基于生存分析模型的游客停留天数影响因素分析——以大连滨海旅游为例

运筹与管理 ›› 2014, Vol. 23 ›› Issue (1): 123-130.

基于生存分析模型的游客停留天数影响因素分析——以大连滨海旅游为例

王尔大^1,2, 李花¹, Bertis B. Little^1,2

1.大连理工大学工商管理学院,辽宁大连 116023;
2.塔尔顿州立大学计算机科学与数学系,美国德克萨斯州斯蒂芬维尔市 76402-0010

收稿日期:2012-01-13 出版日期:2014-01-25
作者简介:王尔大,男,博士,教授,博士生导师,大连理工大学工商管理学院人力资源与旅游管理研究所所长,美国德克萨斯塔尔顿州立大学兼职教授;Bertis B. Little,大连理工大学海外特聘教授。
基金资助:
教育部博士点科研基金项目(20110041110026)

A Survival Model Analysis on Factors Contributing to Tourists'Length of Stay in Dalian

WANG Er-da^1,2, Li Hua¹, Bertis B. Little^1,2

1. School of Business Administration, Dalian University of Technology, Dalian 116023, China;
2. Department of Computer Science and Mathematics, Tarleton State University, Stephenville, Texas 76402-0010, USA

Received:2012-01-13 Online:2014-01-25

摘要/Abstract

摘要： 游客的停留天数是影响旅游经济发展的一个重要因素。但是,由于停留天数变量特有的统计属性和复杂性,如数据删失和非负性,使得经济研究领域很少有学者系统地的研究这一问题。本文通过使用计量经济学的参数化生存分析模型分析游客停留天数的决定因素,这对旅游需求研究是一个很好的创新。在研究过程中,为了揭示影响游客停留天数的主要因素,本文考虑了多个关于游客的社会-人口统计特征等变量。结果显示,重复旅行的游客和距离较远的游客会停留较长的天数。因此,未来研究需要进一步分析具有这些特征的游客群体以及他们的经济状况和旅游活动特征等情况。游客的收入水平和年龄也对停留天数具有显著的影响。此外,游客受教育程度越高,停留天数越少。最后,本文分别分析了这些结果对旅游管理决策的含义。

关键词: 旅游经济, 生存分析, Cox模型, 回归分析, 游客停留天数

Abstract: Length of stay is one of the most important determinants of the overall impact of tourism in a given economy. However, due to its statistical nature and complexity such as censoring and non-negativity, it is rarely systematically analyzed in economic research literature. This article estimates an econometric parametric survival analysis model to learn the determinants of length of stay, in a novel way in the tourism demand literature. In the process, a number of tourist’s socio-demographic characteristics are analyzed in order to disclose the most important factors that can contribute to the length of tourist stays. Results indicate that being a repeat visitor and with far travel distance are important criteria to identify tourists who are likely to experience longer stays. Thus, future research should characterize such groups and their economic and activity involvement. Level of tourist income and age also play highly statistically significant role in determining length of stay. In addition, a higher degree of education is associated with shorter expected stays. Finally, all those findings'policy implications are addressed accordingly.

Key words: tourism economics, survival analysis, cox model, regression analysis, tourist’s length of stay

中图分类号:

F590

王尔大, 李花, Bertis B. Little. 基于生存分析模型的游客停留天数影响因素分析——以大连滨海旅游为例[J]. 运筹与管理, 2014, 23(1): 123-130.

WANG Er-da, Li Hua, Bertis B. Little. A Survival Model Analysis on Factors Contributing to Tourists'Length of Stay in Dalian[J]. Operations Research and Management Science, 2014, 23(1): 123-130.

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