10. FORECASTING SOCIAL RATES OF RETURN

The U.S. Department of Commerce would like to be able to forecast the social rates of return from the investments in new technology supported by the ATP program. Clearly, there is no reason in principle why such forecasts cannot be made if one is willing to estimate the probability of technical success and the probability of commercialization (given technical success), development and commercialization cost and time, (P₁ - P₂ ), Q₂ , and the relevant profits. However, due to scanty data at the early proposal review time, such forecasts may be quite inaccurate. The later in the R&D/commercialization stage forecasting is attempted, the better the data are likely to be, and the more reliable the forecast.

One point to bear in mind is that the rate of growth of Q₂ will often have a major impact on the social rate of return. Economists have done a great deal of research on the factors influencing the rate of growth of Q₂. The diffusion of an innovation is often a slow process. For example, measuring from the date of first commercial application, it generally took more than ten years for all of the major American firms in the relevant industries to begin using industrial robots (Mansfield, 1989, 1993). Similar results have been obtained for the chemical and other industries as well. Also, the rate of diffusion varies widely. Sometimes it took decades for firms to install a new technique, but in other cases they imitated the innovator very quickly.

The rate of diffusion of an innovation depends on the average profitability of the innovation, the variation among firms in the profitability of the innovation, the size of the investment required to introduce the innovation, the number of firms in the industry, their average size, the inequality in their sizes, and the amount that they spend on research and development. Using these variables, it is possible to explain a large proportion of the variation among innovations in the rate of diffusion. Moreover, this seems to be the case in a wide variety of industries and in other countries as well as in the United States.

Firms where the expected returns from the innovation are highest tend to be quickest to introduce an innovation. Also, holding constant the profitability of the innovation, big firms tend to introduce an innovation before small firms. In some industries, this may be due to the fact that larger firms, although not necessarily the largest ones—are more progressive than small firms. But even if the larger firms were not more progressive, one would expect them to be quicker, on the average, to begin using a new technique for reasons discussed in our earlier studies.¹¹ Also, holding other factors constant, firms with younger and better-educated managers tend to be quicker to introduce new techniques—or at least, this seems to be the case in industries where firms are small.

Companies also differ greatly with regard to the intra-firm rate of diffusion—the rate at which, once it has begun to use the new technique, a firm substitutes it for older methods. A considerable amount of this variation can be explained by differences among companies in the profitability of the innovation, the size of the firm, and its liquidity. Also, there is a tendency for late starters to "catch up". That is, firms that are slow to begin using an innovation tend to substitute it for older techniques more rapidly than those that are quick to begin using it. It is also relevant to note that the same sort of process occurs on the international scene; countries that are slow to begin using an innovation tend to substitute it for older techniques more rapidly than countries that are quick to begin using it. The reasons for this tendency, both at the firm and national levels, seem clear enough.

Sociologists have studied the nature and sources of information obtained by managers concerning new techniques. Judging from the available evidence, firms, once they hear of the existence of an innovation, may wait a considerable period of time before beginning to use it. In many cases, this is quite rational. But to some extent this may also be due to incomplete or erroneous information, prejudice, and resistance to change. For example, see Mansfield (1993). The sources of information sometimes vary depending on how close the manager is to adopting the innovation. For example, in agriculture, mass media are most important sources at the very early stages of a manager's awareness of the innovation, but friends and neighbors are most important sources when a manager is ready to try the innovation. Also, there is evidence of a "two-step flow of communication". The early users of an innovation tend to rely on sources of information beyond their peer group's experience; after they have begun using the innovation, they become a model for their less expert peers, who can imitate their performance.

In addition, the diffusion process may be slowed by bottlenecks in the production of the innovation—as in the case of the Boeing 707. Also, the extent of advertising and other promotional activities used by producers of the new product or equipment will have an effect. So too will the innovation's requirements with respect to knowledge and coordination, the diffusion process being impeded if the innovation requires new kinds of knowledge on the part of the user, new types of behavior, and the coordinated efforts of a number of organizations. If an innovation requires few changes in socio-cultural values and behavior patterns, it is likely to spread more rapidly. Also, the policies adopted by relevant labor unions influence the rate of diffusion. For example, some locals of the painter's union have refused to use the spray gun. There is, of course, a considerable literature on the effect of collective bargaining on the rate of adoption of new techniques.

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Date created: June 15, 2006
Last updated: June 16, 2006

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