Choosing and Evaluating Technology Policy: A Multicriteria Approach

The multicriteria nature of choosing and evaluating technology policy can be dealt with by outranking methods, enabling us to avoid weak approaches such as following rules or routines or imitating best practices on one hand, and fictitious multicriteria methods on the other. Outranking methods can strongly support policy makers and social scientists in choosing and evaluating technology policy. They are consistent with behavioral-evolutionary theory, and they allow us to maintain the variety and realism of problem solving in technology policy. Being based on formal and robust algorithms, they also represent a sound theoretical alternative to neo-classical approaches, both in their orthodox and hidden versions. The adoption of outranking methods has a number of theoretical and policy implications. A tutorial (and numerical) example shows how easily they can be applied. Copyright , Beech Tree Publishing.

[1]  L. Georghiou,et al.  Equilibrium and Evolutionary Foundations of Technology Policy , 1998 .

[2]  Loet Leydesdorff,et al.  A Triple Helix of University—Industry—Government Relations , 1998, Scientometrics.

[3]  Stefan Kuhlmann,et al.  Evaluation of technology policy programmes in Germany , 1995 .

[4]  Evangelos Triantaphyllou,et al.  Multi-criteria Decision Making Methods: A Comparative Study , 2000 .

[5]  Z. Griliches Patent Statistics as Economic Indicators: a Survey , 1990 .

[6]  Barry Bozeman,et al.  Technology transfer and public policy: a review of research and theory , 2000 .

[7]  G. Hodgson Economics and Institutions: A Manifesto for a Modern Institutional Economics , 1991 .

[8]  S. Winter,et al.  An evolutionary theory of economic change , 1983 .

[9]  Luke Georghiou,et al.  Evaluating technology programs: tools and methods , 2000 .

[10]  Thráinn Eggertsson,et al.  Economic behavior and institutions , 1991 .

[11]  Patel Parimal,et al.  National Innovation Systems: Why They Are Important, And How They Might Be Measured And Compared , 1994 .

[12]  B. Lundvall Innovation Policy in a Global Economy: Technology policy in the learning economy , 1999 .

[13]  Richard R. Nelson,et al.  Understanding Technical Change As an Evolutionary Process , 1987 .

[14]  Albert N. Link,et al.  Evaluating Public Sector Research and Development , 1996 .

[15]  Philippe Vincke,et al.  Multicriteria Decision-Aid , 1992 .

[16]  Geoffrey M. Hodgson,et al.  Economics and Evolution: Bringing Life Back into Economics. , 1995 .

[17]  M. Sharp,et al.  Technology Policy in the European Union , 1998 .

[18]  Marc Roubens,et al.  Multiple criteria decision making , 1994 .

[19]  B. Roy Méthodologie multicritère d'aide à la décision , 1985 .

[20]  Bernard Roy,et al.  Aide multicritère à la décision : méthodes et cas , 1993 .

[21]  Giovanni Dosi,et al.  Technological paradigms, patterns of learning and development: An introductory roadmap , 1995 .

[22]  L. Leydesdorff,et al.  Emergence of a Triple Helix of University-Industry-Government Relations , 1996 .

[23]  D. North Institutions, Institutional Change and Economic Performance: Economic performance , 1990 .

[24]  H. Simon,et al.  Models of Bounded Rationality: Empirically Grounded Economic Reason , 1997 .

[25]  Richard Schmalensee,et al.  Handbook of Industrial Organization , 1989 .

[26]  Henry Etzkowitz,et al.  The Triple Helix as a model for innovation studies , 1998 .

[27]  C. Freeman Technology policy and economic performance : lessons from Japan , 1987 .

[28]  Nathan Rosenberg,et al.  Exploring the black box: Telecommunications: complex, uncertain, and path dependent , 1994 .

[29]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[30]  R. Nelson Recent Evolutionary Theorizing about Economic Change , 2005, Technology, Institutions, and Economic Growth.