IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v32y2023i6p1654-1673.html
   My bibliography  Save this article

Predicting transaction outcomes under customized pricing with discretion: A structural estimation approach

Author

Listed:
  • Bharadwaj Kadiyala
  • Robert Phillips
  • A. Serdar Şimşek
  • Garrett van Ryzin

Abstract

We consider a firm selling heterogeneous products with prices customized for each customer and the final price is set by negotiations between the seller and the customer. This type of pricing modality is referred to as customized pricing with discretion and is commonly used in insurance, consumer loans, mortgages, and many business‐to‐business markets. We assume that each sales agent has a reserve price and each customer has a willingness‐to‐pay, which are jointly drawn from a distribution and, if the transaction is successful, they agree on a price between these two values based on their relative bargaining power. Given the outcomes of a series of negotiations, our goal is to estimate the underlying joint distribution of reserve price and willingness‐to‐pay, and predict the outcomes of future transactions. We assume that the price that prevails as the outcome of the negotiation can be represented as a generalized Nash bargaining equilibrium. We develop a structural estimation method based on the expectation‐maximization algorithm to estimate the parameters of reserve price and willingness‐to‐pay distribution. Using a real‐world data set from indirect auto‐lending industry, we show that our proposed method, which accounts for heterogeneity in sales agent's reserve price and customer's willingness‐to‐pay, improves the predictive accuracy of final price (APR) and take‐up probability (i.e., probability of a customer accepting the loan) on real‐world test data by about 8.70% and 3.68%, respectively, compared to a (Tobit‐based) model, which accommodates unobserved heterogeneity in customer's willingness‐to‐pay only. Using the structural EM estimates, we conduct counterfactual analyses to understand the impact of different pricing policies, which vary in the amount of discretion provided to the sales agent during the negotiation process. For example, we find that the lender may increase profits by 13.63% compared to the status quo by optimally imposing a customized minimum price (annual percentage rate) below which a loan should not be offered to the customer.

Suggested Citation

  • Bharadwaj Kadiyala & Robert Phillips & A. Serdar Şimşek & Garrett van Ryzin, 2023. "Predicting transaction outcomes under customized pricing with discretion: A structural estimation approach," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1654-1673, June.
    • Handle: RePEc:bla:popmgt:v:32:y:2023:i:6:p:1654-1673
    DOI: 10.1111/poms.13931
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.13931
    Download Restriction: no
    File URL: https://libkey.io/10.1111/poms.13931?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. Rubinstein, Ariel, 1982. "Perfect Equilibrium in a Bargaining Model," Econometrica, Econometric Society, vol. 50(1), pages 97-109, January.
    2. Ravi Anupindi & Maqbool Dada & Sachin Gupta, 1998. "Estimation of Consumer Demand with Stock-Out Based Substitution: An Application to Vending Machine Products," Marketing Science, INFORMS, vol. 17(4), pages 406-423.
    3. Ken Binmore & Ariel Rubinstein & Asher Wolinsky, 1986. "The Nash Bargaining Solution in Economic Modelling," RAND Journal of Economics, The RAND Corporation, vol. 17(2), pages 176-188, Summer.
    4. Muthoo,Abhinay, 1999. "Bargaining Theory with Applications," Cambridge Books, Cambridge University Press, number 9780521576475, September.
    5. Zeynep Akşin & Barış Ata & Seyed Morteza Emadi & Che-Lin Su, 2013. "Structural Estimation of Callers' Delay Sensitivity in Call Centers," Management Science, INFORMS, vol. 59(12), pages 2727-2746, December.
    6. Birendra K. Mishra & Ashutosh Prasad, 2004. "Centralized Pricing Versus Delegating Pricing to the Salesforce Under Information Asymmetry," Marketing Science, INFORMS, vol. 23(1), pages 21-27, January.
    7. Zhengliang Xue & Zizhuo Wang & Markus Ettl, 2016. "Pricing Personalized Bundles: A New Approach and An Empirical Study," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 51-68, February.
    8. Pradeep Bhardwaj, 2001. "Delegating Pricing Decisions," Marketing Science, INFORMS, vol. 20(2), pages 143-169, September.
    9. Rajiv Lal, 1986. "Technical Note—Delegating Pricing Responsibility to the Salesforce," Marketing Science, INFORMS, vol. 5(2), pages 159-168.
    10. Charles B. Weinberg, 1975. "An Optimal Commission Plan for Salesmen's Control Over Price," Management Science, INFORMS, vol. 21(8), pages 937-943, April.
    11. Goker Aydin & Serhan Ziya, 2009. "Technical Note---Personalized Dynamic Pricing of Limited Inventories," Operations Research, INFORMS, vol. 57(6), pages 1523-1531, December.
    12. Qi Feng & J. George Shanthikumar, 2018. "Posted Pricing vs. Bargaining in Sequential Selling Process," Operations Research, INFORMS, vol. 66(1), pages 92-103, 1-2.
    13. Christopher T. Conlon & Julie Holland Mortimer, 2013. "Demand Estimation under Incomplete Product Availability," American Economic Journal: Microeconomics, American Economic Association, vol. 5(4), pages 1-30, November.
    14. Wedad Elmaghraby & Wolfgang Jank & Shu Zhang & Itir Z. Karaesmen, 2015. "Sales Force Behavior, Pricing Information, and Pricing Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 495-510, October.
    15. Gustavo Vulcano & Garrett van Ryzin & Wassim Chaar, 2010. "OM Practice--Choice-Based Revenue Management: An Empirical Study of Estimation and Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 12(3), pages 371-392, February.
    16. Chia-Wei Kuo & Hyun-Soo Ahn & Göker Aydın, 2011. "Dynamic Pricing of Limited Inventories When Customers Negotiate," Operations Research, INFORMS, vol. 59(4), pages 882-897, August.
    17. Preyas S. Desai & Devavrat Purohit, 2004. "“Let Me Talk to My Manager”: Haggling in a Competitive Environment," Marketing Science, INFORMS, vol. 23(2), pages 219-233, August.
    18. Rubinstein, Ariel & Wolinsky, Asher, 1985. "Equilibrium in a Market with Sequential Bargaining," Econometrica, Econometric Society, vol. 53(5), pages 1133-1150, September.
    19. Kostas Bimpikis & Wedad J. Elmaghraby & Ken Moon & Wenchang Zhang, 2020. "Managing Market Thickness in Online Business-to-Business Markets," Management Science, INFORMS, vol. 66(12), pages 5783-5822, December.
    20. Robert Phillips & A. Serdar Şimşek & Garrett van Ryzin, 2015. "The Effectiveness of Field Price Discretion: Empirical Evidence from Auto Lending," Management Science, INFORMS, vol. 61(8), pages 1741-1759, August.
    21. Jun Li & Nelson Granados & Serguei Netessine, 2014. "Are Consumers Strategic? Structural Estimation from the Air-Travel Industry," Management Science, INFORMS, vol. 60(9), pages 2114-2137, September.
    22. Birendra K. Mishra & Ashutosh Prasad, 2005. "Delegating Pricing Decisions in Competitive Markets with Symmetric and Asymmetric Information," Marketing Science, INFORMS, vol. 24(3), pages 490-497, March.
    23. Kalyan Chatterjee & William Samuelson, 1983. "Bargaining under Incomplete Information," Operations Research, INFORMS, vol. 31(5), pages 835-851, 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. Robert Phillips & A. Serdar Şimşek & Garrett van Ryzin, 2015. "The Effectiveness of Field Price Discretion: Empirical Evidence from Auto Lending," Management Science, INFORMS, vol. 61(8), pages 1741-1759, August.
    2. Sandro Shelegia & Joshua Sherman, 2022. "Bargaining at Retail Stores: Evidence from Vienna," Management Science, INFORMS, vol. 68(1), pages 27-36, January.
    3. Matthias Kräkel & Anja Schöttner, 2020. "Delegating Pricing Authority to Sales Agents: The Impact of Kickbacks," Management Science, INFORMS, vol. 66(6), pages 2686-2705, June.
    4. Dai, Yue & Chao, Xiuli, 2016. "Price delegation and salesforce contract design with asymmetric risk aversion coefficient of sales agents," International Journal of Production Economics, Elsevier, vol. 172(C), pages 31-42.
    5. Duncan Simester & Juanjuan Zhang, 2014. "Why Do Salespeople Spend So Much Time Lobbying for Low Prices?," Marketing Science, INFORMS, vol. 33(6), pages 796-808, November.
    6. Jian Chen & He Huang & Liming Liu & Hongyan Xu, 2021. "Price Delegation or Not? The Effect of Heterogeneous Sales Agents," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1350-1364, May.
    7. Noah Lim & Sung H. Ham, 2014. "Relationship Organization and Price Delegation: An Experimental Study," Management Science, INFORMS, vol. 60(3), pages 586-605, March.
    8. Gabrielsen, Tommy Staahl & Roth, Stefan, 2009. "Delegated bargaining in distribution channels," Australasian marketing journal, Elsevier, vol. 17(3), pages 133-141.
    9. Frenzen, Heiko & Hansen, Ann-Kristin & Krafft, Manfred & Mantrala, Murali K. & Schmidt, Simone, 2010. "Delegation of pricing authority to the sales force: An agency-theoretic perspective of its determinants and impact on performance," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 58-68.
    10. Binmore, Ken & Osborne, Martin J. & Rubinstein, Ariel, 1992. "Noncooperative models of bargaining," Handbook of Game Theory with Economic Applications, in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 1, chapter 7, pages 179-225, Elsevier.
    11. Kjell Hausken, 1997. "Game-theoretic and Behavioral Negotiation Theory," Group Decision and Negotiation, Springer, vol. 6(6), pages 511-528, December.
    12. Yan Dong & Yuliang Yao & Tony Haitao Cui, 2011. "When Acquisition Spoils Retention: Direct Selling vs. Delegation Under CRM," Management Science, INFORMS, vol. 57(7), pages 1288-1299, July.
    13. Qi Feng & J. George Shanthikumar, 2018. "Posted Pricing vs. Bargaining in Sequential Selling Process," Operations Research, INFORMS, vol. 66(1), pages 92-103, 1-2.
    14. Birendra K. Mishra & Ashutosh Prasad, 2005. "Delegating Pricing Decisions in Competitive Markets with Symmetric and Asymmetric Information," Marketing Science, INFORMS, vol. 24(3), pages 490-497, March.
    15. Sascha Alavi & Johannes Habel & Paolo Guenzi & Jan Wieseke, 2018. "The role of leadership in salespeople’s price negotiation behavior," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 703-724, July.
    16. Manzini, Paola & Mariotti, Marco, 2005. "Alliances and negotiations," Journal of Economic Theory, Elsevier, vol. 121(1), pages 128-141, March.
    17. Guth, Werner & Ritzberger, Klaus & van Damme, Eric, 2004. "On the Nash bargaining solution with noise," European Economic Review, Elsevier, vol. 48(3), pages 697-713, June.
    18. Joalland, Olivier & Pereau, Jean-Christophe & Rambonilaza, Tina, 2019. "Bargaining local compensation payments for the installation of new power transmission lines," Energy Economics, Elsevier, vol. 80(C), pages 75-85.
    19. Sumitro Banerjee & Alex P. Thevaranjan, 2013. "How to deal with unprofitable customers? A salesforce compensation perspective," ESMT Research Working Papers ESMT-13-05, ESMT European School of Management and Technology.
    20. Venkat Venkatasubramanian & Yu Luo, 2018. "How much income inequality is fair? Nash bargaining solution and its connection to entropy," Papers 1806.05262, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    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:bla:popmgt:v:32:y:2023:i:6:p:1654-1673. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    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.