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An integrated cost-performance model of research and development evaluation

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  • Geisler, E.

Abstract

This paper proposes an integrated model of R & D evaluation which links the cost of research with its various outputs, from proximal or immediate to the intermediate outputs in the client organizations of the R & D performer. This model differs from previous models in that it consolidates both cost and performance assessment. Indexes of cost-performance are constructed, for each category of output, and as a measure of productivity per scientist and engineer engaged in research. The indexes proposed in this model reflect the relative cost-effectiveness of the R & D activity throughout a substantial portion of the innovation process. As a comprehensive and integrated model, it transcends the limitations of immediate outputs utilized by other models. The model allows for comparisons, at the program, corporate and national levels, of the cost-performance of research. Some methodological and implementation problems are discussed.

Suggested Citation

  • Geisler, E., 1995. "An integrated cost-performance model of research and development evaluation," Omega, Elsevier, vol. 23(3), pages 281-294, June.
  • Handle: RePEc:eee:jomega:v:23:y:1995:i:3:p:281-294
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    Cited by:

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    2. Mary M. Crossan & Marina Apaydin, 2010. "A Multi‐Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature," Journal of Management Studies, Wiley Blackwell, vol. 47(6), pages 1154-1191, September.
    3. Gallego, Jorge & Rubalcaba, Luis & Suárez, Cristina, 2013. "Knowledge for innovation in Europe: The role of external knowledge on firms' cooperation strategies," Journal of Business Research, Elsevier, vol. 66(10), pages 2034-2041.
    4. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    5. Zhang, Gupeng & Zhou, Jianghua, 2016. "The effects of forward and reverse engineering on firm innovation performance in the stages of technology catch-up: An empirical study of China," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 212-222.
    6. Chou, Ying-Chyi & Hsu, Ying-Ying & Yen, Hsin-Yi, 2008. "Human resources for science and technology: Analyzing competitiveness using the analytic hierarchy process," Technology in Society, Elsevier, vol. 30(2), pages 141-153.
    7. Guan, Jiancheng & Chen, Kaihua, 2012. "Modeling the relative efficiency of national innovation systems," Research Policy, Elsevier, vol. 41(1), pages 102-115.
    8. Chiang-Ping Chen & Jin-Li Hu & Chih-Hai Yang, 2013. "Produce patents or journal articles? A cross-country comparison of R&D productivity change," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 833-849, March.
    9. Dziallas, Marisa & Blind, Knut, 2019. "Innovation indicators throughout the innovation process: An extensive literature analysis," Technovation, Elsevier, vol. 80, pages 3-29.
    10. Jiancheng Guan & Kairui Zuo, 2014. "A cross-country comparison of innovation efficiency," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 541-575, August.
    11. Peretz, Jean H. & Das, Sujit & Tonn, Bruce E., 2009. "Evaluating knowledge benefits of automotive lightweighting materials R&D projects," Evaluation and Program Planning, Elsevier, vol. 32(3), pages 300-309, August.
    12. Hashimoto, Akihiro & Haneda, Shoko, 2008. "Measuring the change in R&D efficiency of the Japanese pharmaceutical industry," Research Policy, Elsevier, vol. 37(10), pages 1829-1836, December.

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