Time versus market orientation in product concept development: Empirically-based theory generation

Time versus market orientation in product concept development: Empirically-based theory generation

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Article ID: iaor19982119
Country: United States
Volume: 43
Issue: 4
Start Page Number: 465
End Page Number: 478
Publication Date: Apr 1997
Journal: Management Science
Authors: ,
Keywords: quality & reliability, research
Abstract:

In collaboration with industry partners, a normative model of the product concept decision process was developed, supported with tools and techniques, and codified as a decision support process for product development teams. This process (Concept Engineering) was then introduced into a number of product development teams in different companies. A comparative analysis of actual product concept development activities, with and without the use of Concept Engineering, was conducted. All of the observed teams viewed time to market as a critical measure of their success. However, the development processes differed significantly depending on whether relatively more emphasis was placed on time or market considerations. Key variables associated with the product concept development decision process and time-to-market dynamics were identified and a theory of the concept development process was developed using the inductive sytsem diagram technique, a research methodology developed in the course of this work. We believe this work contributes to the operations management literature in three ways. First, it introduces a very detailed, structured decision process for product concept development, enhancing the literature on Quality Function Deployment. Second, it presents a theory of product concept development that can improve understanding of success and failure in product concept development. Third, this work develops new methodology (Inductive Systems Diagrams) for field work in operations management. This methodology marries the grounded theory methods familiar to sociologists with causal-loop modeling familiar to systems dynamicists, yielding a rigorous tool for systematically collecting, organizing, and distilling large amounts of field-based data.

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