Dealing with spatial heterogeneity in entrepreneurship research

Robert J. Breitenecker, Rainer Harms

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)

Abstract

In quantitative research, analyses are generally made using a geographically defined population as the study area. In this context, the relationships between predictor and response variables can differ within the study area, a feature that is known as spatial heterogeneity. Without analyzing spatial heterogeneity, a global model may not be correct, and there may be unclear spatial boundaries in the generalizability of the findings. The authors discuss how the method of geographically weighted regression (GWR) can be used to identify the study area, and illustrate the utility of GWR for empirical analyses in entrepreneurship research. Future entrepreneurship research can benefit from analyzing whether conflicting evidence may be due to spatial heterogeneity and from applying GWR in an exploratory way.
Original languageEnglish
Pages (from-to)176-191
JournalOrganizational research methods
Volume13
Issue number1
DOIs
Publication statusPublished - 2010

Fingerprint

Geographically weighted regression
Spatial heterogeneity
Entrepreneurship research
Generalizability
Predictors
Research benefits
Quantitative research
Global model

Keywords

  • METIS-261848
  • start up rate
  • geographically weightedregression
  • Entrepreneurship
  • Spatial heterogeneity
  • IR-73296

Cite this

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Dealing with spatial heterogeneity in entrepreneurship research. / Breitenecker, Robert J.; Harms, Rainer.

In: Organizational research methods, Vol. 13, No. 1, 2010, p. 176-191.

Research output: Contribution to journalArticleAcademicpeer-review

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AU - Breitenecker, Robert J.

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