
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
Keywords:
Related subjects:
© 2026 Bucur MILANCOVICI, Lavinia Denisia CUC, Gabriel CROITORU, Suzana Monica VERESS, Crina Anina BEJAN, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution 4.0 License.