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The effect of clusters on the innovation performance of enterprises: traditional vs new industries

Author

Listed:
  • Miroslav Žižka

    () (Technical University of Liberec, Czech Republic)

  • Vladimíra Hovorková Valentová

    () (Technical University of Liberec, Czech Republic)

  • Natalie Pelloneová

    () (Technical University of Liberec, Czech Republic)

  • Eva Štichhauerová

    () (Technical University of Liberec, Czech Republic)

Abstract

The present paper assesses the effect of the formation of cluster organisations on the innovation performance of member enterprises in two different industries – the traditional textile manufacturing industry and the new nanotechnology industry. Innovation performance is explored using Data Envelopment Analysis in two phases. In the first phase, it examines the ability of enterprises to transform resources (labour force, long-term capital, intellectual capital) into registered industrial property rights: patents, utility models, industrial designs, and trademarks. In the second phase, it assesses the ability of enterprises to commercialise industrial property rights and generate profits. Innovation performance then integrates both phases. In each industry, two samples were assessed: member enterprises of cluster organisations, and enterprises that operate in the same industry and region but are not members of a cluster organisation. The results of the research show that the existence of a cluster organisation has a greater effect on innovation performance in the traditional textile manufacturing industry. In contrast, in the new nanotechnology industry, the existence of a cluster organisation did not prove to have any significant effect on innovation effectiveness. In this industry, the existence of a cluster organisation had only a partial effect related to better industrial property rights commercialisation. Research shows that the type of industry is an important factor in the innovation performance of clustered enterprises.

Suggested Citation

  • Miroslav Žižka & Vladimíra Hovorková Valentová & Natalie Pelloneová & Eva Štichhauerová, 2018. "The effect of clusters on the innovation performance of enterprises: traditional vs new industries," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 5(4), pages 780-794, June.
  • Handle: RePEc:ssi:jouesi:v:5:y:2018:i:4:p:780-794
    DOI: 10.9770/jesi.2018.5.4(6)
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    References listed on IDEAS

    as
    1. Joe Zhu, 2014. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, edition 3, number 978-3-319-06647-9, March.
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    Cited by:

    1. O. Karasev & A. Beloshitsky & S. Trostyansky & A. Krivtsova & V.N. Valerievna, 2018. "Development of National Innovation Systems in Developed Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 701-712.
    2. Michal Pohludka & Hana Stverkova & Beata Ślusarczyk, 2018. "Implementation and Unification of the ERP System in a Global Company as a Strategic Decision for Sustainable Entrepreneurship," Sustainability, MDPI, Open Access Journal, vol. 10(8), pages 1-16, August.
    3. Xiu SHI & Rui JING & Guang-ming HOU & Jun-peng WANG, 2019. "Network Position Advantage and Technological Innovation of China’s New Energy Vehicle Based on the Perspective of Network Theory," Sustainability, MDPI, Open Access Journal, vol. 11(7), pages 1-18, April.
    4. Piotr Trąpczyński & Łukasz Puślecki & Michał Staszków, 2018. "Determinants of Innovation Cooperation Performance: What Do We Know and What Should We Know?," Sustainability, MDPI, Open Access Journal, vol. 10(12), pages 1-32, November.

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    More about this item

    Keywords

    cluster organisation; industry cluster; textile cluster; nanotechnological cluster; innovation performance; innovation effectiveness; innovation efficiency; data envelopment analysis;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L67 - Industrial Organization - - Industry Studies: Manufacturing - - - Other Consumer Nondurables: Clothing, Textiles, Shoes, and Leather Goods; Household Goods; Sports Equipment
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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