当前位置: X-MOL 学术International Journal of Hospitality Management › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A big data analysis of COVID-19 impacts on Airbnbs’ bookings behavior applying construal level and signaling theories
International Journal of Hospitality Management ( IF 11.7 ) Pub Date : 2023-03-10 , DOI: 10.1016/j.ijhm.2023.103461
Raffaele Filieri 1 , Francesco Luigi Milone 2 , Emilio Paolucci 3 , Elisabetta Raguseo 3, 4
Affiliation  

This study investigates the impact of the COVID-19 pandemic on consumer booking behavior in the peer-to-peer accommodation sector. This study used a dataset composed of 2,041,966 raws containing 69,727 properties located in all 21 Italian regions in the pre- and post-COVID-191. Results show that in the pre-COVID-19 period, consumers preferred P2P accommodations with price premiums and located in rural (versus urban) areas. Although the findings reveal a preference for entire apartments over shared accommodation (i.e., room, apartment), this preference did not change significantly after COVID-19 lockdowns. The contribution of this study lies in combining psychological distance theory and signaling theory to assess P2P performance in the pre- and post-COVID-19 periods.



中文翻译:

应用解释水平和信号理论对 COVID-19 对 Airbnbs 预订行为影响的大数据分析

本研究调查了 COVID-19 大流行对点对点住宿行业消费者预订行为的影响。这项研究使用了一个由 2,041,966 个原始数据组成的数据集,其中包含 69,727 个属性,这些属性位于 COVID-19 前后1的所有 21 个意大利地区。结果表明,在 COVID-19 之前的时期,消费者更喜欢价格溢价且位于农村(相对于城市)地区的 P2P 住宿。尽管调查结果表明人们更喜欢整套公寓而不是合租的住宿(即房间、公寓),但这种偏好在 COVID-19 封锁后并没有发生显着变化。本研究的贡献在于结合心理距离理论和信号理论来评估 COVID-19 前后时期的 P2P 表现。

更新日期:2023-03-10
down
wechat
bug