|
|
|
 |
 National Science
Foundation Award #0545544 |
 |
|
|
CAREER: Building Firm-Level Dynamic Capabilities in the Face of Radical Technological Innovation: The Role of Strategic Alliances and Star Scientists |
| |
| Investigator(s): |
Frank Rothaermel (PI)
|
| Sponsor: |
Georgia Tech Research Corporation - GA Institute of Technology, GA 30332 4043850866
|
| Start Date/Expiration Date |
2006-03-15 to 2007-02-28 (amended 2006-03-14) |
| Awarded Amount to Date: |
$115,906 |
| Abstract: The objective is to enhance our understanding of internal and external firm-level factors that explain why some firms survive and thrive when faced with radical technological innovation while others fail. Understanding firm-level heterogeneity is a defining question in the field of strategy. Studying this question in the context of radical technological innovation allows us to synthesize a diverse set of literatures, and thus to bridge the fields of strategy, innovation, and organizational change.
In particular, I attempt to develop a modified model of radical technological innovation. While the point of the departure remains an exogenous innovation, the revised model accounts for firm-level differences through a focus on dynamic capabilities that firms can build through strategic alliances and by recruiting intellectual human capital, especially highly productive scientists ("stars"). These two factors combine internal and external mechanisms that appear to be most effective in accomplishing a change in a firm' capabilities. This model will be tested on multiple original longitudinal datasets, and thus exposed to empirical falsification.
Assuming the modified model of radical technological innovation receives empirical support, researchers should be able to explain and predict firm-level heterogeneity more readily. Such a model would not only have academic value, but also enable managers to harness technological and organizational innovation more effectively, thus enhancing competitiveness, while avoiding some of the large scale layoffs that frequently result because of delayed or misguided responses to radical innovation. The theoretical model proposed will not only be useful to analyze the implications of technological change, but could also be extended to other industries and situations in which other exogenous shocks produce large restructurings of the competitive landscape such as deregulation and global integration. |
|
| NSF Org: |
SES - Division of Social and Economic Sciences |
| Award Number: |
0545544 |
| Award Instrument: |
Continuing grant |
| Program Manager: |
Robert E. O'Connor
SES Division of Social and Economic Sciences
SBE Directorate for Social, Behavioral & Economic Sciences
|
| NSF Program(s): |
DECISION RISK & MANAGEMENT SCI, INNOVATION & ORG CHANGE (IOC) |
| Field Application(s): |
|
| Program Reference Code(s): |
FACULTY EARLY CAREER DEVELOPMENT PROGRAM, 1045
PECASE- eligible, 1187
UNDERGRADUATE EDUCATION, 9178 |
| Program Element Code(s): |
1321
INNOVATION & ORG CHANGE (IOC), 5376 |
|
|
| |
 |
|
|
|
|
|
|
|
