## 2 Literature Review
### Importance-Performance Analysis  
Importance-performance analysis (IPA), proposed by [PERSON] and [PERSON] (1977), is a graphical tool to classify attributes for improvement and rank their priority based on the importance and performance of each product/service attribute [34,81]. This approach constructs a plot with two dimensions, importance and performance of product/service attribute perceived by consumers, and classifies attributes into four quadrants equipped with different management strategies. An example of IPA is given in Figure 2. Quadrant I is labeled 'Keep up the good work', where attributes are considered highly important, and their performance is high. Attributes located in quadrant I can be considered as the major strengths of the product/service and should be maintained. Quadrant II is labeled 'Possible overkill', where attributes have low importance but high performance. The resources dedicated to these attributes may be excessive, so reallocating limited resources to address other more important attributes is proper. Quadrant III is labeled 'low priority', where attributes have both low importance and performance. Attributes in this quadrant are regarded as the minor weakness and have a low priority for improvement. Quadrant IV is labeled 'Concentrate here', where attributes are considered highly important but are poorly performed. Attributes in this quadrant are regarded as the major weaknesses and should be given a high priority for improvement.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Literature** & **Objective** & **Classifying Method** & **Sample Source** \\ \hline [PERSON] and [PERSON] (2018) [11] & Analyze competitive qualities required for improvement to enhance service quality of models in Taiwan. & Moderated regression & Questionnaire \\ \hline [PERSON] et al., (2020) [10] & Explore the asymmetric effects of attribute performance on customer satisfaction with respect to different market segments. & PRCA & TripAdvisor.com \\ \hline \hline \end{tabular}
\end{table}
Table 1: Cont.  
IPA is applied in a wide variety of research domains, partly due to the clear managerial strategies it provides on how to allocate resources and efforts [82], and also due to its ability to identify the strengths and weaknesses of product/service to guide management in taking effective measures to keep competitive [83]. In hospitality research, IPA is commonly integrated with other techniques, such as SERVQUAL [84,85], data envelopment analysis [86,87], partial least squares path modeling [88], the Kano model [10,30,31,32,33]. Many scholars have applied a combination of the Kano model and IPA on customer satisfaction analysis. For example, [PERSON] et al. [10] applied the Kano model and asymmetric IPA to explore the asymmetric effects of hotel attribute performance on customer satisfaction through online ratings. [PERSON] and [PERSON] [31] integrated the Kano model and IPA into a three-dimensional IPA approach to identify the critical service attributes for hotel online booking through survey. [PERSON] [32] constructed an IPA-Kano model for classifying and diagnosing service attributes at the TPE airport. [PERSON] et al. [33] combined the Kano model and IPA to investigate the critical service quality attributes to enhance customer satisfaction in the chain restaurant industry.  
However, few hotel studies conducted Kano-IPA analysis using online textual review. Furthermore, few studies have applied Kano-IPA model to obtain the hotel attribute priority ranking for resource allocation to get improved across different hotel star ratings. These literature gaps need to be dealt with. Thus, considering the effectiveness of the Kano model and IPA for providing constructive guidelines to hotels to enhance customer satisfaction, it is of great significance to explore the application of Kano-IPA model in hotel textual reviews across different hotel star ratings.