Process Flexibility: A Distribution-Free Bound on the Performance of k -Chain

Xuan Wang () and Jiawei Zhang ()
Additional contact information
Xuan Wang: Leonard N. Stern School of Business, New York University, New York, New York 10012
Jiawei Zhang: Leonard N. Stern School of Business, New York University, New York, New York 10012; and New York University Shanghai, Shanghai, China 200122

Operations Research, 2015, vol. 63, issue 3, 555-571

Abstract: Process flexibility has been widely applied in many industries as a competitive strategy to improve responsiveness to demand uncertainty. An important flexibility concept is the long chain proposed by Jordan and Graves (1995) [Jordan WC, Graves SC (1995) Principles on the benefits of manufacturing process flexibility. Management Sci. 41(4):577–594.]. The effectiveness of the long chain has been investigated via numerical as well as theoretical analysis for specific probability distributions of the random demand. In this paper, we obtain in closed form a distribution-free bound on the ratio of the expected sales of the long chain relative to that of full flexibility. Our bound depends only on the mean and standard deviation of the random demand, but compares very well with the ratio that uses complete information of the demand distribution. This suggests the robustness of the performance of the long chain under different distributions. We also prove a similar result for k -chain, a more general flexibility structure. We further tighten the bounds by incorporating more distributional information of the random demand.

Keywords: process flexibility; problem of moments; asymptotic analysis; worst-case bound (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.2015.1370 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:63:y:2015:i:3:p:555-571

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().