Competition and industrial policies in a ‘history friendly’model of the evolution of the computer industry (original) (raw)
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History-Friendly'Models of Industry Evolution: the Computer Industry
Industrial and Corporate …, 1999
The model presented in this paper is the first of a new generation of evolutionary economic models: 'history-friendly' models. History-friendly models are formal models that aim to capture, in stylized form, qualitative and 'appreciative' theories about the mechanisms and factors affecting industry evolution, technological advance and institutional change put forth by empirical scholars of industrial economics, technological change, business organization and strategy, and other social scientists. In this paper we have analyzed the long-term evolution of the computer industry. In particular we have examined the emergence of a dominant firm in mainframes, the introduction of a major innovation (microprocessor), the opening up of a new market segment (personal computers), and the competition there between newcomers and diversified old established firms. We have taken a body of verbal appreciative theorizing, developed a formal representation of that theory, and found that the formal version of that theory is consistent and capable of generating the stylized facts the appreciative theory purports to explain. Going through this analytic exercise has significantly sharpened our theoretical understanding of the key factors behind salient aspects of the evolution of the computer industry.
Competition, Innovation And Increasing Returns ∗
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This paper concerns the operation of competition in the presence of a high rate of innovation and increasing returns. Given free competition there is likely to exist, in this case, a tendency towards what may be called 'dynamic equilibrium', a tendency, that is to say, for the rate of investment in product development to rise or fall towards the level at which this investment yields only a normal return. Thus, competition, increasing returns and innovation may co-exist.
1 Technology and Industry Evolution
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We would like to thank Barry Bayus, Martin Ganco, Scott Shane, and Mike Tushman for their helpful comments on this manuscript. We would also like to thank Tal Levy for research assistance.
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Inventions differ in terms of the age of the knowledge base they build upon. We examine what effects differences in the recency of knowledge inputs have on financial performance. Using threshold regression analysis, we isolate three regimes that exhibit different associations between recency and stock return. We find that for firms whose new patents use inputs in the mid-range of the technological recency distribution, the relationship is positive; higher recency leads to higher stock return. However, for firms whose new patents make use of either nascent or very mature technological inputs, the effects are negative; higher recency leads to lower stock return. These findings indicate that it is not firms utilizing the most recent technological inputs that experience the highest returns to their inventive activity. Indeed, firms operating at the technological input frontier have market returns significantly below the mean. Rather, it is firms whose new patents utilize medial-aged technological inputs (i.e., firms using inputs slightly behind the technology frontier) that tend to experience the highest returns.
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While the change literature is currently dominated by the punctuated equilibrium paradigm, anomalies have appeared to the paradigm in the form of high velocity change and hypercompetition. D'Aveni (1999) reconciles these anomalies with the punctuated equilibrium paradigm by suggesting that the frequency of change experienced affects the change experienced. This research considered whether the presence of increasing returns in an industry is correlated with the frequency of change experienced by the industry and the types of change that appear, thus providing an explanation for the differing forms of change. A second observation in the literature is that an industry experiences a period of instability after a discontinuity. This research considered whether the temporal proximity or type of a preceding discontinuity influenced the likelihood or type of later discontinuities. A longitudinal study identified discontinuities in nine industries throughout the industries' histories. The industries were categorised as: increasing returns, derived from external network effects (Airlines, Data Communications, Electricity and Shipping Lines), complementarity (Information Storage) or information content (Software), respectively; or as constant returns (Aircraft Manufacturing, Telecommunications Manufacturing and Shipbuilding). A comparison of discontinuities has been made between pairs of industries with a common end-user of the industry outputs, where one industry exhibits increasing returns and the companion industry has constant returns, using Binomial Distribution, Fisher's Exact Test and Generalised Linear Modelling techniques. Further Generalised Linear Models tested the interactions of discontinuities. Industries with increasing returns were found to have greater frequency of change. The types of change experienced were found to affect subsequent change, with both types of discontinuities being correlated with increased proportions of competency-enhancing change for ten years, while competency-destroying and competency-enhancing discontinuities were associated with increased frequency of change for twenty and ten years, respectively. The evidence associating increasing returns with competency type was unreliable. Consequently, increasing returns industries may experience a greater variation of frequency of change, with industries entering and leaving periods of enhanced frequencies of change. Thus, industries with increasing returns are more likely to experience change consistent with hypercompetition and high velocity conditions, compared with the punctuated equilibrium style change experienced by constant returns industries
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An economic theory of technological products
Technological Forecasting and Social Change, 1995
This paper presents the derivation and justification of a new economic theory of a manufacturing firm. It represents a mathematical extension of neoclassical economics in which the technological performance of a product is allowed to vary. The product's unit production costs is presented as a function of its technological performance, production rate, and product-design and production investments. Likewise, the product's unit sales price is presented as a function of its technological performance, sales rate, and advertising and marketing investments. By placing these price and cost functions in an elementary profit equation, a general theory of a manufacturing firm's profitability is achieved. Its mathematical feasibility is confirmed through a numerical example. Its conceptual validity, on the other hand, is confirmed by using it to interpret historical episodes of technological change. The theory of technological products is also used to calculate the conditions for maximizing the long-term profitability of a firm. The results show that neoclassical microeconomics is a restricted case of this theory. of this article is to introduce such a theory: a mathematical theory of a manufacturing firm, whose variables include the technological characteristics of the product. My immediate goal is to present the basic economic relationships that shape the development of technological products and production systems. Far from excluding sociological, political, engineering, and scientific inputs, however, these economic relationships are functions of those factors. Whether or not this theory of technological products will be suitable for technological forecasting, it provides a set of relationships that can increase the rigor
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Studies analyzing the impact of technological innovations on how an industry develops focus on the different effects produced by radical innovations versus incremental innovations. The studies either examine the technology cycles or the market development cycles in isolation without really explaining the interaction between the two. In this paper, we present a model of industry development that takes into account the dynamics of innovation in the industry accentuated by the interplay between technology development cycles and application development cycles. The model proposes that these two cycles go through a linked, predictable double helix pattern. The personal computer (PC) industry is used as an example of this model's operation, as the PC industry has gone through three distinct technology cycles (8-b, 16-b, and 32-b processors) and corresponding three distinct application cycles. We draw some important conclusions about how companies can use this understanding to develop better technology and market strategies to succeed in the various stages of the industry's development.