## 2 Materials and Methods
### Literature Review
#### 2.2.3 Important-Satisfaction Analysis  
[PERSON], [PERSON] and [PERSON], proposed P.Z.B service quality model, and it is customer that determines the service quality. The difference between customer's expectations and actual cognition determines the standard of service quality [11]. The conceptual framework of \"Importance and Satisfaction Analysis\" (IS Analysis) come from another questionnaire analysis method \"Importance-Performance Analysis\" (IPA) [12] proposed by [PERSON] and [PERSON] (1977). The IPA research topics focus around the quality of service, investigating how important and how well it performs a respondent (customers, consumers etc.) feels to a service. The scale used in this analysis is relative comparison in that \"importance\" and \"performance\" use exactly the same questions to measure the respondent's response. IPA is first to calculate the averages of the \"importance\" and \"performance\" of all items individually, and then divide the two-dimensional graph into four quadrants based on the averages of the \"importance\" and \"performance\" of the items. The purpose is to find out the relevant indicators that affect the company's operations, consumption goals or business models, and finally use the relative position of the item to describe the performance of this item, so as to provide researchers (such as industry, service unit) an important information of improvement priority in terms of service quality. Typically, X-axis (horizontal axis) stands for \"Performance\" and Y-axis (vertical axis) stands for \"Importance\". Centered at the average of importance and performance of all items, the plane is divided into four quadrants. Area I: indicating that the degree of importance is high but the degree of performance is low. The attributes falling in this quadrant should be the focus that required urgent improvement. Area II: indicating that both the importance and performance are high, and the attributes that fall into this quadrant should continue to be maintained (keep up the good work). Area III: indicating that both the degree of importance and performance are low, and the attributes falling in this quadrant have a low priority. Area IV: indicating that the importance is low and the performance is high. The attribute falling in this quadrant is possible overkill.In 1992, [PERSON], [PERSON], and [PERSON] (1992) [13] reconceptualized the importance-performance analysis of IPA into Importance-Satisfaction Analysis (IS Analysis), which was different from the original IPA in that the original external strategy concept (consumers and products) is extended to internal operations. This model used in resource management application is to evaluate the importance of key indicators and cognitive satisfaction by organization members, thus it is called \"Importance-Satisfaction Analysis (I-S Analysis)\", as shown in Figure 1.  
The first step of I-S Analysis is to complete a comprehensive list of key indicators, and through literature review and in-depth interview with experts to understand subjective experiences from these interviewees, guiding them to provide some information or express their opinions and thoughts([PERSON], 1991) [14]. Indicators can be collected by either Interviewees talk over the questions raised by the interviewers or group interviews are conducted. I-S Rating is made based on the list of the collected indicators. Interviewee would be asked to score for satisfaction rating for the key indicators on the rating scale (such as a 5-scale score, 1 = very dissatisfied, 5 = very satisfied), and the importance rating is also given to each key indicator. Similar to the satisfaction rating, it is rated on the scale from the \"very unimportant\" to the \"very important\". Importance and Satisfaction have different meanings. Importance refers to the importance of employees' awareness of the organization's various environmental measures, services or management factors, while satisfaction means the degree of satisfaction that employee's sense about each factor.