IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v61y2018icp16-28.html
   My bibliography  Save this article

Performance evaluation of R&D active firms

Author

Listed:
  • Khoshnevis, Pegah
  • Teirlinck, Peter

Abstract

This study focuses on the allocation of R&D resources in R&D active firms. We utilize the input oriented constant (CRS) and variable (VRS) returns to scale data efficiency analysis models to evaluate the efficiency of firms. Scale efficiency and the respective types of returns to scale have been examined by using DEA models with ratio inputs and outputs. We pay attention to the global frontier and the firm's own sector and size frontiers. We highlight the sources of inefficiency and suggestions are proposed to improve efficiencies of R&D resources allocation. The analysis is based on a representative set of (quasi-) permanent R&D active firms in Belgium. We consider R&D related inputs in the year 2009 and include firm performance in terms of turnover and net added value per employee in a four year time span. The paper highlights that on average, R&D active firms suffer from both technical inefficiency and scale size problems since the average of the CRS and the VRS efficiency are low, and also the average of scale efficiency is modest. According to firm size, small-sized firms suffer from scale and technical inefficiency. Medium-sized firms endure scale inefficiency rather than technical inefficiency. Large firms present a higher average scale efficiency and technical efficiency. According to sector of activity, firms in specialized supplier industries tend to outperform other firms in terms of average scale efficiency and average technical efficiency. Firms in science based industries are found to underperform on average in terms of VRS and scale efficiency.

Suggested Citation

  • Khoshnevis, Pegah & Teirlinck, Peter, 2018. "Performance evaluation of R&D active firms," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 16-28.
    • Handle: RePEc:eee:soceps:v:61:y:2018:i:c:p:16-28
    DOI: 10.1016/j.seps.2017.01.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012116300131
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2017.01.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    2. Dominique Guellec & Bruno Van Pottelsberghe de la Potterie, 2004. "From R&D to Productivity Growth: Do the Institutional Settings and the Source of Funds of R&D Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 353-378, July.
    3. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    4. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    5. Feller, Irwin, 1990. "Universities as engines of R&D-based economic growth: They think they can," Research Policy, Elsevier, vol. 19(4), pages 335-348, August.
    6. David J. TEECE, 2008. "Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy," World Scientific Book Chapters, in: The Transfer And Licensing Of Know-How And Intellectual Property Understanding the Multinational Enterprise in the Modern World, chapter 5, pages 67-87, World Scientific Publishing Co. Pte. Ltd..
    7. Cherchye, L. & Abeele, P. Vanden, 2005. "On research efficiency: A micro-analysis of Dutch university research in Economics and Business Management," Research Policy, Elsevier, vol. 34(4), pages 495-516, May.
    8. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2013. "Dealing with the Endogeneity Problem in Data Envelopment Analysis," MPRA Paper 47475, University Library of Munich, Germany.
    9. B. Hollingsworth & P. Smith, 2003. "Use of ratios in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 10(11), pages 733-735.
    10. Valentina Meliciani, 2000. "The relationship between R&D, investment and patents: a panel data analysis," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1429-1437.
    11. Nooteboom, Bart & Van Haverbeke, Wim & Duysters, Geert & Gilsing, Victor & van den Oord, Ad, 2007. "Optimal cognitive distance and absorptive capacity," Research Policy, Elsevier, vol. 36(7), pages 1016-1034, September.
    12. Timmer, Marcel P., 2003. "Technological development and rates of return to investment in a catching-up economy: the case of South Korea," Structural Change and Economic Dynamics, Elsevier, vol. 14(4), pages 405-425, December.
    13. repec:adr:anecst:y:1998:i:49-50:p:05 is not listed on IDEAS
    14. Francesco Bogliacino & Mario Pianta, 2016. "The Pavitt Taxonomy, revisited: patterns of innovation in manufacturing and services," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(2), pages 153-180, August.
    15. Zvi Griliches, 1998. "Productivity, R&D, and Basic Research at the Firm Level in the 1970s," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 82-99, National Bureau of Economic Research, Inc.
    16. Mansfield, Edwin, 1980. "Basic Research and Productivity Increase in Manufacturing," American Economic Review, American Economic Association, vol. 70(5), pages 863-873, December.
    17. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    18. Hatami-Marbini, Adel & Emrouznejad, Ali & Tavana, Madjid, 2011. "A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making," European Journal of Operational Research, Elsevier, vol. 214(3), pages 457-472, November.
    19. Alfred Kleinknecht & Kees Van Montfort & Erik Brouwer, 2002. "The Non-Trivial Choice between Innovation Indicators," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 11(2), pages 109-121.
    20. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    21. Goto, Akira & Suzuki, Kazuyuki, 1989. "R&D Capital, Rate of Return on R&D Investment and Spillover of R&D in Japanese Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 555-564, November.
    22. Riahi-Belkaoui, Ahmed, 1999. "Net Value Added and Earnings Determination," Review of Quantitative Finance and Accounting, Springer, vol. 13(4), pages 393-399, December.
    23. Guan Jiancheng & Wang Junxia, 2004. "Evaluation and interpretation of knowledge production efficiency," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(1), pages 131-155, January.
    24. Korhonen, Pekka & Tainio, Risto & Wallenius, Jyrki, 2001. "Value efficiency analysis of academic research," European Journal of Operational Research, Elsevier, vol. 130(1), pages 121-132, April.
    25. Spithoven, André & Teirlinck, Peter, 2015. "Internal capabilities, network resources and appropriation mechanisms as determinants of R&D outsourcing," Research Policy, Elsevier, vol. 44(3), pages 711-725.
    26. Wei Meng & Zhenhua Hu & Wenbin Liu, 2006. "Efficiency evaluation of basic research in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 85-101, October.
    27. Zhong, Wei & Yuan, Wei & Li, Susan X. & Huang, Zhimin, 2011. "The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data," Omega, Elsevier, vol. 39(4), pages 447-455, August.
    28. Widiarto, Indra & Emrouznejad, Ali, 2015. "Social and financial efficiency of Islamic microfinance institutions: A Data Envelopment Analysis application," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 1-17.
    29. Alexander Cotte Poveda, 2012. "Violence And Economic Development In Colombian Cities: A Dynamic Panel Data Analysis," Journal of International Development, John Wiley & Sons, Ltd., vol. 24(7), pages 809-827, October.
    30. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
    31. Boris Lokshin & René Belderbos & Martin Carree, 2008. "The Productivity Effects of Internal and External R&D: Evidence from a Dynamic Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(3), pages 399-413, June.
    32. Cohen, Wesley M & Klepper, Steven, 1996. "Firm Size and the Nature of Innovation within Industries: The Case of Process and Product R&D," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 232-243, May.
    33. Joe Zhu & Zhao-Han Shen, 1995. "A discussion of testing DMUs' returns to scale," European Journal of Operational Research, Elsevier, vol. 81(3), pages 590-596, March.
    34. Souitaris, Vangelis, 2002. "Technological trajectories as moderators of firm-level determinants of innovation," Research Policy, Elsevier, vol. 31(6), pages 877-898, August.
    35. Cordero, Rene, 1990. "The measurement of innovation performance in the firm: An overview," Research Policy, Elsevier, vol. 19(2), pages 185-192, April.
    36. James D. Adams & Zvi Griliches, 1998. "Research Productivity in a System of Universities," Annals of Economics and Statistics, GENES, issue 49-50, pages 127-162.
    37. O. Olesen & N. Petersen, 2009. "Target and technical efficiency in DEA: controlling for environmental characteristics," Journal of Productivity Analysis, Springer, vol. 32(1), pages 27-40, August.
    38. Belderbos, Rene & Carree, Martin & Lokshin, Boris, 2004. "Cooperative R&D and firm performance," Research Policy, Elsevier, vol. 33(10), pages 1477-1492, December.
    39. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    40. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    41. Zhu, Joe, 2000. "Multi-factor performance measure model with an application to Fortune 500 companies," European Journal of Operational Research, Elsevier, vol. 123(1), pages 105-124, May.
    42. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    43. W. Cooper & Shanling Li & L. Seiford & Kaoru Tone & R. Thrall & J. Zhu, 2001. "Sensitivity and Stability Analysis in DEA: Some Recent Developments," Journal of Productivity Analysis, Springer, vol. 15(3), pages 217-246, May.
    44. Jacques Mairesse & Pierre Mohnen, 2001. "To Be or Not To Be Innovative: An Exercise in Measurement," NBER Working Papers 8644, National Bureau of Economic Research, Inc.
    45. Scherer, F. M., 1983. "The propensity to patent," International Journal of Industrial Organization, Elsevier, vol. 1(1), pages 107-128, March.
    46. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    47. Olesen, O. B. & Petersen, N. C., 1995. "Incorporating quality into data envelopment analysis: a stochastic dominance approach," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 117-135, April.
    48. Hung, Shiu-Wan & Wang, An-Pang, 2012. "Entrepreneurs with glamour? DEA performance characterization of high-tech and older-established industries," Economic Modelling, Elsevier, vol. 29(4), pages 1146-1153.
    49. Olesen, Ole Bent & Petersen, Niels Christian & Podinovski, Victor V., 2015. "Efficiency analysis with ratio measures," European Journal of Operational Research, Elsevier, vol. 245(2), pages 446-462.
    50. C S Sarrico & R G Dyson, 2000. "Using DEA for planning in UK universities—an institutional perspective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(7), pages 789-800, July.
    51. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    52. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    53. Zhang, Anming & Zhang, Yimin & Zhao, Ronald, 2003. "A study of the R&D efficiency and productivity of Chinese firms," Journal of Comparative Economics, Elsevier, vol. 31(3), pages 444-464, September.
    54. 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.
    55. Lee, Hakyeon & Park, Yongtae & Choi, Hoogon, 2009. "Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach," European Journal of Operational Research, Elsevier, vol. 196(3), pages 847-855, August.
    56. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    57. Belderbos, Rene & Carree, Martin & Lokshin, Boris, 2004. "Cooperative R&D and firm performance," Research Policy, Elsevier, vol. 33(10), pages 1477-1492, December.
    58. Mansfield, Edwin, 1988. "Industrial R&D in Japan and the United States: A Comparative Study," American Economic Review, American Economic Association, vol. 78(2), pages 223-228, May.
    59. Balaji S. Chakravarthy, 1986. "Measuring strategic performance," Strategic Management Journal, Wiley Blackwell, vol. 7(5), pages 437-458, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohd Chachuli, Fairuz Suzana & Mat, Sohif & Ludin, Norasikin Ahmad & Sopian, Kamaruzzaman, 2021. "Performance evaluation of renewable energy R&D activities in Malaysia," Renewable Energy, Elsevier, vol. 163(C), pages 544-560.
    2. 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).
    3. Geetha, Selvaraj & Jeon, JeongHwan, 2023. "Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    4. Jian Xu & Jae-Woo Sim, 2018. "Characteristics of Corporate R&D Investment in Emerging Markets: Evidence from Manufacturing Industry in China and South Korea," Sustainability, MDPI, vol. 10(9), pages 1-18, August.
    5. Carlos Alano Soares de Almeida & Jansen Maia Del Corso & Leonardo Andrade Rocha & Wesley Vieira da Silva & Claudimar Pereira da Veiga, 2019. "Innovation and Performance: The Impact of Investments in R&D According to the Different Levels of Productivity of Firms," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1-21, August.
    6. Zhou, Xiaoyang & Chen, Hao & Chai, Jian & Wang, Shouyang & Lev, Benjamin, 2020. "Performance evaluation and prediction of the integrated circuit industry in China: A hybrid method," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    7. Tong Zhao & Zhijie Song & Tianjiao Li, 2018. "Effect of innovation capacity, production capacity and vertical specialization on innovation performance in China's electronic manufacturing: Analysis from the supply and demand sides," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    8. Mehdi Toloo & Soroosh Nalchigar & Babak Sohrabi, 2018. "Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1027-1051, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    2. 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).
    3. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    4. Yang, Guoliang & Ahlgren, Per & Yang, Liying & Rousseau, Ronald & Ding, Jielan, 2016. "Using multi-level frontiers in DEA models to grade countries/territories," Journal of Informetrics, Elsevier, vol. 10(1), pages 238-253.
    5. Lee, Hakyeon & Shin, Juneseuk, 2014. "Measuring journal performance for multidisciplinary research: An efficiency perspective," Journal of Informetrics, Elsevier, vol. 8(1), pages 77-88.
    6. Peilei Fan, 2011. "Innovation capacity and economic development: China and India," Economic Change and Restructuring, Springer, vol. 44(1), pages 49-73, April.
    7. Zhang, Daqun & Banker, Rajiv D. & Li, Xiaoxuan & Liu, Wenbin, 2011. "Performance impact of research policy at the Chinese Academy of Sciences," Research Policy, Elsevier, vol. 40(6), pages 875-885, July.
    8. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    9. Congcong Yang & Alfred Taudes & Guozhi Dong, 2017. "Efficiency analysis of European Freight Villages: three peers for benchmarking," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 91-122, March.
    10. Aristovnik, Aleksander, 2014. "Efficiency of the R&D Sector in the EU-27 at the Regional Level: An Application of DEA," MPRA Paper 59081, University Library of Munich, Germany.
    11. Chen, Ping-Chuan & Hung, Shiu-Wan, 2016. "An actor-network perspective on evaluating the R&D linking efficiency of innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 303-312.
    12. Lu, Wen-Min & Liu, John S. & Kweh, Qian Long & Wang, Chung-Wei, 2016. "Exploring the benchmarks of the Taiwanese investment trust corporations: Management and investment efficiency perspectives," European Journal of Operational Research, Elsevier, vol. 248(2), pages 607-618.
    13. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    14. Wang, Eric C., 2007. "R&D efficiency and economic performance: A cross-country analysis using the stochastic frontier approach," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 345-360.
    15. Vladimír Holý & Karel Šafr, 2018. "Are economically advanced countries more efficient in basic and applied research?," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 933-950, December.
    16. Hahn, G.J. & Brandenburg, M. & Becker, J., 2021. "Valuing supply chain performance within and across manufacturing industries: A DEA-based approach," International Journal of Production Economics, Elsevier, vol. 240(C).
    17. Sahoo, Biresh K. & Singh, Ramadhar & Mishra, Bineet & Sankaran, Krithiga, 2017. "Research productivity in management schools of India during 1968-2015: A directional benefit-of-doubt model analysis," Omega, Elsevier, vol. 66(PA), pages 118-139.
    18. Ole Bent Olesen & Niels Christian Petersen & Victor V. Podinovski, 2022. "Scale characteristics of variable returns-to-scale production technologies with ratio inputs and outputs," Annals of Operations Research, Springer, vol. 318(1), pages 383-423, November.
    19. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    20. Liu, W.B. & Zhang, D.Q. & Meng, W. & Li, X.X. & Xu, F., 2011. "A study of DEA models without explicit inputs," Omega, Elsevier, vol. 39(5), pages 472-480, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:61:y:2018:i:c:p:16-28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.