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Optimal due date quoting for a risk-averse decision-maker under CVaR
Stockholm University, Faculty of Social Sciences, Stockholm Business School. Nanjing University of Aeronautics and Astronautics, China.
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
Number of Authors: 42018 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 56, no 5, p. 1934-1959Article in journal (Refereed) Published
Abstract [en]

This study investigates a due date quoting problem for a project with stochastic duration, taking the decision-maker's risk attitude into consideration. The project profit is defined as the difference between the price and the cost that is comprised of production cost and earliness-tardiness penalties. In this situation, the due date determination has to be modelled as a stochastic optimisation due to stochastic duration. Conditional value at risk is thus employed as a performance measure to describe the decision-maker's risk attitude. In fixed price contract, when the unit production cost is not smaller than the unit penalty on earliness, the optimal due date increases with the increase of the degree of a decision-maker's risk aversion, the unit penalty on delay, and the decrease of the unit penalty on earliness. Besides, when the price is proportional to the due date and the slope is no bigger than the unit penalty on tardiness, the optimal due date is smaller than the result in fixed price. This is because high price for a short due date encourages a decision-maker to quote a small due date. Further, we compare the optimal due date in different parameter setting where the penalty coefficient of earliness is negative or zero, which means there is reward or no penalty on earliness, respectively. Finally, a case study is conducted to validate the effectiveness and efficiency of the proposed model.

Place, publisher, year, edition, pages
2018. Vol. 56, no 5, p. 1934-1959
Keywords [en]
due date quoting, CVaR, stochastic duration, just in time, risk analysis, decision support systems
National Category
Economics and Business Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:su:diva-158215DOI: 10.1080/00207543.2017.1394587ISI: 000433967300013OAI: oai:DiVA.org:su-158215DiVA, id: diva2:1235364
Available from: 2018-07-25 Created: 2018-07-25 Last updated: 2018-07-25Bibliographically approved

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Tao, LiangyanWu, Desheng DashDolgui, Alexandre
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