A Queuing Approach to Pricing Strategy in B2B Markets

Fatemeh  Ghasemzadeh; Babak Ghahremannasab

doi:10.31181/sdmap31202632

Authors

Fatemeh Ghasemzadeh Department of Management and Accounting, University of Zanjan, Zanjan, Iran Author https://orcid.org/0000-0002-6988-1083
Babak Ghahremannasab Department of Management and Accounting, University of Zanjan, Zanjan, Iran Author https://orcid.org/0009-0009-4201-325X

DOI:

https://doi.org/10.31181/sdmap31202632

Keywords:

B2B, Pricing, Queueing, Customer classification

Abstract

Business-to-business (B2B) pricing strategies are intentionally complex and crucial levers of profitability and competitive advantage because of differences in temporal preferences, operational constraints, and multi-stakeholder decision-making. Static segmentation also neglects behavioral subtleties that correspond with service urgency; meanwhile, traditional models provide an inadequate representation of time-sensitive variables, such as delivery lead time and capacity utilization. This paper addresses such shortcomings by establishing a new and holistic framework that combines queuing theory and value-based pricing for the revenue optimization of a capacity-constrained B2B system. Related models combine game-theoretical frameworks, data-driven predictions with algorithms, and adaptive capacity control, through which firms can modulate prices in real time whenever requests, service times, and competitors' behaviors deviate. The results show that pricing, which considers temporal preferences and operational efficiency, reduces the conflict between service speed and profitability and offers insights into tiered pricing and resource allocation. Uniting queuing dynamics with segmentation strategies, the framework bolsters intellectual dialogue in calls for the creative development of B2B pricing literature. It allows managers to build customer loyalty, exploit time-sensitive demand, and mitigate margin erosion due to panic discounting.

Downloads

Download data is not yet available.

References

Friess, M., & Kassemeier, R. (2024). Price increases and their financial consequences in international business-to-business selling. Journal of International Marketing, 32(1), 92–111. https://doi.org/10.1177/1069031X231214160

Indounas, K. (2019). Market-based pricing in B2B service industries. Journal of Business & Industrial Marketing, 34(5), 1030–1040. https://doi.org/10.1108/JBIM-03-2018-0103

Zhang, J. Z., Netzer, O., & Ansari, A. (2014). Dynamic targeted pricing in B2B relationships. Marketing Science, 33(3), 317–337. https://doi.org/10.1287/mksc.2013.0842

Gligor, D. M., & Maloni, M. J. (2022). More is not always better: The impact of value co-creation fit on B2B and B2C customer satisfaction. Journal of Business Logistics, 43(2), 209–237. https://doi.org/10.1111/jbl.12278

Indounas, K. (2020). New B2B product pricing. Journal of Business & Industrial Marketing, 35(11), 1861–1869. https://doi.org/10.1108/JBIM-05-2019-0187

Taghizadeh, S. K., Rahman, S. A., & Marimuthu, M. (2022). Value co-creation and new service performance: Mediated by value-informed pricing. Journal of Business & Industrial Marketing, 37(4), 705–722. https://doi.org/10.1108/JBIM-10-2020-0469

Rodríguez, R., Svensson, G., Román, S., & Wood, G. (2018). Teleological sales and purchase approaches in complex business relationships–customers' expectations before and perceptions after purchase. Journal of Business & Industrial Marketing, 33(4), 523–538. https://doi.org/10.1108/JBIM-11-2016-0262

Mier, J., Carlson, J., Bellenger, D. N., & Johnston, W. J. (2020). Business buyers are people too: Exploring how geodemographics affects business-to-business selling effectiveness. Journal of Business & Industrial Marketing, 35(10), 1539–1552. https://doi.org/10.1108/JBIM-01-2019-0037

Masitenyane, L. A., & Dhurup, M. (2023). Predictors of business-to-business loyalty and repurchase intentions in South Africa's concrete product market. South African Journal of Business Management, 54(1), 1–12. https://doi.org/10.4102/sajbm.v54i1.3575

Saura, J. R., Palos-Sanchez, P., & Blanco-González, A. (2020). The importance of information service offerings of collaborative CRMs on decision-making in B2B marketing. Journal of Business & Industrial Marketing, 35(3), 470–482. https://doi.org/10.1108/JBIM-12-2018-0412

Chowdhury, N., Balaraman, P., & Liu, J. (2023). The evolution of B2B strategies in the rise of value co-creation and service management. Journal of Strategy and Management, 16(4), 708–732. https://doi.org/10.1108/JSMA-03-2023-0064

Osei, F., Ampomah, G., Kankam-Kwarteng, C., Bediako, D. O., & Mensah, R. (2021). Customer satisfaction analysis of banks: The role of market segmentation. Science Journal of Business and Management, 9(2), 126–138. https://doi.org/10.11648/j.sjbm.20210902.19

Tavor, T., Gonen, L. D., & Spiegel, U. (2023). Customer segmentation as a revenue generator for profit purposes. Mathematics, 11(21), 4425. https://doi.org/10.3390/math11214425

Srivastava, V., Rangarajan, D., & Badrinarayanan, V. (2024). Customer equity drivers and repurchase intent among B2B customers: The moderating role of perceived switching cost. Journal of Business & Industrial Marketing, 39(5), 949–966. https://doi.org/10.1108/JBIM-02-2023-0084

Shui, W., & Li, M. (2020). Integrated pricing and distribution planning for community group purchase of fresh agricultural products. Scientific Programming, 2020(1), 8839398. https://doi.org/10.1155/2020/8839398

Boyaci, T., & Ray, S. (2003). Product differentiation and capacity cost interaction in time and price sensitive markets. Manufacturing & Service Operations Management, 5(1), 18–36. https://doi.org/10.1287/msom.5.1.18.12757

Shan, W. (2025). Optimal pricing strategies and decision-making systems in e-commerce using integrated fuzzy multi-criteria method. Expert Systems, 42(1), e13468. https://doi.org/10.1111/exsy.13468

Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: A bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467–2497. https://doi.org/10.1108/IMDS-05-2021-0300

Ferreira, J. J., Veiga, P. M., Fernandes, C. I., & Kraus, S. (2022). B2B marketing strategies in healthcare management: Intellectual structure and research trends. Journal of Business & Industrial Marketing, 37(8), 1580–1593. https://doi.org/10.1108/JBIM-07-2020-0339

Gupta, S., Malhotra, N. K., Czinkota, M., & Foroudi, P. (2016). Marketing innovation: A consequence of competitiveness. Journal of Business Research, 69(12), 5671–5681. https://doi.org/10.1016/j.jbusres.2016.02.042

Hinterhuber, A., & Liozu, S. M. (2017). Is innovation in pricing your next source of competitive advantage? In Innovation in pricing (pp. 11–27). Routledge. https://doi.org/10.1016/j.bushor.2014.01.002

Makgopa, S. S. (2019). The influence of service innovation practices on business performance. University of Pretoria (South Africa).

Chen, Y., & Zhang, T. (2015). Interpersonal bundling. Management Science, 61(6), 1456–1471. https://doi.org/10.1287/mnsc.2014.2004

Balan, C. (2014). Pay what you want: A participative price setting mechanism. International Journal of Economic Practices and Theories, 4(5), 952–963.

Kim, J.-Y., Natter, M., & Spann, M. (2009). Pay what you want: A new participative pricing mechanism. Journal of Marketing, 73(1), 44–58. https://doi.org/10.1509/jmkg.73.1.044

Yan, R., Pei, Z., & Myers, C. (2016). Do channel members value the multiple-cooperation strategy? Journal of Retailing and Consumer Services, 30, 84–95. https://doi.org/10.1016/j.jretconser.2016.01.002

Schulz, F., Schlereth, C., Mazar, N., & Skiera, B. (2015). Advance payment systems: Paying too much today and being satisfied tomorrow. International Journal of Research in Marketing, 32(3), 238–250. https://doi.org/10.1016/j.ijresmar.2015.03.003

Lin, H., & Wang, I. Y. (2015). Competition and price discrimination: Evidence from the parking garage industry. The Journal of Industrial Economics, 63(3), 522–548. https://doi.org/10.1111/joie.12080

Zhang, H. L., Feng, G. H., Wang, B. S., Liu, X. M., & Liu, X. (2020). Application of queuing theory in production efficiency of direct rolling process of long product. Materials Science Forum, 977, 34. https://doi.org/10.4028/www.scientific.net/MSF.977.34

Netessine, S. (2006). Dynamic pricing of inventory/capacity with infrequent price changes. European Journal of Operational Research, 174(1), 553–580. https://doi.org/10.1016/j.ejor.2004.12.015

Fakokunde, T. O., Mustapha, A. M., & Aremu, M. (2016). Understanding the queuing theory for improved service delivery: An entrepreneurial-mindset approach. Ethiopian Journal of Business and Economics, 6(1), 33–47. https://dx.doi.org/10.4314/ejbe.v6i1.2

Levin, Y., McGill, J., & Nediak, M. (2010). Optimal dynamic pricing of perishable items by a monopolist facing strategic consumers. Production and Operations Management, 19(1), 40–60. https://doi.org/10.1111/j.1937-5956.2009.01046.x

Ozcelik, Y., & Ozdemir, Z. D. (2011). Market transparency in business-to-business e-commerce: A simulation analysis. International Journal of E-Business Research, 7(4), 62–78. https://doi.org/10.4018/jebr.2011100105

Kim, S. W., & Bell, P. C. (2019). Stochastic optimization models with substitution as a result of price differences and stockouts. International Transactions in Operational Research, 26(6), 2129–2151. https://doi.org/10.1111/itor.12667

Dolgui, A., & Proth, J.-M. (2010). Pricing strategies and models. Annual Reviews in Control, 34(1), 101–110. https://doi.org/10.1016/j.arcontrol.2010.02.005

Devi, O. (2016). Portfolio rule-based clustering at automobile insurance in Portugal. Universidade NOVA de Lisboa (Portugal).