Optimal retail location and CO₂ emissions

Abstract

In this article, the p-median model is used to find the location of retail stores that minimizes CO₂ emissions from consumer travel. The optimal location is then compared with the existing retail location, and the excess CO₂ emissions compared with the optimal solution is calculated. The results show that by using the environmentally optimal location, CO₂ emissions from consumer travel could be reduced by approximately 22%.

Keywords:

• firm location
• spatial distribution of firms
• p-median model
• emission reduction

JEL Classification:

• D22
• L13
• L81
• R12

Acknowledgement

The financial support received from the Swedish Retail and Wholesale Development Council is gratefully acknowledged.

Notes

¹ Jia et al. (2013) found, in a study of consumers’ travel to a shopping centre, that the consumers generally opted for the shortest route.

² The road distance serves as a proxy for the CO₂ emissions. Määttä-Juntunen et al. (2011) elaborate on more refined proxies for the CO₂ emissions derived from the road distance. Primarily, these are based on highway and urban roads with two different average speeds. In addition, in Carling et al. (2013), a detailed approach for measuring CO₂ emissions was found to be strongly correlated with the travelling distance, once outside the inner-city area. Consequently, we have not attempted to refine the measure of CO₂ emissions further as this study is conducted in a rural area with a national road network with little variation in road types, average speed and traffic flow.

³ Our adaptive scheme to dynamically adjust temperature works as follows: after n = 10 iterations with no improvement, the temperature is increased according to newtemp = temp * 3 ^ β, where β starts at 0.5 and is increased by 0.5 each time the system is reheated. As a result, the SA will never be in a frozen state for long. The temperature decreases each iteration with a factor of 0.95. The aforementioned settings are a result of substantial preliminary testing on these data and problem.