Planning Matters

Abstract

Problem, research strategy, and findings: Recent research reveals growing spatial disparities in warehousing-related environmental externalities, including air pollution and traffic safety concerns, across municipalities. The existing research, however, fails to present how institutional factors contribute to spatial variations. In this study, I explore how variations in planning practices contribute to the different trajectories of warehousing development. I interviewed planners, local residents, warehousing developers, and regional agency staff to identify local planning practices and policy elements that affect the location choice of warehousing facilities. My results show land use policies (land use permission, industrial zoning, and land parcel division schemes), job-related policies (job creation initiatives and job density requirements), financial incentives (tax rates and financial incentives), and environmental regulations (building design, land use buffering, and landscaping) are the major planning elements that affect warehousing development. Relative to brownfield redevelopment in the municipalities close to the urban core of a metropolitan area, developing greenfield warehousing facilities in suburban cities is likely to cause more environmental concerns in the near future. However, unmeasured factors could be responsible for some of the warehousing development patterns I find in the data.

Takeaway for practice: Knowledge, communication, and collaboration are needed to cope with the rapid growth and, in particular, the disproportionate concentration of warehousing-related environmental externalities in certain municipalities. In this study I also provide planning strategies to regulate excessive warehousing development, including land use- and job-related policies, financial incentives, and environmental regulations. With these strategies, planners in warehousing-intensive cities can determine the best way to reduce the impacts of environmental externalities on local communities in the long term.

Keywords:

• institutional factors
• planning practices
• qualitative method
• spatial disparities
• warehousing location

Supplemental Material

Supplemental data for this article can be found on the publisher’s website.

Notes

Notes

1 In this study, warehousing facilities (or warehouses), broadly defined, include all industrial facilities whose major function is storing bulk produce or goods for commercial purposes, including storage warehouses, distribution centers, fulfillment centers, cold storage warehouses, etc. Please refer to Sicola (2017) for more details on this definition.

2 According to Acemoglu and Restrepo (2017), the negative effects of robot penetration on wages and employment are primarily from “a displacement effect (by directly displacing workers from tasks they were previously performing)” (p. 2). They also say, “The employment effects of robots are most pronounced in manufacturing, and in particular, in industries most exposed to robots; in routine manual, blue collar, assembly and related occupations; and for workers with less than college education” (p. 5). The warehousing industry is definitely among these industries given its employment composition.

3 I retrieved the industrial land rent data from LoopNet.com and calculated the final rates based on average values of industrial property rent.

4 I identified facilities in the warehousing and storage industry (including warehouses, distribution centers, intermodal warehouses, and refrigerated warehouses) with rentable built-up areas of at least 30,000 ft² as “warehousing facilities” in this study.

5 In this step, I first focused on all 14 municipalities with the most warehousing square footage (more than 5 million ft²) because I am most interested in how those cities become warehousing hot spots. I then searched for their neighbors within the same subregion and with zero or second-lowest levels of warehousing square footage (no more than 2 million ft²), so that the two municipalities in each pair have very different levels of warehousing development. These processes result in 24 pairs of municipalities in the entire region. The full list of these pairs is available upon request.

6 I regard 2008 as the midpoint of the observation period and the land use data in that year as an average status of land use development during the period. I referred to the land use data in 2008 provided by the Southern California Association of Governments.

Additional information

Notes on contributors

Quan Yuan

QUAN YUAN ([email protected]) is a postdoctoral research associate in the Department of City and Regional Planning at the University of North Carolina Chapel Hill.