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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
business, management and accounting
Multi-mode interaction among technologies
Research Policy, Volume 26, No. 1, Year 1997
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Description
Technological innovation is manifested in the development of new products, processes and techniques such that emerging technologies often substitute for more mature technologies. The interaction between technologies is typically referred to as competition, implying a confrontational interaction. The setting of technology strategy is thus often concerned with issues relating to the competition between emerging technologies and the response of mature technologies to the offense from emerging technologies - strategies for attack and defense. In this paper it is argued that the interaction between technologies should be viewed in a broader sense than mere competition, and it is suggested that a multi-mode framework provides a much richer setting for assessing the interaction of two or more technologies. This concept has been successfully applied in biological and organizational ecology, and it is shown that it can be equally useful when applied to the dynamics of technological interaction. It is proposed that the effect that one technology has on another's growth rate be taken as a classification criterion. Examples are given to illustrate that three major modes of interaction exist, namely pure competition, symbiosis and predator-prey. In addition, the notion that the interaction between technologies can in general shift temporally from one mode to another is motivated. It is suggested that, since the characteristics of the three modes differ from one another, it is appropriate to develop managerial strategies that apply specifically to each of the three modes, instead of just applying generic 'competition' strategies. © 1997 Elsevier Science B.V. All rights reserved.
Authors & Co-Authors
Pistorius, Carl W.I.
South Africa, Pretoria
University of Pretoria
Utterback, James M.
United States, Cambridge
Mit Sloan School of Management
Statistics
Citations: 187
Authors: 2
Affiliations: 2
Identifiers
Doi:
10.1016/S0048-7333(96)00916-X
ISSN:
00487333