Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

Nonparametric tests of optimizing behavior in public service provision: Methodology and an application to local safety

We develop a positive non-parametric model of public sector production that allows us to test whether an implicit procedure of cost minimization at shadow prices can rationalize the outcomes of public sector activities. The basic model focuses on multiple C-outputs and does not imply any explicit or implicit assumption regarding the trade-offs between the different inputs (in terms of relative shadow prices) or outputs (in terms of relative valuation). The proposed methodology is applied to a cross-section sample of 546 Belgian municipal police forces. Drawing on detailed task-allocation data and controlling, among others, for the presence of state police forces, the cost minimization hypothesis is found to provide a good fit of the data. Imposing additional structure on output valuation, derived from available ordinal information, yields equally convincing goodness-of-fit results. By contrast, we find that aggregating the labor input over task specializations, a common practice in efficiency assessments of police departments, entails a significantly worse fit of the data.Public agencies, optimizing behavior, nonparametric production, local police departments

How can we know if EU cohesion policy is successful? Integrating micro and macro approaches to the evaluation of Structural Funds

In this paper we describe an integrated approach for assessing the general economic effectiveness, efficiency and impact of public policy actions for large investment programs of the kind implemented over the past fifteen years in EU-aided Structural Fund programmes. Far from being rigid, our modelling philosophy includes both formal tools designed to assess all relevant effects, as well as informal (intuitive) elements to allow for flexible policy design and evaluation. When setting up an integrated micro-macro (IMM) model we are trying to over-come two major shortcomings in actual policy design and analysis: Firstly, to bridge the gap between the scientific requirements of model-based decision making and evaluation and the practical requirement for flexible and easy to use decision support tools that are well suited for day-to-day application. Secondly, to address the observed discrepancy in policy analysis between programme monitoring and evaluation realized at a highly aggregate level using quantitative macromodels (the so called “top down” approach) and the highly disaggregated approach to project evaluation, marked as micro- or “bottom up”-approaches.

Supplier Selection by the Pair of Nondiscretionary Factors-Imprecise Data Envelopment Analysis Models

Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method.Full Tex

Peer review for the evaluation of the academic research: the Italian experience

Peer review, that is the evaluation process based on judgments formulated by independent experts, is generally used for different goals: the allocation of research funding, the review of the research results submitted for publication in scientific journals, and the assessment of the quality of research conducted by Universities and university-related Institutes. The paper deals with the latter type of peer review. The aim is to understand how the characteristics of the Italian experience provide useful lessons for improving peer review effectiveness for evaluating the academic research. More specifically, the paper investigates the peer review process developed within the Three-Year Research Assessment Exercise (VTR) in Italy. Our analysis covers four disciplinary sectors: chemistry, biology, humanities and economics. Thus, the choice includes two “hard science” sectors, which have similar type of research output submitted for the three-year evaluation process, and two sectors with different types of output. The results provide evidences, which highlight the important role played by peer review for judging the quality of the academic research in different fields of science, and for comparing different institutions’ performance. Moreover, some basic features of the evaluation process are discussed, in order to understand their usefulness for reinforcing the effectiveness of the peers’ final outcome.Scientific research, Evaluation, Peer review, University, Academic institutions