Detecting Spatial Clustering Using a Firm-Level Cluster Index. Issue 6 (2nd June 2016)

• Record Type: Journal Article
• Authors: Scholl, Tobias; Brenner, Thomas
• Is Part Of: Regional studies. Volume 50:Issue 6(2016)
• Page Start: 1054
• Page End: 1068
• Publication Date: 2016-06-02
• Subjects: Clusters -- Modifiable areal unit problem (MAUP) -- Distance-based measures -- Localization -- Spatial concentration; 群聚 -- 可调整地区单元问题（MAUP） -- 根据距离的测量 -- 在地化 -- 空间集中; Grappes -- Problème de l'unité areal modifiable (MAUP) -- Mesures basées sur la distance -- Localisation -- Concentration géographique; Cluster -- Problem der veränderbaren Gebietseinheiten (MAUP) -- Entfernungsbasierte Maßstäbe -- Lokalisierung -- Räumliche Konzentration; Aglomeraciones -- Problema de la unidad de área modificable (MAUP) -- Medidas basadas en la distancia -- Localización -- Concentración espacial; C40 -- C60 -- R12; Regional planning -- Periodicals; Regional planning -- Great Britain -- Periodicals; 307.14
• DOI: 10.1080/00343404.2014.958456
• Languages: English
• ISSNs: 0034-3404

Abstract

Abstract : Scholl T. and Brenner T. Detecting spatial clustering using a firm-level Cluster Index. Regional Studies . A new statistical method is presented that detects industrial clusters at a firm level. The proposed method does not divide space into subunits, whereby it is not affected by the modifiable areal unit problem (MAUP). Hence, it is the first method to identify clusters without predetermined borders. The metric differs in both its calculation and its interpretation from existing distance-based metrics and shows three central properties that enable its meaningful use for cluster analysis. The method fulfils all five criteria for a test of localization proposed by Duranton and Overman in 2005.