IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v33y2014i3p317-337.html
   My bibliography  Save this article

Dynamic Targeted Pricing in B2B Relationships

Author

Listed:
  • Jonathan Z. Zhang

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Oded Netzer

    (Columbia Business School, Columbia University, New York, New York 10027)

  • Asim Ansari

    (Columbia Business School, Columbia University, New York, New York 10027)

Abstract

We model the multifaceted impact of pricing decisions in business-to-business (B2B) relationships that are governed by trust. We show how a seller can develop optimal intertemporal targeted pricing strategies to maximize profits over time while taking into consideration the impact of pricing decisions on short-term profit margin, reference price formation, and long-term relationships. Our modeling framework uses a hierarchical Bayesian approach to weave together a multivariate nonhomogeneous hidden Markov model, buyer heterogeneity, and control functions to facilitate targeting, capture the evolution of trust, and control for price endogeneity. We estimate our model on longitudinal transactions data from a retailer in the industrial consumables domain. We find that buyers in our data set can be best represented by two latent states of trust toward the seller---a “vigilant” state that is characterized by heightened price sensitivity and a cautious approach to ordering and a “relaxed” state with purchase behaviors that are consistent with high relational trust. The seller's pricing decisions can transition buyers between these two states. An optimal dynamic and targeted pricing strategy based on our model suggests a 52% improvement in profitability compared with the status quo. Furthermore, a counterfactual analysis examines the seller's optimal pricing policy under fluctuating commodity prices.

Suggested Citation

  • Jonathan Z. Zhang & Oded Netzer & Asim Ansari, 2014. "Dynamic Targeted Pricing in B2B Relationships," Marketing Science, INFORMS, vol. 33(3), pages 317-337, May.
    • Handle: RePEc:inm:ormksc:v:33:y:2014:i:3:p:317-337
    DOI: 10.1287/mksc.2013.0842
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.2013.0842
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.2013.0842?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    2. Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
    3. Duncan I. Simester & Peng Sun & John N. Tsitsiklis, 2006. "Dynamic Catalog Mailing Policies," Management Science, INFORMS, vol. 52(5), pages 683-696, May.
    4. Oded Netzer & James M. Lattin & V. Srinivasan, 2008. "A Hidden Markov Model of Customer Relationship Dynamics," Marketing Science, INFORMS, vol. 27(2), pages 185-204, 03-04.
    5. Tülin Erdem & Michael Katz & Baohong Sun, 2010. "A simple test for distinguishing between internal reference price theories," Quantitative Marketing and Economics (QME), Springer, vol. 8(3), pages 303-332, September.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    8. Akerlof, George A, 1979. "The Case against Conservative Macroeconomics: An Inaugural Lecture," Economica, London School of Economics and Political Science, vol. 46(183), pages 219-237, August.
    9. Michael Lewis, 2005. "Research Note: A Dynamic Programming Approach to Customer Relationship Pricing," Management Science, INFORMS, vol. 51(6), pages 986-994, June.
    10. V. Kumar & S. Sriram & Anita Luo & Pradeep K. Chintagunta, 2011. "Assessing the Effect of Marketing Investments in a Business Marketing Context," Marketing Science, INFORMS, vol. 30(5), pages 924-940, September.
    11. Gurumurthy Kalyanaram & Russell S. Winer, 1995. "Empirical Generalizations from Reference Price Research," Marketing Science, INFORMS, vol. 14(3_supplem), pages 161-169.
    12. Romana Khan & Michael Lewis & Vishal Singh, 2009. "Dynamic Customer Management and the Value of One-to-One Marketing," Marketing Science, INFORMS, vol. 28(6), pages 1063-1079, 11-12.
    13. Wedel, Michel & Leeflang, Peter S. H., 1998. "A model for the effects of psychological pricing in Gabor-Granger price studies," Journal of Economic Psychology, Elsevier, vol. 19(2), pages 237-260, April.
    14. Bruce G. S. Hardie & Eric J. Johnson & Peter S. Fader, 1993. "Modeling Loss Aversion and Reference Dependence Effects on Brand Choice," Marketing Science, INFORMS, vol. 12(4), pages 378-394.
    15. Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
    16. David A. Schweidel & Eric T. Bradlow & Peter S. Fader, 2011. "Portfolio Dynamics for Customers of a Multiservice Provider," Management Science, INFORMS, vol. 57(3), pages 471-486, March.
    17. Johnston, Wesley J. & Lewin, Jeffrey E., 1996. "Organizational buying behavior: Toward an integrative framework," Journal of Business Research, Elsevier, vol. 35(1), pages 1-15, January.
    18. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    19. Krishnamurthi, Lakshman & Mazumdar, Tridib & Raj, S P, 1992. "Asymmetric Response to Price in Consumer Brand Choice and Purchase Quantity Decisions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(3), pages 387-400, December.
    20. David R. Bell & James M. Lattin, 1998. "Shopping Behavior and Consumer Preference for Store Price Format: Why “Large Basket” Shoppers Prefer EDLP," Marketing Science, INFORMS, vol. 17(1), pages 66-88.
    21. Daniel S. Putler, 1992. "Incorporating Reference Price Effects into a Theory of Consumer Choice," Marketing Science, INFORMS, vol. 11(3), pages 287-309.
    22. Kahneman, Daniel & Knetsch, Jack L & Thaler, Richard, 1986. "Fairness as a Constraint on Profit Seeking: Entitlements in the Market," American Economic Review, American Economic Association, vol. 76(4), pages 728-741, September.
    23. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sojin Jung & Hyeon Jeong Cho & Byoungho Ellie Jin, 2020. "Does effective cost transparency increase price fairness? An analysis of apparel brand strategies," Journal of Brand Management, Palgrave Macmillan, vol. 27(5), pages 495-507, September.
    2. Kopalle, Praveen K. & Kannan, P.K. & Boldt, Lin Bao & Arora, Neeraj, 2012. "The impact of household level heterogeneity in reference price effects on optimal retailer pricing policies," Journal of Retailing, Elsevier, vol. 88(1), pages 102-114.
    3. Jonathan Z. Zhang & Chun-Wei Chang, 2021. "Consumer dynamics: theories, methods, and emerging directions," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 166-196, January.
    4. Sojin Jung & Hyeon Jeong Cho & Byoungho Ellie Jin, 0. "Does effective cost transparency increase price fairness? An analysis of apparel brand strategies," Journal of Brand Management, Palgrave Macmillan, vol. 0, pages 1-13.
    5. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
    6. Toshiaki Iizuka & Hitoshi Shigeoka, 2020. "Asymmetric Demand Response when Prices Increase and Decrease: The Case of Child Healthcare," NBER Working Papers 28057, National Bureau of Economic Research, Inc.
    7. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    8. Robert Slonim & Ellen Garbarino, 2009. "Similarities and differences between stockpiling and reference effects," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 351-371.
    9. Dmitri Kuksov & Kangkang Wang, 2014. "The Bright Side of Loss Aversion in Dynamic and Competitive Markets," Marketing Science, INFORMS, vol. 33(5), pages 693-711, September.
    10. van Oest, Rutger, 2013. "Why are Consumers Less Loss Averse in Internal than External Reference Prices?," Journal of Retailing, Elsevier, vol. 89(1), pages 62-71.
    11. David R. Bell & James M. Lattin, 2000. "Looking for Loss Aversion in Scanner Panel Data: The Confounding Effect of Price Response Heterogeneity," Marketing Science, INFORMS, vol. 19(2), pages 185-200, May.
    12. Bernhard Baumgartner & Daniel Guhl & Thomas Kneib & Winfried J. Steiner, 2018. "Flexible estimation of time-varying effects for frequently purchased retail goods: a modeling approach based on household panel data," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 837-873, October.
    13. Moon, Sangkil & Voss, Glenn, 2009. "How do price range shoppers differ from reference price point shoppers?," Journal of Business Research, Elsevier, vol. 62(1), pages 31-38, January.
    14. Necati Tereyağoğlu & Peter S. Fader & Senthil Veeraraghavan, 2018. "Multiattribute Loss Aversion and Reference Dependence: Evidence from the Performing Arts Industry," Management Science, INFORMS, vol. 64(1), pages 421-436, January.
    15. Ioana Popescu & Yaozhong Wu, 2007. "Dynamic Pricing Strategies with Reference Effects," Operations Research, INFORMS, vol. 55(3), pages 413-429, June.
    16. Yasemin Boztug & Lutz Hildebrandt, 2005. "An empirical test of theories of price valuation using a semiparametric approach, reference prices, and accounting for heterogeneity," SFB 649 Discussion Papers SFB649DP2005-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Park, Chang Hee & Park, Young-Hoon & Schweidel, David A., 2018. "The effects of mobile promotions on customer purchase dynamics," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 453-470.
    18. El Ouardighi, Fouad & Feichtinger, Gustav & Grass, Dieter & Hartl, Richard & Kort, Peter M., 2016. "Autonomous and advertising-dependent ‘word of mouth’ under costly dynamic pricing," European Journal of Operational Research, Elsevier, vol. 251(3), pages 860-872.
    19. Ahrens, Steffen & Pirschel, Inske & Snower, Dennis J., 2017. "A theory of price adjustment under loss aversion," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 78-95.
    20. Richards, Timothy J. & Liaukonyte, Jura & Streletskaya, Nadia A., 2016. "Personalized pricing and price fairness," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 138-153.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:33:y:2014:i:3:p:317-337. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.