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Optimal Pilfering Policies for Dynamic Continuous Thieves

Author

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  • Suresh P. Sethi

    (University of Toronto)

Abstract

This paper considers the problems of a dynamic continuous thief, such as a habitual shoplifter or a gas siphoner, who must choose the pilfering rate (which increases the probability of his arrest over time) to maximize the present value of his total expected gain over a given finite or infinte horizon. The gain function incorporates the amount of pilfering, the one-shot penalty at the time of arrest and the continuous punishment subsequent to arrest. A thief is classified as a profit-maximizer, a kleptomaniac, or a risk-averter depending on whether he considers his gain function to be linear, convex, or concave in the pilfering rate, respectively. Optimal pilfering rates are obtained for each of these different types of thieves by using the methods of optimal control. It is shown that the optimal pilfering policy of a profit-maximizing thief is bang-bang, i.e., either to pilfer at the maximum possible rate or not to pilfer at all. In the particular case of a finitely-lived profit-maximizing thief, the optimal policy is not to pilfer while the thief is young and then to pilfer at the maximum rate toward the end of his life so that the continuous punishment subsequent to his arrest will not last too long. In the infinite horizon cases, both the profit-maximizing thieves and kleptomaniacs will either never pilfer or pilfer at the maximum rate depending on whether the parameters of the problem they are facing are unfavorable or favorable. The risk-averse thief, on the other hand, would settle at an intermediate pilfering rate throughout the infinite horizon. Finally, it is expected that knowledge of these optimal policies will have implications for the allocation of money between police, courts and penal institutions.

Suggested Citation

  • Suresh P. Sethi, 1979. "Optimal Pilfering Policies for Dynamic Continuous Thieves," Management Science, INFORMS, vol. 25(6), pages 535-542, June.
  • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:6:p:535-542
    DOI: 10.1287/mnsc.25.6.535
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    Citations

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    Cited by:

    1. Alain Bensoussan & Suresh P. Sethi, 2007. "The Machine Maintenance and Sale Age Model of Kamien and Schwartz Revisited," Management Science, INFORMS, vol. 53(12), pages 1964-1976, December.
    2. A. Bensoussan & Q. Feng & S. P. Sethi, 2022. "Integrating equipment investment strategy with maintenance operations under uncertain failures," Annals of Operations Research, Springer, vol. 317(2), pages 353-386, October.
    3. Luiz de Mello, 2009. "Avoiding the Value Added Tax," Public Finance Review, , vol. 37(1), pages 27-46, January.
    4. Alex Coram, 2006. "An asymmetric dynamic struggle between pirates and producers," UMASS Amherst Economics Working Papers 2006-07, University of Massachusetts Amherst, Department of Economics.
    5. Baveja, Alok & Caulkins, Jonathan P. & Liu, Wensheng & Batta, Rajan & Karwan, Mark H., 1997. "When haste makes sense: Cracking down on street markets for illicit drugs," Socio-Economic Planning Sciences, Elsevier, vol. 31(4), pages 293-306, December.
    6. Hausken, Kjell, 2008. "Whether to attack a terrorist's resource stock today or tomorrow," Games and Economic Behavior, Elsevier, vol. 64(2), pages 548-564, November.
    7. Suresh P. Sethi & Sushil Gupta & Vipin K. Agrawal & Vijay K. Agrawal, 2022. "Nobel laureates’ contributions to and impacts on operations management," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4283-4303, December.
    8. Huseyin Cavusoglu & Birendra Mishra & Srinivasan Raghunathan, 2005. "The Value of Intrusion Detection Systems in Information Technology Security Architecture," Information Systems Research, INFORMS, vol. 16(1), pages 28-46, March.

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