本研究採取敘述性個案研究，藉個案公司提供詳實資料為基礎，建立銀行授信於太陽能電池產業之評估模式與層級架構。運用文獻分析及專家意見，彙整銀行授信於太陽能電池產業評估準則，再運用模糊多準則分析延請專家在所建立的評估準則和層級中進行評估，促使決策過程中概念的模糊性充分地表達，以決定最佳授信評估模式。獲致影響銀行授信要素有： 一、銀行授信新創產業之評估模式涵蓋三項準則細分18項要素組成，為一系統化評估機制。評估準則之重要性依序為管理、財務、經濟。相較當前銀行授信普遍採用的3F5C，認為財務狀況影響性較大，但由於新興產業之設備、技術、產品以及服務尚未有定型，存有忽略公司前瞻性與未來發展性。因此，較重視管理面的評估。 二、銀行授信新創產業評估模式之18項要素，其重要性的前五項依序為銀行往來、財務情形、負責人概況、信用風評、公司概況。 三、本研究所建構之評估模式，對缺乏具體佐證量化資料之新興產業放款風險評估，具有提供相當程度的實證數據，弭補受限財務報表上的數字反映企業營運的績效，提升放款風險評估效度與客觀性。 四、依本研究之敘述性個案研究結果，發現建構的評估模式納入考量新興產業之負責人概況與銀行往來狀況等面向，具有縮短授信案件評估時程，提高授信效率及品質的效益。
This study descriptive case studies, by providing detailed case information based on the establishment of bank credit on the solar cell industry level evaluation model and framework. The process of research literature analysis and expert opinion, compile bank credit in the solar cell industry evaluation criteria, then the use of fuzzy multiple criteria decision making often invited experts in the established assessment criteria and level of assessment to promote decision-making process in the ambiguity of the concept full expression, to determine the best credit evaluation model. Finally, to achieve the elements of bank credit are: First, bank credit evaluation model of emerging industries covered by the three criteria for the 18 sub-elements, for systematic assessment mechanism. order of importance of evaluation criteria for management, finance, economic. Compared widely adopted in the current banking credit 3F5C, that the financial situation is greater, but because the new industry equipment, technologies, products and services not yet finalized, if assessment of financial indicators. There ignored the forward-looking and future development of the company. Therefore, more attention to the management side of the assessment. Second, bank credit evaluation model for a new industry record of 18 elements, the first five order of their importance between the banking, financial situation, the responsible person profile, credit risk assessment, the company profile. Third, this research to assess the model, the lack of specific quantitative data supporting the emerging industry loans risk assessment, has provided substantial and sufficient to participate in the empirical data collected, make up for limited banking contact person in charge profile and credit rating assessment of wind inadequate information to improve risk assessment of lending validity and objectivity. Fourth, this research of descriptive case study findings, the evaluation model constructed in this study included examination amount of new industry leader profile and status for bank transactions, credit cases with reduced assessment process, improve efficiency and quality of credit effectiveness.