Utilizing environmental information and pricing strategies to reduce externalities of tourism: the case of invasive species in the Galapagos

The increase in demand for nature-based tourism brings economic and educational benefits but risks the introduction of invasive species. Increasing the length of tourist trips can better balance these benefits and risks by maintaining revenues while reducing the number of unique contacts with tourists. Changing the relative prices of trips can induce tourists to take longer trips. We hypothesized that providing information about the negative externalities of tourism could improve the effectiveness of such pricing strategies.

We administered one of two discrete choice surveys to tourists considering a trip to the Galapagos. One of the surveys described the Galapagos as a fragile ecosystem susceptible to invasive species; the second described it as a standard nature-based destination. For each sample, we estimated the probability of the tourist choosing a short versus long trip, given the tourist's personal information and trip options presented to him. We then simulated the demand for trips using three pricing strategies. We found that providing information on invasive species significantly increased the efficacy of strategic pricing. We propose using a two-prong approach to tourism management: educate potential tourists about the islands’ vulnerabilities, and simultaneously increase the per-day cost of short trips relative to that of longer trips.     

Assessing recreation carrying capacity of the environment attributes based on visitors’ willingness to pay

Recreation carrying capacity (RCC) is one of the most important indictors used in measuring the usage limits for the forest park resources. However, the consensus has not been reached with respect to the RCC’s content and its measuring metrics. In this paper, we attempt to establish a new RCC theoretical framework based on the demand theory of the tourism product characteristics. In the process, the choice experiment and orthogonal design methods are used in questionnaire designs and the conditional Logit model is used for parameter estimates. More than 700 park visitors are surveyed for data collection at the Shenyang National Forest park of Liaoning province in China. The primary park attributes being considered encompass vegetation, coverage, water quality, number of rubbish on the park trail path, admission fees, and congestion. The carrying capacity threshold for each specific attribute is identified.     

Effect of watermarks as visual cues for guiding consumer choice: An experiment with restaurant menus

Priming can influence preferences. In this experiment, we extend this idea by using watermark visual primes. On a restaurant menu cart, primes related to the sea, countryside (or no prime) were used with alone diners in a restaurant. The results show that, compared to the control no-prime condition, primes related to the sea significantly increased the consumption of fish dishes whereas primes related to the countryside did not significantly increase the consumption of meat dishes.     

乡村旅游偏好差异测量研究:基于离散选择模型

消费者偏好分析是进行产品开发、市场营销的基础,本文运用离散选择模型中的Multinomial logit(MNL)模型,分析旅游消费者在产品选择过程中,其个人特征及行为特征对某类旅游产品偏好的影响。通过大连乡村旅游消费者产品选择行为的实证研究,表明乡村旅游消费者对不同类别产品的偏好,会随着消费者个人特征和行为特征的不同而发生变化。MNL模型能较为合理地解释乡村旅游者个人特征和行为特征与乡村旅游产品选择偏好之间的关系。     

现金股利对会计信息的治理

会计只能提供相对相关和可靠的信息,在控制逆向选择和道德风险方面作用有限,形成了会计目标实现的障碍,这迫使投资者不得不去寻找其他信息渠道,以期更有效地决策。现金股利就是投资者寻找的信息渠道之一,它和会计信息在提高信息的相关性、可靠性以及控制逆向选择和道德风险方面共同发挥作用,并形成竞争态势,这种竞争态势实质上起到了对会计信息的治理作用。     

外来务工人员就业流动性的影响因素分析——基于广州市外来务工人员的抽样调查

在我国城市化飞速发展的今天,外来务工人员在城市中就业岗位的不断流动已成为普遍现象。文章基于广州市这个珠三角典型城市的抽样调查,通过构建probit量模型,探求城市外来务工人员就业决策的影响因素,重,董分析个人因素、社会因素和企业因素等对外来务工人员就业偏好的具体影响。建议政府部门针对外来务工者的就业特征,制定促进就业的相应政策;而企业也应根据这种偏好,制定和完善相应的人力资源战略举措,促进企业持续健康发展。     

巨灾保险:内涵、市场失灵、政府救济与现实选择

巨灾保险问题是一个全球性的问题,是保险业正在拓展的一个新领域,也是保险理论研究的一个新课题。深刻剖析巨灾风险的特殊内涵,明确指出目前巨灾保险存在的“市场失灵”问题,并提出政府干预是解决该问题的根本方法,从而为我国巨灾保险制度建立和完善提供现实选择。     

Values as determinants of motivation: Tourism and other career choices

Neuman, Yoram, Abraham Pizam and Arie Reichel, Values as Determinants of Motivation: Tourism and Other Career Choices. Annals of Tourism Research 1980, VII (3): 428–442. This study examined the predictive validity of work values in explaining motivational patterns of three groups of career preparation differing in their occupational specificity: Tourism/Hospitality, Management, and Liberal Arts. It was found that the higher the occupational specificity of a career preparation the higher is the predictive validity of work values in explaining work motivations. As predicted, the best relationships between values and motivation was found in the maximally specified occupation, namely: tourism/hospitality students, followed by management students with the liberal arts students — the most flexible occupational group — having the lowest relationship between values and motivation. The implications of the findings for employee selection and motivation prediction in the tourism/hospitality industry are discussed.     

Travel motivations and destination choice: A study of British outbound market

Abstract

Knowledge of people's travel motivations and its association with destination selection plays a critical role in predicting future travel patterns. The objectives of this study were to uncover the underlying push and pull factors of motivation associated with British outbound pleasure travelers as well as to identify key motivational factors that have significant effects on destination choice. Six push factors and five pull factors were found. “Knowledge seeking” and “cleanliness & safety” were perceived as the most important push and pull factors respectively. The results of logistic regression analyses snowed that the British tend to visit the U.S. for “fun & excitement” and “outdoor activities,” Oceania for “family & friend togetherness,” and Asia to seek a “novel experience.” The findings of differential motivational factors across seven destinations suggest that a destination can capitalize on its strengths with an optimal combination of push and pull factors to attract and retain the British travelers.     

MODELING SEQUENTIAL TOURIST FLOWS: WHERE IS THE NEXT DESTINATION?

This paper analyzes the subsequent decisions of tourists with respect to sequential destinations: why they visit a given destination after visiting a previous one and where they are most likely to go. Using a dataset from an on-site tourist survey in Nanjing, China, we study this decision process by partitioning it into three stages, and a nested logit model is used to estimate the determinants in each stage. Apart from the individual characteristics of tourists and destination attributes, we find that the spatial configuration of destinations (spatial structure) also tends to influence tourists’ destination choice. Finally, a series of simulations are carried out to understand the competition/substitution patterns between subsequent destinations.