ALGORİTMİK YÖNETİMDEN ALGORİTMİK LİDERLİĞE: ALANIN TEORİK TEMELLERİ ÜZERİNE BİR ATIF ANALİZİ

Öz

Günümüzde devam eden dijital dönüşüm süreci, örgütsel karar alma mekanizmalarını, iş tasarımını ve liderlik paradigmalarını temelden sarsmaktadır. Bu süreçte ortaya çıkan algoritmik yönetim, geleneksel denetim mekanizmalarının yerini alarak operasyonel bir araç olmanın ötesine geçmiş ve liderlik uygulamalarını yeniden tanımlayan stratejik bir güce evrilmiştir. Bu çalışma, algoritmik yönetim literatürünün kavramsal gelişimini bibliyometrik bir yaklaşımla derinlemesine incelemekte ve alanın salt yönetimsel kontrolden etkileşimsel bir liderlik perspektifine doğru gösterdiği teorik evrimi ortaya koymaktadır. Araştırma kapsamında Web of Science (WoS) veri tabanından elde edilen 247 nitelikli akademik çalışma, VOSviewer yazılımı aracılığıyla eş-atıf analizine (co-citation analysis) tabi tutulmuştur. Elde edilen bulgular, literatürün üç temel entelektüel kümede yoğunlaştığını göstermektedir: Birinci küme algoritmik kontrolün çalışan psikolojisi, davranışı ve insan kaynakları süreçleri üzerindeki etkilerini; ikinci küme platform ekonomisi ve dijital ekosistemlerin stratejik yönetimini; üçüncü küme ise dijital inovasyonun analitik ve teknolojik temellerini ele almaktadır. Ortaya çıkan ağ haritaları, algoritmaların artık yalnızca verimlilik odaklı denetim araçları değil, örgütsel süreçleri yönlendiren, anlamlandıran ve liderlik işlevlerini fiilen üstlenen "aktif aktörler" olduğunu kanıtlamaktadır. Bu çalışma, algoritmik liderlik kavramını teorik bir çerçeveye oturtarak hem akademiye hem de dijitalleşen iş dünyasındaki uygulamacılara özgün bir perspektif sunmaktadır.

Anahtar Kelimeler

• Algoritmik Yönetim
• Algoritmik Liderlik
• Dijital Dönüşüm
• Bibliyometrik Analiz
• Eş-Atıf Analizi.

FROM ALGORITHMIC MANAGEMENT TO ALGORITHMIC LEADERSHIP: A CITATION ANALYSIS ON THE THEORETICAL FOUNDATIONS OF THE FIELD

Öz

The ongoing digital transformation is fundamentally reshaping organizational decision-making mechanisms, job design, and leadership paradigms. Within this context, algorithmic management has emerged as a disruptive force, replacing traditional oversight mechanisms and evolving from a mere operational tool into a strategic entity that redefines leadership practices. This study provides an in-depth exploration of the conceptual trajectory of algorithmic management literature through a comprehensive bibliometric lens, uncovering its theoretical evolution toward a sophisticated leadership perspective. Utilizing the Web of Science (WoS) database, 247 high-impact academic studies were retrieved and subjected to co-citation analysis using VOSviewer software. The findings reveal that the intellectual structure of the field is concentrated within three primary thematic clusters: (1) the psychological and behavioral implications of algorithmic control on employees and human resource management; (2) the strategic governance of platform economies and digital ecosystems; and (3) the analytical foundations of digital innovation and organizational design. The resulting network visualizations demonstrate a clear paradigm shift from surveillance-oriented management to a strategic and interactional leadership framework. This research offers a unique theoretical contribution by repositioning algorithms not as passive socio-technical tools, but as active agency-bearing actors that direct organizational processes and fulfill leadership functions in the digital age.

Anahtar Kelimeler

• Algorithmic Management
• Algorithmic Leadership
• Management
• Leadership.

Kaynakça

1. Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1–11. https://doi.org/10.1111/1748-8583.12090
2. Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
3. Ashford, S. J., Caza, B. B., & Reid, E. M. (2018). From surviving to thriving in the gig economy: A research agenda for individuals in the new world of work. Research in Organizational Behavior, 38, 23–41. https://doi.org/10.1016/j.riob.2018.11.001
4. Autio, E., Nambisan, S., Thomas, L. D., & Wright, M. (2018). Digital affordances, spatial affordances, and the genesis of entrepreneurial ecosystems. Strategic Entrepreneurship Journal, 12(1), 72–95. https://doi.org/10.1002/sej.1266
5. Baiocco, S., Fernández-Macías, E., Rani, U., & Pesole, A. (2022). The algorithmic management of work and its implications in different contexts (JRC Working Papers Series on Labour, Education and Technology, No. 2022/02). European Commission. https://hdl.handle.net/10419/262292
6. Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84. https://doi.org/10.1145/2133806.2133826
7. Boudreau, K. J. (2012). Let a thousand flowers bloom? An early look at large numbers of software app developers and patterns of innovation. Organization Science, 23(5), 1409–1427. https://doi.org/10.1287/orsc.1110.0678
8. Cameron, L. D. (2024). The making of the “good bad” job: How algorithmic management manufactures consent through constant and confined choices. Administrative Science Quarterly, 69(2), 458–514. https://doi.org/10.1177/00018392241236163

9. Cameron, L. D., & Rahman, H. (2022). Expanding the locus of resistance: Understanding the co-constitution of control and resistance in the gig economy. Organization Science, 33(1), 38–58. https://doi.org/10.1287/orsc.2021.1557
10. Cappelli, P., & Keller, J. R. (2013). Classifying work in the new economy. Academy of Management Review, 38(4), 575–596. https://doi.org/10.5465/amr.2011.0302
11. Ceccagnoli, M., Forman, C., Huang, P., & Wu, D. J. (2012). Cocreation of value in a platform ecosystem! The case of enterprise software. MIS Quarterly, 36(1), 263–290. https://doi.org/10.2307/41410417
12. Cenamor, J., Parida, V., & Wincent, J. (2019). How entrepreneurial SMEs compete through digital platforms: The roles of digital platform capability, network capability and ambidexterity. Journal of Business Research, 100, 196–206. https://doi.org/10.1016/j.jbusres.2019.03.035
13. Cennamo, C. (2018). Building the value of next-generation platforms: The paradox of diminishing returns. Journal of Management, 44(8), 3038–3069. https://doi.org/10.1177/0149206316658350 Cennamo, C., & Santalo, J. (2013). Platform competition: Strategic trade-offs in platform markets. Strategic Management Journal, 34(11), 1331–1350. https://doi.org/10.1002/smj.2066
14. Cheng, M. M., & Hackett, R. D. (2021). A critical review of algorithms in HRM: Definition, theory, and practice. Human Resource Management Review, 31(1), Article 100698. https://doi.org/10.1016/j.hrmr.2019.100698
15. Cusumano, M. A., Gawer, A., & Yoffie, D. B. (2019). The business of platforms: Strategy in the age of digital competition, innovation, and power. Harper Business.
16. Del Giudice, M., Scuotto, V., Orlando, B., & Mustilli, M. (2023). Toward the human-centered approach: A revised model of individual acceptance of AI. Human Resource Management Review, 33(1), Article 100856. https://doi.org/10.1016/j.hrmr.2021.100856
17. Duggan, J., Sherman, U., Carbery, R., & McDonnell, A. (2020). Algorithmic management and app-work in the gig economy: A research agenda for employment relations and HRM. Human Resource Management Journal, 30(1), 114–132. https://doi.org/10.1111/1748-8583.12258
18. Feshchenko, P. (2021). Algorithmic management & algorithmic leadership: A systematic literature review [Master's thesis, University of Jyväskylä]. JYX Digital Repository. https://urn.fi/URN:NBN:fi:jyu-202101221224
19. Frimpong, V. (2025). Algorithmic authority and the complexities of delegated decision-making: Case studies on ethical challenges for 21st-century leadership. International Journal of Organizational Leadership, 14(3), 637–655.
20. Harms, P. D., & Han, G. (2019). Algorithmic leadership: The future is now. Journal of Leadership Studies, 12(4), 74–75. https://doi.org/10.1002/jls.21615
21. Höddinghaus, M., Sondern, D., & Hertel, G. (2021). The automation of leadership functions: Would people trust decision algorithms? Computers in Human Behavior, 116, Article 106635. https://doi.org/10.1016/j.chb.2020.106635
22. Ismail, R., Sedjati, M., Saling, Indriaty, L., Yahya, N., & Izwan, I. D. M. (2025). Algorithmic leadership through artificial intelligence in organizational strategy: A case study of Papua Pegunungan Province, Indonesia. International Journal of Research and Innovation in Social Science, 9(10), 1906–1915. https://doi.org/10.47772/IJRISS.2025.910000160
23. Jabagi, N., Croteau, A. M., Audebrand, L. K., & Marsan, J. (2020). Perceived organizational support in the face of algorithmic management: A conceptual model. Proceedings of the 53rd Hawaii International Conference on System Sciences. https://hdl.handle.net/10125/64231
24. Jarrahi, M. H., Möhlmann, M., & Lee, M. K. (2023). Algorithmic management: The role of AI in managing workforces. MIT Sloan Management Review. https://sloanreview.mit.edu/
25. Jarrahi, M. H., Newlands, G., Lee, M. K., Wolf, C. T., Kinder, E., & Sutherland, W. (2021). Algorithmic management in a work context. Big Data & Society, 8(2), 1–14. https://doi.org/10.1177/20539517211020332
26. Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
27. Kelly-Lyth, A., & Thomas, A. (2022). Algorithmic management: Assessing the impacts of AI at work (SSRN Scholarly Paper). SSRN. https://ssrn.com/abstract=4251502
28. Leavitt, K., Barnes, C. M., & Shapiro, D. L. (2025). The role of human managers within algorithmic performance management systems: A process model of employee trust in managers through reflexivity. Academy of Management Review, 50(4), 745–767. https://doi.org/10.5465/amr.2022.0058
29. Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 1–16. https://doi.org/10.1177/2053951718756684
30. Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). Working with machines: The impact of algorithmic and data-driven management on human workers. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1603–1612. https://doi.org/10.1145/2702123.2702548
31. Li, A. K. (2024). Working with algorithmic management: Design logic, algorithmic unfitness, and labor repair behind the wall. New Media & Society. Advance online publication. https://doi.org/10.1177/14614448231221238
32. Mateescu, A., & Nguyen, A. (2019). Explainer: Algorithmic management in the workplace. Data & Society Research Institute.
33. Möhlmann, M., Salge, C. A. L., & Marabelli, M. (2023). Algorithm sensemaking: How platform workers make sense of algorithmic management. Journal of the Association for Information Systems, 24(1), 35–64. https://doi.org/10.17705/1jais.00774
34. OECD. (2025). Algorithmic management in the workplace: New evidence from an OECD employer survey. OECD Publishing. https://doi.org/10.1787/287c13c4-en
35. Pirzada, W. (2025). Transforming leadership for the digital age: A conceptual model of algorithmic leadership and human capital management. Business, Technology & Innovation Studies Journal, 1(1).
36. Rilinger, G. (2024). Algorithmic management and the social order of digital markets. Theory and Society, 53, 765–794. https://doi.org/10.1007/s11186-024-09555-6
37. Schildt, H. (2017). Big data and organizational design–the brave new world of algorithmic management and computer augmented transparency. Innovation, 19(1), 23–30. https://doi.org/10.1080/14479338.2016.1252043
38. Stark, D., & Vanden Broeck, P. (2024). Principles of algorithmic management. Organization Theory, 5, 1–22. https://doi.org/10.1177/26317877241257213
39. Tomprou, M., & Lee, M. K. (2022). Employment relationships in algorithmic management: A psychological contract perspective. Computers in Human Behavior, 126, Article 107022. https://doi.org/10.1016/j.chb.2021.106997
40. van Zoonen, W., Sivunen, A. E., & Treem, J. W. (2024). Algorithmic management of crowdworkers: Implications for workers’ identity, belonging, and meaningfulness of work. Computers in Human Behavior, 152, Article 108066. https://doi.org/10.1016/j.chb.2023.108089
41. Vignola, E. F., Baron, S., Abreu Plasencia, E., Hussein, M., & Cohen, N. (2023). Workers’ health under algorithmic management: Emerging findings and urgent research questions. International Journal of Environmental Research and Public Health, 20(2), Article 1239. https://doi.org/10.3390/ijerph20021239
42. Woodcock, J. (2021). The limits of algorithmic management: On platforms, data, and workers’ struggle. South Atlantic Quarterly, 120(4), 703–713. https://doi.org/10.1215/00382876-9443266