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Synthesizing Data to Explore the Dynamic Spatial Patterns of Hotel Development

1
Department of Urban and Regional Planning, State University of New York, Buffalo, NY 14214, USA
2
School of Information Engineering, China University of Geosciences, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(10), 448; https://doi.org/10.3390/ijgi8100448
Received: 29 August 2019 / Revised: 30 September 2019 / Accepted: 10 October 2019 / Published: 12 October 2019
The spatio-temporal relationship between tourism product similarity and spatial proximity has not been adequately studied empirically because of data and methodological limitations. New forms of data available at high temporal frequencies and low levels of spatial aggregation, together with large commercial data and expanding computational ability allow a variety of theories, old and new to be explored and evaluated more meticulously and systemically than has been possible hitherto. This study uses spatial visualization and data harvesting to synthesize a variety of data for exploring the evolution of hotel clusters and co-location synergies in US cities. The findings question the reliability of the current data to be used for identifying and analyzing the formation of tourist destination clusters and their dynamics. We conclude that synthesizing social media and large commercial data can generate a more robust database for research on tourism development and planning and improving opportunities for the examining spatial patterns of tourism activities. We also devise a protocol to combine ‘social media’ sources with big commercial sources for tourism development and planning, and eventually other sectors. View Full-Text
Keywords: hotel development; spatial proximity; synthesizing data hotel development; spatial proximity; synthesizing data
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Yin, L.; Wu, L.; Cole, S.; Wu, L. Synthesizing Data to Explore the Dynamic Spatial Patterns of Hotel Development. ISPRS Int. J. Geo-Inf. 2019, 8, 448.

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