以羅吉斯迴歸分析旅館訂房取消政策之決定因素

Abstract

本篇研究目的為分析旅館取消政策之訂定，應用統計方法中之羅吉斯迴歸模型，探討取消政策類型與影響因子間之關聯，作為旅館經理人在收益管理及訂房取消政策上之參考依據。兩種取消政策為：可以免費取消、不可免費取消。旅館在房型之取消政策訂定時，可以選擇其中一種，或者同時提供兩種選擇。本篇研究僅針對旅館取消政策中之其中兩種情形做進一步分析探討：同時具有免費取消與不可取消之政策、僅提供免費取消之政策。 於2020年初爆發之新冠肺炎造成全球疫情爆發，旅遊業首當其衝。本篇研究想了解旅館訂定取消政策是否會因為疫情而有所調整。因此，本研究選擇之樣本分別為新冠肺炎疫情前兩個日期：2019年11月9日及2019年11月20日，以及疫情後兩個日期：2020年4月9日及2020年4月15日，分別就四個日期之不同房型的資料，針對旅館經理人主動管理程度指標、地區、星級等等因子進行羅吉斯迴歸分析。建構旅館取消政策訂定模式，瞭解影響同時具有免費取消及不可取消政策，與僅有免費取消政策之關鍵因子。 根據本研究之結果推論，不論疫情前後時間，旅館經理人之主動管理程度與地區是否位於觀光區或台北市，皆對於取消政策有顯著影響。反而，星級豪華與否、以及旅館房間數與旅館取消政策的訂定沒有顯著的關係。

The purpose of this study is to analyze the formulation of hotel cancellation policies. This study applies the Logistic regression model in statistical methods, and explores the relationship between cancellation policy types and impact factors as a reference for hotel managers in revenue management and reservation cancellation policies. There are two cancellation policies: free cancellation and non-free cancellation. This study only further analyzes and discusses two types in the hotel cancellation policy: there are both free cancellation and non-cancellation policies, and only free cancellation policies. COVID-19 outbreaks in early 2020 caused a globally pandemic, and the tourism industry was therefore being the first to suffer from great impact. This study wants to know whether the cancellation policy set by the hotel will be adjusted owing to the epidemic situation. Therefore, the samples selected in this study were the two dates before COVID-19 outbreak: November 9th, 2019 and November 20th, 2019, and the two after COVID-19 outbreak: April 9th, 2020 and April 15th, 2020. Based on the data of the different room types on the four dates, the Logistic regression analysis was carried out on the factors such as the index, area, star rating and other factors of the hotel manager's active management. Constructing a hotel cancellation policy setting model to understand the key factors that affect both free cancellation and non-cancellation policies and only free cancellation policies. According to the results of this study, regardless of the time before and after the epidemic, the degree of active management of the hotel manager and whether the area is located in the tourist area or Taipei City have a significant impact on the cancellation policy. On the contrary, there is no significant relationship between star luxury and the number of hotel rooms and hotel cancellation policies.