Startup Density Literature Review

McNair Project

Startup Density Literature Review
Project Information
Project Title	Startup Density Literature Review
Owner	Yunnie Huang
Start Date	10/23/2017
Deadline
Primary Billing
Notes
Has project status
Is dependent on	Urban Start-up Agglomeration
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Below is a list of citations I have gathered looking up key words related to startup density, clustering, and agglomeration.

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}

startup clustering

Super-peer-based Routing and Clustering Strategies for RDF-based Peer-to-peer Networks by Wolfgang Nejdi

  @inproceedings{nejdl_super-peer-based_2003,
  address = {New York, NY, USA},
  series = {{WWW} '03},
  title = {Super-peer-based {Routing} and {Clustering} {Strategies} for {RDF}-based {Peer}-to-peer {Networks}},
  isbn = {9781581136807},
  url = {http://doi.acm.org/10.1145/775152.775229},
  doi = {10.1145/775152.775229},
  abstract = {RDF-based P2P networks have a number of advantages compared with simpler P2P networks such as Napster, Gnutella or with approaches based on distributed indices such as CAN and CHORD. RDF-based P2P networks allow complex and extendable descriptions of resources instead of fixed and limited ones, and they provide complex query facilities against these metadata instead of simple keyword-based searches.In previous papers, we have described the Edutella infrastructure and different kinds of Edutella peers implementing such an RDF-based P2P network. In this paper we will discuss these RDF-based P2P networks as a specific example of a new type of P2P networks, schema-based P2P networks and describe the use of super-peer based topologies for these networks. Super-peer based networks can provide better scalability than broadcast based networks, and do provide perfect support for inhomogeneous schema-based networks, which support different metadata schemas and ontologies (crucial for the Semantic Web). Furthermore, as we will show in this paper, they are able to support sophisticated routing and clustering strategies based on the metadata schemas, attributes and ontologies used. Especially helpful in this context is the RDF functionality to uniquely identify schemas, attributes and ontologies. The resulting routing indices can be built using dynamic frequency counting algorithms and support local mediation and transformation rules, and we will sketch some first ideas for implementing these advanced functionalities as well.},
  urldate = {2017-10-27},
  publisher = {ACM},
  author = {Nejdl, Wolfgang and Wolpers, Martin and Siberski, Wolf and Schmitz, Christoph and Schlosser, Mario and Brunkhorst, Ingo and Löser, Alexander},
  year = {2003},
  keywords = {distributed RDF repositories, peer-to-peer, schema-based routing, semantic web},
  pages = {536--543}

Lowest-ID with adaptive ID reassignment by D. Gavalas

  @inproceedings{gavalas_lowest-id_2006,
  title = {Lowest-{ID} with adaptive {ID} reassignment: a novel mobile ad-hoc networks clustering algorithm},
  shorttitle = {Lowest-{ID} with adaptive {ID} reassignment},
  doi = {10.1109/ISWPC.2006.1613559},
  abstract = {Clustering is a promising approach for building hierarchies and simplifying the routing process in mobile ad-hoc network environments. The main objective of clustering is to identify suitable node representatives, i.e. cluster heads (CHs), to store routing and topology information and maximize clusters stability. Traditional clustering algorithms suggest CH election exclusively based on node IDs or location information and involve frequent broadcasting of control packets, even when network topology remains unchanged. More recent works take into account additional metrics (such as energy and mobility) and optimize initial clustering. However, in many situations (e.g. in relatively static topologies) re-clustering procedure is hardly ever invoked; hence initially elected CHs soon reach battery exhaustion. Herein, we introduce an efficient distributed clustering algorithm that uses both mobility and energy metrics to provide stable cluster formations. CHs are initially elected based on the time and cost-efficient lowest-ID method. During clustering maintenance phase though, node IDs are re-assigned according to nodes mobility and energy status, ensuring that nodes with low-mobility and sufficient energy supply are assigned low IDs and, hence, are elected as CHs. Our algorithm also reduces control traffic volume since broadcast period is adjusted according to the nodes mobility pattern: we employ infrequent broadcasting for relative static network topologies, and increase broadcast frequency for highly mobile network configurations. Simulation results verify that energy consumption is uniformly distributed among network nodes and that signaling overhead is significantly decreased.},
  booktitle = {2006 1st {International} {Symposium} on {Wireless} {Pervasive} {Computing}},
  author = {Gavalas, D. and Pantziou, G. and Konstantopoulos, C. and Mamalis, B.},
  month = jan,
  year = {2006},
  keywords = {Ad hoc networks, Batteries, Broadcasting, Clustering algorithms, Communication system traffic control, Intrusion detection, Network topology, Nominations and elections, Routing, Stability, ad hoc networks, adaptive ID reassignment, battery exhaustion, broadcast period, broadcasting, cluster heads, clustering maintenance, control packets, control traffic volume, cost-efficient lowest-ID method, distributed clustering algorithm, energy metrics, highly mobile network configurations, infrequent broadcasting, mobile ad-hoc networks clustering algorithm, mobile radio, nodes mobility, nodes mobility pattern, relative static network topologies, routing process, stable cluster formations, telecommunication network routing, telecommunication network topology, topology information},
  pages = {5 pp.--}

A P2P hierarchical clustering live video streaming system by De-Kai Liu and Ren-Hung Hwang

  @inproceedings{liu_p2p_2003,
  title = {A {P}2P hierarchical clustering live video streaming system},
  doi = {10.1109/ICCCN.2003.1284158},
  abstract = {This paper describes P2broadcast, a novel live video streaming system for P2P networks which organizes peers into hierarchical clusters to reduce startup latency and the service interruption probability. P2broadcast has two key features: highly available and efficient join, and low service interruption probability. The highly available and efficient join algorithm uses RTT of two peers as a hint of available bandwidth between them. As a consequence, the startup latency can be shortened and overhead can be reduced. In addition, P2broadcast constructs a "short and wide" overlay tree which reduces the probability of service interruption due to the leave or failure of a peer. Our simulation results show that P2broadcast outperforms in startup latency and service interrupt probability over existing approaches in the literature.},
  booktitle = {Proceedings. 12th {International} {Conference} on {Computer} {Communications} and {Networks} ({IEEE} {Cat}. {No}.03EX712)},
  author = {Liu, De-Kai and Hwang, Ren-Hung},
  month = oct,
  year = {2003},
  keywords = {Availability, Bandwidth, Clustering algorithms, Computer science, Delay estimation, IP networks, Information retrieval, Internet, Network servers, Scalability, Streaming media, application level multicasting, hierarchical clustering, live video streaming system, multicast communication, overlay tree network, peer broadcast, peer-to-peer network, round trip time, service interruption probability, startup latency},
  pages = {115--120}

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 Of Empirical Studies by Maryann P. Feldman

  @article{feldman_new_1999,
  title = {The {New} {Economics} {Of} {Innovation}, {Spillovers} {And} {Agglomeration}: {Areview} {Of} {Empirical} {Studies}},
  volume = {8},
  issn = {1043-8599},
  shorttitle = {The {New} {Economics} {Of} {Innovation}, {Spillovers} {And} {Agglomeration}},
  url = {http://dx.doi.org/10.1080/10438599900000002},
  doi = {10.1080/10438599900000002},
  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 four separate strains in thc 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 knowlcdge, and the characteristics of firms.},
  number = {1-2},
  urldate = {2017-10-28},
  journal = {Economics of Innovation and New Technology},
  author = {Feldman, Maryann P.},
  month = jan,
  year = {1999},
  keywords = {Geography, Innovation, L2, Location JEL Classification: 03, Spillovers},
  pages = {5--25}

Geography, Industrial Organization, and Agglomeration by Stuart S. Rosenthal and William C. Strange

  @article{rosenthal_geography_2003,
  title = {Geography, {Industrial} {Organization}, and {Agglomeration}},
  volume = {85},
  issn = {0034-6535},
  url = {https://doi.org/10.1162/003465303765299882},
  doi = {10.1162/003465303765299882},
  number = {2},
  urldate = {2017-10-28},
  journal = {The Review of Economics and Statistics},
  author = {Rosenthal, Stuart S. and Strange, William C.},
  month = may,
  year = {2003},
  pages = {377--393}

Chapter 49 - Evidence on the Nature and Sources of Agglomeration Economies by Stuart S. Rosenthal and William C. Strange

  @incollection{rosenthal_chapter_2004,
  series = {Cities and {Geography}},
  title = {Chapter 49 - {Evidence} on the {Nature} and {Sources} of {Agglomeration} {Economies}},
  volume = {4},
  url = {http://www.sciencedirect.com/science/article/pii/S1574008004800063},
  abstract = {This paper considers the empirical literature on the nature and sources of urban increasing returns, also known as agglomeration economies. An important aspect of these externalities that has not been previously emphasized is that the effects of agglomeration extend over at least three different dimensions. These are the industrial, geographic, and temporal scope of economic agglomeration economies. In each case, the literature suggests that agglomeration economies attenuate with distance. Recently, the literature has also begun to provide evidence on the microfoundations of external economies of scale. The best known of these sources are those attributed to Marshall (1920): labor market pooling, input sharing, and knowledge spillovers. Evidence to date supports the presence of all three of these forces. In addition, there is also evidence that natural advantage, home market effects, consumption opportunities, and rent-seeking all contribute to agglomeration.},
  urldate = {2017-10-28},
  booktitle = {Handbook of {Regional} and {Urban} {Economics}},
  publisher = {Elsevier},
  author = {Rosenthal, Stuart S. and Strange, William C.},
  editor = {Henderson, J. Vernon and Thisse, Jacques-François},
  month = jan,
  year = {2004},
  note = {DOI: 10.1016/S1574-0080(04)80006-3},
  keywords = {agglomeration economies, external economies, microfoundations, productivity, urban growth},
  pages = {2119--2171}

Aspiring, nascent and fledgling entrepreneurs: an investigation of the business start-up process by Beate Rotefoss and Lars Kolvereid

  @article{rotefoss_aspiring_2005,
  title = {Aspiring, nascent and fledgling entrepreneurs: an investigation of the business start-up process},
  volume = {17},
  issn = {0898-5626},
  shorttitle = {Aspiring, nascent and fledgling entrepreneurs},
  url = {http://rsa.tandfonline.com/doi/abs/10.1080/08985620500074049}
  doi = {10.1080/08985620500074049},
  abstract = {This study focuses on three different milestones in the business gestation process, i.e. becoming an aspiring entrepreneur, a nascent entrepreneur, and a founder of a fledgling new business. Moreover, this study uses a combination of both individual and regional (or environmental) factors in predicting individuals’ success or failure to reach each of these three milestones. Hypotheses are developed to test the effect that human and environmental resources have on the odds of reaching the different milestones in the business start-up process. The study is based on interviews of a representative sample of 9533 Norwegians aged 18 years or older. From this group, 197 respondents qualified as nascent entrepreneurs. These were subsequently interviewed in follow-up interviews conducted in 1996, 1997 and 1999. In addition, regional data at the municipality level is included to measure the available pool of environmental resources. The results indicate that entrepreneurial experience is the single most important factor for predicting the outcome of the business start-up process. Even though environmental resources play a role, human resources are generally found to be better predictors of the outcome of the business start-up process. Several important implications for policy-makers are presented.},
  number = {2},
  urldate = {2017-10-28},
  journal = {Entrepreneurship \& Regional Development},
  author = {Rotefoss, Beate and Kolvereid, Lars},
  month = mar,
  year = {2005},
  pages = {109--127}

@article{peer_who_2008, title = {Who enters, where and why? {The} influence of capabilities and initial resource endowments on the location choices of de novo enterprises}, volume = {6}, issn = {1476-1270}, shorttitle = {Who enters, where and why?}, url = {https://doi.org/10.1177/1476127008090007}, doi = {10.1177/1476127008090007}, abstract = {Some geographical locations have characteristics that create opportunities for de novo enterprises, but not all new firms can access the benefits presented by a potential location. The ability of new firms to appropriate benefit and avoid risk depends on the resources that entrepreneurs can marshal for their enterprise. This article develops a model of the interplay between the attributes of de novo entrants and their founding locations. The model assumes that de novo entrants tend to appear in the region where their founders live, but that founders choose among locations within their regions.The test of the model, using data on all de novo entrants in the Canadian manufacturing sector during 1984—98, reveals that entrants with greater resource and capability endowments are more likely to locate in areas with an agglomeration of similar firms, but this effect reverses at high endowment levels. Additionally, larger entrants are less likely to locate in areas characterized by intense local competition and potential entry deterrence, while smaller and well-endowed entrants tend to locate in areas where entry barriers are lower and asset turnover higher. These findings suggest that entrants choose locations strategically within their founding regions.They also indicate that the strategic imperatives of de novo entrants differ significantly from those of geographically diversifying firms, and thus suggest amendments to theories of location choice when modeling the decisions of new ventures.}, language = {en}, number = {2}, urldate = {2017-10-31}, journal = {Strategic Organization}, author = {Pe'er, Aviad and Vertinsky, Ilan and King, Andrew}, month = may, year = {2008}, pages = {119--149}

@article{peer_are_2013, title = {Are all startups affected similarly by clusters? {Agglomeration}, competition, firm heterogeneity, and survival}, volume = {28}, issn = {0883-9026}, shorttitle = {Are all startups affected similarly by clusters?}, url = {http://www.sciencedirect.com/science/article/pii/S0883902612000626}, doi = {10.1016/j.jbusvent.2012.03.004}, abstract = {Are all startups similarly affected by the survival benefits and drawbacks of locating in geographic clusters? In this paper, we argue that prior theorizing may have missed important contingencies that affect whether a startup experiences the benefits and costs of locating in a cluster. In particular, while the local levels of skilled labor, suppliers, and purchasers have a beneficial influence and local competition has a detrimental influence on startup survival, these relationships are moderated by heterogeneity in firms' resources and capabilities. We find support for these arguments using a dataset covering the early life of all independent startups in the Canadian manufacturing sector from 1984 to 1998.}, number = {3}, urldate = {2017-10-31}, journal = {Journal of Business Venturing}, author = {Pe'er, Aviad and Keil, Thomas}, month = may, year = {2013}, keywords = {Agglomeration, Capability, Cluster, Resource, Survival}, pages = {354--372}