Recommender Systems and Strategic Decision-Making in E-Commerce: A Bibliometric Review Using VOSviewer
References
- Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734–749. https://doi.org/10.1109/TKDE.2005.99
- Adomavicius, G., Bockstedt, J. C., Curley, S. P., & Zhang, J. (2018). Effects of online recommendations on consumers’ willingness to pay. Information Systems Research, 29(1), 84–102. https://doi.org/10.1287/isre.2017.0703
- Bellogín, A., Castells, P., & Cantador, I. (2017). Statistical biases in information retrieval metrics for recommender systems. Information Retrieval Journal, 20(6), 606–634. https://doi.org/10.1007/s10791-017-9312-z
- Burke, R. (2002). Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, 12(4), 331–370. https://doi.org/10.1023/A:1021240730564
- Chen, Y. (2022). Analysis on the impact of recommender systems on consumer decision-making. In Proceedings of the ACM International Conference (pp. 1–10). https://doi.org/10.1145/3537693.3537734
- Cuc, L. D., Rad, D., Hațegan, C. D., Trifan, V. A., & Ardeleanu, T. (2024). The mediating role of the financial recommender system. Proceedings of the International Conference on Business Excellence (PICBE), 210–223. https://doi.org/10.2478/picbe-2024-0190
- Ekstrand, M. D., Willemsen, M. C., Barrera, D., & Konstan, J. A. (2022). Algorithmic transparency for recommender systems: Trust, fairness, and user control. ACM Transactions on Interactive Intelligent Systems, 12(1), 1–30. https://doi.org/10.1145/3491119
- Gawer, A. (2014). Bridging differing perspectives on technological platforms: Toward an integrative framework. Research Policy, 43(7), 1239–1249. https://doi.org/10.1016/j.respol.2014.03.006
- Hwangbo, H., Kim, Y. S., & Cha, K. J. (2018). Recommendation system development for fashion retail e-commerce. Electronic Commerce Research and Applications, 28, 94–101. https://doi.org/10.1016/j.elerap.2018.01.002
- Jannach, D., Zanker, M., Felfernig, A., & Friedrich, G. (2010). Recommender systems: An introduction. Cambridge University Press.
- Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
- 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
- Koren, Y., Bell, R., & Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30–37. https://doi.org/10.1109/MC.2009.263
- Lops, P., de Gemmis, M., & Semeraro, G. (2011). Content-based recommender systems: State of the art and trends. In F. Ricci, L. Rokach, B. Shapira, & P. Kantor (Eds.), Recommender systems handbook (pp. 73–105). Springer. https://doi.org/10.1007/978-0-387-85820-3_3
- North, D. C. (1991). Institutions. Journal of Economic Perspectives, 5(1), 97–112. https://doi.org/10.1257/jep.5.1.97
- Nobel, C. (2024). How algorithms shape consumer choice and trust. Harvard Business Review.
- O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
- Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution. W. W. Norton & Company.
- Porter, M. E. (2008). The five competitive forces that shape strategy. Harvard Business Review, 86(1), 78–93.
- Ricci, F., Rokach, L., & Shapira, B. (2015). Recommender systems handbook (2nd ed.). Springer.
- Schwartz, B. (2004). The paradox of choice: Why more is less. HarperCollins.
- Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of Retailing, 80(2), 159–169. https://doi.org/10.1016/j.jretai.2004.04.001
- Sruthi, M., & Prabhu, S. (2022). User interface design and recommender systems in fashion e-commerce. Journal of Retailing and Consumer Services, 65, Article 102870. https://doi.org/10.1016/j.jretconser.2021.102870
- van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact (pp. 285–320). Springer. https://doi.org/10.1007/978-3-319-10377-8_13
- Zhang, Y., & Chen, X. (2020). Explainable recommendation: A survey and new perspectives. Foundations and Trends in Information Retrieval, 14(1), 1–101. https://doi.org/10.1561/1500000066
- Zhou, Y., Xu, X., Wang, Y., & Li, J. (2022). Recommender systems, pricing strategies, and market structure. Management Science, 68(9), 6513–6534. https://doi.org/10.1287/mnsc.2021.4142
DOI: https://doi.org/10.2478/picbe-2026-0271 | Journal eISSN: 2558-9652
Language: English
Page range: 3641 - 3659
Published on: Jul 22, 2026
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
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© 2026 Bucur MILANCOVICI, Lavinia Denisia CUC, Gabriel CROITORU, Suzana Monica VERESS, Crina Anina BEJAN, published by Bucharest University of Economic Studies
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