Technology Development and Innovative Practice

Technology Development and Innovative Practice

Robert S. Friedman (New Jersey Institute of Technology, USA), Desiree M. Roberts (Rensselaer Polytechnic Institute, NY, USA) and Jonathan D. Linton (Rensselaer Polytechnic Institute, NY, USA)
DOI: 10.4018/978-1-60566-038-7.ch003
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Abstract

This chapter on innovative practice supporting technological development has several thematic overlays that show some consistency in terms of patterns, but also some diversity in terms of strategies that researchers have employed in this area. Beginning with Hage and Aiken’s (1969) seminal work on routinization and how the social structures of organizations affect technological development and innovation, readers will see two general trends in terms of approach: the statistical and the sociological. Whether it is Aldrich’s (1972) use of path analysis to study the nature and effects of organizational variables on innovative practice, or Rothwell et al.’s (1974) identification of innovation success factors, or Downs and Mohr’s (1976) defining of innovation through factors of variability, quantitative methods are shown to be increasingly powerful tools in identifying the nature of innovation and technology development. Nelson and Winter (1977) continue in this vein by establishing an inclusive theoretical structure for innovation, Dewar and Hage (1978) identify variables of structural differentiation and complexity that affect this domain, and Kimberly and Evanisko (1981) suggest variables to follow that come from both within individual organization units and their wider contexts. Pavitt (1984) uses sectoral pattern analysis to describe how a combination of technology sources, user requirements, and potential technology appropriation affect how we understand technical change and the structural relationships between technology and industry. Fisher and Fry (1971) end the quantitatively based section with a discussion of their substitution forecasting model.
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Introduction

This chapter on innovative practice supporting technological development has several thematic overlays that show some consistency in terms of patterns, but also some diversity in terms of strategies that researchers have employed in this area. Beginning with Hage and Aiken’s (1969) seminal work on routinization and how the social structures of organizations affect technological development and innovation, readers will see two general trends in terms of approach: the statistical and the sociological. Whether it is Aldrich’s (1972) use of path analysis to study the nature and effects of organizational variables on innovative practice, or Rothwell et al.’s (1974) identification of innovation success factors, or Downs and Mohr’s (1976) defining of innovation through factors of variability, quantitative methods are shown to be increasingly powerful tools in identifying the nature of innovation and technology development. Nelson and Winter (1977) continue in this vein by establishing an inclusive theoretical structure for innovation, Dewar and Hage (1978) identify variables of structural differentiation and complexity that affect this domain, and Kimberly and Evanisko (1981) suggest variables to follow that come from both within individual organization units and their wider contexts. Pavitt (1984) uses sectoral pattern analysis to describe how a combination of technology sources, user requirements, and potential technology appropriation affect how we understand technical change and the structural relationships between technology and industry. Fisher and Fry (1971) end the quantitatively based section with a discussion of their substitution forecasting model.

From a more qualitative orientation, Abernathy and Clark (1985) introduce “transilience,” or a set of categories of technological change that is aligned with evolutionary developments that are altered by varying managerial environments. Anderson and Tushman (1990) continue on the evolutionary track with an explanation of their cyclical model of technological change. Their model shares some basic affinities with Clark’s (1985) evolutionary based view of technological change shaped by customer demands. Barley (1986, 1990) presents two sociologically oriented sets of ideas, one examining patterns of action and interaction, and the other presenting the benefits of examining the interaction between social action and social form in technologically innovative organizations. Dosi (1982), concluding this chapter, invokes the Kuhnian paradigm to demonstrate the strength of identifying patterns of continuous changes and moments of discontinuity in technologically innovative environments.

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