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Decision Sciences: An Integrative Perspective

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Kleindorfer(K)does a good job of covering the conventional wisdom of the decision science establishment.Tversky and Kahneman,Hogarth and Einhorn,Slovic and Lichtenstein,Shoemaker,Kunreuther,Ellsberg,etc.,are all covered explicitly or implicitly.Unfortunately,the path breaking and monumental discoveries made by John Maynard Keynes in his 1921 magnum opus,A Treatise on Probability,are completely ignored.This is probably due to the misguided importance attached to two extremely poor and inaccurate book reviews of Frank Ramsey that were published in 1922 and 1926,respectively.Ramsey badly misinterpreted Keynes's definitions of the words nonnumerical and nonmeasurable to mean that numbers could rarely be used to calculate an estimate of probability in Keynes's system.In fact,Keynes's argument was that it took two numbers,not one,to generally make an estimate of probability.Nonnumerical meant not by a single numeral.Keynes is the founder of the interval(set)estimate approach to probability.Keynes also specified an index to measure ambiguity which Keynes called the weight of the evidence,w.It is defined on the unit interval between 0 and 1,0<=w<=1.IT IS IDENTICAL TO ELLSBERG'S rho index,0<=rho<=1.In chapter 26 of the TP,Keynes generalized the expected value/expected utility rules by constructing a decision weight that Keynes called a conventional coefficient of risk and weight,c.Let p equal the probabibity of success ,q equal the probability of failure and A equal the outcome .A decisionmaker maximizes cA,instead of pA or pU(A),where c=1/(1+q)[2w/(1+w)].Keynes was the firest scholar in history to specify an index for w and a decision weight c.Keynes at least merits as many pages as allocated to D.Ellsberg.