TY - JOUR
T1 - Evaluating firms’ R&D performance using best worst method
AU - Salimi, Negin
AU - Rezaei, Jafar
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Best worst method (BWM)
KW - R&D measures
KW - R&D performance
KW - Small-to-medium-sized enterprises (SMEs)
UR - http://resolver.tudelft.nl/uuid:9ce2e853-b2bd-4d6b-a7e7-f55c5219744c
UR - http://www.scopus.com/inward/record.url?scp=85032362842&partnerID=8YFLogxK
U2 - 10.1016/j.evalprogplan.2017.10.002
DO - 10.1016/j.evalprogplan.2017.10.002
M3 - Article
AN - SCOPUS:85032362842
SN - 0149-7189
VL - 66
SP - 147
EP - 155
JO - Evaluation and Program Planning
JF - Evaluation and Program Planning
ER -