Should I Stay or Should I Go: Predicting Advanced Producer Services Firm Expansion and Contraction (Record no. 11136)
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100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Neal, Zachary P. |
245 ## - TITLE STATEMENT | |
Title | Should I Stay or Should I Go: Predicting Advanced Producer Services Firm Expansion and Contraction |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Name of publisher, distributor, etc | Sage, |
Date of publication, distribution, etc | 2019. |
300 ## - PHYSICAL DESCRIPTION | |
Pages | Vol 42, Issue 2, 2019(207-229 p.) |
520 ## - SUMMARY, ETC. | |
Summary, etc | The literature on firm location selection allows us to retrospectively explain why firms did locate in particular places. However, it remains challenging to prospectively predict where they will locate. In this article, we propose a simple conceptual model of firm location decisions, then operationalize it using the ordinal stochastic degree sequence model (oSDSM). We use this model to predict whether 104 advanced producer service firms will expand, contract, or maintain their presence in each of 525 cities, and find that these predictions are accurate in more than 86 percent of cases. We conclude with suggestions for further refinement of this model. |
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Subject | location models, |
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Subject | spatial analysis, |
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Subject | methods, |
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Subject | city size and city systems, |
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Subject | urban and regional spatial structure, |
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Subject | spatial structure, |
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Subject | producer services, |
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Subject | stochastic degree sequence model, |
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Subject | world cities |
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Added Entry Personal Name | Derudder, Ben |
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Added Entry Personal Name | Taylor, Peter J. |
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Host Biblionumber | 11129 |
Host Itemnumber | 15490 |
Place, publisher, and date of publication | Sage, 2019. |
Title | International regional science review |
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Uniform Resource Identifier | https://doi.org/10.1177/0160017618784739 |
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