Evaluating firms' R & D performance using best worst method

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.