基于贝叶斯多元有序probit模型的休闲渔业游客满意度研究

游客满意度是休闲渔业景区制定管理决策的重要参考信息。通过探究游览过程中游客对各单一维度的满意程度与旅游总满意度之间的关系,管理者可以从中准确了解游客偏好、消费行为以及获取旅游产品设计等重要信息。据此,本文采取实地调研,获取11家全国休闲渔业示范基地1510份游客满意度信息,使用马尔科夫链蒙特卡洛法(Markov Chain Monte Carlo, MCMC),估算贝叶斯多元有序probit模型,并利用模型后验结果衡量休闲渔业游客7种分满意度对总体满意度的贡献。研究结果表明:渔憩体验满意度、景区环境满意度以及旅游餐饮满意度是对总体满意度影响程度最大的三种分满意度,所占比例分别为43.58%、24.67%、10.62%。

Analyzing Recreational Fishery Satisfaction Based on Bayesian Multiple Ordered Probit Model

Tourist satisfaction is an important referral information for management decision makings of recreational fishery scenic spots. Through exploring the relationship between individual aspects of tourist satisfaction and the overall tourist satisfaction, managers can obtain important information about a better understanding of the tourists' preferences and their consumption behaviors as well as the tourism product designs. There are a large number of the studies associated with the consumers' satisfaction. Nevertheless, little attentions has been paid to the satisfaction issues on the recreational fisheries. To fill out the gap, we attempt to explore the relationship between the individual aspects of the tourists' satisfactions and the overall tourism satisfaction as they are engaged in various types of leisure fishery activities. We conductthe field survey through interviewing a total of 1510 tourists with regards to their satisfaction with the various aspects in their recreational activities based on the eleven National Recreation Fishery Demonstration Bases. The data is utilized in estimating the Bayesian multiple ordered probit model by applying a MCMC. The estimated posterior results are used to reflect the contribution of seven divisor satisfactions to the overall tourist satisfaction. The study results indicate that recreational experience, scenic environment, and food consumption are three divisor satisfactions which exert the greatest influence on the overall tourist satisfaction with each counting for 43.58%, 24.67%, and 10.62%, respectively.