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What is Geographically Weighted Regression

Chapter 22
Handbook of Research on Smart Technology Applications in the Tourism Industry
Geographically Weighted Regression is a geographical method of analysis which allows to identify areas where the impact of predictors on dependent variable is significant, positive or negative. The method solves reported issues of global statistics like ordinary least squares regression.GWR enables local models for every considered spatial unit of analysis, and neighbouring unitis. In other words, GWR allows to estimate local spatial patterns of any investigated dependent variable ( Gao& Li 2011 ; Huang et al. 2015 ).
Published in Chapter:
Smart Tourism Planning: Geographical Evidence From Poland
Katarzyna Leśniewska-Napierała (University of Lodz, Poland), Tomasz Napierała (University of Lodz, Poland), Sevda Sahilli Birdir (Mersin University, Turkey), and Kemal Birdir (Mersin University, Turkey)
Copyright: © 2020 |Pages: 15
DOI: 10.4018/978-1-7998-1989-9.ch022
Abstract
This chapter discusses geographical context of smart tourism planning through the analysis of relations between spatial planning, tourism development, and technology. The main question addressed in this enquiry is whether development of technology and tourism respects sustainable spatial planning. Thus, geographical influence of tourism and ICT on spatial planning was investigated. Research is carried out in Poland as tourist destinations in the country are substantially different regarding their tourist attractions, infrastructure, and development. Geographically weighted regression (GWR) was applied to identify regions where spatial planning is significantly influenced by tourism, and technology development as well. Both mentioned phenomena were recognized as competing in terms of spatial planning. Tourism and technology development did not support spatial planning parallely. Hence, establishing and developing smart tourism planning was confirmed as challenging from the geographical perspective.
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