This study investigates the impacts of regional characteristics on the early-stage performance of New Technology-Based Firms (NTBFs) in catch-up regions where a mature industrial cluster has yet to be formed. It hypothesized that the average NTBF performance in a region is a function of its scientist job market conditions, cultural diversity, venture capital, academic research, industrial structure, and local entrepreneurial climate. Using the events of Initial Public Offerings (IPO) and Merger & Acquisitions (M&A) as an indicator of early-stage success of NTBFs, this study constructs a set of Zero-Inflated-Negative-Binomial (ZINB) models to predict the spatial distribution of such events in the U.S. biopharmaceutical and Information Technology (IT) service industries during the period from 1996 to 2005.
Several empirical findings emerge from this study. First, the local entrepreneurial climate plays a significant and positive role on NTBF performance in both industries. Second, the positive impact of cultural diversity is more significant in the IT service industry than in the biopharmaceutical industry. Third, the scientist job market size and absolute salary level have positive impacts on NTBF performance, but the effect of relative salary level is negative. Fourth, proximity to venture capital firms has positive but non-linear effects, but the adverse effect of excess venture capital is stronger in the IT service industry. Fifth, there is little evidence of the direct effects of academic research in determining the NTBF performance in both industries. Finally, industrial specialization is significant and positive only in the IT service industry. The results suggest that promoting local entrepreneurial climate and cultural diversity are two effective policy instruments for catch-up regions to foster their NTBF growth.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/22547 |
| Date | 01 April 2008 |
| Creators | Xiao, Wenbin |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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