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Competitive advantage in an industry cluster: The case of Dalian Software Park in China

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  • Zhao, Weilin
  • Watanabe, Chihiro
  • Griffy-Brown, Charla

Abstract

This paper explores the competitive advantage of Chinese software parks for promoting industrial development. These industry clusters provide competitive advantage because they are rooted in local institutional systems. Taking the case of Dalian Software Park in China, this analysis is conducted qualitatively based on Porter's “diamond” model, SWOT framework and interview results. Industry clusters, which encompass a series of interconnected firms in designated geographic concentrations, show competitive advantages for industrial development with substantial resources rooted in local institutional systems including government, industry and academia aspects. In order to successfully navigate the economic paradigm shift from mass manufacturing production to innovative new product development in China, it is essential that the competitive advantages of industry clusters are strengthened and sustained in order to enhance industrial development, generate innovation and increase regional economic growth.

Suggested Citation

  • Zhao, Weilin & Watanabe, Chihiro & Griffy-Brown, Charla, 2009. "Competitive advantage in an industry cluster: The case of Dalian Software Park in China," Technology in Society, Elsevier, vol. 31(2), pages 139-149.
    • Handle: RePEc:eee:teinso:v:31:y:2009:i:2:p:139-149
    DOI: 10.1016/j.techsoc.2009.03.008
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    1. Hu, Albert Guangzhou, 2007. "Technology parks and regional economic growth in China," Research Policy, Elsevier, vol. 36(1), pages 76-87, February.
    2. Peter B. Doeringer & David G. Terkla, 1995. "Business Strategy and Cross-Industry Clusters," Economic Development Quarterly, , vol. 9(3), pages 225-237, August.
    3. North, Douglass C, 1994. "Economic Performance through Time," American Economic Review, American Economic Association, vol. 84(3), pages 359-368, June.
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    Cited by:

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    2. Natenapang Thongsri & Alex Kung-Hsiung Chang, 2019. "Interactions Among Factors Influencing Product Innovation and Innovation Behaviour: Market Orientation, Managerial Ties, and Government Support," Sustainability, MDPI, vol. 11(10), pages 1-21, May.
    3. Bratanova, Alexandra & Pham, Hien & Mason, Claire & Hajkowicz, Stefan & Naughtin, Claire & Schleiger, Emma & Sanderson, Conrad & Chen, Caron & Karimi, Sarvnaz, 2022. "Differentiating artificial intelligence activity clusters in Australia," Technology in Society, Elsevier, vol. 71(C).
    4. Chan-Yuan Wong & Xiao-Shan Yap, 2012. "Mapping technological innovations through patent analysis: a case study of foreign multinationals and indigenous firms in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 773-787, June.
    5. E. E. Kolchinskaya & L. E. Limonov & E. S. Stepanova, 2022. "Does Working in a Cluster Provide Higher Productivity to Industrial Enterprises in Russia?," Regional Research of Russia, Springer, vol. 12(2), pages 204-214, June.
    6. Watanabe, Chihiro & Naveed, Kashif & Zhao, Weilin, 2015. "New paradigm of ICT productivity – Increasing role of un-captured GDP and growing anger of consumers," Technology in Society, Elsevier, vol. 41(C), pages 21-44.
    7. Vanzetti, Nicolás & Corsano, Gabriela & Montagna, Jorge M., 2017. "A comparison between individual factories and industrial clusters location in the forest supply chain," Forest Policy and Economics, Elsevier, vol. 83(C), pages 88-98.
    8. Chan-Yuan Wong & Kim-Leng Goh, 2012. "The pathway of development: science and technology of NIEs and selected Asian emerging economies," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 523-548, September.

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