Application of the industry cluster concept by development agencies is limited because cluster policies benefit economically powerful core regions over periphery regions and are of little use when a region has no competitive industries. To address these limitations, industry complexes can be used as an alternative to traditional cluster approaches. To demonstrate this, 49 labor complexes in Missouri are identified using cluster and discriminant function analyses, and their application to workforce development policy in Missouri is discussed. Labor complexes can be used to assist (a) job placement programs by identifying industries that are similar in labor but dissimilar in primary economic activity, (b) economic development by identifying existing pools of specialized labor for recruitment, and (c) development of customized training and education programs that meet industry demands.
Aldenderfer, M., & Blashfield, R. (1984). Cluster analysis (Sage University Paper Series on Quantitative Applications in the Social Sciences, Series Number 07-044). London: Sage.
2.
Austrian, Z. (2000). Cluster case studies: The marriage of quantitative and qualitative information for action. Economic Development Quarterly, 14, 97-110.
3.
Best, M. (1990). The new competition: Institutions of industrial restructuring. Cambridge, MA: Polity.
4.
Ellison, G., & Glaeser, E. L. (1997). Geographic concentration in U.S. manufacturing industries: A dartboard approach. Journal of Political Economy, 105, 889-927.
5.
Everitt, B. (1979). Unresolved problems in cluster analysis. Biometrics, 35, 169-184.
6.
Fagan, J. H. (2000). Do Northeast Ohio’s drivers derive competitive advantage from shared labor?Economic Development Quarterly, 14, 111-125.
7.
Feser, E. (1998a). Enterprises, external economies and economic development. Journal of Planning Literature, 12, 283-302.
8.
Feser, E. (1998b). Old and new theories of industry clusters. In M. Steiner (Ed.), Clusters and regional specialisation (pp. 18-40). London: Pion Limited.
9.
Fujita, M., & Hamaguchi, N. (2001). Intermediate goods and the spatial structure of an economy. Regional Science and Urban Economics, 31, 79-109.
10.
Fujita, M., Krugman, P., & Venables, A. (1999). The spatial economy: Cities, regions and international trade. Cambridge, MA: MIT Press.
11.
Harrison, B. (1992). Industrial districts: Old wine in new bottles?Regional Studies, 26, 469-483.
12.
Harrison, B., Kelly, E., & Gant, J. (1996). Innovative firm behavior and local milieu: Exploring the intersection of agglomeration, firm effects, industrial organization and technological change. Economic Geography, 72, 233-258.
13.
Held, J. R. (1996). Clusters as an economic development tool: Beyond the pitfalls. Economic Development Quarterly, 10, 249-261.
14.
Henderson, J. V. (1986). Efficiency of resource usage and city size. Journal of Urban Economics, 19, 47-70.
15.
Henderson, J. V. (1997). Externalities and industrial development. Journal of Urban Economics, 42, 449-470.
16.
Hill, E. W., & Brennan, J. F. (2000). A methodology for identifying the drivers of industrial clusters: The foundation for regional competitive advantage. Economic Development Quarterly, 14, 65-96.
17.
Hoover, E. M. (1937). Location theory and the shoe and leather industry. Cambridge, MA: Harvard University Press.
18.
Jaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. Quarterly Journal of Economics, 108, 577-598.
19.
Kaufman, A., Gitell, R., Merenda, M., Naumes, W., & Wood, C. (1994). Porter’s model for geographic competitive advantage: The case of New Hampshire. Economic Development Quarterly, 8, 43-66.
20.
Kim, J.-O., & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues (Sage University Paper Series on Quantitative Applications in the Social Sciences, Series Number 07-014). London: Sage.
21.
Kim, Y., Barkley, D. L., & Henry, M. S. (2000). Industry characteristics linked to establishment concentrations in nonmetropolitan areas. Journal of Regional Science, 40, 231-259.
22.
Loehlin, J. C. (1992). Latent variable models: An introduction to factor, path and structural analysis. London: Lawrence Erlbaum.
23.
Lublinski, A. E. (2003). Does geographic proximity matter? Evidence from clustered and non-clustered aeronautic firms in Germany. Regional Studies, 37, 453-467.
24.
Markusen, A. (1996). Sticky places in slippery space: A typology of industrial districts. Economic Geography, 72, 293-313.
25.
Marshall, A. (1890). Principles of economics: An introductory volume. London: Macmillan.
26.
Marshall, A. (1892). The economics of industry. London: Macmillan.
27.
Martin, R., & Sunley, P. (1996). Paul Krugman’s geographical economics and its implications for regional development theory: A critical assessment. Economic Geography, 72, 259-292.
28.
McMichael, P. (1996). Development and social change: A global perspective. Thousand Oaks, CA: Pine Forge Press.
29.
Milligan, G. W., & Cooper, M. C. (1985). An examination of procedures for detecting the number of clusters in a dataset. Psychometrika, 50, 159-179.
30.
Mojena, R. (1977). Hierarchical grouping methods and stopping rules: An evaluation. Computer Journal, 20, 359-363.
31.
Ohlin, B. (1933). Interregional and international trade. Cambridge, MA: Harvard University Press.
32.
Parr, J. B. (2002a). Agglomeration and trade: Some additional perspectives. Regional Studies, 36, 675-684.
33.
Parr, J. B. (2002b). Missing elements in the analysis of agglomeration economies. International Regional Science Review, 25, 151-168.
34.
Perroux, F. (1950). Economic space: Theory and applications. Quarterly Journal of Economics, 64, 89-104.
35.
Porter, M. E. (1990). The competitive advantage of nations. New York: Free Press.
36.
Porter, M. E. (2000). Location, competition and economic development: Local clusters in a global economy. Economic Development Quarterly, 14, 15-34.
37.
Robinson, E. A. G. (1958). The structure of competitive industry. Cambridge, UK: Cambridge University Press.
38.
Rosenfeld, S. A. (1997). Bringing business clusters into the mainstream of economic development. European Planning Studies, 5, 3-23.
39.
Rosenfeld, S. A. (2000). Community college/cluster connections: Specialization and competitiveness in the United States and Europe. Economic Development Quarterly, 14, 51-62.
40.
Steiner, M. (1998). The discrete charmofclusters: An introduction. In M. Steiner (Ed.), Clusters and regional specialisation (pp. 1-17). London: Pion Limited.
41.
Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics. New York: HarperCollins.
42.
Tichy, G. (1998). Clusters: Less dispensable and more risky than ever. In M. Steiner (Ed.), Clusters and regional specialisation (pp. 226-237). London: Pion Limited.
43.
U.S. Bureau of Labor Statistics. (2002a). Occupation employment statistics for Missouri [CD-ROM]. Washington, DC: Author. Distributed by Missouri Department of Economic Development, Jefferson City, MO.
44.
U.S. Bureau of Labor Statistics. (2002b). Quarterly census of employment and wages for Missouri [CD-ROM]. Washington, DC: Author. Distributed by Missouri Department of Economic Development, Jefferson City, MO.
45.
Waits, M. J. (2000). The added value of the industry cluster approach to economic analysis, strategy development, and service delivery. Economic Development Quarterly, 14, 35-50.
46.
Ward, J. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58, 236-244.
