建構我國私立技專校院繼續經營預測模式之研究

Abstract

我國少子化危機帶給各級學校招生困窘問題，從小學階段逐漸蔓延至大學，於105年8月第一波浪潮正式衝擊高等教育，此波浪潮又以私立技專院校所受衝擊最為嚴重，未來十年私立技專院校因少子化危機，多數將面臨招生人數遞減之壓力，其所產生之經營困境問題、組織衰退現象，將如何設計其評估指標與預測模式，以有效的予以評估、衡量，使其能及早因應現在及未來的內外在環境變化，預為研擬對策以作因應處理，將是教育主管機關及學校管理當局相當重要的課題。 本研究以私立技專院校為對象，對學校繼續經營能力、財務困境、信用評等、私立學校財務制度、財務分析技術、組織衰退及學生選校行為等相關文獻進行文件分析，據以建構繼續經營能力評估指標，並以此蒐集100學年至102學年相關財務與非財務之量化資訊，並以羅吉斯回歸分析與區別分析建構繼續經營預測模式。 本研究依研究目的，文件分析、統計分析結果，經過整理及分析後，歸納提出下列研究結論：1.本研究建構之私立技專院校繼續經營能力評估指標，包括10個一級指標，150項二級指標，有57項二級指標在正常組與衰退組之間，達到0.1%顯著差異水準，可供教育主管機關及私立學校管理當局進行學校財務分析之用。2.羅吉斯迴歸分析各預測模式選入之指標，最具顯著性著多為本研究創新指標，本研究發展之指標具有預測價值。3.區別分析對各典型區別函數貢獻最大之8個指標，有半數為現金流量指標，應更重視現金流量指標對預測學校繼續經營能力之影響。4.區別分析預測模式分類正確率優於羅吉斯回歸分析預測模式，可優先考量使用區別分析預測模式。5.二種方法之各類指標預測模式對衰退學校分類正確率各有強項，依據指標類別分別採用不同之預測模式，將可提升衰退學校整體分類正確率。6.繼續經營預測模式所選用之指標，有48項創新指標4項傳統指標，創新指標經驗證有應用價值。 依據本研究在文件分析內容與實證分析結果，對教育主管機關提出7項建議，對學校提出5項建議，對後續研究亦提出5項建議。

The low birth rate in Taiwan impacts enrollment at all levels of schooling, gradually spreading from primary school to university. The first wave of the low birth rate phenomenon will affect higher education, especially private junior colleges, colleges of technology, and universities of science& Technology (PJCU), in August of 2016. Within the next decade, PJCU, due to the declining birthrate crisis, will face the pressure of decreasing enrollment. Most schools will encounter problems of financial distress and organization decline. How to construct a set of indicators and predictive models to assess financial difficulties and organizational decline are very important for PJCU. The study employed documentary analysis methodology to construct on-going concern indicators. The indicatorsinclude on-going concern, financial distress, credit rating theory, the financial system and financial analysis of private schools, organizational decline theory, and criteria students use to choose a school. The study collected financial and non-financial quantitative data from PJCU between 2011 and 2013. The logistic regression analysis and discriminant analysis were employed to construct predictive models. Based on the purpose of this study, and the findings of the study, the conclusions are as follows: 1. This study constructs on-going concern indicators for PJCU, including 10 indicators of first level and 150 indicators of secondary level, to assess the ability of sustainable operation. There are 57 secondary indicators with a significant level of 0.1% between the normal group and the declining group. Such findings could apply to financial analysis for educational authorities and private schools. 2. In the logistic regression analysis model, the most significant indicators are innovative. Therefore, the indicators of this study are of prediction value. 3. The discriminant analysis shows that there are 8 indicators contributing to canonical discriminant function. Among those indicators, 4 of them are relevant to cash-flow aspects. In other words, cash-flow indicators are of more importance to predict the sustainable operation of schools. 4. The correct classification rate of discriminant analysis is higher than that of logistic regression analysis, which means discriminant analysis is a preferable prediction model. 5. The prediction models of logistic regression analysis and discriminant analysis have their own advantages for predicting declining schools. The entire correct classification rate can be enhanced if some indicators employ discriminant analysis prediction models and some indicators employ logistic regression prediction models. 6. There are 48 creative indicators and 4 traditional indicators used within the on-going concern prediction models. The creative indicators are useful for practical application. According to the study, from the documentary analysis and empirical analysis, there are 7 recommendations to educational authorities, 5 proposals for schools, and 5 proposals for follow-up studies.