IDEAS home Printed from https://ideas.repec.org/p/upf/upfgen/533.html
   My bibliography  Save this paper

Revenue management under general discrete choice model of consumer behavior

Author

Listed:
  • Kalyan Talluri
  • Garrett van Ryzin

Abstract

Customer choice behavior, such as 'buy-up' and 'buy-down', is an important phe-nomenon in a wide range of industries. Yet there are few models or methodologies available to exploit this phenomenon within yield management systems. We make some progress on filling this void. Specifically, we develop a model of yield management in which the buyers' behavior is modeled explicitly using a multi-nomial logit model of demand. The control problem is to decide which subset of fare classes to offer at each point in time. The set of open fare classes then affects the purchase probabilities for each class. We formulate a dynamic program to determine the optimal control policy and show that it reduces to a dynamic nested allocation policy. Thus, the optimal choice-based policy can easily be implemented in reservation systems that use nested allocation controls. We also develop an estimation procedure for our model based on the expectation-maximization (EM) method that jointly estimates arrival rates and choice model parameters when no-purchase outcomes are unobservable. Numerical results show that this combined optimization -estimation approach may significantly improve revenue performance relative to traditional leg-based models that do not account for choice behavior.

Suggested Citation

  • Kalyan Talluri & Garrett van Ryzin, 2000. "Revenue management under general discrete choice model of consumer behavior," Economics Working Papers 533, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2001.
    • Handle: RePEc:upf:upfgen:533
    as

    Download full text from publisher

    File URL: https://econ-papers.upf.edu/papers/533.pdf
    File Function: Whole Paper
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. S. L. Brumelle & J. I. McGill, 1993. "Airline Seat Allocation with Multiple Nested Fare Classes," Operations Research, INFORMS, vol. 41(1), pages 127-137, February.
    2. Barry C. Smith & John F. Leimkuhler & Ross M. Darrow, 1992. "Yield Management at American Airlines," Interfaces, INFORMS, vol. 22(1), pages 8-31, February.
    3. Youyi Feng & Guillermo Gallego, 1995. "Optimal Starting Times for End-of-Season Sales and Optimal Stopping Times for Promotional Fares," Management Science, INFORMS, vol. 41(8), pages 1371-1391, August.
    4. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    5. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    6. Tak C. Lee & Marvin Hersh, 1993. "A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings," Transportation Science, INFORMS, vol. 27(3), pages 252-265, August.
    7. Gabriel Bitran & René Caldentey & Susana Mondschein, 1998. "Coordinating Clearance Markdown Sales of Seasonal Products in Retail Chains," Operations Research, INFORMS, vol. 46(5), pages 609-624, October.
    8. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    9. Anton J. Kleywegt & Jason D. Papastavrou, 1998. "The Dynamic and Stochastic Knapsack Problem," Operations Research, INFORMS, vol. 46(1), pages 17-35, February.
    10. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    11. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    12. Richard D. Wollmer, 1992. "An Airline Seat Management Model for a Single Leg Route When Lower Fare Classes Book First," Operations Research, INFORMS, vol. 40(1), pages 26-37, February.
    13. Dror, Moshe & Trudeau, Pierre & Ladany, Shaul P., 1988. "Network models for seat allocation on flights," Transportation Research Part B: Methodological, Elsevier, vol. 22(4), pages 239-250, August.
    14. Peter P. Belobaba, 1989. "OR Practice—Application of a Probabilistic Decision Model to Airline Seat Inventory Control," Operations Research, INFORMS, vol. 37(2), pages 183-197, April.
    15. Yigao Liang, 1999. "Solution to the Continuous Time Dynamic Yield Management Model," Transportation Science, INFORMS, vol. 33(1), pages 117-123, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kalyan Talluri, 2003. "On equilibria in duopolies with finite strategy spaces," Economics Working Papers 701, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    3. Uzma Mushtaque & Jennifer A. Pazour, 2020. "Random Utility Models with Cardinality Context Effects for Online Subscription Service Platforms," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(4), pages 276-290, August.

    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. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    2. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    3. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    4. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    5. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    6. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    7. Feng, Youyi & Xiao, Baichun, 2006. "A continuous-time seat control model for single-leg flights with no-shows and optimal overbooking upper bound," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1298-1316, October.
    8. Pak, K. & Piersma, N., 2002. "airline revenue management," ERIM Report Series Research in Management ERS-2002-12-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    9. Pak, K. & Piersma, N., 2002. "Airline revenue management: an overview of OR techniques 1982-2001," Econometric Institute Research Papers EI 2002-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Youyi Feng & Baichun Xiao, 2001. "A Dynamic Airline Seat Inventory Control Model and Its Optimal Policy," Operations Research, INFORMS, vol. 49(6), pages 938-949, December.
    11. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
    12. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
    13. Feng, Youyi & Xiao, Baichun, 2006. "Integration of pricing and capacity allocation for perishable products," European Journal of Operational Research, Elsevier, vol. 168(1), pages 17-34, January.
    14. E. Andrew Boyd & Ioana C. Bilegan, 2003. "Revenue Management and E-Commerce," Management Science, INFORMS, vol. 49(10), pages 1363-1386, October.
    15. Richard Van Slyke & Yi Young, 2000. "Finite Horizon Stochastic Knapsacks with Applications to Yield Management," Operations Research, INFORMS, vol. 48(1), pages 155-172, February.
    16. Wang, Xiubin & Regan, Amelia, 2006. "Dynamic yield management when aircraft assignments are subject to swap," Transportation Research Part B: Methodological, Elsevier, vol. 40(7), pages 563-576, August.
    17. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    18. Dai Yao & Chuang Tang & Junhong Chu, 2023. "A Dynamic Model of Owner Acceptance in Peer-to-Peer Sharing Markets," Marketing Science, INFORMS, vol. 42(1), pages 166-188, January.
    19. Muzaffer Buyruk & Ertan Güner, 2022. "Personalization in airline revenue management: an overview and future outlook," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 129-139, April.
    20. Youyi Feng & Guillermo Gallego, 2000. "Perishable Asset Revenue Management with Markovian Time Dependent Demand Intensities," Management Science, INFORMS, vol. 46(7), pages 941-956, July.

    More about this item

    Keywords

    yield management; revenue management; discrete choice theory; airlines; dynamic programming;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    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:upf:upfgen:533. 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: the person in charge (email available below). General contact details of provider: http://www.econ.upf.edu/ .

    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.