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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (11): 46-53    DOI: 10.11925/infotech.2096-3467.2018.0836
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Impacts of Landlords on Tenants of Short-term Rentals
Liang Xiaobei, Xu Zhen(), Li Jingjing
School of Economics and Management, Tongji University, Shanghai 200092, China
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Abstract  

[Objective] This study explores the influences of room owners on their tenants’ Electronic Word of Mouth(eWOM). [Methods] First, we retrieved data from Airbnb with the help of a Web crawler. Then, we proposed a Poisson Regression model based on the signal theory. Finally, we studied the impacts of room owners’ service on consumers’ eWOM. [Results] The eWOM of the available rooms was positively correlated with features introduction, after-sales interaction, instant reservation, calendar update, response time, high-quality service and identity certification. [Limitations] More samples from regions outside of Beijing should be included. [Conclusions] The proposed model could improve the service of short-term rentals.

Key wordsSharing Short-term Rental Platform      Host Attributes      eWOM     
Received: 26 July 2018      Published: 11 December 2018
ZTFLH:  G203  

Cite this article:

Liang Xiaobei,Xu Zhen,Li Jingjing. Impacts of Landlords on Tenants of Short-term Rentals. Data Analysis and Knowledge Discovery, 2018, 2(11): 46-53.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0836     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I11/46

变量类型 变量名 变量符号 变量描述
因变量 总评论数 reNum 短租客户对列表房源的总评论数量
半年评论数 halfNum 短租客户对列表房源的近半年的评论数量
客户需求 特色介绍 space 商家是否介绍列表房源周边的特色情况(0表示没有特色介绍, 1表示有特色介绍)
售后互动 Inter 商家是否承诺客户入住后含有售后服务(0表示商家没有承诺, 1表示有承诺)
服务响应 即时预订 insBook 是否需要获得商家的批准才能预订房源(0表示需要获得批准, 1表示不需要获得)
日历更新 calender 商家最近一次更新可订房间日历的时间
回复时间 resTime 商家平均回复客户咨询的时间
安全保证 身份认证 identity 商家是否经过平台的各项身份认证(0表示未经过身份认证, 1表示已经过认证)
优质商家 SuperHost 商家是否是平台认证的优质商家(0表示不是优质商家, 1表示是优质商家)
控制变量 房源地点 location 列表房源的所在位置(0表示房源在郊区, 1表示在市区)
房源价格 price 列表房源的房间价格
房源数量 listNum 商家拥有的所有列表房源数量
商家年限 member 商家的注册年限
变量类型 变量名 平均值 标准差 最小值 最大值
因变量 reNum 12.05 19.80 1 250
halfNum 3.42 4.82 0 45
自变量 space 0.76 0.43 0 1
Inter 0.65 0.48 0 1
insBook 0.58 0.49 0 1
calender 3.29 1.28 1 5
resTime 3.75 0.64 1 4
identity 0.46 0.50 0 1
SuperHost 0.25 0.43 0 1
控制变量 location 0.84 0.37 0 1
price 462.34 572.30 64 10 000
listNum 10.61 24.33 1 224
member 2.02 1.24 0 8
主模型
因变量: 总评论数
稳健性检验
因变量: 半年的评论数
系数 标准误 P值 系数 标准误 P值
space .482 .011 0.000 .222 .019 0.000
Inter .181 .009 0.000 .231 .016 0.000
insBook .171 .007 0.000 .419 .013 0.000
calender .116 .003 0.000 .164 .005 0.000
resTime .183 .007 0.000 .543 .018 0.000
identity .389 .007 0.000 -.010 .012 0.459
SuperHost .521 .006 0.000 .698 .012 0.000
location .675 .012 0.000 .629 .021 0.000
Log(price) -.064 .005 0.000 -.122 .009 0.000
Log(listNum) -.106 .003 0.000 -.162 .005 0.000
member .227 .002 0.000 .024 .005 0.000
_cons -.208 .038 0.000 -.214 .083 0.000
Obj. 8 867 8 867 8 867 8 867 8 867 8 867
Mean VIF 1.24 1.24
LR chi2(11) 50128.28(p=0.000) 13090.64(p=0.000)
Log like -74920.90 -25885.049
假设 结果
H1a: 商家的特色介绍属性对eWOM有显著的正向影响。 支持
H1b: 商家的售后互动属性对eWOM有显著的正向影响。 支持
H2a: 商家的即时预订属性对eWOM有显著的正向影响。 支持
H2b: 商家的日历更新属性对eWOM有显著的正向影响。 支持
H2c: 商家的回复时间属性对eWOM有显著的正向影响。 支持
H3a: 商家的身份认证属性对eWOM有显著的正向影响。 支持
H3b: 商家的优质商家属性对eWOM有显著的正向影响。 支持
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