Operationalization of Importance-Performance Analysis With Nine Categories and Tested for Green Practices and Financial Evaluation

Abstract

The Importance-Performance Analysis is a widely used diagnostic tool in many fields of economic activity, such as: transport, health, construction, public food industry, finance, banking, sustainable activities, etc. Despite its use for over 40 years in many economic and social fields, this tool has some important drawbacks that affect the accuracy of managerial decisions. Over time, many variants for improving the standard Importance-performance matrix have been proposed. The aim of our research is to propose a method to solve one of the biggest problems of the standard Importance-Performance Analysis, respectively a method of boosting confidence in the positioning of attributes in the matrix. We use a mathematical method, inspired by classification theory tools, to apply the nine categories division of attributes in the importance-performance plane. Moreover, we introduce a level of confidence in a nine categories Importance-performance matrix, which helps the practitioners to prioritize a decision on attributes, according to the resources, managerial plan, competition, etc. We test and discuss the effectiveness of the new method on two studies: on the green practices in educational restaurant operations and on the financial performance evaluation.

Evaluation of the Quality of Higher Education Services by Revised IPA in the Perspective of Digitization

“…The proposed method lends itself very well when there are many attributes tion, as is the case here. According to Ban et al [45], the thresholding axes are g (see Figure 2): We chose to apply the Nine-Quadrant Importance-Performance analysis method with a confidence value (9Qc-IPA) due to its compatibility with the number of attributes used in the study and the suggestive way of representing the results. This involves the distribution of a given set of service attributes/factors/characteristics into four categories as described in Figure 1.…”

“…Ban et al [45] improved the original IPA by providing a mathematical support for the 9-quadrant IPA (Figure 2), complementing the idea of Albrecht and Bradford [46] by proposing the 9Q-IPA, which is actually a rigorous thresholding procedure of importanceperformance axes. It is observed that in the method proposed by Albrecht and Bradford [46], the resulting matrix has 9 quadrants, of which only 4 propose strategic measures for the contained attributes (clear category).…”

“…It is observed that in the method proposed by Albrecht and Bradford [46], the resulting matrix has 9 quadrants, of which only 4 propose strategic measures for the contained attributes (clear category). The names of the 4 quadrants in the method of Albrecht and Bradford [46] correspond to those of the importance-performance analysis of Martilla and James [37] Ban et al [45] mathematically defined the boundaries of the quadrants and proposed a parameter "c" (which is α in original paper) that allows the adjustment of strategic measures according to the experience of the decision-maker, taking into account resources, competitors, and objectives pursued. The confidence value, c ∈ 0,1 , gives some elasticity in the application of the method (9Qc-IPA).…”

Romania Residents’ Attitude Investigation toward the Transition to Renewable Energy Sources through Importance-Performance Analysis

“…Ban et al [34] propose a method (9Q-IPA) to solve one of the most pressing problems of standard importance-performance analysis: the positioning of attributes in quadrants. They used a mathematical approach found in the tools of classification theory to apply the attribute/factor division in the importance-performance plane to the nine categories.…”

“…They used a mathematical approach found in the tools of classification theory to apply the attribute/factor division in the importance-performance plane to the nine categories. They [34] improve the 9Q-IPA method by introducing a parameter that gives a certain elasticity to our approach (9Qc-IPA). The efficiency of this method is seen when there are a large number of attributes/factors, and the positioning of many of them near the matrix axes makes it difficult and questionable to assign them to one quadrant or another.…”