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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/77245


    Title: Inno-Qual efficiency of higher education: Empirical testing using data envelopment analysis
    Authors: Chen, Jui-kuei;Chen, I-shuo
    Contributors: 淡江大學未來學研究所
    Keywords: Inno-Qualefficiency;Higher education;The Inno-Qual performance system;Dataenvelopmentanalysis
    Date: 2011-03
    Issue Date: 2012-06-14 09:15:18 (UTC+8)
    Publisher: Kidlington: Pergamon
    Abstract: Since the overall quality of Taiwanese university education has been decreasing in recent years, and universities are losing their competitive advantage while facing foreign countries’ education systems and the threat of closing, upgrading innovation performance and improving total quality performance (Inno-Qual performance) so as to enhance overall operational performance have become an urgent issue. Although relative measurement models are increasingly being used for conquering the above-mentioned difficulties, such as the Inno-Qual performance system (IQPS), which integrates the features of innovation and TQM, currently, no studies empirically evaluate the efficiency of such improvement, meaning that the costs of using the Inno-Qual performance system are increasing, particularly the human administrative cost for providing intellectual products, which is the nature of higher education. To overcome this problem, in this study, the IQPS is adopted by using dataenvelopmentanalysis (DEA) to evaluate the Inno-Qualefficiency of 99 Taiwanese universities divided into five types (research-intensive, teaching-intensive, profession-intensive, research & teaching-intensive, and education-in-practice-intensive). On the basis of the empirical results, we found that over half (73%) of the universities are highly inefficient in improving the Inno-Qual performance, and thus we conclude that improving the Inno-Qualefficiency based on our results will be helpful for reducing the majority of cost expenditures.
    Relation: Expert Systems with Applications 38(3), pp.1823-1834
    DOI: 10.1016/j.eswa.2010.07.111
    Appears in Collections:[未來學研究所] 期刊論文

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