An Empirical Investigation of Dynamic Ordering Policies

Chad R. Larson (), Danko Turcic () and Fuqiang Zhang ()
Additional contact information
Chad R. Larson: Bauer College of Business, University of Houston, Houston, Texas 77004
Danko Turcic: Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130
Fuqiang Zhang: Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130

Management Science, 2015, vol. 61, issue 9, 2118-2138

Abstract: Adaptive base stock policy is a well-known tool for managing inventories in nonstationary demand environments. This paper presents empirical tests of this policy using aggregate, firm-level data. First, we extend a single-item adaptive base stock policy in previous literature to a multi-item case. Second, we transform the policy derived for the multi-item case to a regression model that relates firm-level inventory purchases to firm-level sales and changes in sales forecasts. We focus on two research questions: Can the adaptive base stock policy explain cross-sectional ordering behaviors under sales growth? To the extent that the adaptive base stock policy fails to explain ordering behaviors under sales growth, are there frictions that explain such a finding? Our empirical results demonstrate disparities in ordering behaviors between firms experiencing high and moderate sales growth. Contrary to theoretical prediction, this implies that inventory purchases are a function of not only current sales and changes in sales forecast but also past sales growth. As potential explanations for this departure from theoretical prediction, we show that both future demand dynamics and inventory holding risks depend on past sales growth. In addition, we find that firms' inventory holding risks may also be affected by purchasing constraints imposed by supply chain contracts. Our results provide managerial implications for practitioners and inform future theoretical research. This paper was accepted by Martin Lariviere, operations management .

Keywords: inventory policies; stochastic models; forecasting; ARIMA processes; nonstationary demand (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2014.2077 (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:ormnsc:v:61:y:2015:i:9:p:2118-2138

Access Statistics for this article

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