{"title":"Service Quality Asymmetric Effect on Student Satisfaction in Korean Higher Education","authors":"Heuiju Chun, Byunghak Leem, Jongchan Lee","doi":"10.1007/s40299-024-00841-6","DOIUrl":null,"url":null,"abstract":"<p>This study investigates the asymmetric effects of quality attributes on student satisfaction in Korean higher education. Using Penalty–Reward–Contrast and Asymmetric Impact–Performance Analysis, it classifies attributes into basic (major and liberal arts curriculum, non-curricular courses, educational environment), one-dimensional (administrative services, academic system), and attractive (student support) factors. As a result of AIPA analysis, for the improvement of education quality, the most effective strategy is to set the priority of resource allocation in the order of basic, one-dimensional, and attractive factors. The study proposes a proportional odds logit model for more accurate classification, contributing a new perspective to the discourse on educational quality and satisfaction.</p>","PeriodicalId":501239,"journal":{"name":"The Asia-Pacific Education Researcher","volume":"67 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Asia-Pacific Education Researcher","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40299-024-00841-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the asymmetric effects of quality attributes on student satisfaction in Korean higher education. Using Penalty–Reward–Contrast and Asymmetric Impact–Performance Analysis, it classifies attributes into basic (major and liberal arts curriculum, non-curricular courses, educational environment), one-dimensional (administrative services, academic system), and attractive (student support) factors. As a result of AIPA analysis, for the improvement of education quality, the most effective strategy is to set the priority of resource allocation in the order of basic, one-dimensional, and attractive factors. The study proposes a proportional odds logit model for more accurate classification, contributing a new perspective to the discourse on educational quality and satisfaction.