Abstract

Performance evaluation is an important measure of the total quality management, which can be used to assess the performance of an individual or an organization with respect to set goals and targets. The metrics/parameters used for evaluating the performance and the way in which these are measured by using appropriate tools and techniques play a major role in the evaluation process. Performance evaluation is even more challenging in the case of R and D organizations, where the outcome/output may not be tangible/measurable and varies from one organization to another, depending on the nature, vision, charter and character. A methodology is proposed to arrive at a framework that can help in objectively assessing or evaluating the performance of each of the laboratories of CSIR (Council of Scientific and Industrial Research) based on four knowledge portfolios which are appropriately given weightages according to the impact they have on the four goods viz-Public, Private, Social and Strategic Appropriate parameters have been identified which can help in objectively evaluating the performance of the laboratory. The proposed analytical framework will facilitate quantification of performance of an R and D organization to enable resource allocation in a rational manner.

Keywords:

Knowledge portfolios, mapping strategies, performance evaluation, R and D organizations,

References

1. Baek, Y., 2006. Publishing productivity of US academic scientists and engineers: An empirical examination through date envelopment analysis. Draft Report, Georgia Institute of Technology.
   
2. Baglieri, E., V. Chiesa, A. Grando and R. Manzini, 2001. Evaluating Intangible Assets: The Measurement of R and D Performance. Research Division Working Paper No. 01/49.
   Direct Link
3. Bowon, K. and O. Heungshik, 2002. An effective R and D performance measurement system: Survey of Korean R & D researchers. Omega, 30: 19-31.
   CrossRef    
4. Brown, W.B. and D. Gobeli, 1992. Observations on the measurement of R & D productivity: A case study. IEEE T. Eng. Manage., 39(4): 325-331.
   CrossRef    
5. Cebeci, U. and B. Sezerel, 2008. Performance evaluation model for R & D department: An integrated balanced scorecard and analytical hierarchy process approach. Proceeding of the 3rd International Conference on Intelligent System and Knowledge Engineering, pp: 11276-128.
   CrossRef    
6. Chiesa, V., F. Frattini, V. Lazzarotti, R. Manzini and I. Troja, 2008. An Exploratory Study on R & D Performance Measurement Practices: A Survey on Italian R & D-Intensive Firms. Liuc Papers No. 218, SeieTechnologia 14, Iuglio.
   
7. CSIR Report, 2005. Reinventing the CSIR: A road map for implementation. A Restricted Internal Report.
   
8. Deen, J. and H. Vossensteyn, 2006. Measuring performance of applied R&D: A study into performance measurement of applied R & D in the Netherlands and some other countries. Report for the Center for Science and Technology Studies (CEST).
   
9. Ghameri, M.S., M. Hashemi and M. Aghaei, 2012. Intangible assets reporting. Aust. J. Bus. Manage. Res., 1(11): 70-73.
   
10. Gold, B., 1989. Some key problems in evaluating R & D performance. J. Eng. Technol. Manage., 6: 59-70.
    CrossRef    
11. Jang, Y. and N.S. Vonortas, 2002. Performance measurement for government R & D programs: In search of best practice. Final Report to the Korea Institute of S&T Evaluation and Planning Seoul, Republic of Korea. Center for International Science and Technology Policy, the George Washington University.
    
12. Kelkar, V., 2004. Reinventing the CSIR. Report of the Committee to Assess and Evaluate the Outcomes of CSIR Activities [A restricted internal report], New Delhi, July 19, 2004.
    
13. Martin, R., M.H. Hector and C.D. Douglas, 2009. Measuring scientists performance: A view from organismal biologists. Interciencia, 34(1): 830-835.
    
14. Nishimura, J. and H. Okamuro, 2010. R & D Productivity and the Organization of Cluster Policy: An Empirical Evaluation of the Industrial Cluster Project in Japan. DRUID Working Paper No. 10-06, Danish Research Unit for Industrial Dynamics (DRUID).
    
15. Ojanen, V. and M. Tuominen, 2002. An analytic approach to measuring the overall effectiveness of R&D: A case study in the telecom sector. Proceedings of the International Engineering Management Conference (IEMC). Cambridge, U.K., 2: 667-672.
    CrossRef    
16. Ojanen, V. and O. Vuola, 2003. Categorizing the Measures and Evaluation Methods of R & D Performance: A State-of-the-art Review on R & D Performance Analysis. Lappeenranta University of Technology, Lappeenranta.
    
17. Ojanen, V. and O. Vuola, 2006. Coping with the multiple dimensions of R & D performance analysis. Int. J. Technol. Manage., 33(2): 279-290.
    CrossRef    
18. Vijayalakshmi, S. and R. Iyer Nagesh, 2011. Mapping strategies and performance evaluation of research organizations. Proceeding of the 5th International Conference on Communications and Information Technology (CIT'11). Corfu Island, Greece, July 14-17, pp: 50-53.
    
19. Werner, B.M. and W.E. Souder, 1997. Measuring R & D performance-U.S. and German practices. Res. Technol. Manage., 40(3): 28-32.
    

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The authors have no competing interests.

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