旧金山国际机场顾客满意度的决定因素

IF 0.7 Q4 HOSPITALITY, LEISURE, SPORT & TOURISM
Ashok K. Singh, Myongjee Yoo, Rohan J. Dalpatadu
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引用次数: 5

摘要

本研究试图利用随机森林的分类方法,从旧金山国际机场(SFO)的航空公司乘客中确定整体满意度因素。该分析基于SFO 2014年进行的年度调查,该调查收集了乘客人口统计数据以及对机场设施和服务的满意度。本研究结果表明,对于SFO旅客的整体满意度,某些服务属性比其他服务属性更重要。研究结果有望为机场行业提供实用的见解。此外,本研究将随机森林的机器学习方法引入到旅游研究中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determinants of Customer Satisfaction at the San Francisco International Airport
This study attempts to determine the overall satisfaction factors from airline passengers at the San Francisco International Airport (SFO), using the classification method of random forest. The analysis is based on the 2014 annual survey conducted by SFO that collects data on passenger demographics and satisfaction with airport facilities and services. Results of this study indicate that some service attributes are more important than others for passengers’ overall satisfaction at SFO. Study results are expected to provide practical insights to the airport industry. This study, in addition, introduces the machine learning method of random forest to tourism research.
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来源期刊
European Journal of Tourism Hospitality and Recreation
European Journal of Tourism Hospitality and Recreation HOSPITALITY, LEISURE, SPORT & TOURISM-
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