Importance-Performance Analysis (IPA) Concept
Importance-performance analysis (IPA) is a widely accepted method for measuring service quality that is well known of its simplicity and stress-free application. The concept of IPA was introduced in 1977 by Martilla and James . Essentially, the idea of IPA comes from the theory of customer satisfaction as a function of the expectation on important attribute and the judgment of attribute performance . The underlying assumption in IPA is the relationship between importance attribute and attribute performance toward customer satisfaction is linear and symmetric . Thus, IPA focuses on the gap between the customer expectation on the importance and judgment on the performance of speciﬁc attribute of service consumed. The objective is to identify which attributes or its combination gives more impact toward customer satisfaction and leads to the repetitive customer purchase behavior . It is useful information to evaluate competitive position and enable prioritization of available strategies to enhance customer satisfaction.
In order to operationalize IPA analysis, it is critical to clearly determine the attributes of service delivered to the customer. Based on the predetermined attribute, two dimensions are classiﬁed: (1) the importance of each attribute and
(2) judgments of its performance. Therefore, the questions are developed to assess each attribute that surrounds the signiﬁcance of the attribute and how well the deliverable of attribute is separated into two sections.
Then, the questions were asked to the selected sample of customers to get their feedback. Using the feedback gathered from the customers, central tendency of each (mean values) attribute is calculated and rank ordered from high to low categories. The central tendency of each attribute's importance and performance will be paired and used as coordinates for plotting respective attribute in twodimensional grid that has been divided into four quadrants as illustrated in Fig. 12.2.
As observed in Fig. 12.2, each quadrant in IPA is divided by the importance of attribute from high to low (in vertical axis) and the performance of attribute from high to low (in horizontal axis). As a result, the disparity between importance and performance can be established. It provides indication that the customer is either satisﬁed or dissatisﬁed on the attributes of service consumed . Further analysis of IPA can be accomplished by locating each attribute into appropriate quadrant in order of its relative importance and performance, moving from the top to the bottom
Fig. 12.2 Four quadrants of importance-performance analysis (IPA) developed by Martilla and James 
of the quadrant . The placement of attributes will translate different impact upon the strategic interpretation within each quadrant. Four quadrants of IPA postulate different situation with different potential strategy for each quadrant. Further explanations of each quadrant are as follows:
Quadrant I: Keep Up the Good Work
The attribute placed in this quadrant has high importance and high performance. It indicates that the customers value such attribute as relevant to the service they consumed. Besides, the customers are also satisﬁed on how the attribute enhances the delivery of services. Therefore, such attribute must be maintained and exploited to achieve its maximum beneﬁts as potential competitive advantage. At this point, it is important to sustain optimum level of resources to sufﬁce its maximum beneﬁts.
Quadrant II: Concentrate Here
The attribute located in this quadrant has high importance, but low performance. It is an indicative of the critical performance shortfalls whereby the importance attribute fails to satisfy the customers. In order to ensure good quality of services delivered to the customers, such attribute should become a priority to be attained ﬁrst. This situation requires immediate actions and allocation of additional resources. If it is not immediately attained, it may become a major weakness that potentially reduces the level of competitiveness.
Quadrant III: Low Priority
The attribute situated in this quadrant has low importance and low performance. It shows the attribute is underperforming, but it requires no further action since it does nothing to the betterment of the services in the eyes of customers who consumed it. As such, there is no need for any changes in the efforts or resources allocated. Any extra efforts and resources spent on the attribute will just go in vain as the attribute has minimum impact to the consumed services.
Quadrant IV: Possible Overkill
The attribute which falls into this quadrant has low importance but high performance. It demonstrates the attribute was successfully performed but unfortunately deemed irrelevant by the customers. At this point, it is important to redeﬁne the need to allocate more resources toward such attribute. Perhaps it is more beneﬁcial to curtail the resource allocation and redeploy the efforts to the other attribute that needs immediate action.
The acceptance of IPA as the measurement of service quality is corroborated by
extensive application of IPA, largely in the tourism sector [26, 27], followed by banking sector , education sector [25, 29–31], electric and electronic sector , automotive sector , and many others. Until these days, IPA still received a lot of attention among the researchers discussing its potential applicability in various industries with just little modiﬁcation to suit the industry's nature of businesses. Thus, it is important to scrutinize it suitability to be combined with other measurement method to maximize its usability and beneﬁts.