, Algorithmic platform management and risk-taking behavior among Chinese food delivery riders, iScience, Volume 28, Issue 12, 2025, 114244, ISSN 2589-0042, https://doi.org/10.1016/j.isci.2025.114244.
[8] W. Chen, A. Li, C.Pan, T. Yu, A. Ali, Y. Sun, Algorithmic management in the workplace: A systematic review and topic modeling integration using BERTopic, International Journal of Information Management, Volume 86, 2026, 102994, ISSN 0268-4012, https://doi.org/10.1016/j.ijinfomgt.2025.102994.
[9] G. Migliora, Platform work and algorithmic management: Protecting workers irrespectively of their employment status, Computer Law & Security Review, Volume 60, 2026, 106267, ISSN 2212-473X, https://doi.org/10.1016/j.clsr.2026.106267.
[10] F. Shahzad, M. T. Hoque, I. S. Khan, A.Arslan, AI for the underdogs: Navigating risk and growth in high-tech micro-firms through generative artificial intelligence, Journal of Strategy & Innovation, Volume 37, Issue 1, 2026, 200566, ISSN 3050-7901, https://doi.org/10.1016/j.jsinno.2026.200566.
[11] L. Fontanelli, M. Guerini, R. Miniaci, A. Secchi, Predictive AI and productivity growth dynamics: Evidence from French firms, Journal of Economic Behavior & Organization, Volume 240, 2025, 107336, ISSN 0167-2681, https://doi.org/10.1016/j.jebo.2025.107336.
[12] X. Yu, K. Chen, Z. Ren, Building the efficiency bridge: Artificial intelligence innovation, high-growth firms and industry competition through governance, Journal of Innovation & Knowledge, Volume 14, 2026, 100961, ISSN 2444-569X, https://doi.org/10.1016/j.jik.2026.100961.
[13] P. Hernández-Lagos, The transparency of AI and the profits of the firm, Journal of Corporate Finance, Volume 99, 2026, 103002, ISSN 0929-1199, https://doi.org/10.1016/j.jcorpfin.2026.103002.
[14] J. J. Adams, M. Fang, Z. Liu, Y. Wang, The rise of AI pricing: Trends, driving forces, and implications for firm performance, Journal of Monetary Economics, Volume 157, 2026, 103875, ISSN 0304-3932, https://doi.org/10.1016/j.jmoneco.2025.103875.
[15] J. Xu, B. Zhang, H. Li, J. Lu, Y.Yu, From optimization to disruption: The role of AI-driven innovation in shaping firms’ market competitiveness, Journal of Engineering and Technology Management, Volume 80, 2026, 101962, ISSN 0923-4748, https://doi.org/10.1016/j.jengtecman.2026.101962.
[16] J. Chen, J. Bai, N. Mirza, M. Umar, Investing in intelligence: The impact of AI adoption and investment intensity on supply chain efficiency of green firms, Technological Forecasting and Social Change, Volume 227, 2026, 124631, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2026.124631.
[17] A. Pastor-Merino, X. Martínez-Barbero, M. R. Vicente, J. Domenech, Does AI boost firm productivity? A web scraping and LLMs approach, Telecommunications Policy, Volume 50, Issue 2, 2026, 103138, ISSN 0308-5961, https://doi.org/10.1016/j.telpol.2025.103138.
[18] K. Luchkov, G. Chipriyanova, M. Chipriyanov, (2025). Implementing Innovative Strategies for Competitiveness in the Era of Digital Transformation. In: Alzoubi, H.M., Cheng Ling, T., El Khatib, M. (eds) Innovative Dynamics in Management and Engineering (IDME) . ISCME 2024. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-90131-7_29
[19] G. Chipriyanova, M. Chipriyanov, K. Luchkov, Investigation and Analysis of Attitudes Towards the Implementation of Artificial Intelligence in Internal Business Processes. In: Proceedings of the 15th International Scientific and Practical Conference “Environment, Technology and Resources”, Rezekne, 2024, Vol. II, pp. 61–67. https://doi.org/10.17770/etr2024vol2.8032
[20] T. Stoyanova, A., Koev, S. R., Stoyanov, P. P., Zhyvko, Z., & Laptiev, V. (2019). Strategic management of the personnel development of industry companies. Academy of Strategic Management Journal, 18(3).
[21] V. Zinoviev, D. Koeva, P. Tsankov, R. Kutkarska, Review of Artificial Intelligence Applications in the Digital Energy and Renewable Energy Infrastructures. Energies 2026, 19, 1250. https://doi.org/10.3390/en19051250
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