Modelling inbound international tourism demand in Australia: Lessons from the pandemics

Ghosh, Sudeshna

doi:10.1002/jtr.2483

Cited by 25 publications

(15 citation statements)

References 72 publications

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“…The impression of tourism during and after a Pandemic has been altered by policies and travel restrictions established in numerous countries. The dimensions and issues related to this parameter include sharp reduction in the number of tourist arrivals [222][223][224], increased travel costs and the effects on the restaurant industry [225], airlines industry [226], lockdown of the places of religious tourism [227], and almost entire national economies [228,229].…”

Section: Pandemicsmentioning

confidence: 99%

“…For example, Wang et al [224] developed effective techniques to help predict tourist arrivals after the COVID-19 Pandemic. Ghosh et al [223] studied how international tourism in Australia was influenced by the pandemic. They investigated the primary factors of tourism in favourable times and the principles that may be derived to re-establish international travel in the post-pandemic world.…”

Section: Pandemicsmentioning

confidence: 99%

See 1 more Smart Citation

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Alsahafi¹,

Alzahrani²,

Mehmood³

2023

Preprint

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The Global natural and manmade events are exposing the fragility of the tourism industry and its impact on the global economy. Prior to the COVID-19 pandemic, tourism contributed 10.3% to the global GDP and employed 333 million people but saw a significant decline due to the pandemic. Sustainable and smart tourism requires collaboration from all stakeholders and a comprehensive understanding of global and local issues to drive responsible and innovative growth in the sector. This paper presents an approach for leveraging big data and deep learning to dis-cover holistic, multi-perspective (e.g., local, cultural, national, and international) and objective information on a subject. Specifically, we develop a machine learning pipeline to extract parameters from academic literature and public opinions on Twitter, providing a unique and comprehensive view of the industry from both academic and public perspectives. The academic-view dataset was created from the Scopus database and contains 156,759 research articles from 2000 to 2022, which were modelled to identify 33 distinct parameters in 4 categories: Tourism Types, Planning, Challenges, and Media &amp; Technologies. A Twitter dataset of 485,813 tweets was collected over 18 months starting March 2021 to August 2022 to showcase public perception of tourism in Saudi Arabia, which was modelled to reveal 13 parameters categorized into two broader sets: Tourist Attractions and Tourism Services. Discovering system parameters are re-quired to embed autonomous capabilities in systems and for decision-making and problem-solving during system design and operations. The proposed approach improves AI-based information discovery by extending the use of scientific literature, Twitter, and other sources for autonomous, dynamic optimizations of systems, promoting novel research in the tourism sector and contributing to the development of smart and sustainable societies. The paper also presents a comprehensive knowledge structure and literature review of the tourism sector based on over 250 research articles.

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Section: Pandemicsmentioning

confidence: 99%

Section: Pandemicsmentioning

confidence: 99%

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Alsahafi¹,

Alzahrani²,

Mehmood³

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…By incorporating the full TSA into CGE modelling, Pham et al (2021) projected short-term epidemic impacts on Australian inbound tourism in terms of tourism's direct contributions and its indirect effects via interindustry linkages. Ghosh (2021) leveraged a novel panel model to determine the long-term impacts of multiple factors on Australian inbound tourism. This model was also augmented to address panel heterogeneity and cross-sectional dependence, reinforcing the study's robustness.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of domestic tourism on economy under COVID-19: The perspective of tourism satellite accounts

Wu¹,

Cao²,

Liu³

et al. 2022

Annals of Tourism Research Empirical Insights

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“…Habibi (2017) deals with the economic and non-economic determinants of international tourist arrivals. Ghosh (2022) identifies the impact of economic, social and political factors and the occurrence of natural disasters, wars and epidemics on international travel demand.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Research by Ghosh (2022) affirms that the tourism industry has become extremely important globally over the past decade because of the direct and indirect increase in growth and employment benefits. Vukadinović et al (2016) acknowledged that tourism is one of the most complex industries, significantly impacting other industries.…”

Section: Introductionmentioning

confidence: 99%

An analysis of the relationship between ICT infrastructure and international tourism demand in an emerging market

Nguyen

2022

JHTT

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Purpose This paper aims to examine the impact of the existing information and communication technology (ICT) infrastructure and the development of the destination’s ICT on the tourism demand of international tourists in an emerging economy, Vietnam. Design/methodology/approach Using time-series data from 1995 to 2019, this study applies vector error correction model to analyse the impact of ICT infrastructure in the short- and long term. Findings The results of analysis show that although ICT infrastructure does not affect the number of international tourists in the short term, it positively contributes to tourism development in the long term. In addition, the results also show that in the short term, consumer prices have a negative impact on tourist arrivals while having a positive effect in the long run. Research limitations/implications This study only considers the impact of ICT infrastructure on the whole without going into each factor reflecting different aspects of the ICT infrastructure. Moreover, this research only stops at the pre-pandemic period, so it has not shown the role of ICT infrastructure in travel and tourism demand during severe pandemic periods. Practical implications The research results are an essential basis to support the Vietnamese Government’s strategy to pursue an accelerated investment policy in ICT infrastructure, especially investment in the tourism and hotel industries. On the other hand, the research results also create more motivation and confidence for managers and operators of destinations in Vietnam to invest in ICT infrastructure and apply ICT in management. Originality/value This study adds to the literature on tourism–ICT linkages in an emerging tourism market directly between ICT infrastructure and international arrivals with a dynamic time series–based approach that considers the dynamics in the tourist demand identification model. In addition, this study used consumer price index to assess the impact of price on tourist demand instead of using the exchange rate or using the relative prices between the origin and destination countries.

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Modelling inbound international tourism demand in Australia: Lessons from the pandemics

Cited by 25 publications

References 72 publications

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Impact of domestic tourism on economy under COVID-19: The perspective of tourism satellite accounts

An analysis of the relationship between ICT infrastructure and international tourism demand in an emerging market

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