Skip to main content

Advertisement

SpringerLink
Log in

A search for an industrial cluster in Japanese manufacturing sector: evidence from a location survey

  • Published:
GeoJournal Aims and scope Submit manuscript

Abstract

This paper explores the result of a questionnaire survey on the location decision of new manufacturing plants from 1997 to 2004 and discovers an industrial cluster in Japan. More specifically, performing an exploratory factor analysis across 22 manufacturing industries, this study firstly summarizes agglomeration advantages as a latent location factor, secondly specifies the regional share of industries that emphasize the agglomeration factor, and thirdly identifies the location of industrial cluster based on the regional share. The major finding is that there exists such agglomeration factor, by which most Marshallian location advantages are represented, and the main industrial cluster consists of high-tech industries and spread over the suburb area between Tokyo and Aichi prefectures, where are most manufacturing capacity is concentrated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. Unlike the cost-led location formation, Marshallian advantages are concerned to the various function of local industrial cluster and the theory does not treat firm as an independent entity but as a node of mutually cooperating cluster network. This view is inherited to the subsequent major location theories such as Porter’s cluster theory and policy application of cluster strategies has been the major concern of social scientists (e.g. Rosenfeld 1997; Newlands 2003). Those localized benefits lead to the formation of a local clustering of economic activity and those benefits have been examined in a number of empirical studies (Hanson 2001; Rosenthal and Strange 2003 and reference therein).

  2. The disruptiveness of innovation represents a situation in which large and historical market leaders struggle to develop and introduce new products and service innovations.

  3. Entry mode represents the dichotomous choice between either full or partial ownership control of FDI. Equity level is measured as a continuous span of ownership control from 0 to 100%.

  4. Short-termism is the idea, originally advocated by Porter (1992), that short-term performance is important for securing the long-term goals of a business.

  5. The plants in the questionnaire survey are disaggregated into four types. The first is a production facility integrated with headquarters, which concurrently hold management and administrative functions. The second is a hub production facility specializing in only production and whose production capacity is the largest in the firm. The third is a periphery production facility that takes partial charge of the production of the hub production facility (the second type). The fourth is a new enterprise production facility to promote R&D and project venture businesses. The shares of the first, second, third, and fourth types of plants in the respondents are 38.2, 28.5, 21.9 and 8.4%, respectively, from 1997 to 2004; 3.0% of plants do not belong to any of those four types.

  6. Another set of statistics from the survey indicates that plants are strictly tied to their home location and hardly mobile once the origins of their locations are established. According to the results from 1997 to 2004, 69.94% of new plants locate within the same prefecture where their headquarters are established. While 30.06% of them are constructed to other prefectures, only 11.88% crossed the regional border; therefore, approximately 90% of the new plants end up staying within their headquarters’ region. Furthermore, 92.87% of relocating plants stayed in the original prefecture, 7.13% of them moved to other prefectures, and only 1.06% crossed the regional border. Thus, most relocating plants stayed in the original region. Based on the statistics, this study deems plants as rarely mobile entities; their searching process is fundamentally myopic (Maskell and Malmberg 2007), and their location option does encompass the entire country, but is limited to their original region.

  7. Cronbach’s α measures the consistency of the questionnaire survey. More specifically, the value becomes larger when respondents’ attitudes are parallel to the variables in a factor. For instance, if a respondent believes that market proximity is an important location reason, the respondent must also emphasize access to transport infrastructure to keep the survey consistent, because a transportation advantage improves market proximity and they mutually compensate one another. If this is not the case, the respondent has contradictory attitudes, and the questionnaire results are considered unreliable. Cronbach’s α measures such consistency in exploratory factor analysis results; to guarantee consistency, the value should be higher than 0.7.

References

  • Acs, Z. J., Audretsch, D. B., & Feldman, M. P. (1992). Real effects of academic research: Cooment. Americal Economic Review, 82(1), 363–367.

    Google Scholar 

  • Amin, A., & Thrift, N. (1994). Living in the global. In A. Amin & N. Thrift (Eds.), Globalization, institutions, and regional development in Europe (pp. 1–22). Oxford University Press: Oxford.

    Google Scholar 

  • Asheim, B. (2000). Industrial districts: The contribution of Marshall and beyond. In G. Clark, M. Feldman, & M. Gertler (Eds.), The Oxford handbook of economic geography (pp. 413–431). Oxford: Oxford University Press.

    Google Scholar 

  • Barkley, D. L., & McNamara, K. T. (1994). Manufacturers’ location decisions: Do surveys provide helpful insights? International Regional Science Review, 17(1), 23–47.

    Article  Google Scholar 

  • Bergman, E. M., & Feser, E. J. (1999). Industrial and regional clusters: Concept and comparative applications, web book in regional science. West Virginia University: Regional Research Institute.

    Google Scholar 

  • Blair, J. P., & Premus, R. (1987). Major factors in industrial location: A review. Economic Development Quarterly, 1(1), 72–85.

    Article  Google Scholar 

  • Boschma, R. A., & Frenken, K. (2006). Why is economic geography not an evolutionary science? Towards an evolutionary economic geography. Journal of Economic Geography, 6(3), 273–302.

    Article  Google Scholar 

  • Boschma, R. A., & Lambooy, J. (1999). Evolutionary economics and economic geography. Journal of Evolutionary Economics, 9(4), 411–429.

    Article  Google Scholar 

  • Braun, B., Gaebe, W., Grotz, R., Okamoto, Y., & Yamamoto, K. (2002). Regional networking of small and medium-sized enterprises in Japan and Germany: Evidence from a comparative study. Environment and Planning A: 34(1), 81–99.

    Article  Google Scholar 

  • Calzonetti, F. J., & Walker, R. T. (1991). Factors affecting industrial location decisions: A survey approach. In H. W. Schlottmann & A. M. Herzog (Eds.), Industrial location and public policy. Knowxville: University of Tennessee Press.

    Google Scholar 

  • Cobb, J. C. (1982). The selling of the south. Baton Rouge: Louisiana State University Press.

    Google Scholar 

  • Cruz, S. C. S., & Teixeira, A. A. C. (2010). The evolution of the cluster literature: Shedding light on the regional studies-regional science debate. Regional studies, 44(9), 1263–1288.

    Google Scholar 

  • Czamanski, S. (1974). Study of clustering of industries. Halifax, Nova Scotia, Canada: Institute of Public Affairs, Dalhousie University.

    Google Scholar 

  • Dicken, P., & Lloyd, P. E. (1990). Location in space: Theoretical perspectives in economic geography. New York: HarperCollins Publishers Inc.

    Google Scholar 

  • Dillman, D. A. (1978). Mail and telephone surveys: The total design method. New York: John Wiley and Sons.

    Google Scholar 

  • Doeringer, P. B., & Terkla, D. G. (1992). Japanese direct investment and economic development policy. Economic Development Quarterly, 6(3), 255–272.

    Article  Google Scholar 

  • Feser, E. J., & Bergman, E. M. (2000). National industry templates: A framework for applied regional cluster analysis. Regional Studies, 34(1), 1–19.

    Article  Google Scholar 

  • Feser, E. J., & Sweeney, S. H. (2002). Theory methods and a cross-metropolitan comparison of business clustering. In P. McCann (Ed.), Industrial location economics. Cheltenham: Edward Elgar.

    Google Scholar 

  • Fujita, M. (1988). A monopolistic competition model of spatial agglomeration: Differentiated product approach. Regional Science and Urban Economics, 18(1), 87–124.

    Article  Google Scholar 

  • Fujita, M., & Thisse, J. F. (2002). Economics of agglomeration: Cities, industrial location and regional growth. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Fujita, M., Krugman, P., & Venables, A. J. (1999). The spatial economy: Cities, regions and international trade. Cambridge: MIT Press.

    Google Scholar 

  • Galbraith, C. S., Rodriguez, C. L., & DeNoble, A. F. (2008). SME competitive strategy and location behavior: An exploratory study of high‐technology manufacturing. Journal of Small Business Management, 46(2), 183–202.

    Google Scholar 

  • Glaeser, E. L., Kallal, H. D., Sheinkman, J. A., & Shleifer, A. (1992). Growth in cities. The Journal of Political Economy, 100(6), 1126–1152.

    Article  Google Scholar 

  • Gordon, I. R., & McCann, P. (2000). Industrial clusters: Complexes, agglomeration and/or social networks? Urban Studies, 37(3), 513–532.

    Article  Google Scholar 

  • Govindarajan, V., & Kopalle, P. K. (2006). Disruptiveness of innovations: Measurement and an assessment of reliability. Strategic Management Journal, 27(2), 189–199.

    Article  Google Scholar 

  • Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. Readings in Economic Sociology, 91(3), 481–510.

    Google Scholar 

  • Hair, J. F., Black, B., Babin, B., & Anderson, R. E. (2006). Multivariate data analysis, 6th edition, Pearson Prentice Hall.

  • Hanson, G. H. (2001). Scale economies and the geographic concentration of industry. Journal of Economic Geography, 1(3), 255–276.

    Google Scholar 

  • Harrison, B. (1992). Industrial districts: Old wine in new bottles? Regional Studies, 26(5), 469–483.

    Article  Google Scholar 

  • Head, K., Ries, J., & Swenson, D. (1995). Agglomeration benefits and location choice: Evidence from Japanese manufacturing investments in the United States. Journal of International Economics, 38(3–4), 223–247.

    Article  Google Scholar 

  • Head, K., Ries, J., & Swenson, D. (1999). Attracting foreign manufacturing: Investment promotion and agglomeration. Regional Science and Urban Economics, 29(2), 197–218.

    Article  Google Scholar 

  • Hirschman, A. O. (1958). The strategy for economic development. Yale University Press: Urbana.

    Google Scholar 

  • Jaffe, A. B. (1989). Real effects of academic research. American Economic Review, 79(5), 957–970.

    Google Scholar 

  • Klepper, S. (2009). Spinoffs: A review and synthesis. European Management Review, 6, 159–171.

    Article  Google Scholar 

  • Kodama, T. (2008). The role of intermediation and absorptive capacity in facilitating university-industry linkages: An empirical study of TAMA in Japan. Research Policy, 37, 1224–1240.

    Article  Google Scholar 

  • Krugman, P. (1991a). Geography and trade. Cambridge, MA: MIT Press.

    Google Scholar 

  • Krugman, P. (1991b). Increase returns and economic geography. Journal of Political Economy, 99(3), 483–499.

    Article  Google Scholar 

  • Krugman, P., & Venables, A. J. (1996). Integration, specialization, and adjustment. European Economic Review, 40(3–5), 959–967.

    Article  Google Scholar 

  • Lawson, C., & Lorenz, E. (1999). Collective learning, tacit knowledge and regional innovative capacity. Regional Studies, 33(4), 305–317.

    Article  Google Scholar 

  • Malmberg, A., & Maskell, P. (2002). The elusive concept of localization economics: Towards a knowledge-based theory of spatial clustering. Environment and Planning A, 34(3), 429–449.

    Article  Google Scholar 

  • Mani, S., Antia, K. D., & Rindfleisch, A. (2007). Entry mode and equity level: A multilevel examination of foreign direct investment ownership structure. Strategic Management Journal, 28(8), 857–866.

    Article  Google Scholar 

  • Marginson, D., & McAlay, L. (2008). Exploring the debate on short-termism: A theoretical and empirical analysis. Strategic Management Journal, 29(3), 273–292.

    Article  Google Scholar 

  • Martin, R. (2001). Geography and public policy: The Case of the missing Agenda. Progress in Human Geography, 25(2), 189–210.

    Article  Google Scholar 

  • Martin, R., & Sunley, P. (2003). Deconstructing clusters: Chaotic concept or policy Panacea? Journal of Economic Geography, 3(1), 5–35.

    Article  Google Scholar 

  • Maskell, P., & Malmberg, A. (2007). Myopia, knowledge development and cluster evolution. Journal of Economic Geography, 7(5), 603–618.

    Article  Google Scholar 

  • McCann, P., & Sheppard, S. (2003). The rise, fall and rise again of industrial location theory. Regional Studies, 37(6), 649–663.

    Article  Google Scholar 

  • Myrdal, G. (1957). Economic theory and under-developed regions. London: Duckworth.

    Google Scholar 

  • Newlands, D. (2003). Competition and cooperation in industrial clusters: The implications for public policy. European Planning Studies, 11(5), 521–532.

    Article  Google Scholar 

  • Nishioka, H., & Krumme, G. (1973). Location conditions, factors and decisions: An evaluation of selected location surveys. Land Economics, 44(4), 450–460.

    Google Scholar 

  • Oster, S. (1979). Industrial search for new locations: An empirical analysis. Review of Economics and Statistics, 61, 288–292.

    Article  Google Scholar 

  • Patton, O. M., & Reweta, W. S. J. (2003). Industry clusters for the State of Coloradoworkforce research and analysis, labor market information. Colorado: Colorado Department of Labor and Employment.

    Google Scholar 

  • Piore, M. J., & Sable, C. F. (1984). The second industrial divide. New York: Basic Books Inc.

    Google Scholar 

  • Porter, M. (1990). The competitive advantage of nations. London: Macmillan.

    Google Scholar 

  • Porter, M. (1992). Capital choices: Changing the way America invests in industry. Journal of Applied Corporate Finance, 5(2), 4–16.

    Google Scholar 

  • Porter, M. E. (1998). On competition. Boston: Harvard Business School Publishing.

    Google Scholar 

  • Porter, M. E. (2000). Location, competition, and economic development: Local cluster in a global economy. Economic Development Quarterly, 14(1), 15–34.

    Article  Google Scholar 

  • Puga, D., & Venables, A. J. (1997). Preferential trading arrangements and industrial location. Journal of International Economics, 43(3–4), 347–368.

    Article  Google Scholar 

  • Reuer, J. J., & Ariño, A. (2007). Strategic alliance contracts: Dimensions and determinants of contractual complexity. Strategic Management Journal, 28(3), 313–330.

    Article  Google Scholar 

  • Rivera-Batiz, F. L. (1988). Increasing return, monopolistic competition, and agglomeration economies in consumption and production. Regional Science and Urban Economics, 18(1), 125–154.

    Article  Google Scholar 

  • Roepke, H., Adams, D., & Wiseman, R. (1974). A new approach to the identification of industrial complexes using input-output data. Journal of Regional Science, 14(1), 15–29.

    Article  Google Scholar 

  • Rosenfeld, S. A. (1997). Bringing business clusters into the mainstream of economic development. European Planning Studies, 5(1), 3–23.

    Article  Google Scholar 

  • Rosenthal, S. S., & Strange, W. C. (2003). Geography, industrial organization and agglomeration. The Review of Economics and Statistics, 85(2), 377–393.

    Google Scholar 

  • Sanz-Menendez, L., & Cruz-Castro, L. (2005). Explaining the science and technology policies of regional governments. Regional Studies, 39(7), 939–954.

    Article  Google Scholar 

  • Saxenian, A. (1994). Regional advantage: Culture and competition in silicon valley and route 128. Cambridge, MA: Harvard University Press.

  • Scott, A. J. (1988a). Metropolis: From divisions of labor to urban form. Berkeley: University of California Press.

    Google Scholar 

  • Scott, A. (1988b). New industrial spaces: Flexible production organization and regional development in North America and Western Europe. London: Pion.

    Google Scholar 

  • Scott, A. J. (2000). Economic geography: The great half-century. Cambridge Journal of Economics, 24(4), 483–504.

    Google Scholar 

  • Smith, D. F., & Florida, R. (1994). Agglomeration and industrial location: An econometric analysis of Japanese-affiliated manufacturing establishments in automotive-related industries. Journal of Urban Economies, 36(1), 23–41.

    Article  Google Scholar 

  • Sorenson, O., & Singh, J. (2007). Science, social networks and spillovers. Industry and Innovation, 14(2), 219–238.

    Article  Google Scholar 

  • Storper, M. (1993). Regional worlds of production: Learning and innovation in the technology districts of France, Italy and the USA. Regional Studies, 27(5), 433–455.

    Article  Google Scholar 

  • Stoper, M. (1997). The regional world: Territorial development in a global economy. New York: The Guilford Press.

    Google Scholar 

  • Streit, M. E. (1969). Spatial association and economic linkages between industries. Journal of Regional Science, 9(2), 177–188.

    Article  Google Scholar 

  • Takeda, Y., Kakjikawa, Y., Sakata, I., & Matsushima, K. (2008). An analysis of geographical agglomeration and modularized industrial networks in a regional cluster: A case study at Yamagata Prefecture in Japan. Technovation, 28(8), 531–539.

    Article  Google Scholar 

  • Venables, A. (1996a). Equilibrium locations of vertically linked industries. International Economic Review, 37(2), 341–359.

    Article  Google Scholar 

  • Venables, A. (1996b). Localization of industry and trade performance. Oxford Economic Policy Review, 12(3), 52–60.

    Article  Google Scholar 

  • vom Hofe, R., & Chen, K. (2006). Whither or not industrial cluster: Conclusions or confusions? The Industrial Geographer, 4(1), 2–28.

    Google Scholar 

  • Yamawaki, H. (2002). The evolution and structure of industrial clusters in Japan. Small Business Economics, 18(1), 121–140.

    Article  Google Scholar 

  • Young, S., Hood, N., & Peters, E. (1994). Multinational enterprises and regional economic development. Regional Studies, 28(7), 657–677.

    Google Scholar 

  • Zhou, K. Z., Li, J. J., Zhou, N., & Su, C. (2008). Market orientation, job satisfaction, product quality, and firm performance: Evidence from China. Strategic Management Journal, 29(9), 985–1000.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Waseda University, Tokyo, Japan

    Kazuo Kadokawa

Authors
  1. Kazuo Kadokawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kazuo Kadokawa.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kadokawa, K. A search for an industrial cluster in Japanese manufacturing sector: evidence from a location survey. GeoJournal 78, 85–101 (2013). https://doi.org/10.1007/s10708-011-9433-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10708-011-9433-7

Keywords

Search

Navigation