基于生命历程理论的养老旅游决策行为影响因素研究——以重庆市为例

对养老旅游决策行为影响因素的研究有助于发现旅游主体的内在动因，深入开拓养老旅游市场。本研究基于生命历程理论，选取影响养老旅游决策行为的16个变量设计问卷，在重庆市展开实地调查；运用二元logistic回归模型对调查数据进行分析。结果显示：对养老旅游决策行为的影响中，“个人能动性”影响最为显著，“相互联系的生活”影响较为显著，“一定时空中的生活”有一定影响，“生活的时间性”影响不显著；总体而言，对养老旅游决策行为影响较为显著的因素有居住地、退休前从事职业、退休后年收入水平、是否有需要照顾的家人、文化程度、养老储蓄、个人年际旅游最高频次、动态爱好活动频率。养老旅游决策行为受不同生命历程影响。

INFLUENCING FACTORS OF THE OLD-AGE CARE TOURISM DECISION MAKING BEHAVIOR BASED ON THE LIFE COURSE THEORY: A CASE OF CHONGQING

As the aging of the population increase in China society and the coming of the era of mass tourism, the old-age care tourism as a new endowment mode is highly concerned by the whole society and become the new domain of tourism academic research. The research on the influencing factors of the decision-making behavior of the old-age care tourism is used to find the inner drive of tourism subject and further expand old-age care tourism market. Furthermore, the analysis of the decision-making behavior of the old-age care tourism main body is related to the construction of the destination. The image, infrastructure and service level of old-age care tourism destination are directly affected by the decision-making behavior of the old-age tourism. This is helpful to promote the healthy development of China's old-age care tourism. Therefore, this paper introduces the Life Course Theory to study the decision-making behavior of old-age tourists. In this paper, we design a questionnaire with the variables that affect the decision-making behavior of the old-age care tourism that select based on the Life Course Theory. Field survey was conducted in Chongqing City, and binary logistic regression model was used to analyze the survey data. Put the data into the regression model. At last the results obtained showed:There are eight factors have significant effects on the decision-making behavior of the old-age care tourism. Including area of residence, engaged in the occupation before retirement, annual income level after retirement, whether there is a need to take care of the family, level of education, pension savings, the highest annual travel frequency of individual, the frequency of dynamic activity.