期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2020
卷号：47
期号：3
语种：English
出版社：IAENG - International Association of Engineers
摘要：This study uses derived importance based on the multiple determination coefficient to replace self-stated importance for importance-performance analysis. The traditional importance-performance analysis assumes that there are no interactions among the survey items. Without considering the interactions among the survey items, some items might be either underestimated or overestimated in terms of importance for quadrant classifications, which might result in misunderstanding the major strengths (weaknesses) to minor strength (weaknesses) and vice versa. Thus, the improvement efforts might be in vain. In this study, the proposed framework based on the multiple determination coefficient considers the items interactions to be under the other items influence. A case is illustrated to show how this framework differs from the traditional importance-performance analysis when interactions among the survey items are taken into consideration.
关键词：multiple determination coefficient;importance performance analysis;fuzzy measure;Shapley value
