Logistics State of the Nation

Avijit Sarkar Analysis, Archive, Industry, Methodology, Risk Analysis, Transportation & Logistics

Summary: This study calculates and maps the extent of specialization in logistics employment across the nation at the zip code level. Employment in the logistics sector, specifically in warehousing and transportation businesses is often an indicator of the economic health of a region, or a state, or indeed an entire nation. We find that, for the entire United States, the top twenty local areas (zip codes) that specialize in logistics employment are mostly distributed in cities that are located in states adjacent to the oceans, great lakes, or in one instance the hub of a major global logistics services provider. The employment share of logistics in each of these zip codes is at least 35 times higher than the average employment share of logistics in the entire nation. Also approximately 60% of these logistics-specialized zip codes are located outside metropolitan statistical areas. Location quotients as well as transformed location quotients in Table 1 indicate the extent of specialization. The higher the location quotient, the higher is the extent of specialization. Nationwide maps (static and dynamic) of transformed location quotients of logistics employment at zip code level can be found at http://isea.redlands.edu/.

[table] Table 1: Top 20 zip codes specialized in Logistics Employment in the entire nation

Rank Zip Code Location Quotient Transformed LQ City
1 49528 44.84985 0.9990062 Grand Rapids, MI
2 21130 43.22271 0.9989300 Perryman, MD
3 31624 43.09131 0.9989235 Axson, GA
4 93290 42.93292 0.9989156 Visalia, CA
5 37224 42.03421 0.9988687 Nashville, TN
6 90052 41.43832 0.9988359 Los Angeles, CA
7 85293 41.37217 0.9988322 Casa Grande, AZ
8 27831 40.65151 0.9987905 Garysburg, NC
9 10117 40.64988 0.9987904 Manhattan, NY
10 24318 40.64988 0.9987904 Ceres, VA
11 68659 39.78828 0.9987375 Rogers, NE
12 36907 39.2383 0.9987019 Cuba, AL
13 48343 38.53577 0.9986541 Pontiac, MI
14 13147 38.47026 0.9986495 Scipio Center, NY
15 84307 38.21537 0.9986315 Corinne, UT
16 93005 36.79001 0.9985235 Ventura, CA
17 63855 36.78797 0.9985233 Hornersville, MO
18 47596 36.57381 0.9985059 Westphalia, IN
19 17077 36.54681 0.9985037 Ono, PA
20 62524 36.31572 0.9984847 Decatur, IL
[/table]

US Specialization in Logistics Employment, 2008

Implications:

Millions of businesses around the country require, supply, and/or produce raw materials, semi-finished or finished products, assemblies and sub-assemblies, etc. in various shapes and form. The role of warehouses and transportation facilities for storing the goods, merchandise, etc. worth billions of dollars, keeping them secure, and distributing them in a timely fashion is extremely crucial. In fact the logistics sector can help to propel local economies especially those that specialize in logistics and can leverage that specialization as a competitive advantage. This study provides a framework to visualize national warehousing and goods transportation facilities relative to freight transport infrastructure. Furthermore, location quotients computed at zip code level help us determine areas that specialize in warehousing and transportation. Results and maps generated can be used by businesses for operational decision- making such as carrier selection, and development of transportation strategy as well as strategic decision-making by complementary businesses as well as city level policymakers.

Data Sources:

We have calculated employment data by zip-code for the entire US from the business zip pattern data available from the US Census Bureau for the year 2008. Hence all national level maps and analysis are based on 2008 data. We estimated Southern Californian employment data for the month of April 2011 by combining the business zip pattern data from the US Census bureau with employment data from the California Employment Development Department. Transportation and warehousing business locations as well as locations of ports, airports, and rail yards were obtained from InfoUSA Business Listing data in ESRI’s ArcGIS© Business Analyst©. Other data was also obtained from ESRI products such as StreetMap USA.

Method:

The extent of specialization in logistics employment was measured by calculating location quotients (LQ) for the logistics sector comprising warehousing, transportation (air, rail, water, truck), packing and crating, and logistics consulting businesses. According to the Bureau of Labor Statistics, LQs are ratios that allow an area’s distribution of employment by industry to be compared to a reference or base area’s distribution. If an LQ is equal to 100%, then the industry has the same share of its area employment as it does in the reference area. An LQ greater than 100% indicates an industry with a greater share of the local area employment than is the case in the reference area; hence the area can be considered to be specialized in that industry. It is important to note that the reference/base area for the national level analysis is the entire nation. For Southern California analysis, the reference/base area is comprised of the counties of Los Angeles, Orange, San Diego, Riverside, San Bernardino, Ventura, Kern, and Imperial. For the purposes of this study, traditional LQs were transformed using standard mathematical transformations so that all transformed LQs lie between -1 and +1. This helps us obtain one common scale for mapping transformed LQs regionally (SoCal) as well as nationwide for the entire logistics sector or sub-sectors such as warehousing and transportation.

Caveats:

As mentioned earlier, employment data used for analysis and mapping at the national and regional (Southern California) level comes from two different time periods. It would be ideal if both datasets belonged to the same time period. Furthermore, it is pertinent to note that the computation of location quotients at the zip code level does not take into account the size of a zip code in terms of its actual area. Since logistics businesses impose space constraints, large zip codes offer more space to locate a logistics business thereby increasing the potential for specialization. This can be accounted for by including a non-trivial adjustment for geographic area in the computation of location quotients.

Acknowledgements:

The author acknowledges significant computational assistance provided by Professor Johannes Moenius, ISEA Director. Maps were prepared by Serene Ong, GIS Analyst, The Redlands Institute, University of Redlands.