Nachwuchsstipendium des SNF
Type
applied research project
Start Date
January 1, 2007
End Date
October 1, 2007
Status
ongoing
Keywords
Innovation Control
Industry Dynamics
Description
Together, R&D's complexity, the growing importance of effective innovation efforts for company success, and the increased pressure on R&D to be accountable regarding its actual contribution to company success have aroused the need for formal innovation control. Although it is still controversial that the use of a formal control mechanism in the strategic management of R&D projects is as effective as in the development phase, formalizing the early phases of the innovation process is necessary. Effectively controlling strategic issues of the innovation process, however, is one of the most important, difficult challenges innovation managers face today.
The purpose of this study is to define innovation control mechanisms for firms in high-velocity environments that assure the congruence of the strategic management of innovation and the corporate planning process. The traditional 'strategy of hope' approach to innovation has been replaced by a very systematic one that builds a key cornerstone of business strategy. Control formalizes the decision to invest in technologies or new product developments with the aim of optimizing rationality. Thus, innovation control is understood to support innovation management in leading personal, structuring and handling innovation processes to support effectiveness. A focus is put on time related issues of the strategic management of R&D projects as being the most crucial for firm's competitiveness.
Even though for many firms, innovation is now the single most important factor driving firm success or failure, differences in firms' characteristics require a contingency approach to examine the impact of high-velocity environments on innovation control. Industry's clockspeed is used as a measure of the dynamic nature of an industry. A model will support firms in designing control approaches for different environments.
As the formal control of strategic innovation issues constitutes a young empirical phenomenon an exploratory research method, focusing on qualitative research, has been chosen. Case studies will illustrate modes of formal control in the strategic management of R&D projects and validate the previous propositions as well as first findings out of a benchmarking on innovation control mechanisms. Data analysis will lead to extend existing theory by formulating hypotheses.
The purpose of this study is to define innovation control mechanisms for firms in high-velocity environments that assure the congruence of the strategic management of innovation and the corporate planning process. The traditional 'strategy of hope' approach to innovation has been replaced by a very systematic one that builds a key cornerstone of business strategy. Control formalizes the decision to invest in technologies or new product developments with the aim of optimizing rationality. Thus, innovation control is understood to support innovation management in leading personal, structuring and handling innovation processes to support effectiveness. A focus is put on time related issues of the strategic management of R&D projects as being the most crucial for firm's competitiveness.
Even though for many firms, innovation is now the single most important factor driving firm success or failure, differences in firms' characteristics require a contingency approach to examine the impact of high-velocity environments on innovation control. Industry's clockspeed is used as a measure of the dynamic nature of an industry. A model will support firms in designing control approaches for different environments.
As the formal control of strategic innovation issues constitutes a young empirical phenomenon an exploratory research method, focusing on qualitative research, has been chosen. Case studies will illustrate modes of formal control in the strategic management of R&D projects and validate the previous propositions as well as first findings out of a benchmarking on innovation control mechanisms. Data analysis will lead to extend existing theory by formulating hypotheses.
Leader contributor(s)
Perez-freije, Javier
Funder
Division(s)
Eprints ID
32418