Journal of Science & Technology Policy | Volume 1Issue 2 | Publish date : Saturday, July 25, 2009
Virtual Benchmarking for R&D Projects

Benchmarking is a tool for monitoring performance and searching for the best practice through learning from others. This paper introduces a new model, namely the Virtual Benchmarking Model (VBM), for benchmarking the R&D projects. This model uses the Data Envelopment Analysis (DEA) technique and identifies output indicators based on R&D steps and addresses the problem of monhomogeneous outputs. The proposed model was examined empirically using input-output indicators captured from 30 electronics R&D projects in IROST. Results indicate that efficiency and effectiveness criteria should be used jointly for identifying the best practices. Based on the VBM model, 17 % of R&D projects were distinguished as providing benchmarks for other projects. The main characteristics of these projects were 1) effective human resource planning and; 2) marketing the results of R&D projects. Use of the virtual benchmarking process can lead to enhance mont 08 the performance of R&D projects.

Electronics Projects
Research and Developement(R&D)
Data Envelopment Analysis(DEA)

farhad Abbasi

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Article ID: 535060
Publish Date: Saturday, July 25, 2009
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    1. اخوان، پيمان، الگوبرداري، ماهنامه تدبير، شماره 143، فروردين 1383
    2. عباسي، فرهاد، تخمين كارايي و بهره‌وري صنايع، نشريه نوآوران، سازمان پژوهشهاي علمي وصنعتي ايران، شماره 111، آبان ماه 1379
    3. ساموئل کي. هو، 1995، مديريت کيفيت جامع (TQM)، مترجم حسين حسين زاده، نشر دانشکار، چاپ اول، ص187، بهمن 1379
    4. Congress of the United States, “R&D and Productivity Growth: A Background Paper”, The Congress of the United States, Congressional Budget Office, June 2005
    5. Ettlie, John E., “Innovation and R&D - Industrial Research Institute survey on R&D”, Gardner Publications, Inc. 1997
    6. كيمياگري، علي محمد، راهنماي كاربردي روش بهبود تطبيقي (بنچ ماركينگ)، مركز نشر دانشگاه صنعتي اميركبير (پلي تكنيك تهران) سال انتشار 1378 : چاپ اول.
    8. APQC (1993a),”The Benchmarking Management Guide”, American Productivity and Quality Center, Cambridge, MA: Productivity Press, 1993.
    9. APQC, “Measuring Research and Development (R&D) Productivity: An APQC consortium benchmarking study”, JUNE 3, 2004
    10. Tidd J., Bessant J. & Pavitt K., “Managing innovation: integrating technological, market and organizational change”, 3rd Edition. John Wiley & Sons, Ltd. 582 p, 2005
    11. APQC (1993b), “Basics of Benchmarking”, American Productivity and Quality Center, Houston, 1993
    12. Andersen, Björn & Pettersen, Per-Gaute, “The Benchmarking Handbook. Step-by-step instructions”. London: Chapman & Hall, 1996
    13. عباسي، فرهاد، تعيين بهترين عملكرد تكنولوژيك در پروژه‌هاي تحقيقاتي كاربردي، دومين كنفرانس مديريت تكنولوژي، پژوهشگاه نيرو، ارديبهشت 1384
    14. علي (ع): نهج‌البلاغه، باب گزيده، شماره 73
    15. EIRMA , “Benchmarking in R&D”, Report of EIRMA Working Group 51, 1998 , ttp://
    16. Baglieri E., “R&D Performance measurement: a reference model”, 7th International Forum on Technology Management, Kyoto 1997, Proceedings
    17. Santanu, Roy & NAGPAUL P. S., “A quantitative evaluation of relative efficiencies of Research and Development laboratories: A Data Envelopment Analysis approach”, 8th international conference on scientometrics and informetrics proceedings, Sydney , AUSTRALIE,2001 
    18. Eilat H., Golany B, & Shtub A., “Constructing and Evaluating Balanced Portfolios of R&D Projects with Interactions: A DEA based methodology”, European Journal of Operational Research, 2005
    19. Soner Selin, Önüt Semih & Tuzkaya Umut, “Evaluation and selection of R&D projects using an integrated BSC-DEA methodology”, The 35th International Conference on Computers and Industrial Engineering, , Istanbul, Turkey, June, 2005
    20. Wang, E. C., Huang W. , Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach , Research Policy 36,  pp 260–273, 2007
    21. Tavares, Gabriel, “A BIBLIOGRAPHY OF DATA ENVELOPMENT ANALYSIS (1978-2001)”, Rutgers Center for Operations Research, Rutgers University, JANUARY, 2002
    22. Sun Kai; Ju Xiao-feng; Li Yu-hua , “Performance Evaluation of Chinese Regional Innovation Systems Based on Data Envelopment Analysis”, International Conference on Management Science and Engineering, Page(s):1800 – 1804, Oct. 2006
    23. Korhonen, R. Tainio and J. Wallenius, “Value efficiency analysis of academic research”, European Journal of Operational Research 130, pp. 121–132, 2001
    24. Cherchye and Vanden Abeele, “On research efficiency: a micro-analysis of Dutch university research in economic and business management’, Research Policy 34, pp. 495–516, 2005
    25. Charnes, A., Cooper, W. W. & Rhodes, E., “Measuring the efficiency of decision making units”, European Journal of Operational Research, Vol. 2, pp429-444, 1978
    26. Leibenstein, H., “Allocative Efficiency vs. X-Efficiency”, American Economic Review, June 1966, 56 (3), 392-415, 1966.
    27. Banker, R.D.; Charnes, A. & Cooper, W.W. , “Some models for estimating technical scale inefficiencies in Data Envelopment Analysis”, Management Science, 30(9), 1078-1092, 1984
    28. Coelli, T. J., “A guide to DEAP version 2.1, CEPA”, Working Papers No.8/96, 1996