基于社会资本的中小企业信用评价
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摘要
中小企业在我国经济中的地位日益重要,但融资困难制约着中小企业的发展壮大。为了解决中小企业融资难的现实问题,国内理论界以及实务界在各个方面作出了积极地尝试。面对我国当前以国有大型商业银行为主导的金融体系以及中小企业直接融资渠道不畅通的现状,在目前和今后一段时间内,大型商业银行信贷将是中小企业主要的资金来源。对于商业银行而言,中小企业存在治理结构不健全,财务质量差,抵押担保不足等问题,这些问题成为制约商业银行信贷支持中小企业的瓶颈。
通过有效的信用评价挖掘具有较高信用能力的中小企业是商业银行信贷支持中小企业发展的关键环节,是搭建优质中小企业与信贷资金的桥梁。目前,关于如何提高中小企业信用评价水平在理论上和实践上还存在一些亟待解决的问题。因此,本文拟从社会资本的角度研究中小企业信用评价问题,以丰富和完善中小企业信用评价的理论与方法,为引导信贷资金流向优质中小企业提供理论指导以及方法工具。
本研究从中小企业实际特点以及信用评价理论出发,遵循着构建理论框架、影响因素分析、评价指标选择、评价模型构建的研究逻辑,对中小企业信用评价问题深入研究。研究共分为四部分:
首先,界定中小企业信用评价的概念和特点,建立基于社会资本的中小企业信用评价理论框架,明确中小企业信用评价的主要内容,提出基于社会资本的中小企业信用评价的概念及内涵,在此基础上,深入分析中小企业社会资本的主体界定,并结合中小企业外部关系网络的实际情况,提出中小企业社会资本的维度划分方法。
其次,从中小企业的财务能力、企业社会资本、企业家社会资本三个因素构建中小企业信用评价概念模型,通过对问卷的分析,证实了上述三方面因素对中小企业信用水平的正向影响,证明了概念模型的有效性。
然后,从财务能力、企业社会资本、企业家社会资本三方面选取指标构建指标体系,并运用主成分分析的方法,在保证信息含量不变的基础上,降低指标体系维度。
最后,引入支持向量机作为核心算法,运用信用数据精选参数、通过对模型的训练,得到了预测精度达到90%的中小企业信用评价预测模型。
The small and medium-sized enterprises (SMEs) of our country play more and more important role in the economy, but their development are restricted by the constrictive financing policies. To solve this difficulty in financing of SEMS, the scholars and practicers in our country have made some positive attempts. Our country’s finance system is still leading by the large-scale state commercial banks and the financing of SMEs is difficult and constrained, so the large-scale commercial banks are still the main financing source of SMEs for some time.
The imperfect corporate governance, finance condition and mortagage ability are bottleneck to SMEs to obtain financial supports from commercial banks’credits. The effective evaluation of the credit ability of SMEs is key process of commercial banks to support the development of SMEs with efficient funds. Now there are still some theoretical and practical questions about how to improve the evaluation process and ability of the credit of SMEs should be solved. So this research aims to analysis the credit evaluation of SMEs based on the social capital, enrich and develop the theory and methods of the credit evaluation of SMEs, and finally offer some theoretical guidelines and methodology to lead the credit funds to those capable SMEs.
Starting from the analysis of SME’s features and credit evaluation theories, this paper constructs the theoretical framework of credit evaluation of SMEs based on the social capital, analyzes the influencing factors, selectes the evaluation indexes and establishs the evaluation model to study the credit evaluation of SMEs in depth. This research is divided into four parts.
Firstly, this study defines the concept and feature of the credit evaluation of SMEs,constructs the theoretical frame of credit evaluation system based on social capital, reveals the main content of credit evaluation of SMEs, and propose the concept and definition of credit evaluation of SMEs based on social captial. And then defines the main body of the social capital of SMEs, and proposes the classifying method of the social capital according to the real condition of outside social network of SMEs.
Secondly, analyzes the factors influencing the SMEs’credit from financial ability, corporate social capital and entrepreneurial social captial. Empicial data is collected through the face to face interview and survey. The depicting statistical analysis of the informants shows the background information of entrepreneurs, and the reliability and validity analysises confirm the reliability of the data. The structural equation model is formed and testified based on fit indexes to test the hypotheses and to reveal the degree and direction of factors influencing the credit of SMEs.
Thirdly, constructs the credit level evaluation index system of SMEs which includes the financing ability, corporate social capital and entrepreneurial social capital three first level indexes. The principal component analysis is applied to simplify the structure and reduce the internal correlation of data to optimize the evaluation indexes.
Finally, the credit evaluation model based on social capital of SMEs is formed. Because the credit evaluation process of SMEs always face some difficulties, such as small sample size, non-linear and partial minimum, the support vector machine (SVM) is selected as the core arithmetic of the model to effectively solve these difficulities. The LIBSVM software package is usded to train this evaluation model. The RBF kernel function is chosed as the core function of SVM and the key parameter is confirmed through crossing verification technology, and the forecast precision is testified. The case study is performed to testify the effect of the credit evaluation model.
通过有效的信用评价挖掘具有较高信用能力的中小企业是商业银行信贷支持中小企业发展的关键环节,是搭建优质中小企业与信贷资金的桥梁。目前,关于如何提高中小企业信用评价水平在理论上和实践上还存在一些亟待解决的问题。因此,本文拟从社会资本的角度研究中小企业信用评价问题,以丰富和完善中小企业信用评价的理论与方法,为引导信贷资金流向优质中小企业提供理论指导以及方法工具。
本研究从中小企业实际特点以及信用评价理论出发,遵循着构建理论框架、影响因素分析、评价指标选择、评价模型构建的研究逻辑,对中小企业信用评价问题深入研究。研究共分为四部分:
首先,界定中小企业信用评价的概念和特点,建立基于社会资本的中小企业信用评价理论框架,明确中小企业信用评价的主要内容,提出基于社会资本的中小企业信用评价的概念及内涵,在此基础上,深入分析中小企业社会资本的主体界定,并结合中小企业外部关系网络的实际情况,提出中小企业社会资本的维度划分方法。
其次,从中小企业的财务能力、企业社会资本、企业家社会资本三个因素构建中小企业信用评价概念模型,通过对问卷的分析,证实了上述三方面因素对中小企业信用水平的正向影响,证明了概念模型的有效性。
然后,从财务能力、企业社会资本、企业家社会资本三方面选取指标构建指标体系,并运用主成分分析的方法,在保证信息含量不变的基础上,降低指标体系维度。
最后,引入支持向量机作为核心算法,运用信用数据精选参数、通过对模型的训练,得到了预测精度达到90%的中小企业信用评价预测模型。
The small and medium-sized enterprises (SMEs) of our country play more and more important role in the economy, but their development are restricted by the constrictive financing policies. To solve this difficulty in financing of SEMS, the scholars and practicers in our country have made some positive attempts. Our country’s finance system is still leading by the large-scale state commercial banks and the financing of SMEs is difficult and constrained, so the large-scale commercial banks are still the main financing source of SMEs for some time.
The imperfect corporate governance, finance condition and mortagage ability are bottleneck to SMEs to obtain financial supports from commercial banks’credits. The effective evaluation of the credit ability of SMEs is key process of commercial banks to support the development of SMEs with efficient funds. Now there are still some theoretical and practical questions about how to improve the evaluation process and ability of the credit of SMEs should be solved. So this research aims to analysis the credit evaluation of SMEs based on the social capital, enrich and develop the theory and methods of the credit evaluation of SMEs, and finally offer some theoretical guidelines and methodology to lead the credit funds to those capable SMEs.
Starting from the analysis of SME’s features and credit evaluation theories, this paper constructs the theoretical framework of credit evaluation of SMEs based on the social capital, analyzes the influencing factors, selectes the evaluation indexes and establishs the evaluation model to study the credit evaluation of SMEs in depth. This research is divided into four parts.
Firstly, this study defines the concept and feature of the credit evaluation of SMEs,constructs the theoretical frame of credit evaluation system based on social capital, reveals the main content of credit evaluation of SMEs, and propose the concept and definition of credit evaluation of SMEs based on social captial. And then defines the main body of the social capital of SMEs, and proposes the classifying method of the social capital according to the real condition of outside social network of SMEs.
Secondly, analyzes the factors influencing the SMEs’credit from financial ability, corporate social capital and entrepreneurial social captial. Empicial data is collected through the face to face interview and survey. The depicting statistical analysis of the informants shows the background information of entrepreneurs, and the reliability and validity analysises confirm the reliability of the data. The structural equation model is formed and testified based on fit indexes to test the hypotheses and to reveal the degree and direction of factors influencing the credit of SMEs.
Thirdly, constructs the credit level evaluation index system of SMEs which includes the financing ability, corporate social capital and entrepreneurial social capital three first level indexes. The principal component analysis is applied to simplify the structure and reduce the internal correlation of data to optimize the evaluation indexes.
Finally, the credit evaluation model based on social capital of SMEs is formed. Because the credit evaluation process of SMEs always face some difficulties, such as small sample size, non-linear and partial minimum, the support vector machine (SVM) is selected as the core arithmetic of the model to effectively solve these difficulities. The LIBSVM software package is usded to train this evaluation model. The RBF kernel function is chosed as the core function of SVM and the key parameter is confirmed through crossing verification technology, and the forecast precision is testified. The case study is performed to testify the effect of the credit evaluation model.
引文
[1] Johnson, R. W, Legal. Social and Economoic Issue Implementing Scoring in the US In: Thomas, L.C., Crook, J.N., Edelman, D. B. (Eds.), Credit Scoring and Credit Control. Oxford University Press. Oxford. 1992: 19-32.
[2] Lyn, C.T., A suvrey of Credit and Behavioral Scoring: Forecasting Finnacial Risk of Lending to Consumers. International Journal of Forecasting. 2000,16: 149-172.
[3] Beaver, W. H., Financial Ratios As Predictors of Failure, In: Empirical Research in Accounting: Selected Studies. Supplement to Journal of Accounting Reseacrh. 1966, (5): 179-199.
[4] Altman, E., I. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance. 1968, (23): 589-609.
[5] Deakin, E.B., A Discriminant Analysis of Prediction of Business Failure. Journal of Accounting Research. Spring, 1972: 167-179.
[6] Edmister, R.A., An Emprical Test of Financial Artio Analysis for Small Business Failure Perdiction. Journal of Financial and Quantitative Analysis. 1972, (7): 1477-1493.
[7] Altman, E.I., Hadelman, R.G. and Narayanan, P., Zeta Analysis, A New Model to Identify Bankruptcy Risk of Corporations. Journal of Banking and Finance 1977, (9): 29-51.
[8] Grammatikos, T., Gloubos, G., Predicting Bankruptcy of Industrial Frims in Greece. The University of Priaeus Journal of Economics, Business, Statistics and Operations Reseacrh(Soudai). 1984, (3): 421-443.
[9] Gloubos, G., Grammatikos, T., The Success of Bankruptcy Predietion Models in Greece. Studies in Banking and Finance. 1988,(7): 37-46.
[10] Theodossiou, P., Alternative Models of Assessing the Finnacial Condition of Business in Greece. Journal of Business Finance and Accounting. 1991,(5): 697-720.
[11] Vranas, A.S., Probability Models of the Forecasting of Greek Industrial Firms’Failure (in Greek). The Univessity of Piraeus Journal of Economics,Business, Statistics and Operations Reseacrh (Spoudai). 1991,(4): 431-448.
[12] Vranas, A.S., The Significance of Financial Characteristics in Predicting Business Failure:A Analysis in the Greek Context. Foundations of Computing and Decision Sciences. 1992,(4): 257-275.
[13] Martin, D., Early Warning of Bank Failure. A Logit Regression Approach. Jounral of Banking and Finance. 1977,(1): 249-276.
[14] Ohlson, J.A., Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Reseacrh. 1977,(Spring): 109-131.
[15] Keasey, K., McGuinness, P., The Failure of UK Indusrtial Firms of Period 1976-1984: Logistic Analysis and Entropy Measures. Journal of Business Finance and Accounting. 1990,(1): 119-135.
[16] Grablowsky, B.J., Talley, W.K., Probit and Disciminant Factors for Classifying Credit Applicants: A Comparison. Journal of Economics and Business. 1981, (33): 254-261.
[17] Chatterjee, S., Barcmu, S., A Nonparametric Approach to Credit Sereening. Journal of American Statistical Association. 1970,(65): 150-154.
[18] Ahmet, B.E., Muhittin, O., Amold, R. and Reha, Y., A Credit Scoring Approach for the Commercial Banking Sector. Socio-Economic Planning Sciences. 2003, (37): 103-123.
[19] Marais, M.L., Patell, J.M. and Wolfson, M.A., The Experimental Design of Classification Models: An Application of Recursive Partitioning and Bootstrapping to Commercial Bank loan Classifications. Journal of Accounting Reseacrh. 1988,(22): 87-113.
[20] Frydman, H., Altman, E.I. and Kao, D.L., Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress. The Journal of Finance. 1985: 269-291.
[21] Srinivasna, V., Kim, Y.H., Designing Expert Financial Systems: A Case Study of Corporate Credit Management. Financial Management. 1988,(Autumn): 32- 44.
[22] Freed, N., Glover, F., A Linear Programming Approach to the Discriminant Problem. Decision Sciences. 1981,(12): 68-74.
[23] Gupta, Y.P., Rao, R.P. and Bagghi, P.K., Linear Goal Programming As an Alternative to Multivariate Discriminat Analysis: A Note. Journal of
Business Finance and Accounting. 1990,(4): 593-598.
[24] Kolesar, P., Showers, J.L., A Robust Credit Screening Model Using Categorical Data. Management Sciences. 1985,(31): 123-133.
[25] Mahmood, M.A., Lawrence, E.C., A Peroformance Analysis of Parametric and Nonparametric Discriminant Approaches To Business Decision Making. Decision sciences. 1987,(18): 308-326.
[26] Srinivasan, V., Kim, Y.H. Credit Granting: A Comparative Analysis of Classification Procedures. The Journal of Finance. 1987,(3): 665-683.
[27] Zopounidis, C., Pouliezos, A. and Yannacopoulos, D., Designing a DSS for the Assessment of Company Performance and Viability. Computer Science in Economics and Management. 1992,(5): 41-56.
[28] Diakoulaki, D., Mavrotas, G. and Papayannakis, L., A multicriteria Approach for Evaluating the Performance of Industrial Fimrs. Omega. 1992,(4): 467-474.
[29] Siskos, Y., Zopounidis, C. and Pouliezos, A., A integrated DSS for Financing Firms By an Indusrtial Development Bank in Greece. Decision Support system. 1994, (12): 151-168.
[30] Cronan, T.P., Glorferd, L.W. and Perry, L.G., Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach:An Application to Mortgage, Commercial, and Consumer Lending. Decision Sciences. 1991,(22): 812-845.
[31] Ruparel, B., Srinivasan, V., A Dedicated Shell for Designing Expert Credit Support System. Decision Support System. 1992,(8): 343-359.
[32] Dutta, S., Shekhar, S., Generalization with Neural Network: An Application in the Financial Domain. Journal of Lnformation Science and Technology. 1992, (1): 309-330.
[33] Tam, K.Y., Kiang, M.Y., Managerial Appplications of Neural Networks: The Case of Bank Failure Predictions. Management Science. 1992,(7): 926-947.
[34] Rashmi, M., Malhotra, D.K., Differentiating between Good and Bad Credits Using Neuro-fuzzy Systems. European Journal of Operational Research. 2002, (136): 190-211.
[35] Ahmet, B.E., Muhittin, O., Amold, R. and Reha, Y., A Credit ScoringApproach for the Commercial Banking Sector. Socio-Economic Planning Sciences. 2003, (37): 103-123.
[36]吴晶妹.中国企业与证券的资信评估.北京:中信出版社. 1994.
[37]许剑生.企业信用等级评定指标体系的缺陷及优化.中国投资管理. 1997, (1): 64-69.
[38]夏红芳,赵丽萍.企业债券信用评级指标体系及神经网络方法.华东船舶工业学院学报. 1998,(2): 45-51.
[39]付英.企业信用评级的指标设计.中国投资管理. 1997,(1): 87-92.
[40]翟凤荣.国际证券公司信用评价的七个主要方面及借鉴.价值工程. 2000, (2): 56-61.
[41]毛定祥.基于多元统计分析和模糊综合评判的企业财务信用综合评价.上海大学学报. 2000,(3): 38-42.
[42]周春喜.企业信用等级综合评价指标体系及其评价.科技进步与对策. 2003,(4): 124-126.
[43]李小燕,卢闯等.企业信用评价模型、信用等级与业绩相关性研究.中国软科学. 2003,(5): 81-85.
[44]袁建良.地区信用风险与评级方法.系统工程. 2006,(8): 70-73.
[45]张文锋.地区信用评级方法研究.上海金融. 2007,(6): 73-76.
[46]袁吉伟.中小企业信用评级体系构建研究.财会通讯. 2008,(9). 32-33.
[47]吴金星,王宗军.基于层次分析法的企业信用评价方法研究.华中科技大学学报(自然科学版). 2004,(3): 109-111.
[48]王玉娥,叶莉等.工业企业信用评价方法研究.河北工业大学学报. 2004, (1): 89-92.
[49]夏红芳,张光明,赵丽萍.企业最佳经济规模确定的神经网络方法.全国神经网络研究学术会议论文集.成都:西南交通大学出版社. 1996: 81-92.
[50]杨保安,王春峰等.基于神经网络技术的商业银行信用风险评估.系统工程理论与实践. 1999,(9): 53-56.
[51]肖北溟,李金林.国有商业银行信贷评级研究.中国管理科学. 2004, (5)
[52]吴冲,吕静杰,潘启树,刘云焘.基于模糊神经网络的商业银行信用风险评估模型研究.系统工程理论与实践. 2004,(11): 1-8.
[53]吴德胜,梁樑.遗传算法优化神经网络及信用评价研究.中国管理科学. 2004,12(2): 69-74.
[54]吴德胜,梁梁.遗传繁衍样本策略及神经网络信用评价研究.管理科学. 2004,17(2): 5-13.
[55]姜明辉,王雅林,赵欣,黄伟平. K-近邻判别分析法在个人信用评估中的应用.数量经济技术经济研究. 2004,(2): 143-147.
[56]邹鹏,叶强,李一军.面向巴塞尔新资本协议的自优化神经网络信用评估方法.管理学报. 2005,12(4): 406-409.
[57]刘云焘,吴冲,王敏,乔木.基于支持向量机的商业银行信用风险评估模型研究.预测. 2005,24(1): 52-55.
[58]肖智,王明恺,谢林林.基于支持向量机的大学生助学贷款个人信用评价.清华大学学报(自然科学版). 2006,46(S1): 1120-1124.
[59]吕长征.防范信用风险加速内部信用评级体系建设.金融研究. 2006,(7): 187-190.
[60]王恒,沈利生.客户信用评级系统的经济计量模型检验.数量经济技术经济研究. 2006,(6): 138-147.
[61]马海英.基于混合系统的信用风险评估.清华大学学报(自然科学版). 2006, 46(S1): 1009-1102.
[62]沈利生,王恒.授信风险限额的人工神经网络模型检验.数量经济技术经济研究. 2007,(3): 108-117.
[63]肖文兵,费奇,万虎.基于支持向量机的信用评估模型及风险评价.华中科技大学学报(自然科学版). 2007,35(5): 23-26.
[64]吴冲,王萤,郭英见.基于支持向量机的个人信用评估模型研究.运筹与管理. 2008,17(8): 78-82.
[65]薛锋,柯孔林.粗糙集-神经网络系统在商业银行贷款五级分类中的应用.系统工程理论与实践. 2008,(1): 14-19.
[66]张晨宇,李金林,匡华星.多标准等级判别模型在信用评级中的应用研究.数学的实践与认识. 2008,(3): 49-53.
[67] Robert, E. Thomas. Database Marketing Practice: Protecting Consumer Privacy. Journal of Public Policy&Marketing. 1997,16(1): 147-155.
[68]程道宏.科技型中小企业信用评估模式初探.安徽科技. 2003,(9): 23-25.
[69]吴洁.信用评分技术在中小企业贷款中的应用.现代金融. 2005,(5): 46-48.
[70]何祖玉,韩玉启.中小企业信用风险评价体系及方法.统计与决策. 2003,(9): 36-38.
[71]周巧云.对中小企业信用风险评价方法的探讨—基于关系型贷款的综合评价模型.河南金融管理干部学院学报. 2004,(5): 32-34.
[72]曹继英.规避中小企业信用风险应注意的主要因素.浙江金融. 2004,(3): 42-44.
[73]关伟,薛峰.基于灰色聚类法的中小企业信用风险研究.生产力研究. 2004, (1): 31-32.
[74]田丽红,吴晓燕,常明.中小企业信用风险度量模式的选择分析.石家庄铁路职业技术学院校报. 2005,(2): 36-38.
[75]范伯乃,朱文斌.中小企业信用评价指标的理论遴选与实证分析.科研管理. 2003,(6): 83-88.
[76] Robert D. Putnam.Make Democracy Work: Civic Traditions in Modern Italy. Princeton University Press. 1993: 167.
[77] Nahapiet J., Ghoshal S., Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[78] Paul S. Adler, Seok-Woo Kwon. Social capital: Prospect for a New Concept. Academy of Management Journal. 2002,27: 10-16.
[79]边燕杰,丘海雄.企业的社会资本及其功效.中国社会科学. 2000,(2): 87-89.
[80]张方华.知识型企业的社会资本与技术创新绩效研究.杭州:浙江大学. 2004.
[81]李正彪,文峰.企业社会资本的积累机制研究.云南财贸学院学报. 2005,(4): 68-73.
[82]许萍.企业社会资本和环境适应.经济研究. 2007,(3): 51-52.
[83]徐延辉.企业家的伦理行为与企业社会资本积累——一个经济学和社会学的比较框架分析.社会学研究. 2002,(6): 73-75.
[84]周小虎.企业理论的社会资本逻辑.中国工业经济. 2005,(3): 84-91.
[85]武志伟.企业社会资本的内涵和功能研究.软科学. 2003,(5): 19-21.
[86]王勇.企业社会资本对技术创新的影响.改革. 2006,(2): 13-15.
[87]宇红.信任与企业家社会资本.社会科学辑刊. 2006,(5): 49-53.
[88]韦影.企业社会资本与技术创新——基于吸收能力的实证研究.中国工业经济. 2007,(9): 119-126.
[89]边燕杰.经济体制、社会网络与职业流动.中国社会科学. 2001,(2):77-82.
[90] McDougal, P.P., Oviatt, J.G, International Entrepreneurship: The Intersection of Two Research Paths . Academy of Management Journal. 2000,43(5): 902-908.
[91] Nahapiet J, Ghoshal S. Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[92]许萍.企业社会资本和环境适应.经济研究. 2007,(3): 51-52.
[93] Kirzner, I.M., Entrepreneurial Discovery and the Competitive Market Process: An Austrian Approach. Journal of Economic Literature. 1997,35(1): 60-86.
[94] Adaman, F., Devine, P. A Reconsideration of the Theory of Entrepreneurship: a Participatory Approach. Review of Political Economy. 2002, 14(3): 329-355.
[95] Dacin, M.T., Ventresca, M.J. and Beal, B.D., The Embeddedness of Organizations: Dialogue and Directions. Jounal of Management. 1999,(25): 317-356.
[96]石秀印.中国企业家成功的社会网络基础.管理世界. 1998,(6): 187-190.
[97] Hans Westlund, Roger Bolton. Local Social Capital and Entrepreneurship. Small Business Economics. 2003,21(9): 77-123.
[98]陈传明,周晓虎.关于企业家社会资本的若干思考闭.南京社会科学. 2001, (11): 1-3.
[99]惠朝旭.企业家社会资本:基于社会经济学基础上的解释范式.理论与改革. 2004, (3): 117-120.
[100]王革,张玉利.企业社会资本静态与动态分析.天津师范大学学报(社会科学版). 2004,(1): 16-37.
[101]杨鹏鹏.企业家社会资本及其与企业绩效的关系.当代经济科学. 2005,(4): 202-203.
[102] Nahapiet J, Ghoshal S., Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[103] Bat Batjargal, Mannie Liu. Entrepreneurs’Access to Private Equity in China: The Role of Social Capital. Organization Science. 2004, 15(2): 159-172.
[104]边燕杰,丘海雄.企业的社会资本及其功效.中国社会科学. 2000,(2): 87-89.
[105]赵延东,罗家德.如何测量社会资本:一个经验研究综述.国外社会科学. 2005, (2).
[106]边燕杰,丘海雄.企业的社会资本及其功.中国社会科学. 2000, (2).
[107]贺远琼,田志龙.企业家行为与企业社会资本.财贸研究. 2006, (1).
[108]石秀印.中国企业家成功的社会网络基础.管理世界. 1998, (6).
[109]张维迎,柯荣住.信任及其解释:来自在中国的跨省调查分析.经济研究. 2002, (10).
[110]张维迎.法律制度的信誉基础.经济研究. 2001, (1): 3-13.
[111]刘光明.论市场秩序与企业信用.中国工业经济. 2002, (3): 13-21.
[112]尹柳营.中小企业如何发展与腾飞.北京:清华大学出版社. 2003.9.
[113] Dubini, P., Aldrich, H., Personal and Extended Networks, are Central to the Entrepreneurial Process. Journal of Business Venturing. 1991,(6): 305-313.
[114] Jarillo, C., Entrepreneurship and Groth, the Strategic Use of External Sources. Journal of Business Venturing. 1989,(4): 133-147.
[115] Freel, M., External Linkages and Product Innovation in Small Manufacturing Firms. Entrepreneurship and Regional Development. 2000,(12): 245-266.
[116] Johannisson, B., Networking and Entrepreneurial Growth. In: Sexton, D., Landstrom, H. (Eds.), Handbook of Entrepreneurship. Blackwell, Oxford. 2000: 368-386.
[117] Baum, J., Calabrese, T. and Silverman, B., Don’t Go It Alone: Alliance Network Composition and Startups’Performance in Canadian Biotechnology. Strategic Management Journal. 2000, 21(3): 267-294.
[118] Batjargal, B., Liu, M., Entrepreneurs’Access to Private Equity in China: The Role of Social Capital. Organization Science. 2004, 15(2): 159-172.
[119] Westlund, H., Bolton, R., Local Social Capital and Entrepreneurship. Small Business Economics. 2003, 21(2): 122-123.
[120]黄金华,徐俊.试论企业社会资本及其优化策略.安徽理工大学学报(社会科学版). 2003, (3): 17-20.
[121]石军伟,胡立军.企业社会资本的自愿供给:一个静态博弈模型.数量经济研究. 2005, (8): 102-105.
[122]袁勇志.论企业资本经营──关于企业资本经营理论框架.社会科学家. 2001, (4): 14-20.
[123]王革.企业社会资本静态与动态分析.天津师范大学学报(社会科学版). 2004, (1): 136-138.
[124]李正彪,文峰.企业社会资本的积累机制研究.云南财贸学院学报. 2005, (4): 68 -73.
[125]李敏.论企业社会资本的有机构成及功能.中国工业经济. 2005, (8): 81-88.
[126]谢洪明.社会资本对组织创新的影响:中国珠三角地区企业的实证研究及其启示.科学学研究, 2006, (1): 150-157.
[127]祝涛.企业社会资本在完善公司治理中的作用.财会月刊. 2006, (2): 19-21.
[128]张方华.企业的社会资本与技术合作.科研管理. 2004,(2): 31-35.
[129]韦影.企业社会资本与技术创新——基于吸收能力的实证研究.中国工业经. 2007, (9): 119-126.
[130]郑美群.社会资本对高技术企业绩效的作用分析.工业技术经济. 2005, (2): 77-80.
[131]颜琼,成良斌.企业社会资本对技术创新推动的作用研究.科技管理研究. 2006, (7): 30-33.
[132]李红艳.社会资本与技术创新的扩散.科学学研究. 2004,(3): 333-336.
[133]王霄,胡军.社会资本结构与中小企业创新——一项基于结构方程模型的实证研究.管理世界. 2005,(7): 116-122.
[134] Tsai W., Ghoshal S., Social Capital and Value Creation: The role of Intra-firm Network. Academy of Management Journal. 1998,41: 464-476.
[135]郑胜利,陈国智.企业社会资本积累与企业竞争优势.生产力研究. 2002, (1): 133-137.
[136]王永.企业社会资本对人力资本的整合.山东大学学报(哲学社会科学版). 2007,(01): 57-62.
[137]王晓玉.基于企业社会资本的竞争优势探索.商业研究. 2005,(5): 45-48.
[138]张岚东.我国企业集群中的社会资本.现代经济探讨. 2003,(8): 36-40.
[139] Johanltisson, B., Business Formation A Network Approach. Scandinavian Joumal of Management. 1988: 83-99.
[140] Andreal Lipparini, Maurizio and Sobrero. The Glue and the Pieees:Entrepreneurship and Innovation in Small Firm Networks. Journal of Business Venturing. 1994,9(2): 125-140.
[141] Jan Inge Jenssen, Harold F. Koenig. The Effect of Social NetWorks on Resource Access and Business Start-up. European Plannlng Studies. 2002, 10(8): 1040- 1046.
[142] Sarah L. Jack. The Role, Use and Activation of Strong and Weak Network Ties: A Qualitative Analysis. Jounal of Management Studies. 2005,42(6): 1234-1255.
[143]边燕杰.网络脱生:创业过程的社会学分析.社会学研究. 2006,(6): 74-87.
[144] Mosakowski, Entrepreneurial Resources, Organization Choices, and Competitive Outcomes. Orgnization Science. 1998,9(6): 625-643.
[145] John L.Thompson, A Strategic Perspective of Entrepreneurship. Intenational Jounal of Entrepreneurial Behaviour&Researeh. 1999,5(6): 279-296.
[146] Gnyawali, D.R., Madhavan, R Cooperative Networks and Competitive Dynamics: A Structural Embeddedness Perspective. Academy of Management Review. 2001,26(3): 431-445.
[147] Evan H. Offstein A Strategic Human Resource Perspective of Firm Competitive Behavior. Human Resource Management Review. 2005,(5): 305-318.
[148] Pierre-andre Julien, Eric andriambeloson. Networks, Weak Signals and Technological Innovations Among SMEs in the Land-based Transportation Equipment Sector .Entrepreneurship and Regional. Development. 2004, 16(7): 51-269.
[149]张其仔.新经济社会学.北京:社会科学文献出版社. 2001.
[150]张其仔.社会资本论—社会资本与经济增长.北京:社会科学文献出版社. 1997.
[151]章华.社会网络嵌入与企业家创新.财经论丛. 2005,(4): 66-69.
[152]曾驭然.企业家社会关系对制造业企业创新和绩效的影响.暨南大学博士学位论文. 2005.
[153]赵延东,罗家德.如何测量社会资本:一个经验研究综述.国外社会科学. 2005, (2).
[154] Tsai W. Social Capital, Strategic Relatedness and the Formati on of Intraorganizati Onal Linkages. Strategic Management Journal. 2000,21: 925- 939.
[155] Vincent S Lai H L. Technology Acceptance Model for Internet Banking: An Invariance Analysis. Information & Management. 2005,42(2): 373-386.
[156] T.H. Davenport., L. Prusak. Working Knowledge: How Organizations Management What They Know. Boston. MA. Harvard Business School Press. 1998: 213-232.
[157]郭敏华.信用评级.北京:中国人民大学出版社. 2004.
[158]刘蓉,张毕西,廖朝辉.供应链合作伙伴的选择、评估和动态监控.系统工程. 2005,23(5): 24-27.
[159] Stuart F.Supplier Partnerships: Influencing Factors and Strategic Benefits. Journal of Purchasing and Materials Management. 1993,29(3): 22-28.
[160] Maloni M, Benton W. Power Influences in the Supply Chain. Journal of Business Logistics. 2000,21(1): 49-74.
[161] Johnston D, Mc Cutcheon D and Stuart F, et al. Effects of Supplier Trust on Performance of Cooperative Supplier Relationships. Journal of Operations Management. 2004, 22(1): 23-38.
[162]陈志祥.敏捷供需协调绩效评价指标体系研究.计算机集成制造系统. 2004,10(1): 99-105.
[163]彭本红,孙绍荣,纪利群.动态联盟伙伴选择的组合评价研究. 2005, 8(9):66-70.
[164]张翠华,周红,赵淼,常广庶.供应链协同绩效评价及其应用.东北大学学报(自然科学版). 2006,(6): 706-708.
[165]左小明,李从东.基于DEA模型有效性排序的供应商评价.暨南大学学报(自然科学版). 2008,29(2): 54-58.
[166] Barney J. Firm Resources And Sustained Competitive Advantage. Journal of Management. 1991,17(1): 99-120.
[167] Tian Zhilong, GaoYongqiang and WeiWu. Corporate Political Strategy and Action in China. Management World. 2003,(12): 23-31.
[168] Getz K. Selecting Corporate Political Tactics. Newbury Park: Sage. 1993: 222- 224.
[169] Rehbein K, Schuler D. The Firm As A Filter: A Conceptual Framework forCorporate Political Strategies. Academy of Management Journal. 1995,38(3): 406-410.
[170] WeiWu, Tian Zhilong and GaoHaitao. Themodel of Corporate Political Performance Assessment System. Foreign Economic and Management. 2004,(5): 33-36.
[171]尼古莱·J·福斯,克里斯第安·克努森.企业万能:面向企业能力理论.东北财经大学出版社. 1998: 79-102.
[172] Hillman A, ZardkoohiA and Bierman L. Corporate Political Strategies and Firm Performance: Indications of Firm-specific Benefits From Personal Service in the U. S. Government. Strategic Management Journal. 1999, 20(1): 67-81.
[173] Perry M, Porter R. Oligopoly and the Incentive for Horizontal Merger. American Economic Review. 1985,75(1): 219-227.
[174] Farrell J, Shapiro C. Horizontal Mergers: An Equilibrium Analysis. American Economic Review. 1990,80(1): 107-126.
[175] Douglas D. Corporate Political Activity as a Competitive Strategy: Influencing Public Policy to Increase Firm Performance. Thesis, Texas A&M University. 1995: 117-118.
[176] Klofsten, M., Jones-Evans, D. Comparing Academic Entrepreneurship in Europe: The Case of Sweden and Ireland. Small Business Economics. 2000, 14(4): 299-309.
[177] Bercovitz, J., Feldman, M. Technology Transfer and the Academic Department: Who Participates and Why. Copenhagen: DRUID Summer Conference. June, 2003: 12-14.
[178] D’Este, P., Patel, P. University-industry Linkages in the UK: What are the Factors Underlying The Variety of Interactions With Industry?. Research Policy. 2007,36(9): 1295-1313.
[179] Link, A. N., Siegel, D.S. and Bozeman, B. An Empirical Analysis of the Propensity of Academics to Engage in Informal University Technology Transfer. Industrial and Corporate Change. 2007,16(4): 641-655.
[180] Corley, E., Gaughan, M. Scientists’Participation in University Research Centers: What are the Gender Differences. Journal of Technology Transfer. 2005,30(4): 371-381.
[181] Azagra-Caro, J. M. What Type of Faculty Member Interacts With What Type of Firm? Some Reasons for the Delocalization of University-industry Interaction. Technovation. 2007,27(11): 704-715.
[182]王绍辉.对消费信贷中个人信用评价方法的探索:(学位论文).北京:首都经济贸易大学. 2004.3: 16-17.
[183]李萌. Logit模型在商业银行信用风险评估中的应用研究.管理科学. 2005, (4): 33-38.
[184]董春曦,杨绍全,饶鲜等.支持向量机推广能力估计方法比较.电路与系统学报. 2004,9(4): 86-91.
[185] Vapnik V.统计学习理论的本质.张学工译.北京:清华大学出版社. 2000: 58-60.
[186]卢增祥,李衍达.交互SVM学习算法及其在文本信息过滤中的应用.清华大学学报(自然科学版). 1999,39: 93-97.
[187]张文生,王环,戴国忠.支持向量机中引入后验概率的理论和方法研究.计算机研究与发展. 2002,39(4): 392-397.
[188]郭崇慧,孙建涛,陆玉昌.广义支持向量机优化问题的极大墒方法.系统工程理论与实践. 2005,25(6): 27-32.
[189]邓乃扬,田英杰.数据挖掘中的新方法一支持向量机.北京:科学出版社. 2004: 122-125.
[190] Scholkopf B, Smola A, Williamson R C et al. New Support Vector Algorithms. Neural Computation. 2000,(12): 1207-1245.
[191] Mangasarian O.L., Generalized Support Vector Machines. In: Smola A, Bartlett P. L., Scholkopf B et al., eds. Advances in Large Margin Classifiers. Cambridge, MA: MTT Press. 2000: 135-146.
[192] Song J, Tang H. Support Vector Machines for Classification of Homo- oligomeric Proteins By Incorporating Subsequence Distributions. Journal of Molecular Structure: Theochem. 2005,(22): 97-101.
[193] Byun H, Lee S W. Applications of Support Vector Machines for Pattern Recognition: A Survey. In: Proceedings of the First International Workshop on Pattern Recognition with Support Machines. Niagara Falls. 2002: 213-236.
[194]刘云焘等.基于支持向量机的商业银行信用风险评估模型研究.预测. 2005, 24(1): 52-55.
[195]肖文兵,费奇.基于支持向量机的个人信用评估模型及最优参数选择研究.系统工程理论与实践. 2006,26(10): 73-79.
[196] Keerthi SS, Lin CJ.Asymptotic Behaviors of Supportvector Machines With Gaussian Kernel. Neural Computation. 2003,15(7): 1667-1689.
[197] Chapelle O, Vapnik V. Choosing Multiple Parameters for Support Vector Machines. Machine Learning. 2002,46:131-159.
[198] Chih-Wei Hsu, Chih-Chung Chang and Chih-Jen. A Practical Guide for Support Vector Classification. Technique Report, National Taiwan University. 2003.
[2] Lyn, C.T., A suvrey of Credit and Behavioral Scoring: Forecasting Finnacial Risk of Lending to Consumers. International Journal of Forecasting. 2000,16: 149-172.
[3] Beaver, W. H., Financial Ratios As Predictors of Failure, In: Empirical Research in Accounting: Selected Studies. Supplement to Journal of Accounting Reseacrh. 1966, (5): 179-199.
[4] Altman, E., I. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance. 1968, (23): 589-609.
[5] Deakin, E.B., A Discriminant Analysis of Prediction of Business Failure. Journal of Accounting Research. Spring, 1972: 167-179.
[6] Edmister, R.A., An Emprical Test of Financial Artio Analysis for Small Business Failure Perdiction. Journal of Financial and Quantitative Analysis. 1972, (7): 1477-1493.
[7] Altman, E.I., Hadelman, R.G. and Narayanan, P., Zeta Analysis, A New Model to Identify Bankruptcy Risk of Corporations. Journal of Banking and Finance 1977, (9): 29-51.
[8] Grammatikos, T., Gloubos, G., Predicting Bankruptcy of Industrial Frims in Greece. The University of Priaeus Journal of Economics, Business, Statistics and Operations Reseacrh(Soudai). 1984, (3): 421-443.
[9] Gloubos, G., Grammatikos, T., The Success of Bankruptcy Predietion Models in Greece. Studies in Banking and Finance. 1988,(7): 37-46.
[10] Theodossiou, P., Alternative Models of Assessing the Finnacial Condition of Business in Greece. Journal of Business Finance and Accounting. 1991,(5): 697-720.
[11] Vranas, A.S., Probability Models of the Forecasting of Greek Industrial Firms’Failure (in Greek). The Univessity of Piraeus Journal of Economics,Business, Statistics and Operations Reseacrh (Spoudai). 1991,(4): 431-448.
[12] Vranas, A.S., The Significance of Financial Characteristics in Predicting Business Failure:A Analysis in the Greek Context. Foundations of Computing and Decision Sciences. 1992,(4): 257-275.
[13] Martin, D., Early Warning of Bank Failure. A Logit Regression Approach. Jounral of Banking and Finance. 1977,(1): 249-276.
[14] Ohlson, J.A., Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Reseacrh. 1977,(Spring): 109-131.
[15] Keasey, K., McGuinness, P., The Failure of UK Indusrtial Firms of Period 1976-1984: Logistic Analysis and Entropy Measures. Journal of Business Finance and Accounting. 1990,(1): 119-135.
[16] Grablowsky, B.J., Talley, W.K., Probit and Disciminant Factors for Classifying Credit Applicants: A Comparison. Journal of Economics and Business. 1981, (33): 254-261.
[17] Chatterjee, S., Barcmu, S., A Nonparametric Approach to Credit Sereening. Journal of American Statistical Association. 1970,(65): 150-154.
[18] Ahmet, B.E., Muhittin, O., Amold, R. and Reha, Y., A Credit Scoring Approach for the Commercial Banking Sector. Socio-Economic Planning Sciences. 2003, (37): 103-123.
[19] Marais, M.L., Patell, J.M. and Wolfson, M.A., The Experimental Design of Classification Models: An Application of Recursive Partitioning and Bootstrapping to Commercial Bank loan Classifications. Journal of Accounting Reseacrh. 1988,(22): 87-113.
[20] Frydman, H., Altman, E.I. and Kao, D.L., Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress. The Journal of Finance. 1985: 269-291.
[21] Srinivasna, V., Kim, Y.H., Designing Expert Financial Systems: A Case Study of Corporate Credit Management. Financial Management. 1988,(Autumn): 32- 44.
[22] Freed, N., Glover, F., A Linear Programming Approach to the Discriminant Problem. Decision Sciences. 1981,(12): 68-74.
[23] Gupta, Y.P., Rao, R.P. and Bagghi, P.K., Linear Goal Programming As an Alternative to Multivariate Discriminat Analysis: A Note. Journal of
Business Finance and Accounting. 1990,(4): 593-598.
[24] Kolesar, P., Showers, J.L., A Robust Credit Screening Model Using Categorical Data. Management Sciences. 1985,(31): 123-133.
[25] Mahmood, M.A., Lawrence, E.C., A Peroformance Analysis of Parametric and Nonparametric Discriminant Approaches To Business Decision Making. Decision sciences. 1987,(18): 308-326.
[26] Srinivasan, V., Kim, Y.H. Credit Granting: A Comparative Analysis of Classification Procedures. The Journal of Finance. 1987,(3): 665-683.
[27] Zopounidis, C., Pouliezos, A. and Yannacopoulos, D., Designing a DSS for the Assessment of Company Performance and Viability. Computer Science in Economics and Management. 1992,(5): 41-56.
[28] Diakoulaki, D., Mavrotas, G. and Papayannakis, L., A multicriteria Approach for Evaluating the Performance of Industrial Fimrs. Omega. 1992,(4): 467-474.
[29] Siskos, Y., Zopounidis, C. and Pouliezos, A., A integrated DSS for Financing Firms By an Indusrtial Development Bank in Greece. Decision Support system. 1994, (12): 151-168.
[30] Cronan, T.P., Glorferd, L.W. and Perry, L.G., Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach:An Application to Mortgage, Commercial, and Consumer Lending. Decision Sciences. 1991,(22): 812-845.
[31] Ruparel, B., Srinivasan, V., A Dedicated Shell for Designing Expert Credit Support System. Decision Support System. 1992,(8): 343-359.
[32] Dutta, S., Shekhar, S., Generalization with Neural Network: An Application in the Financial Domain. Journal of Lnformation Science and Technology. 1992, (1): 309-330.
[33] Tam, K.Y., Kiang, M.Y., Managerial Appplications of Neural Networks: The Case of Bank Failure Predictions. Management Science. 1992,(7): 926-947.
[34] Rashmi, M., Malhotra, D.K., Differentiating between Good and Bad Credits Using Neuro-fuzzy Systems. European Journal of Operational Research. 2002, (136): 190-211.
[35] Ahmet, B.E., Muhittin, O., Amold, R. and Reha, Y., A Credit ScoringApproach for the Commercial Banking Sector. Socio-Economic Planning Sciences. 2003, (37): 103-123.
[36]吴晶妹.中国企业与证券的资信评估.北京:中信出版社. 1994.
[37]许剑生.企业信用等级评定指标体系的缺陷及优化.中国投资管理. 1997, (1): 64-69.
[38]夏红芳,赵丽萍.企业债券信用评级指标体系及神经网络方法.华东船舶工业学院学报. 1998,(2): 45-51.
[39]付英.企业信用评级的指标设计.中国投资管理. 1997,(1): 87-92.
[40]翟凤荣.国际证券公司信用评价的七个主要方面及借鉴.价值工程. 2000, (2): 56-61.
[41]毛定祥.基于多元统计分析和模糊综合评判的企业财务信用综合评价.上海大学学报. 2000,(3): 38-42.
[42]周春喜.企业信用等级综合评价指标体系及其评价.科技进步与对策. 2003,(4): 124-126.
[43]李小燕,卢闯等.企业信用评价模型、信用等级与业绩相关性研究.中国软科学. 2003,(5): 81-85.
[44]袁建良.地区信用风险与评级方法.系统工程. 2006,(8): 70-73.
[45]张文锋.地区信用评级方法研究.上海金融. 2007,(6): 73-76.
[46]袁吉伟.中小企业信用评级体系构建研究.财会通讯. 2008,(9). 32-33.
[47]吴金星,王宗军.基于层次分析法的企业信用评价方法研究.华中科技大学学报(自然科学版). 2004,(3): 109-111.
[48]王玉娥,叶莉等.工业企业信用评价方法研究.河北工业大学学报. 2004, (1): 89-92.
[49]夏红芳,张光明,赵丽萍.企业最佳经济规模确定的神经网络方法.全国神经网络研究学术会议论文集.成都:西南交通大学出版社. 1996: 81-92.
[50]杨保安,王春峰等.基于神经网络技术的商业银行信用风险评估.系统工程理论与实践. 1999,(9): 53-56.
[51]肖北溟,李金林.国有商业银行信贷评级研究.中国管理科学. 2004, (5)
[52]吴冲,吕静杰,潘启树,刘云焘.基于模糊神经网络的商业银行信用风险评估模型研究.系统工程理论与实践. 2004,(11): 1-8.
[53]吴德胜,梁樑.遗传算法优化神经网络及信用评价研究.中国管理科学. 2004,12(2): 69-74.
[54]吴德胜,梁梁.遗传繁衍样本策略及神经网络信用评价研究.管理科学. 2004,17(2): 5-13.
[55]姜明辉,王雅林,赵欣,黄伟平. K-近邻判别分析法在个人信用评估中的应用.数量经济技术经济研究. 2004,(2): 143-147.
[56]邹鹏,叶强,李一军.面向巴塞尔新资本协议的自优化神经网络信用评估方法.管理学报. 2005,12(4): 406-409.
[57]刘云焘,吴冲,王敏,乔木.基于支持向量机的商业银行信用风险评估模型研究.预测. 2005,24(1): 52-55.
[58]肖智,王明恺,谢林林.基于支持向量机的大学生助学贷款个人信用评价.清华大学学报(自然科学版). 2006,46(S1): 1120-1124.
[59]吕长征.防范信用风险加速内部信用评级体系建设.金融研究. 2006,(7): 187-190.
[60]王恒,沈利生.客户信用评级系统的经济计量模型检验.数量经济技术经济研究. 2006,(6): 138-147.
[61]马海英.基于混合系统的信用风险评估.清华大学学报(自然科学版). 2006, 46(S1): 1009-1102.
[62]沈利生,王恒.授信风险限额的人工神经网络模型检验.数量经济技术经济研究. 2007,(3): 108-117.
[63]肖文兵,费奇,万虎.基于支持向量机的信用评估模型及风险评价.华中科技大学学报(自然科学版). 2007,35(5): 23-26.
[64]吴冲,王萤,郭英见.基于支持向量机的个人信用评估模型研究.运筹与管理. 2008,17(8): 78-82.
[65]薛锋,柯孔林.粗糙集-神经网络系统在商业银行贷款五级分类中的应用.系统工程理论与实践. 2008,(1): 14-19.
[66]张晨宇,李金林,匡华星.多标准等级判别模型在信用评级中的应用研究.数学的实践与认识. 2008,(3): 49-53.
[67] Robert, E. Thomas. Database Marketing Practice: Protecting Consumer Privacy. Journal of Public Policy&Marketing. 1997,16(1): 147-155.
[68]程道宏.科技型中小企业信用评估模式初探.安徽科技. 2003,(9): 23-25.
[69]吴洁.信用评分技术在中小企业贷款中的应用.现代金融. 2005,(5): 46-48.
[70]何祖玉,韩玉启.中小企业信用风险评价体系及方法.统计与决策. 2003,(9): 36-38.
[71]周巧云.对中小企业信用风险评价方法的探讨—基于关系型贷款的综合评价模型.河南金融管理干部学院学报. 2004,(5): 32-34.
[72]曹继英.规避中小企业信用风险应注意的主要因素.浙江金融. 2004,(3): 42-44.
[73]关伟,薛峰.基于灰色聚类法的中小企业信用风险研究.生产力研究. 2004, (1): 31-32.
[74]田丽红,吴晓燕,常明.中小企业信用风险度量模式的选择分析.石家庄铁路职业技术学院校报. 2005,(2): 36-38.
[75]范伯乃,朱文斌.中小企业信用评价指标的理论遴选与实证分析.科研管理. 2003,(6): 83-88.
[76] Robert D. Putnam.Make Democracy Work: Civic Traditions in Modern Italy. Princeton University Press. 1993: 167.
[77] Nahapiet J., Ghoshal S., Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[78] Paul S. Adler, Seok-Woo Kwon. Social capital: Prospect for a New Concept. Academy of Management Journal. 2002,27: 10-16.
[79]边燕杰,丘海雄.企业的社会资本及其功效.中国社会科学. 2000,(2): 87-89.
[80]张方华.知识型企业的社会资本与技术创新绩效研究.杭州:浙江大学. 2004.
[81]李正彪,文峰.企业社会资本的积累机制研究.云南财贸学院学报. 2005,(4): 68-73.
[82]许萍.企业社会资本和环境适应.经济研究. 2007,(3): 51-52.
[83]徐延辉.企业家的伦理行为与企业社会资本积累——一个经济学和社会学的比较框架分析.社会学研究. 2002,(6): 73-75.
[84]周小虎.企业理论的社会资本逻辑.中国工业经济. 2005,(3): 84-91.
[85]武志伟.企业社会资本的内涵和功能研究.软科学. 2003,(5): 19-21.
[86]王勇.企业社会资本对技术创新的影响.改革. 2006,(2): 13-15.
[87]宇红.信任与企业家社会资本.社会科学辑刊. 2006,(5): 49-53.
[88]韦影.企业社会资本与技术创新——基于吸收能力的实证研究.中国工业经济. 2007,(9): 119-126.
[89]边燕杰.经济体制、社会网络与职业流动.中国社会科学. 2001,(2):77-82.
[90] McDougal, P.P., Oviatt, J.G, International Entrepreneurship: The Intersection of Two Research Paths . Academy of Management Journal. 2000,43(5): 902-908.
[91] Nahapiet J, Ghoshal S. Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[92]许萍.企业社会资本和环境适应.经济研究. 2007,(3): 51-52.
[93] Kirzner, I.M., Entrepreneurial Discovery and the Competitive Market Process: An Austrian Approach. Journal of Economic Literature. 1997,35(1): 60-86.
[94] Adaman, F., Devine, P. A Reconsideration of the Theory of Entrepreneurship: a Participatory Approach. Review of Political Economy. 2002, 14(3): 329-355.
[95] Dacin, M.T., Ventresca, M.J. and Beal, B.D., The Embeddedness of Organizations: Dialogue and Directions. Jounal of Management. 1999,(25): 317-356.
[96]石秀印.中国企业家成功的社会网络基础.管理世界. 1998,(6): 187-190.
[97] Hans Westlund, Roger Bolton. Local Social Capital and Entrepreneurship. Small Business Economics. 2003,21(9): 77-123.
[98]陈传明,周晓虎.关于企业家社会资本的若干思考闭.南京社会科学. 2001, (11): 1-3.
[99]惠朝旭.企业家社会资本:基于社会经济学基础上的解释范式.理论与改革. 2004, (3): 117-120.
[100]王革,张玉利.企业社会资本静态与动态分析.天津师范大学学报(社会科学版). 2004,(1): 16-37.
[101]杨鹏鹏.企业家社会资本及其与企业绩效的关系.当代经济科学. 2005,(4): 202-203.
[102] Nahapiet J, Ghoshal S., Social Capital, Intellectual Capital, and Organizational Advantage. Academy of Management Review. 1998,23(2): 242-266.
[103] Bat Batjargal, Mannie Liu. Entrepreneurs’Access to Private Equity in China: The Role of Social Capital. Organization Science. 2004, 15(2): 159-172.
[104]边燕杰,丘海雄.企业的社会资本及其功效.中国社会科学. 2000,(2): 87-89.
[105]赵延东,罗家德.如何测量社会资本:一个经验研究综述.国外社会科学. 2005, (2).
[106]边燕杰,丘海雄.企业的社会资本及其功.中国社会科学. 2000, (2).
[107]贺远琼,田志龙.企业家行为与企业社会资本.财贸研究. 2006, (1).
[108]石秀印.中国企业家成功的社会网络基础.管理世界. 1998, (6).
[109]张维迎,柯荣住.信任及其解释:来自在中国的跨省调查分析.经济研究. 2002, (10).
[110]张维迎.法律制度的信誉基础.经济研究. 2001, (1): 3-13.
[111]刘光明.论市场秩序与企业信用.中国工业经济. 2002, (3): 13-21.
[112]尹柳营.中小企业如何发展与腾飞.北京:清华大学出版社. 2003.9.
[113] Dubini, P., Aldrich, H., Personal and Extended Networks, are Central to the Entrepreneurial Process. Journal of Business Venturing. 1991,(6): 305-313.
[114] Jarillo, C., Entrepreneurship and Groth, the Strategic Use of External Sources. Journal of Business Venturing. 1989,(4): 133-147.
[115] Freel, M., External Linkages and Product Innovation in Small Manufacturing Firms. Entrepreneurship and Regional Development. 2000,(12): 245-266.
[116] Johannisson, B., Networking and Entrepreneurial Growth. In: Sexton, D., Landstrom, H. (Eds.), Handbook of Entrepreneurship. Blackwell, Oxford. 2000: 368-386.
[117] Baum, J., Calabrese, T. and Silverman, B., Don’t Go It Alone: Alliance Network Composition and Startups’Performance in Canadian Biotechnology. Strategic Management Journal. 2000, 21(3): 267-294.
[118] Batjargal, B., Liu, M., Entrepreneurs’Access to Private Equity in China: The Role of Social Capital. Organization Science. 2004, 15(2): 159-172.
[119] Westlund, H., Bolton, R., Local Social Capital and Entrepreneurship. Small Business Economics. 2003, 21(2): 122-123.
[120]黄金华,徐俊.试论企业社会资本及其优化策略.安徽理工大学学报(社会科学版). 2003, (3): 17-20.
[121]石军伟,胡立军.企业社会资本的自愿供给:一个静态博弈模型.数量经济研究. 2005, (8): 102-105.
[122]袁勇志.论企业资本经营──关于企业资本经营理论框架.社会科学家. 2001, (4): 14-20.
[123]王革.企业社会资本静态与动态分析.天津师范大学学报(社会科学版). 2004, (1): 136-138.
[124]李正彪,文峰.企业社会资本的积累机制研究.云南财贸学院学报. 2005, (4): 68 -73.
[125]李敏.论企业社会资本的有机构成及功能.中国工业经济. 2005, (8): 81-88.
[126]谢洪明.社会资本对组织创新的影响:中国珠三角地区企业的实证研究及其启示.科学学研究, 2006, (1): 150-157.
[127]祝涛.企业社会资本在完善公司治理中的作用.财会月刊. 2006, (2): 19-21.
[128]张方华.企业的社会资本与技术合作.科研管理. 2004,(2): 31-35.
[129]韦影.企业社会资本与技术创新——基于吸收能力的实证研究.中国工业经. 2007, (9): 119-126.
[130]郑美群.社会资本对高技术企业绩效的作用分析.工业技术经济. 2005, (2): 77-80.
[131]颜琼,成良斌.企业社会资本对技术创新推动的作用研究.科技管理研究. 2006, (7): 30-33.
[132]李红艳.社会资本与技术创新的扩散.科学学研究. 2004,(3): 333-336.
[133]王霄,胡军.社会资本结构与中小企业创新——一项基于结构方程模型的实证研究.管理世界. 2005,(7): 116-122.
[134] Tsai W., Ghoshal S., Social Capital and Value Creation: The role of Intra-firm Network. Academy of Management Journal. 1998,41: 464-476.
[135]郑胜利,陈国智.企业社会资本积累与企业竞争优势.生产力研究. 2002, (1): 133-137.
[136]王永.企业社会资本对人力资本的整合.山东大学学报(哲学社会科学版). 2007,(01): 57-62.
[137]王晓玉.基于企业社会资本的竞争优势探索.商业研究. 2005,(5): 45-48.
[138]张岚东.我国企业集群中的社会资本.现代经济探讨. 2003,(8): 36-40.
[139] Johanltisson, B., Business Formation A Network Approach. Scandinavian Joumal of Management. 1988: 83-99.
[140] Andreal Lipparini, Maurizio and Sobrero. The Glue and the Pieees:Entrepreneurship and Innovation in Small Firm Networks. Journal of Business Venturing. 1994,9(2): 125-140.
[141] Jan Inge Jenssen, Harold F. Koenig. The Effect of Social NetWorks on Resource Access and Business Start-up. European Plannlng Studies. 2002, 10(8): 1040- 1046.
[142] Sarah L. Jack. The Role, Use and Activation of Strong and Weak Network Ties: A Qualitative Analysis. Jounal of Management Studies. 2005,42(6): 1234-1255.
[143]边燕杰.网络脱生:创业过程的社会学分析.社会学研究. 2006,(6): 74-87.
[144] Mosakowski, Entrepreneurial Resources, Organization Choices, and Competitive Outcomes. Orgnization Science. 1998,9(6): 625-643.
[145] John L.Thompson, A Strategic Perspective of Entrepreneurship. Intenational Jounal of Entrepreneurial Behaviour&Researeh. 1999,5(6): 279-296.
[146] Gnyawali, D.R., Madhavan, R Cooperative Networks and Competitive Dynamics: A Structural Embeddedness Perspective. Academy of Management Review. 2001,26(3): 431-445.
[147] Evan H. Offstein A Strategic Human Resource Perspective of Firm Competitive Behavior. Human Resource Management Review. 2005,(5): 305-318.
[148] Pierre-andre Julien, Eric andriambeloson. Networks, Weak Signals and Technological Innovations Among SMEs in the Land-based Transportation Equipment Sector .Entrepreneurship and Regional. Development. 2004, 16(7): 51-269.
[149]张其仔.新经济社会学.北京:社会科学文献出版社. 2001.
[150]张其仔.社会资本论—社会资本与经济增长.北京:社会科学文献出版社. 1997.
[151]章华.社会网络嵌入与企业家创新.财经论丛. 2005,(4): 66-69.
[152]曾驭然.企业家社会关系对制造业企业创新和绩效的影响.暨南大学博士学位论文. 2005.
[153]赵延东,罗家德.如何测量社会资本:一个经验研究综述.国外社会科学. 2005, (2).
[154] Tsai W. Social Capital, Strategic Relatedness and the Formati on of Intraorganizati Onal Linkages. Strategic Management Journal. 2000,21: 925- 939.
[155] Vincent S Lai H L. Technology Acceptance Model for Internet Banking: An Invariance Analysis. Information & Management. 2005,42(2): 373-386.
[156] T.H. Davenport., L. Prusak. Working Knowledge: How Organizations Management What They Know. Boston. MA. Harvard Business School Press. 1998: 213-232.
[157]郭敏华.信用评级.北京:中国人民大学出版社. 2004.
[158]刘蓉,张毕西,廖朝辉.供应链合作伙伴的选择、评估和动态监控.系统工程. 2005,23(5): 24-27.
[159] Stuart F.Supplier Partnerships: Influencing Factors and Strategic Benefits. Journal of Purchasing and Materials Management. 1993,29(3): 22-28.
[160] Maloni M, Benton W. Power Influences in the Supply Chain. Journal of Business Logistics. 2000,21(1): 49-74.
[161] Johnston D, Mc Cutcheon D and Stuart F, et al. Effects of Supplier Trust on Performance of Cooperative Supplier Relationships. Journal of Operations Management. 2004, 22(1): 23-38.
[162]陈志祥.敏捷供需协调绩效评价指标体系研究.计算机集成制造系统. 2004,10(1): 99-105.
[163]彭本红,孙绍荣,纪利群.动态联盟伙伴选择的组合评价研究. 2005, 8(9):66-70.
[164]张翠华,周红,赵淼,常广庶.供应链协同绩效评价及其应用.东北大学学报(自然科学版). 2006,(6): 706-708.
[165]左小明,李从东.基于DEA模型有效性排序的供应商评价.暨南大学学报(自然科学版). 2008,29(2): 54-58.
[166] Barney J. Firm Resources And Sustained Competitive Advantage. Journal of Management. 1991,17(1): 99-120.
[167] Tian Zhilong, GaoYongqiang and WeiWu. Corporate Political Strategy and Action in China. Management World. 2003,(12): 23-31.
[168] Getz K. Selecting Corporate Political Tactics. Newbury Park: Sage. 1993: 222- 224.
[169] Rehbein K, Schuler D. The Firm As A Filter: A Conceptual Framework forCorporate Political Strategies. Academy of Management Journal. 1995,38(3): 406-410.
[170] WeiWu, Tian Zhilong and GaoHaitao. Themodel of Corporate Political Performance Assessment System. Foreign Economic and Management. 2004,(5): 33-36.
[171]尼古莱·J·福斯,克里斯第安·克努森.企业万能:面向企业能力理论.东北财经大学出版社. 1998: 79-102.
[172] Hillman A, ZardkoohiA and Bierman L. Corporate Political Strategies and Firm Performance: Indications of Firm-specific Benefits From Personal Service in the U. S. Government. Strategic Management Journal. 1999, 20(1): 67-81.
[173] Perry M, Porter R. Oligopoly and the Incentive for Horizontal Merger. American Economic Review. 1985,75(1): 219-227.
[174] Farrell J, Shapiro C. Horizontal Mergers: An Equilibrium Analysis. American Economic Review. 1990,80(1): 107-126.
[175] Douglas D. Corporate Political Activity as a Competitive Strategy: Influencing Public Policy to Increase Firm Performance. Thesis, Texas A&M University. 1995: 117-118.
[176] Klofsten, M., Jones-Evans, D. Comparing Academic Entrepreneurship in Europe: The Case of Sweden and Ireland. Small Business Economics. 2000, 14(4): 299-309.
[177] Bercovitz, J., Feldman, M. Technology Transfer and the Academic Department: Who Participates and Why. Copenhagen: DRUID Summer Conference. June, 2003: 12-14.
[178] D’Este, P., Patel, P. University-industry Linkages in the UK: What are the Factors Underlying The Variety of Interactions With Industry?. Research Policy. 2007,36(9): 1295-1313.
[179] Link, A. N., Siegel, D.S. and Bozeman, B. An Empirical Analysis of the Propensity of Academics to Engage in Informal University Technology Transfer. Industrial and Corporate Change. 2007,16(4): 641-655.
[180] Corley, E., Gaughan, M. Scientists’Participation in University Research Centers: What are the Gender Differences. Journal of Technology Transfer. 2005,30(4): 371-381.
[181] Azagra-Caro, J. M. What Type of Faculty Member Interacts With What Type of Firm? Some Reasons for the Delocalization of University-industry Interaction. Technovation. 2007,27(11): 704-715.
[182]王绍辉.对消费信贷中个人信用评价方法的探索:(学位论文).北京:首都经济贸易大学. 2004.3: 16-17.
[183]李萌. Logit模型在商业银行信用风险评估中的应用研究.管理科学. 2005, (4): 33-38.
[184]董春曦,杨绍全,饶鲜等.支持向量机推广能力估计方法比较.电路与系统学报. 2004,9(4): 86-91.
[185] Vapnik V.统计学习理论的本质.张学工译.北京:清华大学出版社. 2000: 58-60.
[186]卢增祥,李衍达.交互SVM学习算法及其在文本信息过滤中的应用.清华大学学报(自然科学版). 1999,39: 93-97.
[187]张文生,王环,戴国忠.支持向量机中引入后验概率的理论和方法研究.计算机研究与发展. 2002,39(4): 392-397.
[188]郭崇慧,孙建涛,陆玉昌.广义支持向量机优化问题的极大墒方法.系统工程理论与实践. 2005,25(6): 27-32.
[189]邓乃扬,田英杰.数据挖掘中的新方法一支持向量机.北京:科学出版社. 2004: 122-125.
[190] Scholkopf B, Smola A, Williamson R C et al. New Support Vector Algorithms. Neural Computation. 2000,(12): 1207-1245.
[191] Mangasarian O.L., Generalized Support Vector Machines. In: Smola A, Bartlett P. L., Scholkopf B et al., eds. Advances in Large Margin Classifiers. Cambridge, MA: MTT Press. 2000: 135-146.
[192] Song J, Tang H. Support Vector Machines for Classification of Homo- oligomeric Proteins By Incorporating Subsequence Distributions. Journal of Molecular Structure: Theochem. 2005,(22): 97-101.
[193] Byun H, Lee S W. Applications of Support Vector Machines for Pattern Recognition: A Survey. In: Proceedings of the First International Workshop on Pattern Recognition with Support Machines. Niagara Falls. 2002: 213-236.
[194]刘云焘等.基于支持向量机的商业银行信用风险评估模型研究.预测. 2005, 24(1): 52-55.
[195]肖文兵,费奇.基于支持向量机的个人信用评估模型及最优参数选择研究.系统工程理论与实践. 2006,26(10): 73-79.
[196] Keerthi SS, Lin CJ.Asymptotic Behaviors of Supportvector Machines With Gaussian Kernel. Neural Computation. 2003,15(7): 1667-1689.
[197] Chapelle O, Vapnik V. Choosing Multiple Parameters for Support Vector Machines. Machine Learning. 2002,46:131-159.
[198] Chih-Wei Hsu, Chih-Chung Chang and Chih-Jen. A Practical Guide for Support Vector Classification. Technique Report, National Taiwan University. 2003.