The Multivariate Bullwhip Effect

38 Pages Posted: 8 Nov 2016

See all articles by Chaitra Nagaraja

Chaitra Nagaraja

Fordham University - Gabelli School of Business

Tucker McElroy

U.S. Census Bureau - Center for Statistical Research and Methodology

Date Written: November 7, 2016

Abstract

A multivariate bullwhip expression for m two-stage supply chains with an order-up-to inventory policy is developed. The demand models under consideration are differenced stationary vector time series with a Wold representation for which general forecasting formulas are available, resulting in a large class of possible models (including nonstationary ones). Examples are provided for common demand models and implemented on sales data. It is found that the multivariate approach gives rise to mechanisms for understanding and reducing the bullwhip effect through horizontal information sharing, particularly for the nonstationary demand case. In the stationary setting, a more nuanced approach to bullwhip reduction can be achieved by identifying product bundles based on the relationship between cross-correlations and lead-time.

Keywords: Supply Chain Management, Multivariate Time Series, Cross-Correlated Demand

JEL Classification: C32

Suggested Citation

Nagaraja, Chaitra and McElroy, Tucker, The Multivariate Bullwhip Effect (November 7, 2016). Gabelli School of Business, Fordham University Research Paper No. 2865975, Available at SSRN: https://ssrn.com/abstract=2865975 or http://dx.doi.org/10.2139/ssrn.2865975

Chaitra Nagaraja (Contact Author)

Fordham University - Gabelli School of Business ( email )

113 West 60th Street
Bronx, NY 10458
United States

Tucker McElroy

U.S. Census Bureau - Center for Statistical Research and Methodology ( email )

4600 Silver Hill Road
Washington, DC 20233-9100
United States

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