2016
DOI: 10.1016/j.tourman.2016.06.012
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Exploring the regional distribution of tourism and the extent to which there is convergence

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Cited by 23 publications
(15 citation statements)
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“…Although this measure is statistically sound, the collection of the data through a survey of opinions about the value of these resources is subjective, and therefore its data reliability cannot be estimated. Other works include Andraz et al (2015) who support the convergence hypothesis, and Mérida et al (2016) who do not support convergence.…”
Section: Tourism and The Regional Convergence Hypothesismentioning
confidence: 99%
“…Although this measure is statistically sound, the collection of the data through a survey of opinions about the value of these resources is subjective, and therefore its data reliability cannot be estimated. Other works include Andraz et al (2015) who support the convergence hypothesis, and Mérida et al (2016) who do not support convergence.…”
Section: Tourism and The Regional Convergence Hypothesismentioning
confidence: 99%
“…The process of spatial analysis to be studied primarily includes attribute associations, a spatial single-factor analysis, and a comprehensive superposition analysis [16]. That is, the dataset based on different factors is unified to the same level, and weights are assigned to the adaptive region to ensure that the process is scientific and objective [17]. We select the Z-score scoring method for standardized treatment of the original data to eliminate dimensional differences.…”
Section: Suitability Modelmentioning
confidence: 99%
“…Lee (2009), Lean and Smyth (2008), Tan and Tan (2013), Solarin (2014), Solarin and Lean (2014), Ozcan and Erdogan (2017) and Kourtzidis et al (2018) provided substantial convergence evidence in Singapore, Malaysia, South Africa, Seychelles, Turkey and Australia. However, Mérida et al (2016) showed that convergence does not exist in Spain. The goal of this study is to examine the convergence of tourism by source markets as well as by products in Taiwan, using the residual augmented least squares (RALS) method for the period from July 2008 to September 2016.…”
Section: Introductionmentioning
confidence: 99%