IDEAS home Printed from https://ideas.repec.org/a/eee/epplan/v66y2018icp147-155.html
   My bibliography  Save this article

Evaluating firms’ R&D performance using best worst method

Author

Listed:
  • Salimi, Negin
  • Rezaei, Jafar

Abstract

Since research and development (R&D) is the most critical determinant of the productivity, growth and competitive advantage of firms, measuring R&D performance has become the core of attention of R&D managers, and an extensive body of literature has examined and identified different R&D measurements and determinants of R&D performance. However, measuring R&D performance and assigning the same level of importance to different R&D measures, which is the common approach in existing studies, can oversimplify the R&D measuring process, which may result in misinterpretation of the performance and consequently fallacy R&D strategies. The aim of this study is to measure R&D performance taking into account the different levels of importance of R&D measures, using a multi-criteria decision-making method called Best Worst Method (BWM) to identify the weights (importance) of R&D measures and measure the R&D performance of 50 high-tech SMEs in the Netherlands using the data gathered in a survey among SMEs and from R&D experts. The results show how assigning different weights to different R&D measures (in contrast to simple mean) results in a different ranking of the firms and allow R&D managers to formulate more effective strategies to improve their firm’s R&D performance by applying knowledge regarding the importance of different R&D measures.

Suggested Citation

  • Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    • Handle: RePEc:eee:epplan:v:66:y:2018:i:c:p:147-155
    DOI: 10.1016/j.evalprogplan.2017.10.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0149718917301477
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.evalprogplan.2017.10.002?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. Lazzarotti, Valentina & Manzini, Raffaella & Mari, Luca, 2011. "A model for R&D performance measurement," International Journal of Production Economics, Elsevier, vol. 134(1), pages 212-223, November.
    2. Gupta, Himanshu & Barua, Mukesh Kumar, 2016. "Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 69-79.
    3. Cohen, Wesley M & Klepper, Steven, 1996. "A Reprise of Size and R&D," Economic Journal, Royal Economic Society, vol. 106(437), pages 925-951, July.
    4. Arroyabe, Marta F. & Arranz, Nieves & Fdez. de Arroyabe, Juan Carlos, 2015. "R&D partnerships: An exploratory approach to the role of structural variables in joint project performance," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 623-634.
    5. Leahy, Dermot & Neary, J Peter, 1997. "Public Policy towards R&D in Oligopolistic Industries," American Economic Review, American Economic Association, vol. 87(4), pages 642-662, September.
    6. Negin Salimi & Jafar Rezaei, 2016. "Measuring efficiency of university-industry Ph.D. projects using best worst method," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1911-1938, December.
    7. Aloke Ghosh, 2004. "Increasing Market Share as a Rationale for Corporate Acquisitions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(1-2), pages 209-247.
    8. Negin Salimi, 2017. "Quality assessment of scientific outputs using the BWM," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 195-213, July.
    9. 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.
    10. Patricia Hemert & Peter Nijkamp & Enno Masurel, 2013. "From innovation to commercialization through networks and agglomerations: analysis of sources of innovation, innovation capabilities and performance of Dutch SMEs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 425-452, April.
    11. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    12. Huang, Chi-Cheng & Chu, Pin-Yu & Chiang, Yu-Hsiu, 2008. "A fuzzy AHP application in government-sponsored R&D project selection," Omega, Elsevier, vol. 36(6), pages 1038-1052, December.
    13. Moncada-Paternò-Castello, Pietro & Ciupagea, Constantin & Smith, Keith & Tübke, Alexander & Tubbs, Mike, 2010. "Does Europe perform too little corporate R&D? A comparison of EU and non-EU corporate R&D performance," Research Policy, Elsevier, vol. 39(4), pages 523-536, May.
    14. Dirk Czarnitzki & Bernd Ebersberger & Andreas Fier, 2007. "The relationship between R&D collaboration, subsidies and R&D performance: Empirical evidence from Finland and Germany," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1347-1366.
    15. Tsai, Kuen-Hung & Wang, Jiann-Chyuan, 2005. "Does R&D performance decline with firm size?--A re-examination in terms of elasticity," Research Policy, Elsevier, vol. 34(6), pages 966-976, August.
    16. 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.
    17. Wang, Hsiao-Wen & Wu, Ming-Cheng, 2012. "Business type, industry value chain, and R&D performance: Evidence from high-tech firms in an emerging market," Technological Forecasting and Social Change, Elsevier, vol. 79(2), pages 326-340.
    18. Kim, Bowon & Oh, Heungshik, 2002. "An effective R&D performance measurement system: survey of Korean R&D researchers," Omega, Elsevier, vol. 30(1), pages 19-31, February.
    19. Eilat, Harel & Golany, Boaz & Shtub, Avraham, 2008. "R&D project evaluation: An integrated DEA and balanced scorecard approach," Omega, Elsevier, vol. 36(5), pages 895-912, October.
    20. Gary Jefferson & Bai Huamao & Guan Xiaojing & Yu Xiaoyun, 2006. "R&D Performance in Chinese industry," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 15(4-5), pages 345-366.
    21. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    22. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    23. Pawar, Kulwant S. & Driva, Helen, 1999. "Performance measurement for product design and development in a manufacturing environment," International Journal of Production Economics, Elsevier, vol. 60(1), pages 61-68, April.
    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. Khajehpour, Hossein & Miremadi, Iman & Saboohi, Yadollah & Tsatsaronis, George, 2020. "A novel approach for analyzing the effectiveness of the R&D capital for resource conservation: Comparative study on Germany and UK electricity sectors," Energy Policy, Elsevier, vol. 147(C).
    2. Minaei, Foad & Minaei, Masoud & Kougias, Ioannis & Shafizadeh-Moghadam, Hossein & Hosseini, Seyed Ali, 2021. "Rural electrification in protected areas: A spatial assessment of solar photovoltaic suitability using the fuzzy best worst method," Renewable Energy, Elsevier, vol. 176(C), pages 334-345.
    3. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    4. Zahra Mohammadnazari & Seyed Farid Ghannadpour, 2021. "Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10937-10972, July.
    5. Ertunç, Ela & Uyan, Mevlut, 2022. "Land valuation with Best Worst Method in land consolidation projects," Land Use Policy, Elsevier, vol. 122(C).
    6. van de Kaa, Geerten & Janssen, Marijn & Rezaei, Jafar, 2018. "Standards battles for business-to-government data exchange: Identifying success factors for standard dominance using the Best Worst Method," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 182-189.
    7. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory," Energies, MDPI, vol. 11(7), pages 1-24, July.
    8. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    9. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    10. Haoran Zhao & Huiru Zhao & Sen Guo, 2018. "Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model," Sustainability, MDPI, vol. 10(7), pages 1-23, June.

    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. Geerten Van de Kaa & Daniel Scholten & Jafar Rezaei & Christine Milchram, 2017. "The Battle between Battery and Fuel Cell Powered Electric Vehicles: A BWM Approach," Energies, MDPI, vol. 10(11), pages 1-13, October.
    2. Mališa Žižović & Dragan Pamučar & Goran Ćirović & Miodrag M. Žižović & Boža D. Miljković, 2020. "A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL)," Mathematics, MDPI, vol. 8(5), pages 1-18, May.
    3. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    4. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    5. Javid Nafari & Alireza Arab & Sina Ghaffari, 2017. "Through the Looking Glass: Analysis of Factors Influencing Iranian Student’s Study Abroad Motivations and Destination Choice," SAGE Open, , vol. 7(2), pages 21582440177, June.
    6. Huseyin Kocak & Atalay Caglar & Gulin Zeynep Oztas, 2018. "Euclidean Best–Worst Method and Its Application," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(05), pages 1587-1605, September.
    7. Shih-Chia Chang & Ming-Tsang Lu & Mei-Jen Chen & Li-Hua Huang, 2021. "Evaluating the Application of CSR in the High-Tech Industry during the COVID-19 Pandemic," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
    8. Gupta, Himanshu, 2018. "Evaluating service quality of airline industry using hybrid best worst method and VIKOR," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 35-47.
    9. Badri Ahmadi, Hadi & Kusi-Sarpong, Simonov & Rezaei, Jafar, 2017. "Assessing the social sustainability of supply chains using Best Worst Method," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 99-106.
    10. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    11. Hamzeh Soltanali & Mehdi Khojastehpour & Siamak Kheybari, 2023. "Evaluating the critical success factors for maintenance management in agro-industries using multi-criteria decision-making techniques," Operations Management Research, Springer, vol. 16(2), pages 949-968, June.
    12. Omidipoor, Morteza & Jelokhani-Niaraki, Mohammadreza & Moeinmehr, Athena & Sadeghi-Niaraki, Abolghasem & Choi, Soo-Mi, 2019. "A GIS-based decision support system for facilitating participatory urban renewal process," Land Use Policy, Elsevier, vol. 88(C).
    13. Alexander Kuan Daiy & Kao-Yi Shen & Jim-Yuh Huang & Tom Meng-Yen Lin, 2021. "A Hybrid MCDM Model for Evaluating Open Banking Business Partners," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    14. Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).
    15. van de Kaa, G. & Fens, T. & Rezaei, J. & Kaynak, D. & Hatun, Z. & Tsilimeni-Archangelidi, A., 2019. "Realizing smart meter connectivity: Analyzing the competing technologies Power line communication, mobile telephony, and radio frequency using the best worst method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 320-327.
    16. Vineet Kaushik & Shobha Tewari, 2023. "Modeling Opportunity Indicators Fostering Social Entrepreneurship: A Hybrid Delphi and Best-Worst Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 667-698, August.
    17. Gholamreza Haseli & Reza Sheikh & Jianqiang Wang & Hana Tomaskova & Erfan Babaee Tirkolaee, 2021. "A Novel Approach for Group Decision Making Based on the Best–Worst Method (G-BWM): Application to Supply Chain Management," Mathematics, MDPI, vol. 9(16), pages 1-20, August.
    18. Govindan, Kannan & Shankar, K. Madan & Kannan, Devika, 2020. "Achieving sustainable development goals through identifying and analyzing barriers to industrial sharing economy: A framework development," International Journal of Production Economics, Elsevier, vol. 227(C).
    19. Mohammad Khalilzadeh & Laleh Katoueizadeh & Edmundas Kazimieras Zavadskas, 2020. "Risk identification and prioritization in banking projects of payment service provider companies: an empirical study," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-27, December.
    20. Ren, Jingzheng & Liang, Hanwei & Chan, Felix T.S., 2017. "Urban sewage sludge, sustainability, and transition for Eco-City: Multi-criteria sustainability assessment of technologies based on best-worst method," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 29-39.

    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:epplan:v:66:y:2018:i:c:p:147-155. 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/evalprogplan .

    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.