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Exploring spatial variations of US rock music concerts in relation to population demographics and leisure and hospitality industry.
- Source :
-
Annals of GIS . Sep2022, Vol. 28 Issue 3, p293-306. 14p. - Publication Year :
- 2022
-
Abstract
- Rock music is an integral part of American culture. This paper presents a study of sensing and analysing over 57,000 rock music live performances between 2007 and 2017. Spatial traces of 575 rock music artists performing in concerts nationwide were collected from a major music streaming platform Spotify. Location-based concert data were analysed to explore economic and geographic factors linked to the landscape of rock music live performance and to reveal the importance of population demographics and leisure and hospitality (LH) economics to the culture and music industries from a spatial aspect. Over 90% of rock concerts between 2007 and 2017 were found in 250 counties. The aim of the study is to specify and develop a model that reasonably accounts for spatial heterogeneity present in the concert data. By regressing rock concert data against demographic data and LH establishment data, ordinary least squares (OLS) models were better fitted in metropolitan counties than non-metropolitan counties. Spatial dynamics of concerts were revealed by local R2 values and the obtained structure in the form of spatial heterogeneity was then explained using geographically weighted regression (GWR) models. High population density and LH services in industry-leading cities such as New York City, Los Angeles, Chicago and Houston exhibit advantages in explaining rock concert distributions. Findings from the models reflect the live music industry's interrelationships to the LH industry and suggest LH services being essential considerations in selecting concert destinations for rock musicians. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19475683
- Volume :
- 28
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Annals of GIS
- Publication Type :
- Academic Journal
- Accession number :
- 158387420
- Full Text :
- https://doi.org/10.1080/19475683.2022.2031293