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Articles

Geographic Dimensions of Relocation Activity: A Comparative Analysis of Intrametropolitan and Out-of-State Relocation Activity

Pages 103-113 | Received 01 Sep 2016, Accepted 01 Mar 2017, Published online: 24 Jul 2017
 

Abstract

Over the years, research on relocation activity has provided insights about the characteristics of firms and regions that drive relocation. The spatial dimensions of these relocation decisions, however, particularly within states or metropolitan areas, remain an understudied aspect of the relocation literature. There is also little work comparing the destinations of relocations originating from within metropolitan areas compared to relocation activity from other states. Given the theoretical and practical importance of higher resolution, comparative research on relocation activity within metropolitan areas, this article uses both areal and point-based spatial statistics to test hypotheses about similarities and differences in the relocation behavior of locally oriented and out-of-state businesses within the Phoenix, Arizona, metropolitan area. Analytical results highlight distinct differences in the destinations of relocation activity originating from within the metropolitan area compared to out-of-state relocation activity. Intrametropolitan relocations tend to locate in less expensive and racially and ethnically diverse neighborhoods, whereas out-of-state relocations locate in wealthier, well-known locations of the metropolitan area. Out-of-state relocations are also less likely to locate in the downtown core. This suggests that expensive smokestack-chasing efforts directed at attracting businesses from out of state are unlikely to help revitalize the downtown core.

过去数年来, 有关易址活动的研究, 对于易址的企业特徵与驱动易址的区域提供了洞见。这些易址的决策之空间面向, 特别是在州内或大都会地区内部, 却仍然是易址文献尚未充分研究的面向。也显少有研究比较来自大都会区域内部的易址目的地相较于来自其他州的易址活动。有鉴于对大都会地区内部易址活动进行较高分辨率的比较研究的理论与实务重要性, 本文同时运用根据面积与点的空间统计, 检验亚利桑那凤凰城大都会地区源自在地和来自外州的易址行为之间的相似性与差异之假说。分析结果, 凸显出源自于大都会地区内部的易址活动之目的地, 相较于来自外州的易址活动而言有显着差异。大都会内部的易址, 倾向座落于较便宜、并且在种族和族裔上较为多样的邻里, 而来自外州的易址, 则座落于大都会地区中较为富裕、较为人所知的区位。来自外州的易址, 同时较少座落于市中心。此一发现显示, 瞄准吸引外州商业的昂贵烟囱效应, 可能无法协助重新活化市中心。

Durante años, la investigación relacionada con la actividad de relocalización ha generado comprensión acerca de las características de las firmas y regiones que controlan la relocalización. Sin embargo, las dimensiones espaciales de las decisiones de relocalización, en particular dentro de estados o áreas metropolitanas, siguen siendo un aspecto poco estudiado en la literatura de la relocalización. También es escaso el trabajo sobre los destinos de relocalizaciones que se originan dentro de áreas metropolitanas en comparación con la actividad de relocalización desde otros estados. Dada la importancia teórica y práctica de la investigación comparada de más alta resolución sobre la actividad de la relocalización dentro de áreas metropolitanas, este artículo usa estadísticas espaciales, tanto las areales como las puntuales, para poner a prueba hipótesis acerca de las similitudes y diferencias en el comportamiento de relocalización de negocios, tanto los orientados localmente como los de fuera del estado, dentro del área metropolitana de Phoenix, Arizona. Los resultados analíticos resaltan las diferencias distintas en los destinos de la actividad de relocalización que se originan desde dentro del área metropolitana, en comparación con los que se originan en la actividad de relocalización de fuera del estado. Las relocalizaciones intrametropolitanas tienden a localizarse en vecindarios menos costosos y diversificados racial y étnicamente, mientras las relocalizaciones de fuera del estado se localizan en las más ricas y mejor conocidas ubicaciones del área metropolitana. Las relocalizaciones por fuera del estado son también menos propensas a ubicarse en el núcleo del centro de la ciudad. Esto sugiere que los costosos esfuerzos a la caza de chimeneas orientados a atraer negocios de fuera del estado tienen pocas posibilidades de ayudar a revitalizar el centro de la ciudad.

Notes

1 To deal with issues of changing census geographies, points were joined to block groups' files based on the year that corresponded most closely to the data. For example, 1990 points were joined to 1990 block groups and 2000 points were joined to 2000 block groups.

2 Block groups with no significant cluster hot spots was a fourth category of block groups.

3 This statistic was computed using five nearest neighbors and 1,000 simulations.

Additional information

Notes on contributors

Elizabeth A. Mack

ELIZABETH A. MACK is an Assistant Professor in the Department of Geography, Environment, & Spatial Sciences at Michigan State University, East Lansing, MI 48808. E-mail: [email protected]. Her research is dedicated to understanding business location and economic development with an emphasis on the impacts of urban infrastructure.

Ran Wei

RAN WEI is an Assistant Professor in the Department of Geography at the University of Utah, Salt Lake City, UT 84112. E-mail: [email protected]. Her primary research interests reside in GIScience, spatial optimization, spatial statistics, and spatial data uncertainty with substantive applications in transportation, public health, criminology, and emergency response.

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