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运用最佳-最差方法评估企业的研发绩效。

Evaluating firms' R&D performance using best worst method.

作者信息

Salimi Negin, Rezaei Jafar

机构信息

Science Based Business, Faculty of Science, Leiden University, The Netherlands.

Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands.

出版信息

Eval Program Plann. 2018 Feb;66:147-155. doi: 10.1016/j.evalprogplan.2017.10.002. Epub 2017 Oct 19.

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.

摘要

由于研发是企业生产力、增长和竞争优势的最关键决定因素,衡量研发绩效已成为研发经理关注的核心,并且大量文献已经研究并确定了不同的研发衡量指标以及研发绩效的决定因素。然而,衡量研发绩效并对不同的研发指标赋予同等重要性,这是现有研究中的常见方法,可能会过度简化研发衡量过程,这可能导致对绩效的误解,进而导致错误的研发策略。本研究的目的是考虑研发指标的不同重要程度来衡量研发绩效,使用一种称为最佳最差法(BWM)的多准则决策方法来确定研发指标的权重(重要性),并利用在中小企业调查以及从研发专家那里收集的数据来衡量荷兰50家高科技中小企业的研发绩效。结果表明,与简单均值相比,对不同的研发指标赋予不同权重会导致企业排名不同,并使研发经理能够通过运用有关不同研发指标重要性的知识来制定更有效的策略,以提高其公司的研发绩效。

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