Quantal Theory in Operations Management

  • Yefen Chen
  • Yanan Song


In recent decades, numerous studies on commercial operations have found that human managers are not perfectly rational and their behavioral preferences influence the performance of operations systems. Thus, efficient operations have to account for innate human or situation-based behavioral preferences for their optimization. In this chapter, we introduce a quantal theory, which provides a descriptive model to consider bounded rationality in analyzing operational decisions, based on the assumption that decision-makers make mistakes in calculating payoffs. We organize the applications of quantal theory in operations management, and show how to properly develop an informative behavioral model to analyze operational problems. Further, we discuss how to accommodate bounded rationality into humanitarian operations.


Quantal theory Decision error Behavioral preferences Bounded rationality Operations management problems 



The authors wish to thank the editor and two anonymous reviewers for their guidance and constructive comments. The authors would also like to thank the National Natural Science Foundation of China (71501004) for its support.


  1. Anderson, E., & Weitz, B. (1992). The use of pledges to build and sustain commitment in distribution channels. Journal of Marketing Research, 29(1), 18–34.Google Scholar
  2. Balcik, B., Beamon, B. M., Krejci, C. C., Muramatsu, K. M., & Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities. International Journal of Production Economics, 126(1), 22–34.Google Scholar
  3. Becker-peth, M., & Thonemann, U. W. (2016). Reference points in revenue sharing contracts—How to design optimal supply chain contracts. European Journal of Operational Research, 249(3), 1033–1049.Google Scholar
  4. Bolton, G. E., & Katok, E. (2008). Learning by doing in the newsvendor problem: A laboratory investigation of the role of experience and feedback. Manufacturing & Service Operations Management, 10(3), 519–538.Google Scholar
  5. Cachon, G. P. (2003). Supply chain coordination with contracts. Handbooks in Operations Research and Management Science, 11, 227–339.Google Scholar
  6. Cachon, G. P., & Lariviere, M. A. (2005). Supply chain coordination with revenue-sharing contracts: Strengths and limitations. Management Science, 51(1), 30–44.Google Scholar
  7. Cachon, G. P., & Swinney, R. (2009). Purchasing, pricing, and quick response in the presence of strategic consumers. Management Science, 55(3), 497–511.Google Scholar
  8. Chen, L., Kök, A. G., & Tong, J. D. (2013). The effect of payment schemes on inventory decisions: The role of mental accounting. Management Science, 59(2), 436–451.Google Scholar
  9. Chen, Y., Su, X., & Zhao, X. (2012). Modeling bounded rationality in capacity allocation games with the quantal response equilibrium. Management Science, 58(10), 1952–1962.Google Scholar
  10. Chen, Y., & Zhao, X. (2015). Decision bias in capacity allocation games with uncertain demand. Production and Operations Management, 24(4), 634–646.Google Scholar
  11. Elmaghraby, W., Gülcü, A., & Keskinocak, P. (2008). Designing optimal preannounced markdowns in the presence of rational customers with multiunit demands. Manufacturing & Service Operations Management, 10(1), 126–148.Google Scholar
  12. Fehr, E., & Fischbacher, U. (2004). Social norms and human cooperation. Trends in Cognitive Sciences, 8(4), 185–190.Google Scholar
  13. Fehr, E., & Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation. Quarterly Journal of Economics, 114(3), 817–868.Google Scholar
  14. Fey, M., McKelvey, R. D., & Palfrey, T. R. (1996). An experimental study of constant-sum centipede games. International Journal of Game Theory, 25(3), 269–287.Google Scholar
  15. Goeree, J. K., & Holt, C. A. (2001). Ten little treasures of game theory and ten intuitive contradictions. American Economic Review, 91(5), 1402–1422.Google Scholar
  16. Helsloot, I., & Ruitenberg, A. (2004). Citizen response to disasters: A survey of literature and some practical implications. Journal of Contingencies and Crisis Management, 12(3), 98–111.Google Scholar
  17. Ho, T.-H., Lim, N., & Cui, T. (2010). Reference-dependence in multilocation newsvendor models: A structural analysis. Management Science, 56(11), 1891–1910.Google Scholar
  18. Ho, T.-H., & Su, X. (2009). Peer-induced fairness in games. American Economic Review, 99(5), 2022–2049.Google Scholar
  19. Ho, T.-H., Su, X., & Wu, Y. (2013). Fairness in supply chain contract design. Production and Operations Management, 23(2), 161–175.Google Scholar
  20. Ho, T.-H., & Zhang, J. (2008). Designing price contracts for boundedly rational customers: Does the framing of the fixed fee matter? Management Science, 54(4), 686–700.Google Scholar
  21. Holguín-Veras, J., Jaller, M., Van Wassenhove, L. N., Pérez, N., & Wachtendorf, T. (2012). On the unique features of post-disaster humanitarian logistics. Journal of Operations Management, 30(7), 494–506.Google Scholar
  22. Huang, T., Allon, G., & Bassamboo, A. (2013). Bounded rationality in service systems. Manufacturing & Service Operations Management, 15(2), 263–279.Google Scholar
  23. Jiang, L., & Giachetti, R. E. (2008). A queueing network model to analyze the impact of parallelization of care on patient cycle time. Health Care Management Science, 11(3), 248–261.Google Scholar
  24. Kahneman, D., Knetsch, J. D., & Thaler, R. (1986). Fairness as a constraint on profit seeking: Entitlements in the markets. American Economic Review, 47(2), 263–291.Google Scholar
  25. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 76(4), 728–741.Google Scholar
  26. Katok, E., & Pavlov, V. (2013). Fairness in supply chain contracts: A laboratory study. Journal of Operations Management, 31(3), 129–137.Google Scholar
  27. Katok, E., & Wu, D. Y. (2009). Contracting in supply chains: A laboratory investigation. Management Science, 55(12), 1953–1968.Google Scholar
  28. Kovács, G., & Spens, K. M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37(2), 99–114.Google Scholar
  29. Kovács, G., & Spens, K. M. (2009). Identifying challenges in humanitarian logistics. International Journal of Physical Distribution & Logistics Management, 39(6), 506–528.Google Scholar
  30. Lakshmi, C., & Sivakumar, A. l. (2013). Application of queueing theory in health care: A literature review. Operations Research for Health Care, 2(1), 25–39.Google Scholar
  31. Lim, N., & Ho, T.-H. (2007). Designing price contracts for boundedly rational customers: Does the number of blocks matter? Marketing Science, 26(3), 312–326.Google Scholar
  32. Lorenz, D. F., Schulze, K., & Voss, M. (2017). Emerging citizen responses to disasters in Germany. Disaster myths as an impediment for a collaboration of unaffiliated responders and professional rescue forces. Journal of Contingencies and Crisis Management, 25(3). Scholar
  33. Luce, R. D. (1959). Individual choice behavior: A theoretical analysis. New York, NY: Wiley.Google Scholar
  34. Maon, F., Lindgreen, A., & Vanhamme, J. (2009). Developing supply chains in disaster relief operations through cross-sector socially oriented collaborations: A theoretical model. Supply Chain Management: An International Journal, 14(2), 149–164.Google Scholar
  35. McFadden, D. (1981). Econometric models of probabilistic choice. In C. F. Manski & D. McFadden (Eds.), Structural analysis of discrete data with econometric applications (pp. 198–272). Cambridge, MA: MIT Press.Google Scholar
  36. McKelvey, R. D., & Palfrey, T. R. (1992). An experimental study of the centipede game. Econometrica, 60(4), 803–836.Google Scholar
  37. McKelvey, R. D., & Palfrey, T. R. (1995). Quantal response equilibria for normal form games. Games and Economic Behavior, 10(1), 6–38.Google Scholar
  38. Naor, P. (1969). The regulation of queue size by levying tolls. Econometrica, 37, 15–24.Google Scholar
  39. Pavlov, V. Katok, E., Haruvy, E., & Olsen, T. (2016). Bounded rationality in supply chain contracts. Working Paper.Google Scholar
  40. Perry, R. W., & Lindell, M. K. (2003). Preparedness for emergency response: Guidelines for the emergency planning process. Disasters, 27(4), 336–350.Google Scholar
  41. Schweitzer, M. E., & Cachon, G. P. (2000). Decision bias in the newsvendor problem with a known demand distribution: Experimental evidence. Management Science, 46(3), 404–420.Google Scholar
  42. Song, Y., & Zhao, X. (2016). Strategic customer behavior facing possible stockout: An experimental study. International Journal of Production Economics, 180, 57–67.Google Scholar
  43. Song, Y., & Zhao, X. (2017). A newsvendor problem with boundedly rational strategic customers. International Journal of Production Research, 55(1), 228–243.Google Scholar
  44. Spengler, J. J. (1950). Vertical integration and antitrust policy. Journal of Political Economy, 58(4), 347–352.Google Scholar
  45. Su, X. (2008). Bounded rationality in newsvendor models. Manufacturing & Service Operations Management, 10(4), 566–589.Google Scholar
  46. Thaler, R. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214.Google Scholar
  47. Tomasini, R., & Van Wassenhove, L. N. (2009a). From preparedness to partnerships: Case study research on humanitarian logistics. International Transactions in Operational Research, 16(5), 549–559.Google Scholar
  48. Tomasini, R., & Van Wassenhove, L. N. (2009b). Humanitarian logistics. London, UK: Palgrave Macmillan.Google Scholar
  49. Van Wassenhove, L. N. (2006). Blackett memorial lecture. Humanitarian aid logistics: Supply chain management in high gear. Journal of the Operational Research Society, 57(5), 475–489.Google Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  • Yefen Chen
    • 1
  • Yanan Song
    • 2
  1. 1.Cainiao Smart Logistics NetworkHangzhouChina
  2. 2.Academy of Mathematics and System Sciences, Chinese Academy of SciencesBeijingChina

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