Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team

Liu, Anyu; Vici, Laura; Ramos, Vicente; Giannoni, Sauveur; Blake, Adam

doi:10.1016/j.annals.2021.103182

Cited by 73 publications

(55 citation statements)

References 49 publications

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“…Research focusing on COVID-19 and tourism has been published rapidly. Most of the studies shed light on the influence of the pandemic on economic growth ( Yang et al, 2020 ), society ( Qiu et al, 2020 ) and the recovery path ( Liu et al, 2021 ). In the health discipline, scholars investigated people's reaction to social distancing measures ( Teasdale et al, 2014 ) based on individual's risk perception to the pandemic but also their health ( Xie et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Social distancing, trust and post-COVID-19 recovery

Kim

Liu

2022

Tourism Management

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With the tourism and hospitality sector reopening post-lockdown of COVID-19, the recovery of customers' purchase intentions is essential to reboot the sector. This study aims to examine the relationship between social distancing measures and purchase intentions in the UK's restaurant and hotel sectors using a propensity score weighting experimental design method. The findings suggest that the impact of social distancing measures on purchase intentions is mediated by the trust in the targeted restaurant and hotel. Risk tolerance significantly moderates the influence of social distancing measures on trust; (non-) cash promotions have an insignificant impact on purchase intentions. The introduction of the propensity score weighting scheme addresses the endogeneity caused by the sampling bias in non-probability sampling experiment studies.

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Section: Introductionmentioning

confidence: 99%

Social distancing, trust and post-COVID-19 recovery

Kim

Liu

2022

Tourism Management

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“…The scenario planning technique typically includes a description of an initial situation, the identification of the key driving forces, and the design of the most probable future changes, accompanied, sometimes, by their probability of success. Scenario-based forecasting has been incorporated in previous tourism research in times of crises [29,33].…”

Section: Methodsmentioning

confidence: 99%

“…The pandemic is giving rise to specific literature on its impact [23,24] on how companies in the hospitality sector have managed, and are managing, periods of crisis [25,26] and on the challenges for a new tourism in the post-COVID-19 risk scenario [27,28]. When external unpredictable shocks occur, more and new research is necessary [29] because accurate forecasting of the full scale of the impact on the tourism industry and market recovery is critical for strategic planning by tourist destinations and tourism-related businesses [30]. The profound impact of the coronavirus pandemic on global tourism activity has rendered statistical approaches on tourism demand forecasting obsolete because they cannot capture the impacts of global unanticipated events [31].…”

Section: Introductionmentioning

confidence: 99%

“…The profound impact of the coronavirus pandemic on global tourism activity has rendered statistical approaches on tourism demand forecasting obsolete because they cannot capture the impacts of global unanticipated events [31]. An appropriate alternative is to provide analysis based on different scenarios [29] as an approach to anticipate disruptions in the tourism system [32].…”

Section: Introductionmentioning

confidence: 99%

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CoVid Key Figures and New Challenges in the HoReCa Sector: The Way towards a New Supply-Chain

2021

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The profound impact of the coronavirus pandemic on global tourism activity and the hospitality industry has rendered statistical approaches on tourism-demand forecasting obsolete. Furthermore, literature review shows the absence of studies on the supply chain in the HoReCa (hotel, restaurant, catering) sector from a sustainability perspective that also addresses economic and social aspects, and not only environmental ones. In this context, the objective of this article is to carry out a prospective analysis on how the changes in the behaviour of consumers during the pandemic and the uncertainties regarding the exit from the health emergency can give rise to social trends with a high impact on the HoReCa sector in the coming years and, specifically, how they will affect the HoReCa supply chain. In the absence of investigations due to the proximity of what has happened, public sources and reports of international relevance have been identified and analysed from the future studies and strategic and competitive intelligence disciplines. The HoReCa sector in Spain has been chosen as field of observation. This analysis draws the future of the HoReCa sector, describes the changes in customer behaviour regarding food and beverages, explains the changes in distribution chains, and reflects on the impact of potential scenarios on the sector. The confluence of all these changes and trends can even configure a new supply chain in the hospitality sector with the emergence of new actors and the increase of access routes to a new final customer for whom security prevails in all its dimensions: physical, emotional, economic, and digital.

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“…This general observation indicates the strong ability of crisis severity data in improving the forecast accuracy of time-series models during the social unrest period. Although previous research has attempted to use the crisis severity to predict the tourism demand recovery from COVID-19 (Liu et al, 2021), this is the first study to empirically disclose the effectiveness of crisis severity on the improvement of forecasting accuracy during the crisis. The story is even more interesting in the forecasting results taking November as the test set.…”

Section: Crisis Severity and Occupancy Rate Forecastsmentioning

confidence: 99%

Timing matters: crisis severity and occupancy rate forecasts in social unrest periods

Qiu

Liu

Stienmetz

et al. 2021

IJCHM

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Purpose The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example. Design/methodology/approach Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy. Findings Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises. Originality/value The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.

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Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team

Cited by 73 publications

References 49 publications

Social distancing, trust and post-COVID-19 recovery

Social distancing, trust and post-COVID-19 recovery

CoVid Key Figures and New Challenges in the HoReCa Sector: The Way towards a New Supply-Chain

Timing matters: crisis severity and occupancy rate forecasts in social unrest periods

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