Retail Store Density and the Cost of Greenhouse Gas Emissions

Gérard P. Cachon

Management Science · 2014 · 281 citations · 40 references

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Concepts

TL;DR

Store density, size, and location shape retailer and consumer costs, with sparse networks forcing longer travel and dense networks shortening trips, making supply‑chain layout relevant for emission‑reduction goals and urban planning. The study asks whether small local shops are preferred over large “big‑box” retailers. A retail‑supply‑chain model is developed that incorporates operating costs and a carbon‑emission externality cost. Focusing solely on operating‑cost minimization can raise emissions by 67%, a carbon price is ineffective, and doubling consumer vehicle fuel efficiency cuts long‑run emissions by about one‑third while truck efficiency has little effect. The paper was accepted by Yossi Aviv in Operations Management.

Abstract

The density, size, and location of stores in a retailer's network influences both the retailer's and the consumers' costs. With stores few and far between, consumers must travel a long distance to shop, whereas shopping trips are shorter with a dense network of stores. The layout of the retail supply chain is of interest to retailers who have emission reduction targets and urban planners concerned with sprawl. Are small local shops preferred over large, “big-box” retailers? A model of the retail supply chain is presented that includes operating costs (such as fuel and rent for floor space) as well as a cost for environmental externalities associated with carbon emissions. A focus on exclusively minimizing operating costs may substantially increase emissions (by 67% in one scenario) relative to the minimum level of emissions. A price on carbon is an ineffective mechanism for reducing emissions. The most attractive option is to improve consumer fuel efficiency—doubling the fuel efficiency of cars reduces long-run emissions by about one-third, whereas an improvement in truck fuel efficiency has a marginal impact on total emissions. This paper was accepted by Yossi Aviv, operations management.

References

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