2015
DOI: 10.1016/j.annals.2015.07.001
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Tourism expenditure patterns in China

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Cited by 44 publications
(46 citation statements)
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References 28 publications
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“…The results of the narrative review on antecedents revealed that studies on tourism expenditure need to use new theories, pragmatic methods, and novel analytical approaches within various data scales obtained from different geographical contexts in order to explain the complexities of the tourism expenditure phenomena (Brida & Scuderi, 2013;Dolnicar et al, 2008;Lin et al, 2015;Olya & Mehran, 2017;Wang & Davidson, 2010b).…”
Section: Discussion On Ote Theories and Methodsmentioning
confidence: 99%
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“…The results of the narrative review on antecedents revealed that studies on tourism expenditure need to use new theories, pragmatic methods, and novel analytical approaches within various data scales obtained from different geographical contexts in order to explain the complexities of the tourism expenditure phenomena (Brida & Scuderi, 2013;Dolnicar et al, 2008;Lin et al, 2015;Olya & Mehran, 2017;Wang & Davidson, 2010b).…”
Section: Discussion On Ote Theories and Methodsmentioning
confidence: 99%
“…Nevertheless, the incremental growth rate of OTE publications has been steady since 2015. Similarly, Kim et al (2018) found that the number of overall review studies in a tourism and hospitality context had (Lin, Shanshan, Mao, & Song, 2015), while at the macro level, there were few studies indicating that economic factors were not associated with OTE (Olya & Mehran, 2017). Income is one the most commonly used predictors of expenditure and the most important antecedent in indicating purchasing behaviour, but it is used in OTE modelling as a positive significant regressor (Brida & Scuderi, 2013;Dogru et al, 2017).…”
Section: Insert Figure 3 Herementioning
confidence: 99%
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“…With the development of social economy and the improvement of people's living standard, more public holidays, faster transportation (e.g., convenient air networks and highspeed railways), and greater openness toward the world, China's domestic and outbound demand for tourism have grown unprecedentedly since the 2000s [1]. According to the National Bureau of Statistics of China, the number of domestic tourists reached 3,611 million in 2014.…”
Section: Introductionmentioning
confidence: 99%
“…There is a substantial body of literature discussing different research methods applied to evaluation and choice of tourism destination. These methods include (1) Multinomial Logit Model (MNL) [4][5][6][7]; (2) Binary Regression Model [8][9][10][11]; (3) Multinomial Probit Model [12]; (4) Scobit Based Discrete-Continuous Choice Model [13]; (5) Structural Equation Model [14][15][16][17][18][19]; (6) Meta-analysis [20]; (7) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [21][22][23][24]; (8) Principal Component Analysis [25][26][27][28][29][30]; and (9) Analytic Hierarchy Process (AHP) [31][32][33][34][35][36][37]. Some of the methods may have already been known to the public.…”
Section: Introductionmentioning
confidence: 99%