Print Email Facebook Twitter R&D productivity in the pharmaceutical industry. Scenario simulations using a Bayesian belief network Title R&D productivity in the pharmaceutical industry. Scenario simulations using a Bayesian belief network Author Van Vierssen Trip, F.W. Contributor Den Hartig, E. (mentor) Van Beers, C.P. (mentor) Van den Berg, J. (mentor) Faculty Technology, Policy and Management Department Section Technology, strategy and entrepreneurship Programme Management of Technology Date 2013-10-29 Abstract The pharmaceutical industry is in a R&D productivity crisis. Rapidly increasing development costs, decreasing profitability of new medical entities and missing breakthrough innovation are afflicting the future of the pharmaceutical industry. This complex problem requires a systems thinking approach. In this study, we ought to map the general pharmaceutical R&D productivity system in the form of a Bayesian belief network. This model, based on literature and experts’ views, not only supports users to understand the system but is able to simulate different future scenarios. By doing so, decision makers are able to identify the leverage points of the pharmaceutical R&D productivity system. These leverage points could be the foundation of any further strategy development. Potentially, the R&D productivity system archetype is also applicable for other R&D intensive industries. Subject Bayesian belief networksleverage pointsmanagementpharmaceutical industryR&D productivity To reference this document use: http://resolver.tudelft.nl/uuid:1cf4d7a7-c612-4531-953b-04c99627a89e Embargo date 2013-10-16 Access restriction Campus only Part of collection Student theses Document type master thesis Rights (c) 2013 Van Vierssen Trip, F.W.