R&D Value Mapping: A New Approach to Case Study-Based Evaluation* Barry Bozeman School of Public Policy and the Technology Policy and Assessment Center, Georgia Tech Atlanta, GA 30332 Gordon Kingsley School of Public Policy and the Technology Policy and Assessment Center, Georgia Tech Atlanta, GA 30332 Abstract This study presents an approach to harnessing the power of case studies for research evaluation called R&D value mapping (RVM). While this method uses case studies in the traditional manner to provide in-depth insights, it also structures case studies throughan analyticalframework thatyields quantitative data and less subjective "lessons learned." When properly applied, RVM can yieM an inventory of outcomes and empirical generalizations regarding the determining variables. A particular advantage of the approach is that it not only provides an indication of the type and amount (though not a single numerical index) of outcome, but als Ogives insight into the reasons outcomes are achieved. Thus, RVM is usefulfor policy management strategies seeking to replicate success. The specific steps associated with the R VM method are illustrated through studies that have applied the technique. The set of analytical tools for assessing the social and economic impacts of R&D has expanded significantly during the past ten years. Not so long ago, evaluation of R&D impacts and technology development seemed equal parts alchemy and vaguely derived numbers. As a result of methodological developments, the numbers are currently derived with a bit more rigor. While alchemy still holds sway, serious evaluations are much more common. Despite advances in application of such research evalu- ation techniques as cost-benefit analysis (Averch 1994), benehmarking (Rush et al. 1995) and bibliometrics (Rao 1996), one set of obviously relevant techniques, case studies, has remained somewhat stunted in its develop- ment. Case study approaches to research impact evaluation generally have credibility with policy-makers and officials and are popular among evaluators and policy analysts (Kingsley 1993). But with the conspicuous exception of the methodological advances provided by Robert Yin (1994), case study approaches to research evaluation re- main fragmented, piecemeal and difficult to aggregate. Case studies, in research evaluation as elsewhere, seem to "tell us more and more about less and less." Case studies provide richness and depth of understanding but, all too often, one is left to one's own devices in trying to deter- mine "what it all means." While ease studies can provide *The authors gratefully acknowledge support from of the Department of Energy, Basic Energy Sciences and previ- ous contracts from Sandia National Laboratories and the New York State Energy Research & Development Author- ity. A number of persons have made useful comments on the RVM method. We are particularly grateful to David Roessner, Juan Rogers, Gretchen Jordan and Iran Thomas. Journal of Technology Transfer Vol. 22 (2): 33-42. important lessons, the lessons depend as much on the interpretive ability of the reader as the science of the evaluator. The objective of this paper is to outline advances in a new approach to harnessing the power of ease studies for research evaluation, an approach that has promise, if sue- cessful, of using case studies in the traditional manner to provide in-depth insights; but, at the same time, it may use case studies in an analytical framework that yields quanti- tative data and less subjective "lessons learned." The method, termed R&D value mapping yields an inventory of benefits and empirical generalizations of the determinants of those benefits and has been applied in several studies (Bozeman et al. 1992; Bozeman and Roessner 1995; Kingsley and Bozeman 1997; Kingsley and Farmer 1997; Kingsley, Bozeman, and Coker 1996). A particular advantage of the approach is that it not only provides an indication of the type and amount (though not a single numerical index) of value, but also gives insight into the reasons benefits are achieved. Thus, R&D value mapping (RVM) is useful for policy management strate- gies seeking to replicate success. RVM has much in common with earlier case study- based attempts to assess research but is in many respects a significantdeparture. As in previous case studies of R&D impacts, RVM focuses intensely on particular projects and the events surrounding them. Case studies "tell a story" about the chronology and events contained within the boundaries of the project, and RVM is similar to traditional case studies in that it yields such a narrative. There is also an expectation that the case studies can contain a richness that goes beyond traditional aggregated quantitative stud- ies to provide insights from detail and nuance. RVM, 33