In this article the results are presented of an empirical study focusing on the effectiveness of R&D performance measurement practices in the Netherlands. First, a theoretical examination of the subject R&D performance measurement' is given within the context of performance control. A distinction is made between feedback and feed forward control and between the R&D function and the R&D organisation. Subsequently, a description is given of the current practices of R&D performance measurement in terms of measurement purposes, metrics, measurement techniques, norms setting, etc. Furthermore, the influence of contingencies on measurement system design is explored.

Based on a comprehensive literature review and the activities of numerous case study companies, it is argued in this paper that performance measurement in R&D is a fundamental aspect to quality in R&D and to overall business performance. However, it is apparent from the case companies that many companies still struggle with the issue of R&D performance measurement. Excuses for not measuring are easily found, but there are also empirical examples and literature available with suggestions how it can be done. In this article this literature is reviewed and placed within the context of general performance control and contingency theory. Furthermore, the main measurement system design parameters are discussed and some basic system requirements are described as well as several design principles that can be useful for those who accept the challenge of establishing a meaningful measurement system. 1 In this paper, we will use the abbreviation R&D as a general term to indicate activities varying from basic research, to product development and introduction. If at any point basic research or any other specific R&D category is intended then it will be clearly distinguished in that context.

There have been considerable changes in the way that Research and Development (R&D) has been managed over recent years, many of which have been influenced by the external environment. These have been discussed in a number of publications with much of the debate centring around the movement from the so-called first generation to fifth generation models of R&D management.What has not been debated to the same extent are the implications of recent and likely future trends in R&D management for the way performance is, and should be, measured. In this paper we focus on these implications, drawing upon both the existing literature on performance measurement (PM) in R&D and our own research into organisations which have chosen to move towards a more profit-centred approach to the management of their technical resources.Finally, we present and discuss the findings of our review, which indicate that although there are common features, some differences, requiring careful consideration by management, can be identified when movement from a cost-to a profit-centred approach occurs.

In this article, a comprehensive descriptive model of R&D knowledge management is presented and its use illustrated. Knowledge is defined as: information internalized by means of research, study or experience, that has value for the organization. First, the issue of knowledge management is placed in the context of R&D management, and set alongside what has been written in R&D management literature about topics such as information management, information technology in R&D, technology transfer, communication and organizational learning. Then, we present our descriptive model, and apply it in a case study concerning a Dutch multinational in the chemical industry. The model served as an aid to identify bottlenecks, and was a useful starting point for formulating improvement plans, some of which are presented. The paper concludes with an evaluation of the model as a communication and analysis tool, and ideas for further improvement.

In this paper we describe a framework for analysing the creation and justification of Research & Development. The 4S framework is developed for analysing the scope, scale, skills and social network aspects of Research & Development value. The framework is based on social system theory, a process contingency model, and recent Research & Development metrics. We present a first empirical assessment based on a workshop using the 4S framework for leveraging Research & Development. Results that assist in the assessment of value creation utilising R & D within networks are very relevant in high tech industries. The multi–dimensional process approach of this framework seems promising for understanding and managing R&D value creation, but needs further operationalisation. Case studies are described and a Dutch network on leveraging R&D has been initiated.