At first sight, the choice of a socially best economic policy and the choice of an optimal engineering design seem to be quite separate issues. A closer look, however, shows that both approaches which aim at generating a (set of) best alternative(s) have much in common. We describe and characterize axiomatically an aggregation method that uses a set of evaluations that are arranged on a common scale. This scale establishes a common language, so to speak, which conforms to the criteria that are deemed relevant in order to compare various design options. Two conditions are able to characterize the proposed aggregation mechanism. One is a simple dominance requirement, and the other called cancellation independence makes use of the fact that for any pair of objects, rank differences of opposite sign can be reduced without changing the aggregate outcome of the ranking procedure. The proposed method has its origin in voting theory but may have the potential to prove useful in engineering design as well.
References
[1]
Franssen, M. (2005) Arrow’s Theorem, Multi-Criteria Decision Problems and Multi-Attribute Preferences in Engineering Design. Research in Engineering Design, 16, 42-56. http://dx.doi.org/10.1007/s00163-004-0057-5
[2]
Arrow, K.J. (1951, 1963) Social Choice and Individual Values. Wiley, New York.
[3]
Scott, M.J. and Antonsson, E.K. (1999) Arrow’s Theorem and Engineering Design Decision Making. Research in Engineering Design, 11, 218-228. http://dx.doi.org/10.1007/s001630050016
[4]
Dym, C.L., Wood, W.H. and Scott, M.J. (2002) Rank Ordering Engineering Designs: Pairwise Comparison Charts and Borda Counts. Research in Engineering Design, 13, 236-242.
[5]
Kuhn, T.S. (1962) The Structure of Scientific Revolutions. The University of Chicago Press, Chicago.
[6]
Kuhn, T.S. (1977) Objectivity, Value Judgment, and Theory Choice. In: Kuhn, T.S., Ed., The Essential Tension—Selected Studies in Scientific Tradition and Change, The University of Chicago Press, Chicago, 320-339.
[7]
Gaertner, W. and Wüthrich, N. (2015) Evaluating Competing Theories via a Common Language of Qualitative Verdicts. Synthese, 1-7. http://dx.doi.org/10.1007/s11229-015-0929-4
[8]
Balinski, M. and Laraki, R. (2007) A Theory of Measuring, Electing, and Ranking. Proceedings of the National Academy of Sciences, 104, 8720-8725. http://dx.doi.org/10.1073/pnas.0702634104
[9]
Balinski, M. and Laraki, R. (2010) Majority Judgment. The MIT Press, Cambridge, Mass.
[10]
Gaertner, W. and Xu, Y. (2012) A General Scoring Rule. Mathematical Social Sciences, 63, 193-196.
http://dx.doi.org/10.1016/j.mathsocsci.2012.01.006
[11]
Pugh, S. (1990) Total Design. Addison-Wesley, Reading.
[12]
Von Neumann, J. and Morgenstern, O. (1953) The Theory of Games and Economic Behavior. Princeton University Press, Princeton.
[13]
Hazelrigg, G.A. (1999) An Axiomatic Framework for Engineering Design. ASME Journal of Mechanical Design, 121, 342-347. http://dx.doi.org/10.1115/1.2829466
[14]
Gaertner, W. (2009) A Primer in Social Choice Theory. 2nd Edition, Oxford University Press, Oxford.
[15]
Gaertner, W. (2016) Wickedness in Social Choice. Journal of Economic Surveys. http://dx.doi.org/10.1111/joes.12143
[16]
Brams, S.J. and Fishburn, P.C. (1983) Approval Voting. Birkhäuser, Boston.
[17]
Smith, W.D. (2000) Range Voting. http://rangevoting.org/
