First Advisor

James G. Strathman

Date of Publication


Document Type


Degree Name

Doctor of Philosophy (Ph.D.) in Urban Studies


Urban Studies and Planning




High technology industries -- Location, Metropolitan areas -- United States



Physical Description

4, vii, 129 leaves: ill. 28 cm.


The theme of high-technology economic base and regional development, around which this research is based, has been receiving increased attention from policy-makers and researchers in recent years. This partly reflects the reappraisal of the emerging structural changes which have been stimulated by the negative effects of the economic recessions of the past decade. It also reflects the rapid growth and expansion of high-technology firms in centers like the well-publicized Silicon Valley in California, Route 128 in Massachusetts, and the Research Triangle in North Carolina. Promoting a high-technology economic base thus has been widely adopted as a regional development policy for the 1980s. The objective of this research is to examine and analyze those attributes of the regional economy that contribute to the start-up and expansion of high-technology activity. It is hypothesized that the forces determining where new firms will locate are different from those determining whether existing firms expand, contract, or move. This study utilizes the product life cycle model as the conceptual framework, and seeks to identify factors and conditions which are critical in determining the growth and locational patterns of high technology firms. To address the suggested hypotheses, this study involves an analysis of the 100 largest U.S. metropolitan areas covering the period from 1976 to 1984. High-technology firms were selected as those Standard Industrial Classifications (SICs) with a proportion of technology-oriented workers equal to or greater than the average for all manufacturing industries, and whose ratios of R&D expenditures to sales were close to or above average for all industries. Data on birth rates, closure rates, expansion rates, contraction rates, and net change in number of firms were used as dependent variables in the analysis. Independent variables were various measures of high-technology employment, total employment, venture capital, research and development, average housing price, state corporate tax rate, tax effort, average manufacturing wage, industrial incentive, transportation access, climate index, effective property tax rate, unitary tax, and U.S. regions. A descriptive analysis of the geographic variations in dependent variables, and tests of significance to determine if there are differences in values among U.S. census regions, is reported. The result showed that high-technology firms growth rate is not distributed evenly across the regions. The regional differences in high-tech growth rates are largely due to differences in birth rates. The West South Central, Pacific, and South Atlantic regions have the highest birth rates of high-technology firms; while New England States and Northeast regions have the lowest birth rates of high-tech firms. Expansion and closure rates parallel the same pattern as birth rates, while contraction rates are relatively consistent in all regions. Multiple regression analysis was employed to test the relationships between dependent and independent variables. Results showed that high levels of high-technology employment were not positively associated with the growth rate of high-technology firms. The high-tech employment variable, however, did not distinguish between the proportion of low and high-tech occupations among high-tech industry grouping and, therefore, may not represent the availability of highly skilled labor. The wage rate variable, which reflects skill levels, indicates a positive relationship with birth and closure rates. This result is an indication that a high level of wage is positively associated with high-tech birth as well as closure, suggesting that the causal relationship may be operating in the opposite direction. That is, high-technology activity drives up wage rates thereby reflecting probable skill levels. Moreover, it appears that high-technology firms are less sensitive to wage rates. Housing price is both positively related and statistically significant to expansion rates. This did not, however imply that the cost of housing may be a cause for expansion, but rather may represent a growth pressure on the housing supply due to job location. Furthermore, from the results presented in this study, factors such as venture capital, industrial incentives, amenities, and transportation accessibility were found to have very low or negligible association with the growth rate of high-technology firms. Other location factors, such as taxes, were negatively related. The research findings of this study tended not to support the product cycle model. On the basis of these findings, the present research suggests caution in using the product cycle model for interpreting and explaining the development of high-technology complexes. This study concludes that there may be a need to incorporate market, time and place oriented concept to future study that will contribute more to the understanding of high technology development so that communities seeking to attract high-technology firms can understand the stages of a company's growth, the products it makes, the type of work force it employs, and the attributes of the area.


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