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Relating the perspectives of the balanced scorecard for R&D by means of DEA

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  • García-Valderrama, Teresa
  • Mulero-Mendigorri, Eva
  • Revuelta-Bordoy, Daniel

Abstract

The objective of this article is to propose a framework for analysis of the relationships between the four perspectives of the balanced scorecard (BSC) of Kaplan and Norton. To this end, several different models of efficiency have been developed, utilising data envelopment analysis (DEA). Each of the variables has been extracted from a model of the BSC for research and development (R&D) activities. A study has been carried out with 90 companies to illustrate a case of this analysis.

Suggested Citation

  • García-Valderrama, Teresa & Mulero-Mendigorri, Eva & Revuelta-Bordoy, Daniel, 2009. "Relating the perspectives of the balanced scorecard for R&D by means of DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1177-1189, August.
    • Handle: RePEc:eee:ejores:v:196:y:2009:i:3:p:1177-1189
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    3. Bošković, Aleksandra & Krstić, Ana, 2018. "Combined Use of BSC and DEA Methods for Measuring Organizational Efficiency," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018, pages 82-88, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    4. M. Hurol Mete & Onder Belgin, 2022. "Impact of Knowledge Management Performance on the Efficiency of R&D Active Firms: Evidence from Turkey," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(2), pages 830-848, June.
    5. Chi, Shu-Yi & Chien, Li-Hsien, 2023. "Why defuzzification matters: An empirical study of fresh fruit supply chain management," European Journal of Operational Research, Elsevier, vol. 311(2), pages 648-659.
    6. Liu, Hui-hui & Yang, Guo-liang & Liu, Xiao-xiao & Song, Yao-yao, 2020. "R&D performance assessment of industrial enterprises in China: A two-stage DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    7. Basso, Antonella & Casarin, Francesco & Funari, Stefania, 2018. "How well is the museum performing? A joint use of DEA and BSC to measure the performance of museums," Omega, Elsevier, vol. 81(C), pages 67-84.
    8. Ozer, Muammer, 2011. "Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions," European Journal of Operational Research, Elsevier, vol. 211(2), pages 359-369, June.
    9. Santos, Sérgio P. & Belton, Valerie & Howick, Susan & Pilkington, Martin, 2018. "Measuring organisational performance using a mix of OR methods," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 18-30.
    10. Zervopoulos, Panagiotis D. & Brisimi, Theodora S. & Emrouznejad, Ali & Cheng, Gang, 2016. "Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US," European Journal of Operational Research, Elsevier, vol. 250(1), pages 262-272.
    11. Amado, Carla A.F. & Santos, Sérgio P. & Marques, Pedro M., 2012. "Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment," Omega, Elsevier, vol. 40(3), pages 390-403.
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    14. Youchao Tan & Yang Zhang & Roohollah Khodaverdi, 2017. "Service performance evaluation using data envelopment analysis and balance scorecard approach: an application to automotive industry," Annals of Operations Research, Springer, vol. 248(1), pages 449-470, January.

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