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Modelling Australian Domestic and International Inbound Travel: a Spatial-Temporal Approach

Author

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  • Minfeng Deng
  • George Athanasopoulos

Abstract

In this paper Australian domestic and international inbound travel are modelled by an anisotropic dynamic spatial lag panel Origin-Destination (OD) travel flow model. Spatial OD travel flow models have traditionally been applied in a single cross-sectional context, where the spatial structure is assumed to have reached its long run equilibrium and temporal dynamics are not explicitly considered. On the other hand, spatial effects are rarely accounted for in traditional tourism demand modelling. We attempt to address this dichotomy between spatial modelling and time series modelling in tourism research by using a spatial-temporal model. In particular, tourism behaviour is modelled as travel flows between regions. Temporal dependencies are accounted for via the inclusion of autoregressive components, while spatial autocorrelations are explicitly accounted for at both the origin and the destination. We allow the strength of spatial autocorrelation to exhibit seasonal variations, and we allow for the possibility of asymmetry between capital-city neighbours and non-capital-city neighbours. Significant spatial dynamics have been uncovered, which lead to some interesting policy implications.

Suggested Citation

  • Minfeng Deng & George Athanasopoulos, 2009. "Modelling Australian Domestic and International Inbound Travel: a Spatial-Temporal Approach," Monash Econometrics and Business Statistics Working Papers 10/09, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2009-10
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2009/wp10-09.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Carvalho Pedro & Márquez Miguel A. & Díaz Montserrat, 2016. "Do neighbouring countries encourage the demand of international business tourism?," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 7(3), pages 156-167, December.
    2. Marrocu, Emanuela & Paci, Raffaele, 2013. "Different tourists to different destinations. Evidence from spatial interaction models," Tourism Management, Elsevier, vol. 39(C), pages 71-83.
    3. Yang, Yang & Liu, Ze-Hua & Qi, Qiuyin, 2014. "Domestic tourism demand of urban and rural residents in China: Does relative income matter?," Tourism Management, Elsevier, vol. 40(C), pages 193-202.
    4. Gallardo-Vázquez Dolores & Hernández-Ponce Oscar Ernesto & Valdez-Juárez Luis Enrique, 2019. "Impact factors for the development of a competitive and sustainable tourist destination. Case: Southern Sonora Region," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 9(2), pages 3-14, December.
    5. Chansoo Park & Young-Rae Kim & Jihwan Yeon, 2023. "Stronger together: International tourists “spillover†into close countries," Tourism Economics, , vol. 29(5), pages 1204-1224, August.
    6. Salvatore Costantino & Maria Francesca Cracolici & J. Paul Elhorst, 2023. "A spatial origin‐destination approach for the analysis of local tourism demand in Italy," Papers in Regional Science, Wiley Blackwell, vol. 102(2), pages 393-419, April.
    7. Yang, Yang & Zhang, Honglei, 2019. "Spatial-temporal forecasting of tourism demand," Annals of Tourism Research, Elsevier, vol. 75(C), pages 106-119.
    8. Vu, Huy Quan & Li, Gang & Law, Rob & Ye, Ben Haobin, 2015. "Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos," Tourism Management, Elsevier, vol. 46(C), pages 222-232.
    9. Armand Viljoen & Andrea Saayman & Melville Saayman, 2019. "Determinants influencing inbound arrivals to Africa," Tourism Economics, , vol. 25(6), pages 856-883, September.
    10. Heping Huang & Wei Zhong & Qingsheng Lai & Yishu Qiu & Hong Jiang, 2020. "The Spatial Distribution, Influencing Factors, and Development Path of Inbound Tourism in China—An Empirical Analysis of Market Segments Based on Travel Motivation," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    11. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.
    12. Zhang, Ziqiong & Qiao, Shuchen & Chen, Ying & Zhang, Zili, 2022. "Effects of spatial distance on consumers' review effort," Annals of Tourism Research, Elsevier, vol. 94(C).

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    More about this item

    Keywords

    Tourism demand; Dynamic panel models; Travel flow model.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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