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A model for R&D performance measurement

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  • Lazzarotti, Valentina
  • Manzini, Raffaella
  • Mari, Luca

Abstract

R&D activities are increasingly costly and risky and, as a consequence, measuring their performance and contribution to value becomes critical. This paper illustrates a formal model for measuring R&D performance, based upon a balanced and synthetic evaluation of quantitative indicators from five different perspectives of performance: financial, customer, innovation and learning, internal business, alliances, and networks. The model is built in coherence with the suggestions coming from the theory of measurement in soft systems, which gives relevant guidelines for ensuring validity, objectivity and inter-subjectivity of the model. Then, an application in a real R&D setting is described, which helps to understand the model and to enlighten its main advantages and limits.

Suggested Citation

  • Lazzarotti, Valentina & Manzini, Raffaella & Mari, Luca, 2011. "A model for R&D performance measurement," International Journal of Production Economics, Elsevier, vol. 134(1), pages 212-223, November.
  • Handle: RePEc:eee:proeco:v:134:y:2011:i:1:p:212-223
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    References listed on IDEAS

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    4. Lo Nigro, Giovanna & Morreale, Azzurra & Enea, Gianluca, 2014. "Open innovation: A real option to restore value to the biopharmaceutical R&D," International Journal of Production Economics, Elsevier, vol. 149(C), pages 183-193.
    5. Svetlana Klessova & Sebastian Engell & Catherine Thomas, 2022. "Assessment of the advancement of market-upstream innovations and of the performance of research and innovation projects," Post-Print hal-03636260, HAL.
    6. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    7. Klessova, Svetlana & Engell, Sebastian & Thomas, Catherine, 2022. "Assessment of the advancement of market-upstream innovations and of the performance of research and innovation projects," Technovation, Elsevier, vol. 116(C).
    8. Piaopeng Song & Yuxiao Gu & Bin Su & Arifa Tanveer & Qiao Peng & Weijun Gao & Shaomin Wu & Shihong Zeng, 2023. "The Impact of Green Technology Research and Development (R&D) Investment on Performance: A Case Study of Listed Energy Companies in Beijing, China," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
    9. Wellington L. L. Rocha & Maria Fatima L. Almeida & Rodrigo F. Calili, 2022. "Measuring and Evaluating Organizational Innovation Capacity and Performance from Systemic and Sustainability-Oriented Perspective," Sustainability, MDPI, vol. 15(1), pages 1-37, December.
    10. Kseniia Boiko, 2022. "R&D activity and firm performance: mapping the field," Management Review Quarterly, Springer, vol. 72(4), pages 1051-1087, December.
    11. João Nuno Morais Lopes & Luís Farinha, 2018. "Measuring the Performance of Innovation and Entrepreneurship Networks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(2), pages 402-423, June.
    12. Behrooz Noori, 2014. "Prioritizing strategic business units in the face of innovation performance: Combining fuzzy AHP and BSC," Proceedings of International Academic Conferences 0802059, International Institute of Social and Economic Sciences.
    13. VAN CAMP, Jelle & BRAET, Johan, 2013. "Proposing a taxonomy for performance measurement systems' failures," Working Papers 2013004, University of Antwerp, Faculty of Business and Economics.
    14. Emad Harash & Suhail Nassir Al-Timimi & Fatima Jasem Alsaad & Abdulkhaliq Y. Zaier Al-Badran & Essia Ries Ahmed, 2014. "Contingency Factors and Performance of Research and Development (R&D): The Moderating Effects of Government Policy," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 4(2), pages 47-58, February.

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