Market demand variations,room capacity,and optimal hotel room rates

This short note develops an optimal hotel room rate model and proposes optimal room rate strategies in both high and low seasons. We then examine our model with the data from tourist hotels in Taipei, Taiwan. The empirical results support our model's major predictions: (1) market demand variations significantly affect the difference between high season and low season optimal room rates; and (2) hotel's room capacity negatively affect the difference between high season and low season optimal room rates, which also means that fixed costs shall negatively affect the high season optimal room rate. This result contradicts with conventional wisdom.     

基于排队论的方特欢乐世界主题公园容量研究

文章以芜湖方特欢乐世界为案例地,采用运筹学的排队理论,根据游客可忍受的最长等待时间,分别测算公园各项目的合理日容量,根据游客等待时间比例关系测算出公园合理日容量,根据旺季天数和游客量比例关系求得合理年容量,并对其结果和公园原有设计容量进行比较分析.针对公园供需矛盾和游客等待心理特征,提出实施淡旺季时间分流机制、引入项目空间疏散机制、启动项目容量调控管理库、构建排队管理网络系统等公园容量管理对策,以期为主题公园容量管理研究与实践提供借鉴.     

西安旅游气候舒适度与客流量年内变化相关性分析

气候舒适度是影响旅游地开发的重要因素，直接影响到旅游季节的长短及客流量的年内变化。利用近30年气候资料，对西安及周边山地旅游气候舒适性进行了评价，划分了适宜性等级和时段分布；结合2000-2002年入境旅游、国内旅游和本地游憩客流量的年内变化，划分了旅游活动的淡旺季和月指数；在对气候舒适度与特殊因子数值化的基础上，采用OLS方法建立了客流量月指数与气候舒适度的相关性。结果显示：入境游客年内变化受气候影响，入境旅游月指数气候弹性系数3．44％；大雁塔和骊山国内旅游不仅受气候舒适性影响，还受“五一”和“十一”黄金周影响，客流量月指数气候弹性系数为2．06％和2．33％；太白山和楼观台本地居民游憩，还受4～5月春游、8月学生暑假和9月秋淋的影响，客流量月指数的气候弹性系数为2．99％和2、64％。本项研究为西安市及周边客流量预测和景区规划提供了科学依据。     

发展我国旅游购物的思考——以"香港购物节"为例

近几年，“香港购物节”的举办，成功地把香港的旅游淡季变成了旺季，并全面推动了香港旅游业及整体经济发展水平的提高。本文在分析“香港购物节”成功经验的基础上，重点分析了我国内地发展旅游购物的相应措施。     

A probabilistic analysis of guided tours for tourists during the slack season

Issues germane to the provision of guided tours for tourists wishing to visit a particular location during the slack season have received scant theoretical attention in the tourism literature. Therefore, we conduct a stochastic analysis of guided tours for tourists during the slack season. We first delineate a general model that accounts for the common features of guided tours to city attractions and to other scenic locations. Second, we determine the long run fraction of demand that is lost to the firm providing the guided tours. Third, we ascertain the long run fraction of time that the guided tour providing firm is unable to satisfy the demand for such tours. Finally, we use the stationary Poisson process and show how our previous two general results might be used to shed practical light on the slack season provision of guided tours to tourists.     

Modelling and forecasting daily international mass tourism to Peru

Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten Peruvian sites on UNESCO's World Heritage List. For the potentially negative impacts of mass tourism on the environment, and hence on future international tourism demand, to be managed appropriately require modelling growth rates and volatility adequately. The paper models the growth rate and volatility (or the variability in the growth rate) in daily international tourist arrivals to Peru from 1997 to 2007. The empirical results show that international tourist arrivals and their growth rates are stationary, and that the estimated symmetric and asymmetric conditional volatility models all fit the data extremely well. Moreover, the estimates resemble those arising from financial time series data, with both short and long run persistence of shocks to the growth rate in international tourist arrivals.     

A latent class approach to tourists’ length of stay

In this paper, a conditional demand function is estimated for the length of stay at a tourist destination. The microeconomic model specifies the demand for the length of stay conditional on the remaining holiday characteristics that the tourist has chosen (the destination, type of accommodation etc.). The empirical model uses a latent class truncated Poisson regression, which acknowledges the existence of groups or segments of demand with different preferences. In the case under study, a distinction is made between two segments with a preference for either a longer or shorter holiday. The statistical model also resolves a problem of multimodality, acknowledged in previous analyses to be one of the main characteristics of this variable.     

Identifying a destination’s optimal tourist market mix: Does a superior portfolio model exist?

Extant tourism research has used various portfolio model types to determine optimal tourist market mixes which simultaneously maximize total tourist expenditure and minimise the instability of international inbound tourism demand. We analyse the three portfolio models that have been applied in the tourism literature: two varieties of a levels model (that use the level of tourist arrivals, or bed nights to quantify tourist activity) and a growth rates model (that deploys the growth in the level of tourist activity). Applying these models using per capita expenditure in four distinctively different destination countries (Australia, Greece, Japan, and USA), we demonstrate that the Levels Model 1 is superior to the Levels Model 2 and the Growth Rates Model. It produces solutions that provide noticeably higher tourist expenditure with less instability of international tourism demand than the status quo. Theoretical contributions and practical implications for tourism policy makers and destination marketers are discussed.     

Sustaining the Physical and Social Dimensions of Wilderness Tourism: The Perceptual Approach to Wilderness Management in New Zealand

The dynamics of the tourism industry are well illustrated by the case of New Zealand's tourism development over the last decade. The number of international tourists visiting New Zealand has doubled in the last ten years to approximately 1.5 million annual visitors. Associated with this growth has been a significant shift in patterns of tourist demand. No longer do most tourists simply comply with established tourist routes linking the high profile scenic attractions. Rather tourists have demonstrated a preference for more independent and dispersed patterns of travel, including an increase in demand for settings that offer subjective qualities of wilderness experience. This poses a complex but intriguing management challenge. If wilderness recreation involves pristine natural settings in the complete absence of facility development and visitor management, then these resources are more prone to degradation so than any other natural tourism resources. This paper suggests that an understanding of tourist perceptions of wilderness is crucial to the management of wilderness tourism, and considers the application of the perceptual approach to wilderness tourism as a means of sustaining wilderness values while promoting the satisfaction of visitor expectations.     

The Determinants of the Travel Demand on International Tourist Arrivals to Thailand

The purpose of this study is to develop a travel demand model of international tourist arrivals to Thailand and to assess the impact of crisis incidents on Thailand's tourism industry. A 20-year (1987–2006) annual time series data of “number of international tourist arrivals”, “exchange rate”, “promotion budget”, and dummy variables of “Asia financial crisis”, “special promotional campaigns”, “SARS” and “tsunami” were used to develop the travel demand model by performing a multiple regression analysis. The results showed that travel demand of international tourist arrivals to Thailand could be explained by “exchange rate”, “promotion budget”, “Asia financial crisis” and “SARS”.     

基于出游半径的自驾车旅游市场特征差异分析——以苏州市为例

自驾车旅游成为休闲旅游的重要方式。自驾出游半径不同市场需求存在一定差异,根据市场需求差异开发适应市场需求的自驾车旅游产品,对自驾车旅游市场发展具有重要意义。本文通过市场抽样调查方法,分析苏州市出游半径不同的5类自驾车旅游市场特征差异。结果表明,5类自驾车旅游市场在旅游动机、信息渠道、出游方式、出游时间、停留时间和旅游消费等6个方面存在一定差异性,但差异程度不同;研究还发现,影响自驾车旅游市场发展的主要限制性因素是道路标识系统不完善、旅游服务设施建设滞后、自驾车旅游经济成本高以及驾车安全隐患等4个方面;最后针对不同类型自驾车旅游市场特征以及影响其发展的因素,提出科学合理的自驾车旅游市场开发对策。     

Seasonality and regional productivity in the Spanish accommodation sector

This study quantifies the impact of peak demand and seasonality on regional productivity in the Spanish accommodation sector. We then identify factors affecting seasonal fluctuations and their relative contributions to regional variations in seasonality. The results show that demand for accommodation in the peak season mainly determines productivity. Thus, improving a region's attractiveness as a tourist destination is most effective for tourism-based regional development. In addition, reducing seasonal variations has a non-negligible impact on productivity. A decomposition analysis reveals that providing climate-independent tourist attractions and attracting business travelers are effective in reducing seasonality.     

基于本地旅游需求驱动的旅游地空间系统重构

旅游地空间系统是一个复杂而敏感的系统,易受空间内外部各种因素特别是市场要素变化的影响.文章在对以外来旅游需求为牵引的传统旅游空间系统及其不足和形成机理进行深入分析的基础上,结合国民休闲和内需扩大战略背景下本地旅游需求不断提升的现实变化,重构了内外需求更为平衡条件下的新旅游地空间系统.该系统应具有良好的空间外部环境、通畅高效的信息流、域面平滑流畅的旅游地发育、便捷立体的旅游通道、趋向均衡互补的内外部旅游市场等内涵,从而对传统旅游空间系统进行了补充和完善.     

Hospitality Industry Responses to Climate Change: A Benchmark Study of Taiwanese Tourist Hotels

Hotels are one of the tourism businesses most vulnerable to climate change because of their fixed assets. Results are presented of a baseline study that explores the awareness, attitudes, and behaviours of Taiwanese tourist hotels with respect to climate change and its potential impacts as well as their overall environmental practices. Tourist hotels are defined by the Taiwanese government as hotel establishments of over 80 rooms in rural areas and 50 rooms in city areas. Although the 104 tourist hotels represent only 3.7% of the total number of hotels in Taiwan, they account for over half of international guest nights and had a combined revenue of over TWD$43 billion in 2010. Questionnaires were distributed via email to all tourist hotels in Taiwan and 45 valid returns were received, representing an effective response rate of 43.3%. The results of research illustrate the level of understanding of climate change within Taiwanese tourist hotels and identify the specific climate change adaptation and mitigation strategies that tourist hotels have initiated. Access to such baseline data provides a potentially significant contribution to evaluating the response of the Taiwanese accommodation sector to environment change as well as providing a basis for further comparative studies and benchmarking.     

Cross country relations in European tourist arrivals

This paper introduces an optimized Multivariate Singular Spectrum Analysis (MSS) algorithm for identifying leading indicators. Exploiting European tourist arrivals data, we analyse cross country relations for European tourism demand. Cross country relations have the potential to aid in planning and resource allocations for future tourism demand by taking into consideration the variation in tourist arrivals across other countries in Europe. Our findings indicate with statistically significant evidence that there exists cross country relations between European tourist arrivals which can help in improving the predictive accuracy of tourism demand. We also find that MSSA has the capability of not only identifying leading indicators, but also forecasting tourism demand with far better accuracy in comparison to its univariate counterpart, Singular Spectrum Analysis.     

旅游地形象的时间演变与演变机制

旅游地形象是动态变化的,时间是旅游地形象动态变化的一个重要维度。现有旅游地形象研究主要从游客感知角度来解构旅游地形象属性,并对游客不同游览阶段、大事件前后的旅游地形象变化进行实证研究。少有文献对旅游地形象的季节波动、生命周期变化等时间演变问题进行探究,且相关研究多忽视了供给方层面的旅游地形象。研究认为,旅游地形象涉及旅游者和供给方两个层面,并分别包含感知形象和发射形象。研究对国内外旅游地形象时间演变的相关研究成果进行了梳理,包括旅游地形象随游览阶段的演变、事件前后的旅游地形象变化、旅游地形象的生命周期演变、旅游地形象的季节波动等,提出了更为系统的旅游地形象时间演变机制,并从供给方与游客两个层面对感知形象与发射形象的演变过程进行了分析。     

Estimating the effect of overcrowding on tourist attraction: The case of Canary Islands

This paper analyzes the influence of the tourist’s perception of overcrowding on a destination’s appeal. To do so, the use of the population density estimates is suggested to measure degrees of overcrowding in a tourist area, which in this paper is undertaken using panel data analysis. A tourist demand model is estimated in the study case, which consists of a number of resorts located in five islands of the same archipelago, Canary Islands. This distinctive case of close but different destinations makes it possible to isolate variations in demand due to changes in population density and other supply-side factors from other demand-oriented ones. Annual tourists coming from two different European countries to the islands were considered as endogenous variables. The empirical findings provide an indicator of each island’s maximum capacity and test some policy measures laid down to extend these limits. The estimation of the effect of population density on demand can serve as a useful tool for planning the future development in destinations where tourist attraction is mainly based on the natural values of the site.     

Does residents' perceived life satisfaction vary with tourist season? A two-step survey in a Mediterranean destination

Recent attention has been dedicated to the relationship between tourism and subjective well-being, however studies have mainly focused on the tourist side. Since residents are an indispensable partner for the success of any tourism program, understanding whether and how tourism affects residents' perceived life-satisfaction is a crucial issue. However, scant attention has been paid to this theme and the majority of studies are cross-sectional. Here we develop a two-step survey, conducted in a seaside resort before and during the tourist season to test for significant differences in residents' perceptions of tourism impact and overall life satisfaction. The results confirm the hypothesis that perceived tourism impact and life satisfaction vary with the tourist season, and that tourism has a hidden cost in terms of perceived life satisfaction.     

Forecasting leisure and tourism - scenario projections for 2000–2010

This article considers likely future trends in leisure time and tourism. The economic climate over the next 20 years is usually predicted to produce an increase in tourism. However, there are clearly discernible limits to the growth of tourist demand in the industrialized countries, due to changing economic conditions, modified consumer behaviour and new technologies. Increasing leisure time will be allocated to other uses besides tourism. The composition of the tourist population will alter, with increasing proportions of, eg senior citizens. There will be greater emphasis on individual/self-determined holidays, and on educational and recreational pursuits. Increasing environmental awareness will effect planning policies and tourist demand. An interdisciplinary, long-term approach to tourism planning is recommended.     

Tourism demand forecasting: A deep learning approach

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. Using a deep learning approach, this research studied the framework in forecasting monthly Macau tourist arrival volumes. The empirical results demonstrated that the deep learning approach significantly outperforms support vector regression and artificial neural network models. Moreover, the construction and identification of highly relevant features from the proposed deep network architecture provide practitioners with a means of understanding the relationships between various tourist demand forecasting factors and tourist arrival volumes.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field