Edwin Mansfield

TECHNICAL CHANGE AND THE RATE OF IMITATION

This paper investigates the factors determining how rapidly the use of a new technique spreads from one firm to another. A simple model is presented to help explain differences among innovations in the rate of imitation. Deterministic and stochastic versions of this model are tested against data showing how rapidly firms in four industries came to use twelve important innovations. The empirical results seem quite consistent with both versions of the model.

Academic Research and Industrial Innovation

The purpose of this study is to estimate the extent to which technological innovations in various industries have been based on recent academic research, and the time lags between the investment in recent academic research projects and the industrial utilization of their findings. Because no attempt (to my knowledge) has been made to estimate the social rate of return from academic research, ’ we also make some rough and tentative estimates of this sort. While the results are subject to many limitations discussed below, they should be of interest to public policy-makers concerned with science and technology, as well as to

Academic Research Underlying Industrial Innovations

There has been no systematic study of the characteristics of the universities and academic researchers that seem to have contributed most to industrial innovation. Nor do we know how such academic research has been funded. This paper, based on data obtained from sixty-six firms in seven major manufacturing industries and from over two hundred academic researchers, sheds new light on the sources, characteristics, and financing of academic research underlying industrial innovation. The findings should be of interest to economists concerned with technological change and to policymakers attempting to increase the economic payoff from the nations academic research. Copyright 1995 by MIT Press.

How Rapidly Does New Industrial Technology Leak Out

There have been no systematic empirical studies of the speed at which various kinds of technological information leak out to rival firms. To help fill this gap, data were obtained from 100 American firms. According to the results, information concerning development decisions is generally in the hands of rivals within about 12 to 18 months, on the average, and information concerning the detailed nature and operation of a new product or process generally leaks out within about a year. These results have important implications both for incentives for innovation and for public policies aimed at stemming the outflow of technology.

Social and Private Rates of Return from Industrial Innovations

I. Introduction, 221.—II. The sample of innovations, 222.—III. Estimation of social benefits: product innovations used by firms, 222.—IV. Parallel innovative efforts, time horizon, and rates of return, 226.—V. Product innovations used by households, 229.—VI. Process innovations, 231.—VII. Social and private rates of return, 233.—VIII. Factors associated with the gap between social and private rates of return, 235.—IX. Unemployment, repercussions on other markets, and future changes in technology, 238.—X. Conclusion, 239.

The modern university: contributor to industrial innovation and recipient of industrial R&D support

Abstract The interface between industry and the universities is of key importance in the promotion of technological change in many industries. There is intense interest in the characteristics of universities that have contributed most importantly to industrial innovation in various fields, but unfortunately very little systematic study has been devoted to this important and complex topic. Also, we know little about the factors determining which universities firms will support to do R&D of various types. Based on data obtained from a carefully selected sample of major US firms in the electronic, information processing, chemical, petroleum, pharmaceutical, instruments, and metal industries, this paper sheds new light on these topics.

Academic research and industrial innovation: An update of empirical findings1

In 1991, I published in this journal estimates of the percentage of new products and processes based on recent academic research—that is, academic research occurring within 15 years of the commercialization of whatever innovation is being considered— in the drug and medical product, information processing, chemical, electrical, instruments, metals, and Ž . oil industries in 1975–1985 Mansfield, 1991, 1992 . Because there has been considerable interest in such estimates , I have gathered similar data from a sample of 77 major firms for 1986–1994, the only significant difference in the sample design being that the machinery industry, which is reasonably active in this regard, has been substituted for oil. 3 Table 1 shows that the overall results for 1986– 1994 are very similar to those for 1975–1985, although particular industries sometimes vary substantially, as one might expect. The industry means in

Technology Transfer to Overseas Subsidiaries by U. S.-Based Firms

Although economists and policy makers have devoted considerable attention to the transfer of technology by U. S.-based multinational firms to their overseas subsidiaries, very little is known about the nature of the technology that is being transferred overseas in this way, the extent to which it leaks out to non-U. S. competitors, the size of the benefits it confers on the host (and other non-U. S.) countries, and the sorts of non-U. S. firms that receive the largest benefits of this sort. This paper presents findings that shed new light on each of these topics.

Overseas Research and Development by US-Based Firms

AbstractThe following sections are included:INTRODUCTIONOVERSEAS R AND D EXPENDITURES: 1960–1980FACTORS INFLUENCING THE PERCENTAGE OF A FIRMs R AND D EXPENDITURES CARRIED OUT OVERSEASOVERSEAS R AND D: MINIMUM ECONOMIC SCALE AND RELATIVE COSTOVERSEAS R AND D: NATURE OF WORK AND RELATION TO DOMESTIC R AND DCONCLUSIONSACKNOWLEDGMENTSNOTESREFERENCES (This abstract was borrowed from another version of this item.)

The Speed of Response of Firms to New Techniques

I. Introduction, 290. — II. Size of firm and the profitability of its investment in the innovation, 291. — III. Model and data, 294. — IV. Empirical results, 297. — V. Growth rate, profitability, age of president, liquidity, and profit trend, 302. — VI. Concentration of technical leadership, 305. — VII. Summary and conclusions, 309.