Conditions that cause risk pooling to increase inventory

Yang, Hongsuk; Schrage, Linus

doi:10.1016/j.ejor.2007.10.064

Cited by 72 publications

(37 citation statements)

References 27 publications

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“…Gerchak and Mossman (1992) and Chen and Lin (1990) show counter results where inventory increases when the ordering decision is centralized using different demand distributions. Yang and Schrage (2009) generalize these results by analytically showing that when demand distributions are right skewed, optimal inventory amount may increase after pooling, defined as inventory anomaly. Using general demand functions, Aydin et al (2012) show that centralization decreases inventory levels if the marginal contribution parameter is high enough.…”

Section: Hypothesesmentioning

confidence: 99%

“…Gerchak and He (2003) and Berman et al (2011) show conditions under which inventory cost savings may increase or decrease with demand variation. Cai and Du (2009) and Yang and Schrage (2009) provide an extensive review of studies on inventory pooling. This paper bridges the theoretical work in operations management with the empirical work in corporate finance.…”

Section: Introductionmentioning

confidence: 99%

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Inventory performance with pooling: Evidence from mergers and acquisitions

Çömez-Dolgan

Tanyeri

2015

International Journal of Production Economics

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a b s t r a c tTheoretical studies show that compared to decentralized inventory management, (i) pooling inventories for different demand sources decreases the optimal safety stock, which in turn decreases inventory costs and (ii) the decrease in stock is related to the correlation between the different demand sources and variabilities of demands. Mergers and acquisitions (M&A) provide a business context to investigate the effects of correlation and variability of the merging firms' demands on potential improvements in inventory performance through inventory pooling. While merging firms may not fully centralize their inventory decisions, the coordination of inventory and supply chain decisions may result in synergies. Using firm-level data for 270 same-industry mergers carried out in U.S. between 1981 and 2009, we find that the inventory turnover of bidder and target firms improves (relative to firms in their industry) following the successful completion of mergers. The improvement in turnover is especially pronounced in deals where the demand of bidder and target firms are negatively correlated prior to the merger. Our results provide novel empirical support for the predictions of theoretical models on inventory economies in M&A.

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Section: Hypothesesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Inventory performance with pooling: Evidence from mergers and acquisitions

Çömez-Dolgan

Tanyeri

2015

International Journal of Production Economics

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“…Jain (2007) studied the beneficial effects of capacity pooling. Yang and Schrage (2009) investigated the inventory management issue when substitutions among products are allowed. Olsson (2009) studied the issue of lateral shipment with two identical locations in a singleechelon inventory system.…”

Section: Literature Reviewmentioning

confidence: 99%

Economical production and transshipment policy for coordinating multiple production sites

Kim

Goyal

2012

International Journal of Systems Science

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In this article, we study the coordination mechanism dealing with a production-transshipment policy across the multiple regions supplying multiple products. It is assumed that each production site has its own dedicated demand region consuming multiple products. The main concern is how to determine both the production quantity and the lot-apportioning policy while minimising the relevant supply chain cost. This decision issue is formulated as a non-linear mathematical model to determine several relevant decision variables. We propose the solution procedure for deriving the production-transshipment policy minimising the overall supply chain cost.

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“…The study of Barahona & Jensen (1998) put the basis of the more recent analysis in operation research, for example Schrijver (2000) and Iwata et al (2001), to solve problems with a huge number of knots in the network. Researchers proved that pooling or aggregating demands reduces the risks associated with forecasting errors and inventory mismanagement (Chopra & Sodhi, 2004) under appropriate conditions (Yang & Schrage, 2009). …”

Section: Risk Poolingmentioning

confidence: 99%