Changes

 Are all startups affected similarly All Startups Affected Similarly by clusters Clusters by Aviad Pe'er and Thomas Keil

Path-Dependent Startup Hubs - Comparing Metropolitan Performance: High-Tech and ICT Startup Density by Dane Stangler @techreport{stangler_path-dependent_2013, address = {Rochester, NY}, title = {Path-{Dependent} {Startup} {Hubs} - {Comparing} {Metropolitan} {Performance}: {High}-{Tech} and {ICT} {Startup} {Density}}, shorttitle = {Path-{Dependent} {Startup} {Hubs} - {Comparing} {Metropolitan} {Performance}}, url = {https://papers.ssrn.com/abstract=2321145}, abstract = {Kansas City and other areas viewed as "new" startup hubs actually have been fostering a culture of entrepreneurship for some time. Many of these cities have a history of strong technology sectors or experienced strong growth among technology startups over the past two decades. A strong regional or local culture of technology entrepreneurship is not a recent phenomenon, contrary to the opinions of many. The top 10 cities in 2010 also ranked among the top 20 cities two decades earlier.This analysis shows that many cities' recent adoption of new entrepreneurship programs is more an indication of the underlying strength of the region and its base of talent on which those programs can build than it is a cause of startup activity. Cities such as Kansas City, Seattle, Portland and Boise all owe their emerging entrepreneurial ecosystems to many years of spinoffs and entrepreneurial spawning.Research universities and other postsecondary institutions are important for metropolitan entrepreneurship, but are not the sole cause in spurring such activity. Instead, the most fertile source of entrepreneurial spawning is the population of existing companies, which has implications for economic policymaking and economic development strategies.Entrepreneurs come from somewhere - this seems obvious, but that observation runs against the prevailing stereotype that entrepreneurs are, or should be, recent college grads or college dropouts. That 'somewhere' usually is a previous job in a big company or at an institution, such as a university, which helps explain the age distribution of entrepreneurs.However, regions should be careful in turning these observations into policy. While spinoffs are important for tech startup growth, such a strategy could be wrongly interpreted as supporting traditional economic development strategies of tax incentives for big companies. More work must be done to understand the local and regional dynamics of entrepreneurship, barriers that may exist to catalyzing a self-fulfilling dynamic of entrepreneurial spinoffs and what the proper role of supporting institutions should be.}, number = {ID 2321145}, urldate = {2017-10-24}, institution = {Social Science Research Network}, author = {Stangler, Dane}, month = sep, year = {2013}, keywords = {entrepreneur, local entrepreneurship, regional entrepreneurship, startup hub} Tech Starts: High-Technology Business Formation and Job Creation in the United States by Ian Hathaway @techreport{hathaway_tech_2013, address = {Rochester, NY}, title = {Tech {Starts}: {High}-{Technology} {Business} {Formation} and {Job} {Creation} in the {United} {States}}, shorttitle = {Tech {Starts}}, url = {https://papers.ssrn.com/abstract=2310617}, abstract = {New and young businesses — as opposed to small businesses generally — play an outsized role in net job creation in the United States. But not all new businesses are the same — the substantial majority of nascent entrepreneurs do not intend to grow their businesses significantly or innovate, and many more never do. Differentiating growth-oriented “start-ups” from the rest of young businesses is an important distinction that has been underrepresented in research on business dynamics and in small business policy.To advance the conversation, we contrast business and job creation dynamics in the entire U.S. private sector with the innovative high-tech sector — defined here as the group of industries with very high shares of employees in the STEM fields of science, technology, engineering, and math. We highlight these differences at the national level, as well as detailing regions throughout the country where high-tech start-ups are being formed each year. The major findings include:• The high-tech sector and the information and communications technology (ICT) segment of high-tech are important contributors to entrepreneurship in the U.S. economy. During the last three decades, the high-tech sector was 23 percent more likely and ICT 48 percent more likely than the private sector as a whole to witness a new business formation.• High-tech firm births were 69 percent higher in 2011 compared with 1980; they were 210 percent higher for ICT and 9 percent lower for the private sector as a whole during the same period. This is important because the productivity growth and job creation unleashed by these new and young firms — aged less than five years — require a continual flow of births each year.• Of new and young firms, high-tech companies play an outsized role in job creation. High tech businesses start lean but grow rapidly in the early years, and their job creation is so robust that it offsets job losses from early-stage business failures. This is a key distinction from young firms across the entire private sector, where net job losses resulting from the high rate of early-stage failures are substantial.• Young firms exhibit an “up-or-out” dynamic, where they tend to either fail or grow rapidly in the early years. The job-creating strength of surviving young firms, while strong for young businesses across the private sector as a whole, is especially distinct for high-tech start-ups: the net job creation rate of these surviving young firms is twice as robust. • High-tech and ICT firm formations are becoming increasingly geographically dispersed. As technological advancement allows for the production of high-tech goods and services in a wider set of areas, many regions are catching up. The opposite has been true for the private sector as a whole, where new business growth has been occurring most in regions with already higher rates of new business formation.}, number = {ID 2310617}, urldate = {2017-10-24}, institution = {Social Science Research Network}, author = {Hathaway, Ian}, month = aug, year = {2013}, keywords = {entrepreneur, entrepreneurship, high-tech, job creation, startup, technology} Venture Capitalists and Cooperative Start-up Commercialization Strategy by David H. Hsu @article{hsu_venture_2006, title = {Venture {Capitalists} and {Cooperative} {Start}-up {Commercialization} {Strategy}}, volume = {52}, issn = {0025-1909}, url = {http://pubsonline.informs.org/doi/abs/10.1287/mnsc.1050.0480}, doi = {10.1287/mnsc.1050.0480}, abstract = {This paper examines the possible impact of venture capital (VC) backing on the commercialization direction of technology-based start-ups by asking: To what extent (if at all) do VC-funded start-ups engage in cooperative commercialization strategies (strategic alliances or technology licensing, or both) relative to a comparable set of start-ups, and with what consequences? To address these questions, I assemble a novel data set that matches firms receiving a federal research and development subsidy through the U.S. Small Business Innovative Research program to VC-funded firms by observable characteristics in five technology-intensive industries. These data allow decoupling of cooperative activity resulting from start-up development via the passage of calendar time from that due to association with VCs. An analysis of the 696 start-ups in the sample (split by an external funding source) suggests substantial boosts in both cooperative activity associated with VC-backed firms and in the likelihood of an initial public offering.}, number = {2}, urldate = {2017-10-27}, journal = {Management Science}, author = {Hsu, David H.}, month = feb, year = {2006}, pages = {204--219} University start-up formation and technology licensing with firms that go public by Joshua Powers @article{powers_university_2005, title = {University start-up formation and technology licensing with firms that go public: a resource-based view of academic entrepreneurship}, volume = {20}, issn = {0883-9026}, shorttitle = {University start-up formation and technology licensing with firms that go public}, url = {http://www.sciencedirect.com/science/article/pii/S0883902604000291}, doi = {10.1016/j.jbusvent.2003.12.008}, abstract = {Although academic entrepreneurship is a topic receiving some attention in the literature, higher education's appetite for expanding technology transfer activities suggests that more research is needed to inform practice. This study investigates the effects of particular resource sets on two university commercialization activities: the number of start-up companies formed and the number of initial public offering (IPO) firms to which a university had previously licensed a technology. Utilizing multisource data on 120 universities and a resource-based view of the firm framework, a set of university financial, human capital, and organizational resources were found to be significant predictors of one or both outcomes.}, number = {3}, urldate = {2017-10-27}, journal = {Journal of Business Venturing}, author = {Powers, Joshua B. and McDougall, Patricia P.}, month = may, year = {2005}, keywords = {Entrepreneurship, Industry, Start-up formation, University}, pages = {291--311} A taxonomy of business start-up reasons and their impact on firm growth and size by Sue Birley and Paul Westhead @article{birley_taxonomy_1994, title = {A taxonomy of business start-up reasons and their impact on firm growth and size}, volume = {9}, issn = {0883-9026}, url = {http://www.sciencedirect.com/science/article/pii/0883902694900248}, doi = {10.1016/0883-9026(94)90024-8}, abstract = {Based on a survey of 405 principal owner-managers of new independent business in Great Britain this paper explores two research questions— are there any differences in the reasons that owner-managers articulate for starting their businesses, and, if there are, do they appear to affect the subsequent growth and size of the businesses? The results of the study indicate an affirmative answer to the first question. From the 23 diverse reasons leading to start-up that were identified in the literature, an underlying pattern emerged via the Principal Components Analysis. Moreover, these were similar to those found in earlier studies. Thus, five of the seven components identified by the model correspond to those identified by Scheinberg and MacMillan (1988) in their eleven-country study of motivations to start a business: “Need for Approval,” “Need for Independence,” “Need for Personal Development,” “Welfare Considerations,” and “Perceived Instrumentality of Wealth.” Two further components were identified by this current study. The first vindicates the decision to add a question not included in the previous study that related to “Tax Reduction and Indirect Benefits,” and the second, the desire to “Follow Role Models” was identified by Dubini (1988) in her study in Italy. In order to take account of possible multiple motivations in the start-up period, cluster analysis was used to provide a classification of founder “types.” The seven generalized “types” of owner-managers were named as follows—the insecure (104 founders), the followers (49 founders), the status avoiders (169 founders), the confused (15 founders), the tax avoiders (18 founders), the community (49 founders), and the unfocused (1 founder). Further, evidence from the final discriminant analysis model suggested that the seven-cluster classification of owner-managers was appropriate and optimal. However, despite these clear differences between clusters, this was not found to be an indicator of subsequent size or growth, as measured by sales and employment levels. The answer to the second research question would be in the negative. Therefore, we conclude that, whereas new businesses are founded by individuals with significantly different reasons leading to start-up, once the new ventures are established these reasons have a minimal influence on the growth of new ventures and upon the subsequent wealth creation and job generation potential. This result is important for investors and policy-makers. It suggests that strategies for “picking winners” solely based upon the characteristics of owner-managers and their stated reasons for wanting to go into business are not supported. Thus, for example, targeting scarce resources to those with high opportunistic and materialistic reasons for venture initiation would miss those with a wider sense of community or those with personal needs for independence who establish similarly sized businesses with comparable levels of wealth creation.}, number = {1}, urldate = {2017-10-27}, journal = {Journal of Business Venturing}, author = {Birley, Sue and Westhead, Paul}, month = jan, year = {1994}, pages = {7--31} The New Economics Off Innovation, Spillovers And Agglomeration: Areview A review Of Empirical Studies by Maryann P. Feldman

abstract = {This paper reviews recent empirical studies of location and innovation. The objective is to highlight the questions addressed, approaches adopted, and further issues that remain. The review is organized around the traditions of measuring geographically mediated spillovers and productivity studies that introduce a geographic dimension. The first part identilies identities four separate strains in thc the empirical spillover literature: innovation production functions; the linkages between patent citations. defined as paper trails: the rnobility of skilled labor based on the notion that knowledge spillovers are transmitted through people; and, last, knowledge spillovers embodied in traded goods. The second part considers the composition of agglomeration economies, the attributes of knowlcdgeknowledge, and the characteristics of firms.},

@article{rosenthal_geography_2003,

urldate = {2017-1011-2806},