【摘要】：在國內(nèi)經(jīng)濟(jì)高速發(fā)展和改革政策不斷深入的條件下,生產(chǎn)高標(biāo)準(zhǔn)、高科技產(chǎn)品的企業(yè)越來越受市場(chǎng)的歡迎,因此具備這些特征的小微型科技創(chuàng)業(yè)企業(yè)近年來獲得蓬勃發(fā)展,在數(shù)量和規(guī)模上都得到快速壯大,有效的促進(jìn)了十二五、十三五期間國民經(jīng)濟(jì)的高質(zhì)量、高速度的發(fā)展。信息技術(shù)的日新月異,使商業(yè)銀行、風(fēng)險(xiǎn)投資公司、其他金融機(jī)構(gòu)與小微型科技創(chuàng)業(yè)企業(yè)之間的信貸方式更加簡便,信貸聯(lián)系更加持久。由于小微型科技創(chuàng)業(yè)企業(yè)相對(duì)于大中型企業(yè)在企業(yè)組織結(jié)構(gòu)、職工能力和素質(zhì)、企業(yè)管理和財(cái)務(wù)水平、抵抗內(nèi)部和外部風(fēng)險(xiǎn)等方面有較大的差異,而現(xiàn)有信用評(píng)價(jià)體系和模型主要面對(duì)大中型企業(yè),不能夠體現(xiàn)小微型科技創(chuàng)業(yè)企業(yè)的和特點(diǎn),因此,對(duì)其并不適用。本文針對(duì)河南省小微型科技創(chuàng)業(yè)企業(yè)的特點(diǎn)和信用現(xiàn)狀,探索和研究適合其信用評(píng)價(jià)的方法和模型,為信用信息需求者提供科學(xué)、準(zhǔn)確的信用評(píng)價(jià)依據(jù)。經(jīng)過仔細(xì)研究和學(xué)習(xí)國內(nèi)外企業(yè)信用評(píng)價(jià)學(xué)術(shù)領(lǐng)域的新舊理論和研究成果,在借鑒現(xiàn)今學(xué)術(shù)領(lǐng)域較為認(rèn)可的信用評(píng)價(jià)方法和模型的基礎(chǔ)上,根據(jù)河南省小微型科技創(chuàng)業(yè)企業(yè)的特征和信用現(xiàn)狀,提出了適合對(duì)其進(jìn)行信用評(píng)價(jià)的科學(xué)方法和模型。本文主要從企業(yè)成長、營運(yùn)、盈利、償債、創(chuàng)新、素質(zhì)、競爭力、信用狀況8個(gè)方面,共計(jì)34個(gè)指標(biāo)來建立信用評(píng)價(jià)指標(biāo)體系,并對(duì)經(jīng)篩選和降維后最終保留的指標(biāo)變量給出了詳細(xì)的解釋。本文主要運(yùn)用因子分析來篩選不相關(guān)的指標(biāo)變量,從而提升指標(biāo)體系和模型的合理性、可操作性,在刪去相關(guān)的9個(gè)變量后,最終保留了25個(gè)指標(biāo)變量。在此基礎(chǔ)上對(duì)本文選擇的100家河南省小微型科技創(chuàng)業(yè)企業(yè)的信用狀況分別使用BP神經(jīng)網(wǎng)絡(luò)和Logistic回歸進(jìn)行實(shí)證分析,根據(jù)模型得出的實(shí)證結(jié)果歸納出本文的實(shí)證結(jié)論和對(duì)應(yīng)的政策建議。
[Abstract]:Under the condition of the rapid development of domestic economy and the deepening of the reform policy, the enterprises that produce high standards and high-tech products are more and more popular in the market. Therefore, the small and micro science and technology entrepreneurial enterprises with these characteristics have been booming in recent years, and have been rapidly expanded in quantity and scale, which has effectively promoted the high quality and high speed development of the national economy during the 12th and 13th five-year Plan period. With the rapid development of information technology, the credit mode between commercial banks, venture capital companies, other financial institutions and small and micro technology startups is easier and more lasting. Compared with large and medium-sized enterprises, small and micro-science and technology entrepreneurial enterprises have great differences in organizational structure, staff ability and quality, enterprise management and financial level, resistance to internal and external risks, and the existing credit evaluation system and model are mainly faced with large and medium-sized enterprises, which can not reflect the sum characteristics of small and micro-science and technology entrepreneurial enterprises, so they are not suitable for them. According to the characteristics and credit status of small and micro science and technology start-up enterprises in Henan Province, this paper explores and studies the methods and models suitable for their credit evaluation, so as to provide scientific and accurate credit evaluation basis for credit information demanders. After careful study and study of the new and old theories and research results in the academic field of enterprise credit evaluation at home and abroad, on the basis of drawing lessons from the credit evaluation methods and models recognized in the current academic field, according to the characteristics and credit status of small and micro science and technology start-up enterprises in Henan Province, this paper puts forward the scientific methods and models suitable for credit evaluation. This paper mainly establishes the credit evaluation index system from 8 aspects of enterprise growth, operation, profit, debt service, innovation, quality, competitiveness and credit status, and gives a detailed explanation of the index variables retained after screening and dimension reduction. In this paper, factor analysis is mainly used to screen unrelated index variables, so as to improve the rationality and maneuverability of the index system and model. After deleting the relevant 9 variables, 25 index variables are retained. On this basis, the credit status of the 100 small and micro science and technology startups in Henan Province selected in this paper is empirically analyzed by BP neural network and Logistic regression, and the empirical conclusions and corresponding policy suggestions are summarized according to the empirical results of the model.
【學(xué)位授予單位】：中原工學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F276.3

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