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Evaluating performance of public–private research collaborations: A DEA analysis

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  • E Revilla

    (Instituto de Empresa, María de Molina)

  • J Sarkis

    (Graduate School of Management, Clark University)

  • A Modrego

    (Universiad Carlos III)

Abstract

The issue of intellectual capital and its measurement is investigated in this paper. We provide an overview of how a data envelopment analysis (DEA) approach was used to investigate some characteristics of performance for joint intersectoral research and development collaboration projects, with a specific emphasis of use of intellectual property (ie, patents) as one of the outcomes of these collaborations. Some knowledge-based factors are investigated in this paper to determine if there is a relationship between these factors and research partnership performance. Of particular focus in this paper, and focusing on the special issue topic, is whether knowledge management and knowledge goals play a role in whether these collaborations perform better or worse. The study is based on empirical data from a programme of technological policy existing in Spain, known as the Concerted Projects.

Suggested Citation

  • E Revilla & J Sarkis & A Modrego, 2003. "Evaluating performance of public–private research collaborations: A DEA analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(2), pages 165-174, February.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:2:d:10.1057_palgrave.jors.2601524
    DOI: 10.1057/palgrave.jors.2601524
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    2. Yaliu Yang & Yuan Wang & Cui Wang & Yingyan Zhang & Cuixia Zhang, 2022. "Temporal and Spatial Evolution of the Science and Technology Innovative Efficiency of Regional Industrial Enterprises: A Data-Driven Perspective," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    3. Kou, Mingting & Yang, Yuanqi & Chen, Kaihua, 2020. "The impact of external R&D financing on innovation process from a supply-demand perspective," Economic Modelling, Elsevier, vol. 92(C), pages 375-387.
    4. Lin, Shoufu & Lin, Ruoyun & Sun, Ji & Wang, Fei & Wu, Weixiang, 2021. "Dynamically evaluating technological innovation efficiency of high-tech industry in China: Provincial, regional and industrial perspective," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
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    6. Sabahi, Sima & Parast, Mahour Mellat, 2020. "The impact of entrepreneurship orientation on project performance: A machine learning approach," International Journal of Production Economics, Elsevier, vol. 226(C).
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