Hotel Service Analysis by Penalty-Reward Contrast Technique for Online Review Data
Abstract
:1. Introduction
2. Research Background
2.1. Three-Factor Theory of Customer Satisfaction
- Basic factor: A factor that causes dissatisfaction if not satisfied yet does not lead to satisfaction if satisfied or exceeded, and has an asymmetric effect on customer satisfaction. Negative performance on these attributes has a greater impact on overall satisfaction than positive performance.
- Excitement factor: A factor that increases customer satisfaction if satisfied, but does not cause dissatisfaction if not satisfied, and has an asymmetric effect on customer satisfaction like a basic factor.
- Performance factor: High performance leads to satisfaction while low performance leads to dissatisfaction, which has a symmetrical effect on customer satisfaction.
2.2. Penalty-Reward Contrast Analysis
2.2.1. Dummy Variable Conversion
2.2.2. Quality Attributes Classification
3. Method
3.1. Data Collection
3.2. Apply Penalty-Reward Contrast Analysis
3.2.1. Dummy Variable Conversion
3.2.2. Regression Analysis
3.2.3. Attribute Classification
4. Results
4.1. Descriptive Analysis
4.2. Geographical Differences in Destinations for The Asymmetric Effects of Hotel Attributes
4.3. Cultural Differences in the Asymmetric Effects of Hotel Attributes
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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City | Language | No. of Hotel | No. of Review |
---|---|---|---|
Shanghai | English | 1170 | 26,236 |
Chinese | 1005 | 13,297 | |
Seoul | English | 574 | 13,016 |
Korean | 484 | 6806 | |
New York | English | 521 | 53,757 |
City | Language | Variables | Min | Max | Mean | Std |
---|---|---|---|---|---|---|
Shanghai | English | Value | 1 | 5 | 4.11 | 0.969 |
Cleanliness | 1 | 5 | 4.45 | 0.854 | ||
Service | 1 | 5 | 4.18 | 1.070 | ||
Location | 1 | 5 | 4.31 | 0.901 | ||
Rooms | 1 | 5 | 4.32 | 0.900 | ||
Sleep Quality | 1 | 5 | 4.38 | 0.912 | ||
Customer Satisfaction | 1 | 5 | 4.23 | 0.968 | ||
Chinese | Value | 1 | 5 | 3.89 | 0.897 | |
Cleanliness | 1 | 5 | 4.24 | 0.806 | ||
Service | 1 | 5 | 4.00 | 0.944 | ||
Location | 1 | 5 | 4.09 | 0.878 | ||
Rooms | 1 | 5 | 4.14 | 0.843 | ||
Sleep Quality | 1 | 5 | 4.12 | 0.869 | ||
Customer Satisfaction | 1 | 5 | 4.10 | 0.856 | ||
Seoul | English | Value | 1 | 5 | 4.03 | 0.969 |
Cleanliness | 1 | 5 | 4.41 | 0.841 | ||
Service | 1 | 5 | 4.28 | 0.955 | ||
Location | 1 | 5 | 4.34 | 0.862 | ||
Rooms | 1 | 5 | 4.14 | 0.950 | ||
Sleep Quality | 1 | 5 | 4.25 | 0.934 | ||
Customer Satisfaction | 1 | 5 | 4.19 | 0.923 | ||
Korean | Value | 1 | 5 | 3.99 | 1.001 | |
Cleanliness | 1 | 5 | 4.25 | 0.979 | ||
Service | 1 | 5 | 4.17 | 1.054 | ||
Location | 1 | 5 | 4.42 | 0.861 | ||
Rooms | 1 | 5 | 4.08 | 1.019 | ||
Sleep Quality | 1 | 5 | 4.22 | 0.952 | ||
Customer Satisfaction | 1 | 5 | 4.14 | 1.025 | ||
New York | English | Value | 1 | 5 | 4.35 | 0.887 |
Cleanliness | 1 | 5 | 4.74 | 0.602 | ||
Service | 1 | 5 | 4.65 | 0.763 | ||
Location | 1 | 5 | 4.79 | 0.513 | ||
Rooms | 1 | 5 | 4.52 | 0.790 | ||
Sleep Quality | 1 | 5 | 4.57 | 0.786 | ||
Customer Satisfaction | 1 | 5 | 4.60 | 0.765 |
Hotel Attributes | Dummy Variable Regression Analysis Coefficients **** | IR-Value | Categorization | |
---|---|---|---|---|
Low Performance | High Performance | |||
Value | −0.747 *** | 0.184 *** | 0.246 | Basic factor |
Cleanliness | −0.408 *** | 0.255 *** | 0.625 | Basic factor |
Service | −1.166 *** | 0.458 *** | 0.393 | Basic factor |
Locations | −0.269 *** | 0.141 *** | 0.524 | Basic factor |
Rooms | −0.286 *** | 0.329 *** | 1.150 | Excitement factor |
Sleep Quality | −0.500 *** | 0.217 *** | 0.434 | Basic factor |
Hotel Attributes | Dummy Variable Regression Analysis Coefficients **** | IR-Value | Categorization | |
---|---|---|---|---|
Low Performance | High Performance | |||
Value | −0.821 *** | 0.228 *** | 0.278 | Basic factor |
Cleanliness | −0.416 *** | 0.215 *** | 0.517 | Basic factor |
Service | −1.040 *** | 0.416 *** | 0.400 | Basic factor |
Locations | −0.081 | 0.182 *** | 2.247 | Excitement factor |
Rooms | −0.575 *** | 0.303 *** | 0.527 | Basic factor |
Sleep Quality | −0.453 *** | 0.212 *** | 0.468 | Basic factor |
Hotel Attributes | Dummy Variable Regression Analysis Coefficients **** | IR-Value | Categorization | |
---|---|---|---|---|
Low Performance | High Performance | |||
Value | −1.039 *** | 0.134 *** | 0.129 | Basic factor |
Cleanliness | −0.245 *** | 0.254 *** | 1.037 | Performance factor |
Service | −1.078 *** | 0.515 *** | 0.478 | Basic factor |
Locations | 1.401 | 0.164 *** | 0.117 | Basic factor |
Rooms | −0.572 *** | 0.281 *** | 0.491 | Basic factor |
Sleep Quality | −0.601 *** | 0.144 *** | 0.240 | Basic factor |
Hotel Attributes | Dummy Variable Regression Analysis Coefficients **** | IR-Value | Categorization | |
---|---|---|---|---|
Low Performance | High Performance | |||
Value | −0.729 *** | 0.178 *** | 0.244 | Basic factor |
Cleanliness | −0.140 | 0.244 *** | 1.743 | Excitement factor |
Service | −1.339 *** | 0.262 *** | 0.196 | Basic factor |
Locations | −0.228 *** | 0.133 *** | 0.583 | Basic factor |
Rooms | −0.408 *** | 0.462 *** | 1.132 | Excitement factor |
Sleep Quality | −0.645 *** | 0.162 *** | 0.251 | Basic factor |
Hotel Attributes | Dummy Variable Regression Analysis Coefficients **** | IR-Value | Categorization | |
---|---|---|---|---|
Low Performance | High Performance | |||
Value | −0.544 *** | 0.171 *** | 0.314 | Basic factor |
Cleanliness | −0.580 *** | 0.021 *** | 0.036 | Basic factor |
Service | −1.262 *** | 0.469 *** | 0.372 | Basic factor |
Locations | −0.081 | 0.224 *** | 2.765 | Excitement factor |
Rooms | −0.913 *** | 0.303 *** | 0.332 | Basic factor |
Sleep Quality | −0.094 *** | 0.177 *** | 1.883 | Excitement factor |
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Zhang, W.T.; Choi, I.Y.; Hyun, Y.J.; Kim, J.K. Hotel Service Analysis by Penalty-Reward Contrast Technique for Online Review Data. Sustainability 2022, 14, 7340. https://doi.org/10.3390/su14127340
Zhang WT, Choi IY, Hyun YJ, Kim JK. Hotel Service Analysis by Penalty-Reward Contrast Technique for Online Review Data. Sustainability. 2022; 14(12):7340. https://doi.org/10.3390/su14127340
Chicago/Turabian StyleZhang, Wen Tu, Il Young Choi, Yun Joo Hyun, and Jae Kyeong Kim. 2022. "Hotel Service Analysis by Penalty-Reward Contrast Technique for Online Review Data" Sustainability 14, no. 12: 7340. https://doi.org/10.3390/su14127340