Bibliometric Analysis of Dynamic Pricing
DOI:
https://doi.org/10.63556/ankad.v10i1.208Keywords:
Dynamic pricing, bibliometric analysis, demand responseAbstract
Dynamic pricing has become one of the most influential pricing strategies for enhancing firms’ marketing performance and revenue optimization. It is widely adopted across industries such as airlines, hospitality, e-commerce, and energy markets, enabled by digital technologies that allow firms to adjust prices in real time based on demand, inventory levels, and competitive conditions. This study conducts a comprehensive bibliometric analysis of global research on dynamic pricing in order to identify the intellectual structure, research trends, and key contributors within the field. Using the search term “dynamic pricing”, publications indexed up to 2023 were retrieved from Web of Science, ScienceDirect, and Google Scholar. After applying systematic screening criteria- removal of duplicates, non-English documents, books, book chapters, editorials, letters, and non-research material- a final sample of 985 peer-reviewed research articles was analyzed. Bibliometric techniques, including citation analysis, co-citation analysis, and keyword co-occurrence analysis, were applied using the bibliometrix package in RStudio and VOSviewer. The findings reveal major publication trends, influential authors, leading countries, prominent journals, and dominant research themes in dynamic pricing research. The study contributes by offering a structured overview of the evolution of dynamic pricing literature and provides practical implications for practitioners as well as directions for future academic research.
References
Anderson, C. K., & Xie, X. (2010). Improving hospitality industry sales: Twenty-five years of revenue management. Cornell Hospitality Quarterly, 51(1), 53-67. https://doi.org/10.1177/1938965509354697
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
Chenavaz, R., Carrier, L. P., Etienne, L., & Paraschiv, C. (2011). Dynamic pricing in management science. Journal of Economics Studies and Research, 2011, 1-16. https://doi.org/10.5171/2011.283281
Dasci, A., & Huang, R. (2017). A continuous approximation method for dynamic pricing problem under costly price modifications. Omega, 72, 38-49. https://doi.org/10.1016/j.omega.2016.11.006
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. https://doi.org/10.1016/j.jbusres.2021.04.070
Goli, F., & Haghighinasab, M. (2022). Dynamic Pricing: A Bibliometric Approach. Iranian Journal of Management Studies (IJMS), 15(1), 111-132. https://doi.org/10.22059/ijms.2021.315212.674336
Harzing, A.-W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: A longitudinal and cross-disciplinary comparison. Scientometrics, 106, 787–804. https://doi.org/10.1007/s11192-015-1798-9
Hayes, D. K., & Miller, A. (2011). Revenue management for the hospitality industry. John Wiley & Sons. (Note: Books typically do not have a DOI, but sometimes have an ISBN: 978-0-470-39308-6)
Kimes, S. E. (2003). Revenue management: A retrospective. Cornell Hotel and Restaurant Administration Quarterly, 44(5-6), 131–138. https://doi.org/10.1177/001088040304400518
Kimes, S. E. (2010). The future of hotel revenue management. Journal of Revenue and Pricing Management, 10, 62–72. https://doi.org/10.1057/rpm.2010.46
Kramer, A., Friesen, M., & Shelton, T. (2018). Are airline passengers ready for personalized dynamic pricing? A study of German consumers. Journal of Revenue and Pricing Management, 17, 115–120. https://doi.org/10.1057/s41272-017-0122-7(Correction: The publication year and volume were slightly adjusted to match the official DOI record)
Levin, Y., McGill, J., & Nediak, M. (2009). Dynamic pricing in the presence of strategic consumers and oligopolistic competition. Management Science, 55(1), 32-46. https://doi.org/10.1287/mnsc.1080.0936(Correction: Updated title and volume/issue to match the official record)
Liu, X., Sun, R., Wang, S., & Wu, Y. J. (2020). The research landscape of big data: A bibliometric analysis. Library Hi Tech, 38(2), 367-384. https://doi.org/10.1108/LHT-01-2019-0024(Correction: Publication year updated to 2020 to match the official journal release)
Su, X. (2007). Intertemporal Pricing with Strategic Customer Behavior. Management Science, 53(5), 726–741. https://doi.org/10.1287/mnsc.1060.0667
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Journal of Anatolian Cultural Research
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
