Dynamics of Australia’s tourism in a multimarket context

Valadkhani, Abbas; O'Mahony, G Barry

doi:10.1016/j.annals.2015.09.007

Cited by 3 publications

(4 citation statements)

References 17 publications

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“…For the purpose of our analysis, we apply monthly international visitor arrivals data from 28 source markets. The data have been extracted from the Australian Bureau of Statistics, have been seasonally adjusted (Valadkhani and O'Mahony, 2015), and are referring to the period from January 1991 to September 2017.…”

Section: Data and Methodological Frameworkmentioning

confidence: 99%

Integration of tourism markets in Australia

Kourtzidis

Heryán

2018

Tourism Economics

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By applying the methodological framework of transition modeling and econometric convergence tests introduced by Philips and Sul, we reveal the existence of convergence clubs and transition convergence paths of international visitor arrivals for Australia. Specifically, by using monthly data of international arrivals over the period of January 1991 to September 2017, we provide evidence that tourism markets can integrate. The analysis suggests the identification of five distinct convergence clubs. This in turn signifies an integration phenomenon of Australia's tourism market, which is revealed through the different convergence patterns of international visitor arrivals. Finally, it is evident that the revealed integration behavior of Australia's international tourism market, will enable policy makers to target better tourism needs through customized policies.

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Section: Data and Methodological Frameworkmentioning

confidence: 99%

Integration of tourism markets in Australia

Kourtzidis

Heryán

2018

Tourism Economics

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“…In Table I, recent empirical researches regarding hospitality management and tourism using modern econometric techniques for pricing and tourism demand, in relation to different economic factors, are summarized (Falk and Lin, 2018b; Usakli and Kucukergin, 2018). Previous literature has focused on the tourism economy in the US (Bonham et al , 2009; Chen et al , 2019) and other countries (Liu et al , 2018; Valadkhani and O’Mahony, 2015; Wu et al , 2014). Such studies have been considerably less frequent for the tourism economies of Central and Eastern European countries (Brida et al , 2015; Pavlic et al , 2015), where tourism could be crucial both for national and local economic development.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Kim and Song (1998) used a cointegration and error correction model for South Korea, while Falk and Lin (2018a) applied the same approach in Switzerland, to analyse inbound tourism. Subsequently, studies on time-series tourism data have been published for countries such as Hong Kong (Wu et al , 2012), the USA (Chen et al , 2019), Austria (Smeral, 2012), Australia (Valadkhani and O’Mahony, 2015) and England (Jeffrey and Barden, 2000), as well as other countries (Tables I and II). A VAR model is potentially useful for tourism studies because it can be applied both for long- and short-run dynamics (Juselius, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The price of overnight stays and inflation are linked to demand. Tourism product price is the crucial instrument (Shen et al , 2011; Wu et al , 2012) by which producers of tourism services (Valadkhani and O’Mahony, 2015) and consumers (tourists) (Chen et al , 2014) are associated, highlighting the value of studying tourism markets and price elasticities.…”

Section: Literature Reviewmentioning

confidence: 99%

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Prices of short-stay accommodation: time series of a eurozone country

Gričar

Bojnec

2019

IJCHM

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Purpose This paper aims to provide a reliable statistical model for time-series prices of short-stay accommodation and overnight stays in a eurozone country. Design/methodology/approach Exploiting the unit root feature, the cointegrated vector autoregressive model solves the problem of misspecification. Subsequently, variables are modelled for a long-run equilibrium with included deterministic variables. Findings The empirical results confirmed that overnight stays for foreign tourists were positively associated with the prices of short-stay accommodation. Research limitations/implications The major limitation lies in the data vector and its time horizon; its extension could provide a more specific view. Practical implications Findings can assist practitioners and hotel executives by providing the information and rationale for adopting seasonal volatility pricing. Structural breaks in price time-series have practical implications for setting seasonal-pricing schemes. Tourists could benefit either from greater price stability or from differentiated seasonal prices, which are important in the promotion of the price attractiveness of the tourist destination. Originality/value The originality of the paper lies in the applied unit root econometrics for tourism price time-series modelling and the prediction of short-stay accommodation prices.

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