In contrast with the situation regarding the level of effort where there is a certain asymmetry in the effects of factors influencing payoff and factors influencing cost, there ought to be more symmetry in decision rules guiding the allocation of effort. Assume that the product in question (being sold by the firm) can have different attributes; cars or television sets can be big or small, models can be deluxe or plain, and so forth. An R&D decision maker ought to have a pretty good (though not infallible) idea regarding what subclasses of “new tech nologies” will lead to a product with one or another set of attributes. A shift in consumer demand toward one set of attributes and away from another changes the mix of production that would be dictated by plausibly responsive production decision rules. But such a shift also ought to influence the allocation of research and development ef fort in the same direction .
Exactly the same demand or payoff argument enables the model to generate the qualitative conclusions that come out of many neoclas sical models relating the direction of inventing, in the sense of factor saving, to factor prices. If the R&D decision maker can identify, ex an te, classes of technology that are relatively rich in elements that will save considerably on labor per unit of output or on capital per unit of output, a “plausibly responsive” decision rule ought to link his search direction to the relative prices of labor and capital. The empirical work that started with Habakkuk (1962) and that was sig nificantly extended by Hayami and Ruttan (1971 ) and Binswanger and Ruttan (1976) has empirically documented the effect of factor prices on the factor bias displayed by innovation . This linkage is as well explained by our “search” model as by the neoclassical formula tion, which assumes a highly unrealistic ability on the part of the in ventors to calculate and foresee .
A good decision rule for allocating research and development resources obviously must attend both to factors on the demand side and to factors that influence the ease or cost of invention . It is no good to pick out projects that are technically exciting and doable but that have no demand, or to undertake a proj ect that if successful would have a high payoff but that would have no chance for success. The question is: What kinds of decision rules have evolved that are responsive to these criteria?
In view of the great size and uneven topography of the set of all possible projects, R&D decision makers must have some simple guidelines for homing in on plausible regions. A widely used proce dure seems to begin by developing lists of projects that if successful would have high payoff, and then screening this list to find those projects that look not only profitable if they can be done, but doable at reasonable cost. In a sense, payoff-side factors are examined first, and those relating to cost or feasibility are looked at second . It ap pears that certain firms, however, proceed with their sorting quite the other way, focusing first on exciting technological possibilities and then screening these to identify the ones that might have high payoff if achieved. Studies suggest that the first of these two strate gies not only is more common but is more likely to result in a com mercially successful project than the second strategy. However, the strategy that looks at interesting technological possibilities first tends to pay off handsomely when it pays off at all. 6
Neither of these two approaches, of course, is literally optimal. Our basic point is that firms cannot hope to find optimal strategies. Since all alternatives cannot be considered, there must be some rather mechanical procedures employed for quickly narrowing the focus to a small set of alternatives and then homing in on promising elements within that set. It is noteworthy that both of the strategies mentioned above pay attention to factors both on the demand or payoff side and on the cost and feasibility side. We interpret the widespread use of strategies of this sort as confirmation of our hy pothesis that p olicies in use, although in no sense optimal , tend to be plausibly responsive to the key variables influencing profitability.
Source: Nelson Richard R., Winter Sidney G. (1985), An Evolutionary Theory of Economic Change, Belknap Press: An Imprint of Harvard University Press.