This study utilizes almost ideal demand system (AIDS) models to examine Hong Kong?s competitiveness as an international tourist destination in comparison with its competitors. The empirical findings of the study shed new light on the destination competitiveness literature and demonstrate that a destination?s competitiveness should be examined from a market-specific perspective. The results also suggest that Hong Kong is more competitive than Macau, particularly in terms of its ability to attract Australian and mainland Chinese tourists, while price elasticity calculations suggest Singapore and South Korea are more competitive than Hong Kong.
Li G (2008) The Nature of Leisure Travel Demand, In: Graham A, Papatheodorou A, Forsyth P (eds.), Aviation and Tourism: Implications for Leisure Travel pp. 7-20 Ashgate: Aldershot
Li G, Song H (2006) Quantitative Techniques for Tourism Competition Analysis, In: Papatheodorou A (eds.), Corporate rivalry and market power pp. 35-53 IB Tauris: London
This work examines key competition issues in the areas of transport for tourism, the accommodation sector and the travel distribution, drawing examples and case ...
This study investigates the performance of combination forecasts in comparison to individual forecasts. The empirical study focuses on the U. K. outbound leisure tourism demand for the United States. The combination forecasts are based on the competing forecasts generated from seven individual forecasting techniques. The three combination methods examined in this study are the simple average combination method, the variance-covariance combination method, and the discounted mean square forecast error method. The empirical results suggest that combination forecasts overall play an important role in the improvement of forecasting accuracy in that they are superior to the best of the individual forecasts over different forecasting horizons. The variance-covariance combination method turns out to be the best among the three combination methods. Another finding is that the encompassing test does not significantly contribute to the improved accuracy of combination forecasts. This study provides robust evidence for the efficiency of combination forecasts.
Song H, Smeral E, Li G, Chen L (2010) Tourism forecasting: the accuracy of alternative econometric models revisited,
Li G, Wu DC, Song H (2013) Forecasting Visitor Arrivals from the US to China: A Comparison of Model Performance,
The purpose of this study is to test a two-step tourist satisfaction index framework empirically. The first step estimates sectoral-level satisfaction indexes based on a structural equation model, and the second obtains an overall tourist satisfaction index by conducting second-order confirmatory factor analysis. This study is a pilot test of the theoretical framework based on three tourism-related service sectors in Hong Kong. The results indicate that mainland Chinese tourists are most satisfied with the hotel sector in Hong Kong, followed by the retail sector, and least satisfied with local tour operators. The aggregate tourist satisfaction index is 74.04 out of 100. The results of this study have important practical implications for long-term destination management. © 2010 John Wiley & Sons, Ltd.
This study examines the role of tourism development in reducing regional income inequality in China. First, the theoretical foundation for how tourism affects regional income inequality is discussed. Second, based on the conditional convergence framework, this study proposes a spatiotemporal autoregressive model to capture spatial and temporal dependence as well as spatial heterogeneity. Tourism development is introduced as a conditional convergence factor in an attempt to examine whether the convergence speed is accelerated by regional tourism development. Third, the effects of international and domestic tourism in narrowing regional inequality are compared both globally and locally. The empirical results indicate that tourism development contributes significantly to the reduction of regional inequality, with domestic tourism making a greater contribution than international tourism.
Liu W, Li G, Biran A (2010) Post-Disaster Tourist Behaviour: Motivation and Intention,
Song H, Li G, van der Veen R, Chen JL (2010) Hong Kong Tourist Satisfaction Index,
Li G (2012) Development of AIDS Models for Tourism Demand Modelling and Forecasting, invited expert presentation,,
The advantages of error correction models (ECMs) and time varying parameter
(TVP) models have been discussed in the tourism forecasting literature. These models
are now combined to give a new single-equation model, the time varying parameter
error correction model (TVP-ECM), which is applied for the first time in the context
of tourism demand forecasting. The empirical study focuses on tourism demand,
measured by tourism spending per capita, by UK residents for 5 key Western
European destinations. Based on the discussion of how the series considered related
to most, the empirical results show that the TVP-ECM can be expected to outperform
a number of alternative econometric and time series models in forecasting the
demand for tourism. By measuring performance in terms of the accuracy of the
forecasts of growth (rates of change) and showing that TVP-ECM performs very well
for this as well as conventional assessment of the level of demand in this study, it is
suggested that forecasters of tourism demand levels and growth rates can feel
comfortable using TVP-ECM given that it is expected to perform well.
Lorde T, Li G, Airey D (2015) Modeling Caribbean Tourism Demand: An Augmented Gravity Approach, Journal of Travel Research
This study uses a gravity framework to model tourism demand for the Caribbean. The basic model is augmented by Linder?s hypothesis?tourist flows are partly determined by the similarity in preferences between the destination and source markets?and climate distance, which measures the gap between climate conditions in origin and destination countries. The results indicate that traditional gravity variables are significant in explaining demand for the region. Habit persistence has the largest impact on demand, a result that holds promise for regional policy makers. Evidence is also unearthed that similarity in preferences between the region and its source markets, as well as climate distance, are important demand determinants.
Li G, Song H, Witt SF (2003) Modelling UK Outbound Tourism Demand Using EC-LAIDS Models,
Shen S, Li G (2006) Statistical Tests of Equal Forecast Accuracy: An Application to Forecasting Tourism Demand,
Li G, Wang Y (2006) Influences of Joint-venture Ownership on Human Resource Development Practices in China?s Hotels,
This study aims to predict the recovery of the Hong Kong tourism industry from the current
global financial and economic crisis. Based on the latest statistics available, this study
provides updated forecasts of tourist arrivals to Hong Kong from 10 key source markets over
the period 2010-2015. The forecasts include annual and quarterly forecasts of tourist arrivals
and the market shares of the source markets concerned. An econometric method is used to
estimate the demand elasticities as well as their confidence intervals, followed by the interval
demand predictions. The total tourist arrivals to Hong Kong are projected to reach 53.8
million by 2015 with the interval forecasts between 38.4 and 74.4 million, representing an
annual growth of 10.48% on average against 2009, with an interval ranging from 4.44% to
16.60%. As far as individual source markets are concerned, their demand recovery takes
varying paces. Overall, tourism demand in Hong Kong is relatively resilient to the global
financial and economic crisis.
Li G, Song H, Witt SF (2003) Modelling and Forecasting Demand for Thai Tourism, Advances in Hospitality and Tourism Research: Proceedings of the conference 8 pp. 393-396
Chen JL, Li G, Song H (2016) Managing tourist satisfaction: An index approach, In: Uysal M, Schwartz Z, Sirakaya-Turk E (eds.), Management Science in Hospitality and Tourism: Theory, Practice and Applications Apple Academic Press
Li G, Song H, Witt SF (2002) Econometric Analysis and Forecasts of International Tourism Demand in Thailand,
The dynamic system-of-equations approach has been used to analyze the demand for outbound tourism among a number of destinations. However, this approach has not been applied to the context of the tourist consumption of different products in a given destination. Given the importance of understanding tourists' consumption behavior to destination management, this study seeks to gain new insights into Hong Kong inbound tourist expenditure patterns using a dynamic system-of-equations approach: the almost ideal demand system model. Based on the estimation of a complete demand system, this study investigates the interactions among the demand for different tourism products (i.e., shopping, hotel accommodation, meals outside hotels, and other) and the impacts of price changes on demand. Tourists from different source markets are examined separately, and the results show that their consumption behavior differs significantly.
Biran A, He B, Sit J, Li G (2010) Wine Tourism in China: Exploring Motivation and Behavioural Intention in an Emerging Market,
Song H, Smeral E, Li G, Chen JL (2012) Tourism Forecasting Using Econometric Models, In: Buhalis D, Costa C (eds.), European Tourism Planning and Organisation Systems 21 Channel View Publications
Jin E, Li G, Song H (2009) Modeling Korean Domestic Casino Gaming Demand,
Song H, Smeral E, Li G, Chen JL (2013) Tourism forecasting using econometric models, In: Buhalis D, Costa C (eds.), Trends in European Tourism Planning and Organisation pp. 289-309 Channel View Publications
Witt SF, Song H, Li G (2009) Time Varying Parameter Structural Time Series Models: An Application to Tourism Demand,
Papatheodorou A, Li G, Arvanitis P (2009) Turning Peripherality into an Advantage by Using Air Transport and Tourism Policies: The Case of Greece,
Athanasopoulos G, Deng M, Li G, Song H (2014) Modelling substitution between domestic and outbound tourism in
Australia: A system-of-equations approach, Tourism Management 45 pp. 159-170
This study uses a system-of-equations approach to model the substitution relationship between Australian domestic and outbound tourism demand. A new price variable based on relative ratios of purchasing power parity index is developed for the substitution analysis. Short-run demand elasticities are calculated based on the estimated error correction almost ideal demand systems. The empirical results reveal significant substitution relationships between Australian domestic tourism and outbound travel to Asia, the UK and the US. This study provides scientific support for necessary policy considerations to promote domestic tourism further.
Wu DC, Li G, Song H (2009) Econometric Analysis of Tourism Demand Systems: A Time-Varying Perspective,
Li G, Song H, Dwyer L, Cao Z (2012) A Critical Review of Recent Developments in Tourism Economics,
Li G, Song H, Cao Z (2011) Evaluating Hong Kong?s Competitiveness as an International Tourism Destination from the Economic Policy Perspective,
Bai X, Li G (2004) Industrial Productivity Convergence in China, Journal of Chinese Economic and Business Studies 2 (2) pp. 155-168 Taylor & Francis
This paper examines the convergence process of industrial productivity between Chinese regions. Both Ã- and ²-convergences are investigated using a panel data set of 30 provinces and autonomous regions over the period 1985?1999. Unconditional Ã- and ²-convergence methods fail to detect productivity convergence over the whole sample period, although they suggest convergence during a sub-period 1985?1990. The estimates of a human capital enhanced production function, with the constant return to scale constraint, show that productivity gaps between Chinese regions declined during 1985?1999 with a rate of convergence of around 1.3% per annum. Similar results are also found when the data are disaggregated into three broader geographic regions.
Greater China, including Mainland China, Hong Kong, Macau, and Taiwan, contributes significantly to both regional and global tourism developments. Empirical research on tourism demand modeling and forecasting has attracted increasing attention of scholars both within and beyond this region. One hundred eighty articles are identified that were published in both English? and Chinese?language journals since the beginning of the 1990s. This study presents the largest scale of literature survey on tourism demand studies. Furthermore, this is the first attempt in tourism demand review studies that focuses exclusively on one geographic region and covers bilingual literature. Particular emphasis of this review is placed on research development, geographic focus, data type and frequency, measurement of tourism demand, modeling and forecasting techniques, demand elasticity analysis, forecasting exercises, and emerging research trends. Comparisons between the two bodies of literature published in two languages show a number of research gaps, such as the diversity and sophistication of the research methodology, rigor of the modeling and forecasting process, and theoretical foundations of demand analysis. Correspondingly, constructive recommendations are made to further advance tourism demand studies related to Greater China.
Li G (2012) Statistical Testing Techniques, In: Dwyer L, Gill A, Seetaram N (eds.), Handbook of Research Methods in Tourism 1 pp. 13-30 Edward Elgar Publishing
Li G, Song H, Wu DC (2010) Forecasting Seasonal Tourism Demand Using Multivariate Structural Time Series Model,
Li G, Song H, Witt SF (2005) Forecasting International Tourism Demand Using the Time Varying Parameter Error Correction Model,
Song H, Witt SF, Li G (2009) The Advanced Econometrics of Tourism Demand, Routledge: London
Eighty-four post-1990 empirical studies of international
tourism demand modeling and forecasting using econometric
approaches are reviewed. New developments are identified,
and it is shown that applications of advanced econometric
methods improve the understanding of international
tourism demand. An examination of the 22 studies that compare
forecasting performance suggests that no single forecasting
method can outperform the alternatives in all cases.
The time-varying parameter (TVP) model and structural
time-series model with causal variables, however, perform
This paper reviews the published studies on tourism demand modelling and forecasting since 2000. One of the key findings of this review is that the methods used in analysing and forecasting the demand for tourism have been more diverse than those identified by other review articles. In addition to the most popular time-series and econometric models, a number of new techniques have emerged in the literature. However, as far as the forecasting accuracy is concerned, the study shows that there is no single model that consistently outperforms other models in all situations. Furthermore, this study identifies some new research directions, which include improving the forecasting accuracy through forecast combination; integrating both qualitative and quantitative forecasting approaches, tourism cycles and seasonality analysis, events' impact assessment and risk forecasting. (C) 2007 Elsevier Ltd. All rights reserved.
Liu W, Li G (2009) Post-Disaster Tourist Behaviour: Motivations of Visiting Sichuan after the Earthquake,
Jin E, Li G, Song H (2009) Modeling Korean Domestic Casino Gaming Demand,
Li G, Song H, Witt SF (2006) Forecasting Tourism Demand Using Econometric Models, In: Buhalis D, Costa C (eds.), Tourism management dynamics: Trends, Management and Tools pp. 219-228 Butterworth-Heinemann: Oxford
As the global tourism industry continues to expand and to become more complex, it is vital that those in the industry identify trends early and design proactive ...
This study considers the dynamics of the consumption behaviour of tourists from an economic perspective. The evolution of various demand elasticities is explored using a time-varying parameter almost ideal demand system model. The top four source markets for tourism in Hong Kong are examined, and three major tourist expenditure categories, including shopping, hotel accommodation and meals outside hotels, are investigated for each market. Elasticity analysis reveals different consumption trends and patterns across the source markets. The findings will serve as a useful reference for Hong Kong tourism-related industries and the government in their efforts to enhance the competitiveness of Hong Kong as an international tourism destination.
Song H, Witt SF, Li G, Guo W (2008) Forecasting Accuracy of Time Varying Parameter Structural Time Series Models,
Addressing the call for a better understanding of tourist behavior in relation to post-disaster destinations, this study explores the motivations and intentions of potential domestic tourists (from non-hit areas) to visit Sichuan, China in the aftermath of an earthquake. Drawing on dark tourism theories, this study offers a more comprehensive insight into the consumption of post-disaster destinations, aiming to capture the impact of the changes to the destination?s attributes on tourist behavior. The findings move beyond the common approach to tourism recovery, which solely focuses on reviving the traditional ??non-dark?? products. This study reveals the importance of newly formed dark attributes that emerge from the disaster as another means to destination recovery, reflected in the emergence of new tourist segments.
This study develops time varying parameter (TVP) linear almost ideal demand system (LAIDS) models in both long-run (LR) static and short-run error correction (EC) forms. The superiority of TVP-LAIDS models over the original static version and the fixed-parameter EC counterparts is examined in an empirical study of modelling and forecasting the demand for tourism in Western European destinations by UK residents. Both the long-run static and the short-run EC-LAIDS models are estimated using the Kalman filter algorithm. The evolution of demand elasticities over time is illustrated using the Kalman filter estimation results. The remarkably improved forecasting performance of the TVP-LAIDS relative to the fixed-parameter LAIDS is illustrated by a one-year- to four-years-ahead forecasting performance assessment. Both the unrestricted TVP-LR-LAIDS and TVP-EC-LAIDS outperform their fixed-parameter counterparts in the overall evaluation of demand level forecasts, and the TVP-EC-LAIDS is also ranked ahead of most other competitors when demand changes are concerned. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Chen JL, Li G, Zhang L, Hu R (2015) Market trends and forecast of Chinese outbound tourism, In: Li X (eds.), Chinese Outbound Tourism 2.0 23 Apple Academic Press
Most tourism programs today have an international component in their curriculum, usually including a global tourism class. This book serves as an excellent supplemental reading for students in these classes.
Li G (2008) An Overview of Tourism Demand Modelling and Forecasting Studies related to Greater China,
Tourism is becoming more and more important in the global economy, and its longterm
prosperity is desired by every tourism destination. Prosperity, however, cannot
be achieved successfully without the involvement of those influenced by the industry,
so, evaluating residents? perceptions of tourism and involving them in as many
aspects of planning and policymaking as possible are important steps in creating
sustainability in tourism destination development. In attempting to fill in the research
gaps in social impact analysis of urban tourism development in the Chinese context, a
face-to-face survey was carried out to explore residents? perceived impacts of tourism
development in Harbin, a famous tourist destination in north-eastern China. The
findings of this survey suggest that residents? reaction towards local tourism
development varies between different interest groups. Age, income and personal
connections with local tourism were found to influence residents? perceptions to some
This study examines the usefulness of the theory of transaction cost economics (TCE) for the online travel market and investigates customer satisfaction and loyalty with the transaction cost over the Internet taken into account. Using structural equation modelling (SEM), the authors identify the relationships among the antecedents (uncertainty, personal security and buying frequency), the mediating variable (transaction costs) and endogenous constructs (customer satisfaction and loyalty). The findings suggest that the satisfaction and loyalty of customers purchasing travel products over the Internet are affected negatively by transaction costs, which are determined by uncertainty, personal security and buying frequency. Moreover, a significantly negative relationship is identified between buying frequency and customer satisfaction.
Li G, Witt SF, Song H, Fei B (2007) Tourism Demand Modelling and Forecasting: Does the Measure Matter?,
Lorde T, Li G, Airey D (2011) Modelling International Tourism Demand for the Caribbean: A Dynamic Panel Augmented-Gravity Approach,
Wu DC, Song H, Li G (2008) A System demand Model for Analysing Tourist expenditures,
The article introduces an integrated market-segmentation and tourism yield estimation framework for inbound tourism. Conventional approaches to yield estimation based on country of origin segmentation and total expenditure comparisons do not provide sufficient detail, especially for mature destinations dominated by large single-country source markets. By employing different segmentation approaches along with Tourism Satellite Accounts and various yield estimates, this article estimates direct economic contribution for subsegments of the UK market on the Mediterranean island of Cyprus. Overall expenditure across segments varies greatly, as do the spending ratios in different categories. In the case of Cyprus, the most potential for improving economic contribution currently lies in increasing spending on ?food and beverages? and ?culture and recreation.? Mass tourism therefore appears to offer the best return per monetary unit spent. Conducting similar studies in other destinations could identify priority spending sectors and enable different segments to be targeted appropriately.
Shen S, Li G, Song H (2009) Is the Time Varying Parameter Model Favourable for Tourism Demand Forecasting? Statistical Evidence, In: Matias Á, Nijkamp P, Neto P (eds.), Advances in Tourism Economics: New Developments pp. 107-120 Physica-Verlag
Han S, Liu X, Li G (2005) Validity of the Zonal Travel Cost Model with Travel Time Using GIS as a Proxy of Travel Cost,
Li G, Song H, Chen JL, Wu DC (2012) Comparing Mainland Chinese Tourists' Satisfaction With Hong Kong and the UK Using Tourist Satisfaction Index, Journal of China Tourism Research 8 (4) pp. 373-394
This study aims to assess Mainland Chinese tourists' satisfaction with the UK and Hong Kong using a Tourist Satisfaction Index (TSI) approach. Based on a survey with Mainland Chinese tourists in the UK who also visited Hong Kong recently, this study computes the overall destination TSIs and sectoral TSIs for both Hong Kong and the UK. The results suggest that, overall, Mainland Chinese tourists were more satisfied with Hong Kong than with the UK as their travel destination. With respect to individual service sectors, Mainland Chinese tourists were more satisfied with six out of the seven surveyed tourism-related service sectors in Hong Kong than their counterparts in the UK. Visitor attractions, hotels, and local tour operators show the most significant contribution to Mainland Chinese tourists' overall satisfaction evaluation in both destinations. These findings suggest that Hong Kong's tourism industry as a whole is more competitive than that of the UK as far as Mainland Chinese tourists are concerned. Cross-cultural perspectives should be adopted in tourism service operations at an international tourist destination. © 2012 Copyright Taylor and Francis Group, LLC.
The linear almost ideal demand system (LAIDS), in both static and dynamic forms, is
examined in the context of international tourism demand. The superiority of the
dynamic error correction LAIDS compared to its static counterpart is demonstrated
in terms of both the acceptability of theoretical restrictions and forecasting accuracy,
using a data set on the expenditure of United Kingdom tourists in twenty-two Western
European countries. Both long-run and short-run demand elasticites are calculated.
The expenditure elasticities show that travelling to most major destinations in
Western Europe appears to be a luxury for UK tourists in the long run. The demand
for travel to these destinations by UK tourists is also likely to be more price elastic in
the long run than in the short run. The calculated cross-price elasticites suggest that
the substitution/complementarity effects vary from destination to destination.
Tourist arrivals and tourist expenditure, in both aggregate and per capita forms, are commonly used measures Of tourism demand in empirical research. This study compares these two measures In the context of econometric modelling and the forecasting Of tourism demand. The empirical Study focuses on demand for Hong Kong tourism by residents of Australia, the UK and the USA. Using the general-to-specific modelling approach, key determinants Of tourism demand are identified based on different demand measures. In addition, the forecasting accuracy of these demand Measures is examined. It is found that tourist arrivals in Hong Kong are influenced mainly by tourists' income and 'word-of-month'/habit persistence effects, while the tourism price in Hong Kong relative to that of the tourist origin country is the most important determinant Of tourist expenditure in Hong Kong. Moreover, the aggregate tourism demand models Outperform the per capita models, with aggregate expenditure models being the most accurate. The implications of these Findings for tourism decision making are that the choice of demand measure for forecasting models Should depend on whether the objective of the decision maker is to maximize tourist arrivals or expenditure (receipts), and also that the models should be specified in aggregate form.
Multivariate forecasting methods are intuitively appealing since they are able to capture the inter-series dependencies, and therefore may forecast more accurately. This study proposes a multi-series structural time series method based on a novel data restacking technique as an alternative approach to seasonal tourism demand forecasting. The proposed approach is analogous to the multivariate method but only requires one variable. In this study, a quarterly tourism demand series is split into four component series, each component representing the demand in a particular quarter of each year; the component series are then restacked to build a multi-series structural time-series model. Empirical evidence from Hong Kong inbound tourism demand forecasting shows that the newly proposed approach improves the forecast accuracy, compared with traditional univariate models.
This study examines the demand for Thai tourism by seven major origin countries ? Australia, Japan, Korea, Singapore, Malaysia, the UK and the USA. The general-to-specific modelling approach is followed in the construction, estimation, testing and selection of the tourism demand models. The empirical results show that habit persistence is the most important factor that influences the demand for Thai tourism by residents from all origin countries. The income, own price, cross price and trade volume variables are also found to be significant in the demand models, but the explanatory power of these variables, judged by the number of times they appear in the models, varies from origin to origin. The Asian financial crisis that occurred in late 1997 and early 1998 also appears to have had a significant impact on tourist arrivals from Singapore, Malaysia, Korea and the UK, but the magnitude and direction of influence are not the same for all models. The models that performed relatively well for each of the origin countries, according to both economic and statistical criteria, are selected to generate ex ante forecasts for the period up to 2010. The results suggest that Korea, Malaysia and Japan are expected to be the largest tourism generating countries by the end of the forecasting period, while the growth rate of tourist arrivals from Korea to Thailand is likely to be the highest among the seven origin countries.
Tourism demand is one of the major areas of tourism economics research. The current research studies the interdependencies of international tourism demand across 24 major countries around the world. To this end, it proposes to develop a tourism demand model using an innovative approach, called the global vector autoregressive (GVAR) model.
While existing tourism demand models are successful in measuring the causal effects of economic variables on tourism demand for a single origin-destination pair, they tend to miss the spillover effects onto other countries. In the era of globalisation, tourism destinations become interdependent on each other. Impacts of a distant event can be transmitted across borders and be felt globally. Hence, modelling international
tourism demand requires one to go beyond a particular origin-destination pair, and take into account the interdependencies across multiple countries. The proposed approach overcomes the ?curse of dimensionality? when modelling a large set of endogenous variables.
The empirical results show that, to different extents, co-movements of international tourism demand and of macroeconomic variables are observed across all the 24 countries. In the event of a negative shock to China?s real income level and that to China?s own price level, it is found that in the short run, almost all countries will face fluctuations in their international tourism demand and their own price. But in the long
run the shocks will impact on developing countries and China?s neighbouring countries more deeply than on developed countries in the West.
The current research contributes to the knowledge on tourism demand. It models tourism demand in the setting of globalisation and quantifies the interdependencies across major countries. On the practical front, tourism policy makers and business practitioners can make use of the model and the results to gauge the scale of impacts of unexpected events on the international tourism demand of their native markets.
This paper aims to provide the most up-to-date survey of tourism economics research and to summarise the key trends in its recent development. Particular attention is paid to the research progress made over the last decade in respect of approaches, methodological innovations, emerging topics, research gaps, and directions for future research. Remarkable but unbalanced developments have been observed across different sub-research areas in tourism economics. While neoclassical economics has contributed the most to the development of tourism economics, alternative schools of thought in economics have also emerged in advancing our understanding of tourism from different perspectives. As tourism studies are multi- and inter-disciplinary, integrating economics with other social science disciplines will further contribute to knowledge creation in tourism studies.
This study develops a global vector autoregressive (global VAR or GVAR) model to quantify the cross-country co-movements of tourism demand and simulate the impulse responses of shocks to the Chinese economy. The GVAR model overcomes the endogeneity and over-parameterisation issues found in many tourism demand models. The results show the size of co-movements in tourism demand across 24 major countries in different regions. In the event of negative shocks to China?s real income and China?s tourism price variable, almost all of these countries would face fluctuations in their international tourism demand and in their tourism prices in the short run. In the long run, developing countries and China?s neighbouring countries would tend to be more negatively affected than developed countries.
Globalization characterizes the economic, social, political, and cultural spheres of the modern world. Tourism has long been claimed as a crucial force shaping globalization, while in turn the developments of the tourism sector are under the influences of growing interdependence across the world. As globalization proceeds, destination countries have become more and more susceptible to local and global events. By linking the existing literature coherently, this study explores a number of themes on economic globalization in tourism. It attempts to identify the forces underpinning globalization and assess the implications on both the supply side and the demand side of the tourism sector. In view of a lack of quantitative evidence, future directions for empirical research have been suggested to investigate the interdependence of tourism demand, the convergence of tourism productivity, and the impact of global events.
Research on migration intentions is relatively fragmented, traditionally drawing conclusions from relatively small survey samples, focussing on individual countries, or relying on public opinion polls which provide very few explanatory variables. This paper addresses these limitations by developing a multi-level model of an extensive range of macro, meso and micro determinants of migration intentions across different time frames. The paper utilises an online panel survey of 20,473 non-student respondents aged 16-35 from 9 EU countries.
Ordinal multi-level modelling, with post-stratification weighting, is used to determine the key drivers of, and barriers to, migration intentions in both a pan-European model, and nine separate national-scale models. The findings confirm the significance of macro, meso and micro factors. While socio-economic factors emerge as powerful explanatory factors, non-pecuniary factors are also important, including sensation seeking. There are broad similarities in the findings across the separate national-level models, but also differences in the relative importance of socio-economic, gender, and personality factors. Migration intentions were highly dependent on the decision-making time frame: 17 per cent of respondents over one year, but 30 per cent over five years, are likely to migrate or to have made firm plans to migrate. The rank ordering of the countries challenges the notion of there being a simple differentiation between the newer and older member states of EU.
Increasing levels of global and regional integration have led to tourist flows between countries
becoming closely linked. These links should be considered when modeling and forecasting
international tourism demand within a region. This study introduces a comprehensive and
accurate systematic approach to tourism demand analysis, based on a Bayesian global vector
autoregressive (BGVAR) model. An empirical study of international tourist flows in nine
countries in Southeast Asia demonstrates the ability of the BGVAR model to capture the spillover
effects of international tourism demand in this region. The study provides clear evidence
that the BGVAR model consistently outperforms three other alternative VAR model versions
throughout one- to four-quarters-ahead forecasting horizons. The potential of the BGVAR
model in future applications is demonstrated by its superiority in both modeling and forecasting
In this study, we investigate the causal relationships between international tourism growth and
regional economic expansion in China, and more importantly, disclose the factors determining the
occurrence of these relationships. The empirical results reveal that 10 out of 29 regions
experienced tourism-led growth (TLG) during 1978 to 2013, whereas nine regions experienced
economic-driven tourism growth (EDTG). Different from the past literature, this study uses
Bayesian probit models to unveil the factors influencing these different growth patterns. Our
results suggest that regions with less-developed economies, larger economic sizes, and covering
larger geographic areas are more likely to experience TLG, and regions with less-developed
economies are more likely to experience EDTG as well. Lastly, practical implications are provided.
This paper reviews literature on travel destination choice and organizes these studies systematically. A ?cell?system? structure is proposed to describe the psychological process of travel destination choice. When forming decisions on vacations, tourists gather information on potential destinations and evaluate visit intentions among potential destinations (?cell?). The visit intentions are successively compared while information is updated in the process (?system?). The ?cell?system? structure provides a clear view of the psychological process of travel destination choice. Empirical studies based on the structure can provide further insights into why and how tourists choose travel destinations.
Corporate philanthropy (CP) is receiving increased attention, especially in transitional
countries, such as China. Focusing on Chinese tourism attraction companies that operate on
public tourism resources and have close relationships with their surrounding communities,
this study investigates the factors driving firms? CP behaviour from a community perspective.
Hypotheses are developed under the legitimacy framework. Probit and tobit regression
models are used with data gathered from listed tourism attraction companies in China
between 2000 and 2015. Three main findings are obtained. First, tourism attraction
companies engage in CP more actively than other companies in the tourism industry. Second,
three community-related features are significant drivers of tourism attraction firms? CP:
unbalanced economic development, fierce business competition within the community and
scarce educational resources. Third, the economic contribution of tourism partially
moderates the associations between community features and tourism attraction firms? CP.
Further interviews with top managers of selected companies confirm the findings of the
above statistical analysis. Both the theoretical and practical implications of the findings are
discussed at the end of the paper.
Tourism forecasting plays an important role in tourism planning and management. Various forecasting techniques have been developed and applied to the tourism context, amongst which econometric forecasting has been winning an increasing popularity in tourism research. This paper therefore aims to introduce the latest developments of econometric forecasting approaches and their applications to tourism demand analysis. Particular emphases are placed on the time varying parameter (TVP) forecasting technique and its application to the almost ideal demand system (AIDS). The discussions in this paper fall into two main parts, in line with the two broad categories of econometric forecasting approaches: the first part refers to the single-equation forecasting techniques, focusing particularly on both long-run and short-term TVP models. The second part introduces the system-of-equations forecasting models, represented by the AIDS and its dynamic versions including the combination with the TVP technique, will be discussed one by one following the order of methodological developments.
The linear almost ideal demand system (LAIDS), in both static and dynamic forms, is examined in the context of international tourism demand. The superiority of the dynamic error correction LAIDS compared to its static counterpart is demonstrated in terms of both the acceptability of theoretical restrictions and forecasting accuracy, using a data set on the expenditure of United Kingdom tourists in twenty-two Western European countries. Both long-run and short-run demand elasticites are calculated. The expenditure elasticities show that travelling to most major destinations in Western Europe appears to be a luxury for UK tourists in the long run. The demand for travel to these destinations by UK tourists is also likely to be more price elastic in the long run than in the short run. The calculated cross-price elasticites suggest that the substitution/complementarity effects vary from destination to destination.
This study develops time varying parameter (TVP) linear almost ideal demand system (LAIDS) models in both long-run (LR) static and short-run error correction (EC) forms. The superiority of TVP-LAIDS models over the original static version and the fixed-parameter EC counterparts is examined in an empirical study of modelling and forecasting the demand for tourism in Western European destinations by UK residents. Both the long-run static and the short-run EC-LAIDS models are estimated using the Kalman filter algorithm. The evolution of demand elasticities over time is illustrated using the Kalman filter estimation results. The remarkably improved forecasting performance of the TVP-LAIDS relative to the fixed-parameter LAIDS is illustrated by a one-year- to four-years-ahead forecasting performance assessment. Both the unrestricted TVP-LR-LAIDS and TVP-EC-LAIDS outperform the fixed-parameter counterparts in the overall evaluation of demand level forecasts, and the TVP-EC-LAIDS is also ranked ahead of most other competitors when demand changes are concerned.
The advantages of error correction models (ECMs) and time varying parameter (TVP) models have been discussed in the tourism forecasting literature. These models are now combined to give a new single-equation model, the time varying parameter error correction model (TVP-ECM), which is applied for the first time in the context of tourism demand forecasting. The empirical study focuses on tourism demand, measured by tourism spending per capita, by UK residents for 5 key Western European destinations. Based on the discussion of how the series considered related to most, the empirical results show that the TVP-ECM can be expected to outperform a number of alternative econometric and time series models in forecasting the demand for tourism. By measuring performance in terms of the accuracy of the forecasts of growth (rates of change) and showing that TVP-ECM performs very well for this as well as conventional assessment of the level of demand in this study, it is suggested that forecasters of tourism demand levels and growth rates can feel comfortable using TVP-ECM given that it is expected to perform well.
This research seeks to advance the understanding of the role of knowledge management in the contribution of tourism development companies (TDCs) to the process of producing tourism development projects (TDPs). The starting point of this research is the recognition of a major research gap relating to tourism product development. Within this field, the role of TDCs is rarely researched or even mentioned in the research literature. Additionally, despite the knowledge-intensive nature of the tourism product development process and TDCs, limited attention has been given to the perspective of knowledge management (KM) in tourism development. KM in this research is viewed as a continuous process which involves three interrelated dimensions, i.e. knowledge creation (KC), knowledge transfer (KT), and knowledge retention (KR). Understanding TDCs as typical project-based organizations, the research adopts a project ecology approach to provide an insightful understanding of knowledge management in tourism development companies in China.
From this perspective, the research involves examination of secondary data (e.g. TDCs` websites) and initial semi-structured interviews with professional participants in the tourism development industry in order to map the framework of TDC project ecologies in China. However, the core of the methodology is multiple case studies conducted in three contrasting TDCs over a period of 10 months. Data were collected through participant observation and informal interview during the case study process, focusing on how knowledge is managed within the project ecologies.
This research provides a relatively detailed description about the entities, and their interrelationships, involved in the project ecology of TDP. Building on the multilevel nature of project ecology, this research discusses the effects of various factors on KM at four different contextual levels (i.e. the individual level, the team level, the organizational level, and the external environment level). Four key findings serve to synthesize the roles of the factors in the four levels respectively: (1) the diverse and intrinsic effects of individual level factors on the individuals` performance in KM-related activities; (2) the aligning functions of the team level factors in configuring individuals` project work and their corresponding KM-related activities; (3) the organizational level factors which exert relatively more ongoing and sustained influences on KM activities despite the varied features of the various projects;(4)the characteristics of the external environment which can also exert latently ongoing, and sometimes notable influences on the interactions and dynamics of these relevant entities in terms of their performance in project and KM-related issues.
As well as bringing a new theoretical perspective to knowledge management in tourism, this research exhibits the ways in which the project ecology of TDPs in China are different from previous models of project ecologies developed in the literature. It does represent a substantial analysis of this topic within the field of tourism. Furthermore, it is intended that the research will also contribute to enhancing the performance of the case study firms, as well as the TDC sector generally.
The purpose of this research is to propose an index approach to study the impact of travel experience on tourists' satisfaction and the further impact on their sense of well?being. Based on the latest development of tourist satisfaction research, that is, the tourist satisfaction indices, this innovative study further extends the two?stage framework of tourist travel experiences to account for subjective well?being and subsequently calculates a tourist well?being index. A questionnaire with 496 respondents was used, which focused on four service sectors' tourist satisfaction indices. From this, a destination overall tourist satisfaction index and a tourist well?being index were produced using the results of structural equation modelling. Some key findings include the higher the impact of the trip on tourist's sense of well?being the higher the loyalty towards the destination. Different cultures had different results concerning the trip experiences (satisfaction) and the impact of the latter on their subjective well?being. Group travellers also had a significantly more positive experience compared with solo travellers. A new innovative indices system capturing tourist satisfaction and its causes and outcomes, in particular its impact on tourist's subjective well?being, was developed. This research therefore extends work done on the impact of tourist experience and quality of life/subjective well?being.
This study investigated the two main dimensions of STEs? community social
responsibility and their impact on firms? objective and subjective performance,
respectively. It also explored the moderating effects of STE owners? demographics on
the relationships between the two community social responsibility dimensions and
firm performance. By the survey data from STEs in the historical towns in
southwestern China, the empirical findings suggested that engaging in socially
responsible behavior at the community level contributes to STEs? subjective
performance; and the influence of community engagement on STEs? performance is
moderated by the owners? demographic characteristics, such as age, gender, ethnicity,
Lifestyle-oriented motivation (LOM) is the reason that the owners of many small
enterprises start and operate businesses in the tourism industry. Using a sample of guesthouses
in historic Chinese towns, this study examines how LOM affects these small businesses?
corporate social responsibility (CSR), performance, and owners? intentions to sustain
operations. Applying the structural equation modeling approach to a sample of 154 guesthouses,
this study finds that LOM positively influences CSR, performance, and owners? operational
intentions. Specifically, LOM promotes each dimension of CSR activities (product,
environment, community, employees, and heritage protection); however, it only increases firms?
subjective performance and has no significant influence on their objective performance. The
mediating effects of CSR and performance on the path from LOM to owners? operational
intentions are also demonstrated. Lastly, the theoretical and managerial implications of the
findings are discussed.
Agency theory has for some time been the dominant on executive compensation research. Behavioural approaches such as prospect theory, behavioural agency theory and reference point theory (including strategic reference point theory) provide new perspectives for research into executive compensation. For the largest transitional economy of China, the shift from a planned and administration-oriented economy to a market-oriented economy remains an on-going process. As behavioural approaches are derived from the understanding of human decision-making patterns, they are therefore less subject to institutional settings and thus more applicable to understanding executive compensation contracting in China.
From a reference point theory perspective, we test a ?three reference point? framework for executive compensation contracting: in external reference to peer firms, internally to other executives on board, and in the time dimension referring to top executives? previous pay. We find that as a superior alternative to agency theory, reference point theory can provide a better explanation for top executive compensation contracting. In our three empirical chapters, we mainly find that: (1) Chinese executive pay levels are externally heavily influenced in their setting by the pay level of executive peer groups; internally by other executives within firms and by the pay level of an individual executive in the previous period. It should also be noted that the loss aversion effect exists in top executive compensation contracting. (2) We test the three reference point effect and use Principal Component Analysis (PCA) to determine the systematic effects of these reference points to empirically test the behavioural determinants of executive pay in China; the three reference points and the systematic effect on top executive compensation are determined to be robust. (3) We document a negative association between top executive pay and a politically-connected board. However, after controlling for the three reference points, this association becomes positive and further strengthens the pay-performance link. We also find that in state-owned and politically connected firms the pay?performance link is the strongest, especially after adjusting for the effect of the three reference points. In private firms that are not politically connected, meanwhile, the pay-for-performance link is weak.
Our findings have important policy implications. They highlight the defects of current corporate governance mechanisms, particularly in executive compensation design and monitoring. The current Chinese Corporate Governance Code largely mimics corporate governance practice in the Anglo-American business environment and relies heavily on agency theory; therefore, to a large extent, it does not work in its own context. Our findings identify that in practice, the ?three reference point? framework and political connections play very important roles in influencing Chinese executive pay setting, in addition to the link to pay-for-performance and corporate governance mechanisms. It is therefore indicated that the Chinese Government should consider developing policies and regulations in addition to its Corporate Governance Code in order to effectively control the problems of the departure of executive compensation from firm performance.
Tourism forecasting is one of the longest standing areas in tourism economics research, with over half a century of history already. The development of tourism forecasting research responds and contributes to the industry practice.
Accurate demand forecasts are the foundation of tourism-related business decisions on pricing and operation strategies, and for governments on infrastructure investment and tourism policymaking. In recent years, tourism forecasting has received more attention from industry practitioners. First, echoing the increasing numbers of international and domestic tourists, the tourism industry has continuously grown and become more dynamic. As a result, industry practitioners have hoped to understand the market and predict future trends more accurately and comprehensively. Second, in recent years, decision makers have realized the increasing importance of quantitative evidence and have become more likely to rely on or refer to it for their strategy and policy formulations. Finally, the development of big data based on Internet technology has made it possible for the industry to obtain more accurate forecasts. Data on online tourist behaviour can be traced and retrieved. With greater understanding of it, the industry can then use it to forecast future trends.
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.
This study develops a tourist satisfaction assessment system based on a dual-model
framework and demonstrates its general applicability. The first model concerns tourist
satisfaction and its key antecedents and consequences. Structural equation modelling is
employed to investigate the relationships amongst the constructs in the theoretical framework,
and is then used as a basis for the computation of sectoral-level tourist satisfaction indexes.
The second model is designed to estimate an aggregate service satisfaction index and an
overall destination satisfaction index using a multiple indicator and multiple cause approach.
The framework is applied to a large dataset that represents six tourism-related sectors and
seven major source markets of inbound tourism to Hong Kong
Air pollution is becoming a serious socio-environmental problem in many modern societies and poses significant economic threats to popular tourism destinations. Despite the documented consequences of air pollution on tourism demand, studies have seldom examined its impact on individuals? psychological states, especially in the tourism context. Through a correlational study and two experiments, our findings indicate that tourists are more likely to be suspicious of local service providers when travelers perceive a destination as having heavy air pollution (vs. one without such pollution). This relationship presumably exists because tourists experience greater pessimism in an environment with high air pollution, which in turn influences their evaluations of service providers. Following this logic, we show that the effect diminishes when tourists are cognizant of (and thus rely less on) their pessimistic feelings when evaluating service providers. Finally, we offer theoretical and practical implications of this effect in tourism.