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  • 學位論文

私立技專校院財務警訊和校務評鑑之實證研究

The Study of Financial Warning and Evaluation in Private Technical Colleges and Universities

指導教授 : 陳若暉

摘要


私立技專校院在面臨生源不足的環競下,將面臨財務危機的可能性。故本研究主要結合私立技專校院整體發展獎補助經費之遭扣減比例與學校財務指標,建構私立技專校院財務危機的評鑑預警模式,並探討如何因應困境,以免陷入財務危機。 本研究係針對2006年至2008年間,各私立技專校院遭教育部扣減40%績效型獎助經費之比率,利用集群分析及多元尺度分析法進行分群與對照。就2002至2006學年度各校各學年度五項財務及量化指標,包括『日間部學生人數』、『生師比』、『人事費佔學雜費比例』、『扣除不動產支出前之現金餘絀率』及『財務支出(利息費用)金額佔總收入比例平均值』進行集群分析,並試著建立私立技專校院財務評鑑警訊模型。另將五項財務及量化指標進行合併集群分析,並試著與扣減獎補助經費之群組對照,試著給予分類與定位。 實證結果顯示: 依『扣減40%績效型獎助經費比率』同時利用集群分析法〈Cluster Analysis〉及多元尺度分析法〈Multidimensional Sca,ling,MDS〉進行分析:依扣減比例由低至高,依序為:『未曾或僅極為輕微比例』之扣減、『輕微比例』之扣減、『非重大比例』之扣減、『重大比例』之扣減及『重大且連續』之扣減等五個群組;結果顯示弱勢群組有:南亞技術學院、仁德醫護管理專校、高美醫護管理專校等3所學校;待改進群組有:明新科技大學、大仁科技大學、中州技術學院、黎明技術學院、台北海洋技術學院、育英醫護管理專校等6所學校。 五項財務及量化指標進行合併分析時,以採用集群分析較具有分析及鑑別力。由相對較優至相對較差共分為五個群組,結果顯示第四集群(待改進群)有:慈濟技術學院、黎明技術學院、崇右技術學院、大同技術學院、台北海洋技術學院、敏惠醫護管理專校、育英醫護管理專校等7所學校;另第五群組(弱勢群)有:親民技術學院、臺灣觀光學院、高美醫護管理專校等3所學校。 當學校五項財務及量化指標合併集群分析為相對弱勢群組時,即在73所私立技專校院中,學校經營較為艱辛。若又因校務缺失、財務缺失、評鑑成績不理想,遭教育部扣減整體發展獎補助經費、扣減招生名額、調降學雜費收費基準等,預期學校體質將更加惡劣。未來面臨出生人口逐年遞減,學生來源不足,高等教育競爭日益嚴重等隱憂。首當其衝的弱勢群組學校應積極擬定開源節流,以避免陷入財務危機困境。

關鍵字

財務警訊

並列摘要


Technical and Vocational Education Colleges (TVECs) are in the state of financial crisis due to inadequate enrollees. The purpose of this study is to construct Financial Warning Assessment Predicting Model for TVECs in conjunction with comprehensive development award subsidy deduction ratios and school financial indicators. Discussions are conducted to find out ways to respond to the constraining situation in order to prevent financial crisis from taking place. Between the period of 2006 and 2008, The Ministry of Education deducted a 40% of performance subsidy ratio from TVECs. Groupings and comparisons were conducted using cluster analysis and multidimensional scaling. The five financial and quantitative indicators for different colleges and school years from 2002 to 2006 include number of day class students, teacher/student ratio, personnel expenditure/tuition fees ratio, cash excess before deducting real estate expenditure, and financial expenditure (interest expenses )/total average ratio. Cluster analysis was then conducted to construct Financial Assessment Warning Model for TVECs. Moreover, the five financial and quantitative indicators were used to conduct combined cluster analysis. Comparisons were then made with the deducted subsidies to classify and position the results. The empirical study results show that: Based on the deductible 40% performance subsidy ratio using cluster analysis and multidimensional scaling, the 5 deductible ratios from low to high are: “no ratio or negligible ratio” deductions, “Slight ratio” deductions, “non-major ratio” deductions, “major ratio” deductions, and “major and continuous” deductions. The results show that the 3 schools falling under the weak group include Nanya Institute of Technology, Jen-Teh Junior College of Medicine, Nursing and Management, and Kaomei College of Health Care & Management. The 6 schools falling under the improving requirement group include Minghsin University of Science and Technology, Tajen University, Chungchou Institute of Technology, Lee-Ming Institute of Technology, Taipei College of Maritime Technology, and Yuh-Ing Junior College of Health Care & Management. Cluster analysis is adopted to conduct combined analysis on the five financial and quantitative indicators, as it has more superior analyzing and identification power. Among the five groups from relatively superior to relatively inferior, the results show that 7 schools fall under the improving requirement group including: Tzu Chi College of Technology, Lee-Ming Institute of technology, Chungyu Institute of technology, Tatung Institute of Commerce and Technology, Taipei College of Maritime Technology, Min-Hwei College of Health Care Management, and Yuh-Ing Junior College of Health Care & Management. Moreover, 3 schools fall under the weak group including: Chin Min Institute of Technology, Taiwan Hospitality and Tourism College, and Kaomei College of Health Care & Management When the cluster analysis of 5 school financial and quantitative indicators comprises of relatively weak group, it signifies that the 73 private TVECs have encountered difficult operations. Also, due to inadequacies in school affair management, inadequacies in financial management, unfavorable assessment results, comprehensive development award subsidies deducted by the Ministry of Education, decreased school recruitment, and reduced standards for miscellaneous fees etc., it is expected that the school quality will worsen as a result. In the future, reduced birthrates will result to potential problems such as inadequate recruitment sources, and fiercer competitions in tertiary education. The weak group are the first to bear the brunt. They ought to actively broaden sources of income and reduce expenditure in order to avoid falling into financial crisis.

並列關鍵字

Financial Warning

參考文獻


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