The Distributional Effect of Events on Rural and Urban Households in China

International tourism is considered an effective means of economic development. However, the effects of tourism are not evenly distributed between rural and urban households in China. In the wake of significant socioeconomic events, the uneven distribution of the economic effects has huge welfare implications for Chinese households. This study is the first attempt to evaluate the distributional effect of two large, recent, sequential events on China's rural and urban households. It adopts an innovative approach that combines an econometric model and a two-household computable general equilibrium model. The results show that in terms of welfare, urban households were more adversely affected by the events than rural households. To mitigate the loss of welfare, measures should be taken to continually promote China as a destination and attract tourists after such events occur. Meanwhile, training and education should be made more accessible to rural households to increase their job opportunities.

Complexity theory and tourism policy research

This paper investigates applications of complexity theory in the social sphere and considers its potential contribution to enhance understanding of tourism policy making. Five concepts are identified to explore complex social circumstances and human interactions that influence policy. Social applications of complexity suggest a move towards localised and deeper studies to explore the dynamics of policy enactment in context. It suggests complexity theory might be used as a thinking tool to enable a more holistic approach to policy analysis and investigate policy in its context, considering interactions between different policies/programmes, and the implications of human agency.

New Developments in Tourism and Hotel Demand Modeling and Forecasting

Abstract Purpose The purpose of the study is to review recent studies published from 2007-2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field. Design/Methodology/approach Articles on tourism and hotel demand modeling and forecasting published in both science citation index (SCI) and social science citation index (SSCI) journals were identified and analyzed. Findings This review found that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area. Research limitations/implications The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implications This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/value The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

The signalling effect of eco-labels in modern coastal tourism

As the demand for environmentally sustainable tourism grows, eco-labels are becoming increasingly popular as a signal of environmental quality. However, the existence of a causal link between awarding a seaside eco-label and the increase in tourism flows is still under discussion in the literature. In this article, we gauge the signalling impact of a specific eco-label, the Blue Flag award, using detailed data on tourism flows to seaside Italian destinations during the period 2008-2012. We adopt a recent econometric modelling strategy - the synthetic control method - in shaping estimation results and testing the sensitivity and robustness of our results. We find that being awarded the Blue Flag increases the flow of domestic tourists for up to three seasons after assignment. However, we find no effect for the flow of international tourists. Investigating the mechanisms driving the results, we find that the award of a Blue Flag only positively affects the flow of domestic tourists when it is used as a driver of organisation, coordination and integrated management of the tourism supply.