Analysis of the Bullwhip Effect in a Multiproduct Setting with Interdependent Demands

Srinivasan Raghunathan (), Christopher S.Tang () and Xiaohang Yue ()
Additional contact information
Srinivasan Raghunathan: Naveen Jindal School of Management, The University of Texas at Dallas, Richardson, Texas 75083
Christopher S.Tang: Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095
Xiaohang Yue: Lubar School of Business, The University of Wisconsin at Milwaukee, Milwaukee, Wisconsin 53201

Operations Research, 2017, vol. 65, issue 2, 424-432

Abstract: The bullwhip effect has been extensively studied primarily based on the analysis of various single-product models with a few exceptions. We extend the single-product analysis to the multiproduct setting of interdependent demand streams with auto-correlation and cross-product correlation, as well as contemporaneous correlation across forecasting errors. We find that interdependency between demand streams plays a critical role in determining the existence and magnitude of the bullwhip effect. Specifically, we consider two operating environments: (a) The firm orders product-specific materials so that the ordering decision is based on the product level; and (b) the firm orders generic materials so that the order decision is based on the category level. We show that, even with demand pooling, a firm operating at the category level can experience a larger bullwhip effect and a larger order variance under certain conditions that depend on the number of products in the category and the demand dependencies.

Keywords: bullwhip effect; demand pooling; forecasting (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1287/opre.2016.1571 (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:65:y:2017:i:2:p:

Access Statistics for this article

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