Abstract
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.
Highlights
Over the past decade, we have seen a wealth of new forms of data produced at high temporal frequencies and low levels of spatial aggregation
The study here draws on previous spatial analysis of recreational accommodation by Yin [23] and tourism dynamic cluster analysis by [21]
In testing an empirical theory, some formal relationships are involved, such as those implied by the heuristics mentioned above, and this in turn implies in estimating model parameters some statistical test or other measure of credibility is to be applied
Summary
We have seen a wealth of new forms of data produced at high temporal frequencies and low levels of spatial aggregation These new data available, 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. ReferenceUSA claim their website contains the “most accurate and comprehensive” information updated monthly on 20 million businesses in Canada and the USA and widely used in research and practice [12,13,14] Such enterprise-level decade-long data series can help to study agglomeration-related issues from scale economies, externalities, co-location, and congestion. We devise a protocol to combine ‘social media’ sources with big commercial sources for tourism development and planning, applicable to other sectors
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