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Applying Geographically Weighted Regression to Conjoint Analysis: Empirical Findings from Urban Park Amenities

Author

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  • Tanaka, Katsuya
  • Yoshida, Kentaro
  • Kawase, Yasushi

Abstract

The objective of this study is to develop spatially-explicit choice model and investigate its validity and applicability in CA studies. This objective is achieved by applying locally-regressed geographically weighted regression (GWR) and GIS to survey data on hypothetical dogrun facilities (off-leash dog area) in urban recreational parks in Tokyo, Japan. Our results show that spatially-explicit conditional logit model developed in this study outperforms traditional model in terms of data fit and prediction accuracy. Our results also show that marginal willingness-to-pay for various attributes of dogrun facilities has significant spatial variation. Analytical procedure developed in this study can reveal spatially-varying individual preferences on attributes of urban park amenities, and facilitates area-specific decision makings in urban park planning.

Suggested Citation

  • Tanaka, Katsuya & Yoshida, Kentaro & Kawase, Yasushi, 2008. "Applying Geographically Weighted Regression to Conjoint Analysis: Empirical Findings from Urban Park Amenities," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6233, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6233
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    File URL: http://purl.umn.edu/6233
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    Keywords

    Choice experiments; conjoint analysis; dogrun; geographically weighted regression; spatial econometrics; Research Methods/ Statistical Methods; Resource /Energy Economics and Policy;

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