Dr Anyu Liu
Academic and research departmentsCentre for Competitiveness of the Visitor Economy, Centre for Digital Transformation in the Visitor Economy.
Anyu is a Senior Lecturer in Hospitality with the research interests of applied economics in tourism and hospitality. He received his BA in Economics in 2008 and MSc in Economics and Statistics in 2011 in Dongbei University of Finance and Economics, China. After working as a research assistant at Peking University, China and the Hong Kong Polytechnic University (PolyU), he started to pursue his PhD at PolyU, focusing on the impact of tourism on economic growth. He gained his PhD degree in 2016, then worked as a postdoc fellow at PolyU for one year and joined Surrey in September 2017. Anyu has been involved in a number of international collaborative projects on tourism and hospitality demand modelling and forecasting, tourism satellite account and tourist satisfaction index.
University roles and responsibilities
- Deputy Director of International Relations
- Supervisor of Food & Wine Society
Affiliations and memberships
Editorial board member of Tourism Review
12 OCT 2020
Surrey’s School of Hospitality and Tourism Management teams up with UNWTO and the G20 to foster sustainable and inclusive tourism
24 SEP 2020
Centre for Competitiveness of the Visitor Economy hosts Tourism Recovery and Competitiveness webinar
In the media
Applied economics in tourism and hospitality
Tourism and hotel demand modelling and forecasting
Quantitative research method for tourism and hospitality studies
This project is funded by China National Tourist Office, New York. The coronavirus COVIE-19 is having a serious impact on the global tourism industry. Given the uncertainties with respect to future developments of the disease, it is necessary to predict its potential short-term and medium-term impacts on tourism. This project represents an initial attempt in the research field of tourism forecasting to quantify the effects of COVIE-19 on tourism demand, in an empirical context of US outbound tourism to China.
The aim of this project is to investigate the impact of COVIE-19 on the US outbound tourism to China and the specific objectives are as follows
- To predict the US outbound tourism to China in the long-run as the baseline scenario.
- To explore the impact of COVIE-19 on the demand in different scenarios.
How far can tourism reach in our economy: An investigation of Macau’s tourism satellite account (Sep 2020 - Aug 2022)
This is a collaborated project with University of Macau. The project is funded by Higher Education Bureau, Macao SAR, China. The aim of the project is to help Macau SAR develop the input-output table and the tourism satellite account.
- Grants and Awards
- Font, X. (PI), A. Liu, J. Chen & A., Riberio. “Experiential sustainable tourism to extend the visitor season”, funded by European Commission 2019-2022 for €23m
- Liu, A. (PI) & Y.R. Kim. “The Analysis of Wine Consumption Market in Surrey”, funded by University of Surrey and Innovate UK in 2020 for £11k [Internal Grant]
- Kim, Y.R. (PI) & A. Liu. “Problem-driven data strategy design and feasibility study of Mozee”, funded by University of Surrey and Innovate UK in 2020 for £8k [Internal Grant]
- Li, G. (PI), C. Scarles, A. Liu, J. Chen & N. Morgan. “An Economic and Social Impact Study of Arts in Surrey”, funded by University of Surrey and Innovate UK in 2020 for £11k [Internal Grant]
- Kim, Y.R. (PI) & A. Liu. “Understanding the Customer Journey and Behavior via Preferences to Brand and Promotion Offers in Urban Areas”, funded by University of Surrey Urban Living Award in 2020 for £4k [Internal Grant].
- Song, H. (PI), A. Liu & G. Li. “General-to-Specific Modelling with Bayesian Bootstrap Aggregation in Tourism Demand” funded by the Hong Kong Polytechnic University in 2019 for £42.5k [Internal Grant].
- Liu, A. (PI) & G. Li. “Impact of Gender on Small Tourism Enterprises’ Performance and Improvement of Community Quality of Life in the Rural Area of China”, funded by FASS Pump Priming grant (PI), University of Surrey in 2019 for £2k [Internal Grant].
- Liu, A. (PI). “The Impact of Cultural Ethnocentrism, Intercultural Competence on Migrants’ Wellbeing —A Mediating and Moderating Effect Analysis” funded by SHTM, University of Surrey in 2019 for £1.5k [Internal Grant].
- Liu, A. (PI) & N. Wang. “The Moderating Role of Tourist Travel Volume on Urban Destination’s Traffic Congestion—A Pilot Study” funded by University of Surrey Urban Living Award in 2019 for £2.5k [Internal Grant].
- Liu, A. (PI). “The Investigation of Travel and Wellbeing of Senior People” funded by Santander Researcher Mobility Award and University of Surrey in 2019 for £1.5k. [Internal Grant]
- Wu, D. C. (PI), A. Liu & G. Li. “The Combination of forward-looking, backward-looking and expert judgment: A new framework and empirical study of tourism demand modeling and forecasting”, funded by The National Natural Science Foundation of China (Reference Number: 71573289) from 2016-2018.
- Consulting and Research Reports
- Kimbu, A. (PI), A. Liu, I. Rodrigues & H. Gooding. “Al-Ula Framework for Inclusive Community Development through Tourism” contracted by UNWTO (CI) in 2020 for €20k
- Chen, J. (PI), G. Li, A., Liu & N. Morgan. “Provision of Review of Evidence of Elasticities Relevant to Tourism in Scotland” contracted by Visit Scotland (CI) in 2020 for £10k
- Tussyadiah, I. (PI), A., Liu & L. Chao. “Loyalty Programme of St Giles Hotels” contracted by St Giles Hotels in 2020 for £11k
- Song, H. (PI), A. Liu, RTR. Qiu, L.Wen, G. Li & V.S. Lin. “Asia Pacific Visitor Forecasts (Various Issues)”, funded by PATA from 2013 onward.
- V.S., Lin (PI), A. Liu & G. Li. “Shanghai Visitor Arrival Forecasting” funded by Shanghai International Theme Park Company Limited (Shanghai Disney Resort) from 2015 onward.
- D.C. Wu (PI), J. Liu, A. Liu, H. Song, H. Ye & H. FU. “The Development of the Data Information System for Guangdong Tourism Satellite Account” funded by Guangdong Tourism Administration, China 2013-2014 for £158k.
- Liu, J. (PI), D.C. Wu, A. Liu, H. Song & H. FU. Guangzhou Tourism Satellite Account funded by Guangzhou Tourism Administration in 2013
Postgraduate research supervision
- Chao (Erin) Ling (Co-Supervisor). Topic: AI/Chatbot for Travel.
- Weizheng Zhang (Co-Supervisor). Topic: Migration and hospitality entrepreneurship
- Max Li (Co-Supervisor). Topic: Vlog in the hospitality industry
- Adrienne Liu (Dual PhD with HKPU, Primary Supervisor at Surrey). Topic: Diaspora tourism
- Sara Dalir (Primary Supervisor). Topic: Experiential tourism and economic impact
- Rachel Hu (Co-Supervisor). Topic: Tourism development and residents' wellbeing
Postgraduate research supervision
Completed postgraduate research projects I have supervised
- Yujia (Penny) Chen, PhD (2020). University of Surrey, UK.
Financial Accounting for the Service Industry
Accounting and Finance for the Service Industry
Hotel Investment and Finance
Competitiveness is a well-discussed research topic in various disciplines and fields, amongst which competitiveness in the visitor economy is a prominent research stream. With rapid transformations in the visitor economy, destinations, regions, sectors and businesses have had to adapt – with varying degrees of success – to internal and external changes, significantly affecting their competitiveness. Existing studies are dominantly based on a few pioneering models and indicators and relatively few empirically challenge the assumed causality of competitiveness factors at different scales. This article, therefore, conducts a systematic literature review of competitiveness in the visitor economy post-2005 and examines the intellectual and conceptual structures of the extant literature as a platform to identify knowledge gaps and emerging trends and perspectives for future research.
Purpose This study aims examine the impact of authentic leadership on the career satisfaction of hospitality employees through the lens of thriving. The two components of thriving, that is, learning and vitality, are tested as mediators, and psychological contract fulfillment is tested as a boundary factor. Design/methodology/approach Data are collected using an online survey through the Qualtrics panel service in the USA. Structural equation modeling and an invariance test are conducted to investigate the framework. Findings The findings show that authentic leadership can determine career satisfaction through the influence of learning and vitality. Moreover, psychological contract fulfillment exerts a conditional effect on this mediation. Practical implications The findings of this study extend the understanding on authentic leadership and its impact under specific conditions. This study offers several meaningful recommendations to hospitality managers on how to influence employees’ career success to maintain sustainable performance. Detailed approaches include establishing practices for regular and authentic leadership development, increasing attention on employee thriving states and addressing employee psychological contracts. Originality/value This study enriches research on authentic leadership and career management in the hospitality industry. Moreover, this study provides meaningful insights by examining the relationships between authentic leadership, thriving, career satisfaction and psychological contracts.
Tourism satellite accounts (TSAs) have been widely recognised as standard tools to measure the contribution of tourism to destination economies. However, issues such as high costs of data collection and delayed release of TSAs have limited their regular compilation and practical application in some countries/regions. This study therefore introduces an innovative Web-based TSA information system that integrates all functions of the entire TSA compilation process chain, covering data input, data storage and management, TSA table compilation, statistical analysis and other extended applications. The system not only improves the efficiency of tourism data management and TSA compilation, but also enhances and extends the usefulness of TSAs for assessing the economic contribution of tourism to destinations. This Web-based TSA information system is established and discussed for a case study in Guangdong Province, China. Overall, the methodology and results reported herein provide academics and practitioners with new perspectives on regional TSA development and applications.
Host attitudes towards tourists are critical to the sustainable development of the tourism industry. Although numerous studies have focused on investigating host attitudes towards tourists and tourism development, the theoretical support from an economic perspective in this field is still underdeveloped. By following the social exchange theory and applying a utility maximization model, the current study not only explains Doxey’s Irridex model from an economic perspective but also complements the findings of the tourism area life cycle model proposed by Butler. Results show that the public resources at the destination, along with the ability of local community in channeling (foreign) tourism income into productivity advancement, influence the optimal level of tourism development in a destination.
Tourism studies commonly focus on the determinants of tourism demand. While most examine factors such as economic determinants, research on the effect of culture on tourism demand remains underdeveloped. This study uses a Bayesian two-stage median regression method to eliminate the potential collinearity between cultural and travel distance and to estimate the impact of cultural distance more appropriately. The results show that while there is a negative relationship between cultural distance and tourism demand, tourism demand is less sensitive to change in cultural distance; the popularity of a travel route moderates the effect of cultural distance on tourism demand; and the influence of cultural distance is different across time and different source markets.
Purpose: Leader–member exchange (LMX) theory is particularly relevant to the hospitality and tourism industry due to its labor-intensive and service-focused nature. However, the hospitality literature regarding the impact of LMX on its various outcomes have inconsistent results. A holistic review of LMX studies is nonexistent in the current literature. Thus, the purpose of this study is to use a meta approach to quantitatively summarize and examine the relationship between LMX and its outcomes in the hospitality and tourism literature. Design/methodology/approach: A total of 89 individual observations from 36 studies conducted between 1997 and 2018 were identified. A Bayesian random effect model was introduced into the hospitality and tourism literature for the first time to implement the meta-analysis. Findings: Results suggest significant differences in the impact of LMX on various groups of outcomes. LMX has the strongest impact on firms’ practice-related outcomes, such as organizational justice and employee empowerment. Few moderators are identified on the impact of LMX, such as LMX measure, culture, industry sector, and statistical method. Practical implications: Findings yielded several recommendations for both hospitality researchers and organizations in developing LMX related studies as well as managing employees. Originality/value: This study is the first Bayesian meta-analysis in the hospitality and tourism literature; it complements LMX theory by linking it to cognitive appraisal theory. Specific characteristics of LMX in the hospitality and tourism industry, such as the measurement of LMX and the effect of industry sector, are also identified.
Tourist decision to visit attractions is a complex process influenced by multiple factors of individual context. This study investigates how the accuracy of tourism demand forecasting can be improved at the micro-level by predicting the number of visits to London museums. The number of visits to London museums is forecasted and the predictive powers of Naïve I, seasonal Naïve, SARMA, SARMAX, SARMAX-MIDAS and artificial neural network models are compared. The empirical findings extend understanding of different types of data and forecasting algorithms to the level of specific attractions. Introducing the Google Trends index on pure time-series models enhances forecasts of the volume of arrivals to attractions. However, none of the applied models outperforms the others in all situations. Different models’ forecasting accuracy varies for short- and long-term demand predictions. The application of higher-frequency search query data allows generation of weekly predictions, which are essential for attraction- and destination-level planning.
Combination is an effective way to improve tourism forecasting accuracy. However, empirical evidence is limited to point forecasts. Given that interval forecasts can provide more comprehensive information, it is important to consider both point and interval forecasts for decision-making. Using Hong Kong tourism demand as an empirical case, this study is the first to examine if and how the combination can improve interval forecasting accuracy for tourism demand. Winkler scores are employed to measure interval forecasting performance. Empirical results show that combination improves the accuracy of tourism interval forecasting for different forecasting horizons. The findings provide government and industry practitioners with guidelines for producing accurate interval forecasts that benefit their policy-making for a wide array of applications in practice.
A survey of 780 UK residents was conducted to identify the extent to which perceived peer-to-peer (P2P) accommodation development is associated with changes in community members’ well-being from economic, social and environmental perspectives, and to understand in which circumstances P2P listings have positive and negative effects on 7 community members’ well-being. Partial least squares analysis demonstrates that the 8 perceived positive community impacts of P2P accommodation are more pronounced than the 9 perceived negative impacts. Additionally, weak but statistically significant effects of 10 perceived P2P accommodation prevalence on residents’ social and environmental well-being 11 are observed. Based on these findings and in accordance with social exchange theory, both 12 policy makers and the P2P accommodation sector should develop strategies to enhance the 13 perceived positive impacts on residents’ well-being and mitigate the perceived negative 14 impacts.
This article uses the dataset of tourist satisfaction index of Hong Kong to investigate the impact of culture difference on the gap between tourists’ expectations and their perceptions of actual service performance. When the demographic profile and travel experience are controlled, it is found that small culture difference (Hong Kong and China) has positive impact on Expectation-Performance Gap (EPG); whereas negative relationship with EPG is identified for large culture difference (Hong Kong and western countries). The practical implication for tourism managers in Hong Kong is that service providers should manage EPG in accordance with the aspects of the culture difference between the destination and the source markets.
The aim of this study is to investigate the long-term determinants of China’s imported wine demand and to forecast wine imports from 2019 to 2023 using econometric methods. Auto-regressive distributed lag models are developed based on neoclassical economic demand theory to investigate the long-term determinants of China’s demand for imported bottled, bulk, and sparkling wine from the top five countries of origin. The empirical results demonstrate that income is the most important determinant of China’s imported wine demand, and that price only plays a significant role in a few markets. Substitute and complement effects are identified between wines from different countries of origin and between imported wines and other liquids. China’s imported wine demand is expected to maintain its rapid growth over the forecast period. Bottled wine will continue to dominate China’s imported wine market. France will have the largest market share in the bottled wine market, Spain will be the largest provider of bulk wine, and Italy will hold the same position for sparkling wine. This is the first study to use a single equation with the general to specific method rather than a system of equations to estimate and forecast China’s demand for imported bottled, bulk, and sparkling wines from different countries of origin. The more specific model setting for each country of origin improves forecasting accuracy.
In a context in which the tourism industry is jeopardised by the COVID-19 pandemic, and potentially by other pandemics in the future, the capacity to produce accurate forecasts is crucial to stakeholders and policy-makers. This paper attempts to forecast the recovery of tourism demand for 2021 in 20 destinations worldwide. An original scenario-based judgemental forecast based on the definition of a Covid-19 Risk Exposure index is proposed to overcome the limitations of traditional forecasting methods. Three scenarios are proposed, and ex ante forecasts are generated for each destination using a baseline forecast, the developed index and a judgemental approach. The limitations and potential developments of this new forecasting model are then discussed. •A new method is developed to provide forecasts under extreme uncertainty.•Uncertainly is addressed by applying judgemental adjustments to scenarios.•A two steps method combines forecasting, judgemental adjustment and scenarios.•A COVID-19 risk exposure index objectively ranks different destinations.•The twenty destinations studied will have different recovery patterns.
Purpose The impact of demand fluctuation during crisis eventsis crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The aim 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. Methodology 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 findings of this research is the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises. Originality 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.
Although numerous studies have focused on forecasting international tourism demand, minimal light has been shed on the factors influencing the accuracy of real-world ex-ante forecasting. This study evaluates the forecasting errors across various prediction horizons by analyzing the annually published forecasts of the Pacific Asia Tourism Association (PATA) from 2013 to 2017, comprising 765 origin-destination pairs covering 31 destinations in the region. The regression analysis shows that the variation in tourism demand and gross domestic product (GDP), covariation between tourism demand and GDP, order of lagged variables, origin, destination, and forecasting method all have significant effects on the forecasting accuracy over different horizons. This suggests that tourism forecasting should account for these factors in the future.
Through a rapid systematic review of international literature, this report provides an overview of the existing estimates of the potential price elasticities of demand (PED) and income elasticities of demand (YED) for tourists to destinations that may be relevant to Scotland, and those using commercial accommodation; price elasticities of supply (PES) of commercial accommodation relevant to Scotland; and other factors influencing changes in demand and supply in tourism. The report also summarises available primary literature on tourists’ behavioural responses to taxation. However, due to the unavailability of studies on Scotland, the evidence reviewed in this report was based on destinations that may be comparable to Scotland as identified in a cluster analysis. Therefore, the results provide a possible approximation rather than the actual elasticities for Scotland. To provide an up-to-date overview of evidence, a systematic literature review was conducted to gather information from primary studies published post-2010. As a systematic approach, the pre-specific search methodology ensures comprehensive, transparent and replicable results. As no empirical study was found to estimate the elasticities for tourism in Scotland, studies on European destinations and Scotland’s top source markets were firstly reviewed. A cluster analysis was then carried out to identify the most comparable tourism destinations to Scotland. As a result, 11 destinations were found most relevant. Elasticities for these destinations estimated by destination-specific studies were then considered as an approximation of tourism elasticities for Scotland. Regarding the European destinations in general, it has been found that the overall median PED for inbound tourism is on the borderline between elastic and inelastic (-1.02), while the overall average PED indicates a relatively elastic demand (-1.26). Regarding the YED, outbound tourism is likely to be perceived as a luxury consumption by tourists from most European countries/regions as well as the top source markets for Scotland. In terms of the most relevant destinations to Scotland as identified through cluster analysis, the overall median estimates suggest that inbound tourism is likely to be price elastic and to be perceived as a luxury consumption. However, the findings are based on limited recent evidence of varying quality for destinations relevant to Scotland. The relatively wide ranges within the elasticities for destinations that might be relevant to Scotland indicate considerable uncertainties potentially caused by the difference in the modelling methods, explanatory variables, destination-source market pairs and data used in the literature. Cautions should be exercised when interpreting the findings. In the search of recent literature on the price effect of taxation, only a limited number of primary studies have been identified. A general understanding is that an increase (or decrease) in tourism taxes may lead to a decrease (or increase) in the quantity of tourism demand, with other factors remain unchanged. This is consistent with the law of demand in economic theory. However, the impact of an increase in tourism taxation on tourists’ expenditure would depend on the tax in question, consumers’ PED, the PES, and other factors influencing both demand and supply. For instance, between VAT and accommodation occupancy taxes, past literature argues that the latter tend to have a more moderate effect on tourism demand, but they are likely to induce a psychological impact on tourists and could affect repeat tourism. As for different travel purposes, business travellers and non-coastal holidaymakers tend to have a price-inelastic demand, while leisure travellers particularly coastal holidaymakers are likely to have a price-elastic demand. Therefore, an increase in tourism taxation would likely result in higher tourism receipts from business travellers and non-coastal holidaymakers, but lower receipts from leisure travellers especially coastal holidaymakers. Additionally, while most of the studies on the impact of tourism taxation focused on the price effect of tourism taxes, tourist behaviour is also affected by non-price factors such as advertising and news, of which research is currently limited. A significant gap in the existing literature is that there is no direct evidence for Scotland. To address this gap, future research on price effects could focus on conducting primary studies underpinned by rigorous modelling methods utilising various primary and secondary data sources. In addition, survey-based tourist behaviour research on non-price effects of tourism taxes is also necessary to reach a fuller understanding of the overall effect of tourism taxation on tourist behavioural changes.
Limited historical data are the primary cause of the failure of tourism forecasts. Bayesian bootstrap aggregation (BBagging) may offer a solution to this problem. This study is the first to apply BBagging to tourism demand forecasting. An analysis of annual and quarterly tourism demand for Hong Kong shows that BBagging can, in general, improve the forecasting accuracy of the econometric models obtained using the general‐to‐specific (GETS) approach by reducing, relative to the ordinary bagging method, the variability in the posterior distributions of the forecasts it generates.
The aim of this study was to explore UK residents’ opinions of how peer-to-peer (P2P) accommodation listings within their communities impact upon their quality of life (QoL). Seven hundred and eighty open-ended questions were collected across the UK and content analysis was conducted to investigate the textual data. It is found that 13% of UK residents held positive opinion on P2P accommodation whereas another 13% expressed negative attitude and the rest kept neutral opinions. More people believed P2P accommodation brought positive economic and negative environmental impacts on the QoL, while the social influence was neutral. Opinions of London residents on P2P accommodation are different from those of non-London residents. Practical implications are provided to policymakers based on the empirical findings.
This study applies 3x2 between-subjects design to examine the effects of service failure dimensions and recovery strategies on satisfaction and customer repurchase intention in peer-to-peer accommodation. The preliminary results, which is based on an online survey with 107 respondents, revealed that the three different dimensions of service failure did not yield significant differences in satisfaction and repurchase intention. However, a significant difference was found between “compensation” and “no compensation” recovery strategies in satisfaction and repurchase intention. The types of service failure only affect the relationship between customer satisfaction and repurchase intention when a compensation is provided. This may be due to the limited response in each scenario. Therefore, in future studies, a larger sample is needed to confirm these preliminary results.
Purpose Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study applies the signaling theory to the booking of Airbnb listings and explores the influence of quality signals on the odds of an Airbnb listing being booked. Methodology A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt. Findings Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments. Value This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.
Most existing studies on the impact of tourism on economic growth adopt an econometric approach that is insufficient to confirm that tourism actually leads to economic growth. Moreover, it cannot explain the causalities of different variables. Taking Mauritius as an example, this study uses the dynamic stochastic general equilibrium approach to investigate the contribution of tourism to economic growth when there is a productivity shock in the tourism sector. A two-sector, small, open economy is modelled under the Dynamic Stochastic General Equilibrium framework. The model is estimated using the Bayesian method based on real tourism and macroeconomic data from Mauritius for the period from 1999 to 2014. The impulse response functions are used to simulate the contribution of tourism to economic growth when there is a productivity shock in the tourism sector. The simulation results show that the Mauritian GDP would increase by 0.09% if the productivity of tourism improved by 1%, indicating that tourism could lead to economic growth. Considering the average annual growth rate of the Mauritian GDP, the contribution of tourism to its economic growth is significant. Furthermore, the effects of tourism on economic growth are moderated by price elasticities in international tourism demand. This is the first study that estimates the dynamic stochastic general equilibrium model using the Bayesian method. By correcting the prior information with real tourism and macroeconomic data, the estimation and simulation results are more robust compared with the calibration method, which has been used frequently in tourism studies.
This paper aims to examine the demand for outbound tourism by mainland Chinese residents to 11 international destinations, and provide long-run forecasts up to the year 2020. The empirical results suggest that the income level and the cost of a stay at a tourism destination compared with that of staying at a Chinese tourism destination are two important factors that affect Chinese residents’ traveling abroad. Results also show that the long-run income elasticities for all destinations range from 0.406 to 1.785, while the own price elasticities vary from −9.490 to −0.152. Based on the response patterns of tourism demand to income and price changes, five main categories of Chinese outbound tourism markets are identified. An ex ante forecasting exercise is also carried out which shows that outbound tourists from China mainly travel to Asian countries/regions during the period 2012–2020. The total number of outbound tourists is expected to reach 138.7 million by 2020.
There has been much rhetoric about tourism's role in promoting world peace. This research takes a global perspective examining the relationship between peace and tourism across 111 different countries using a panel data model using two indicators, international tourist arrivals and the Institute for Economics and Peace's Global Peace Index. The results indicate that tourism is the beneficiary of peace rather than grounds for peace. Peace is most important to tourism in medium income destinations but still important for high income nations. No relationship exists between peace and tourism arrivals for low income nations.
The potential offered by the China outbound tourism market will create pressure on destinations to relax their visa requirements in order to capitalize on the opportunities it presents. Prior research into the impacts of visa liberalization indicates that the volume of arrivals increases substantially. However, little research has been conducted examining changes in profile of visitors and their resultant behaviors. This study examines changes in the Chinese pleasure visitor market to Hong Kong from 1998 to 2012. The study is grounded in market access theory. In addition to the significant increase of arrivals during that time, behavior patterns have changed almost completely, as independent tourists have been freed from the constraints imposed by tour group participation. The study has valuable implications for other destinations that are likely to relax visa requirements for markets like China.
A supply-side structural reform (SSR) has been carried out in China since late 2015, with a view to reducing overproduction in selected products such as coal, iron and steel. This paper examines whether the development of international tourism in China could support SSR, using an multi-methods approach that combines an econometric model and a computable general equilibrium model. It finds that the development of tourism can reduce the outputs of overcapacity industries and reallocate surplus labour to tourism-related industries. The calibration of 30 provincial CGE models demonstrates that the impact of tourism on reform in provinces with severer industry overcapacities is much stronger. This study contributes to the literature on the spillover effects of tourism on non-tourism sectors through its combination of econometric and CGE models. Practical implications are also presented.
Personal security is a major concern for tourists. Most tourists will seek safe and secure destinations and avoid those that have been plagued by terrorism. This research quantifies the relationship between terrorism and tourism in 95 different countries and territories using international tourism demand models. After controlling for income, we find there is no long run effect of terrorism on international tourism demand and the short run effect is quite limited from a global perspective using panel data models. Only nine countries out of the 95 show a long run impact of terrorism on tourism and 25 countries out of the 95 show a short run impact using time series models, implying that international tourism is resilient to terrorism. The influence of terrorism is diverse in destinations with different political instability, income levels and tourism intensities.
- Books & Chapters
- Liu. A., V. S. Lin & H. Song (2016). Analysing and Forecasting Tourism Demand in Cooper, C., N. Scott, S. Volo & W. C. Gartner (Eds) Handbook of Tourism Management: SAGE .
- B. Kim, L. Zhou & A. Liu (2018). Culture and Service Quality: case of Hong Kong in Jafari, J. & Cai, L. (Eds) Bridging Tourism Theory and Practice. Emeraldinsight.
- Books in Chinese
- Duan. P., A. Liu and D. Wu (2011). Macroeconomic Theory: A Dynamic General Equilibrium Approach (M. Wickens, Trans). Dalian: Dongbei University of Finance and Economics Press. (Original work published in 2007).