施工企业信用评价研究
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摘要
施工企业信用是整个社会信用体系的有机组成部分,也是影响施工企业自身核心竞争力的关键因素。由于目前我国建筑市场的信用制度尚未完善,部分施工企业存在比较严重的信用缺失问题,这不仅扭曲了市场双方的信用关系,也阻碍了整个建筑市场的健康发展,建设完备的施工企业信用评价体系已是当务之急。基于此本文针对施工企业信用评价的指标和方法进行研究,并构建科学合理的施工企业信用评价模型,以对建设单位择优选择承包商、防范信用风险提供一定的参考。
施工企业信用评价主要包括两方面的核心内容,即指标体系的构建和评价方法的选择。本文首先阐述了信用评价指标体系的构建原则,包括全面性、层次性、适用性、定性与定量相结合等；然后根据一般企业信用评价理论,结合施工企业的具体特点,提出从企业的履约能力和履约意愿两方面进行考察以确定其信用水平,并据此对评价要素进行筛选,进而建立施工企业信用评价指标体系。
通过对各种企业信用评价方法的分析和比较,本文选用模糊评判理论和灰色关联分析建立了施工企业信用评价模型,即在运用灰色关联分析确定指标权重的基础上对施工企业信用进行模糊综合评判。灰色关联分析对样本的数量和分布规律没有过多要求,其定量分析结果与定性分析结果比较一致,适合于确定多个影响因素的主次关系；模糊综合评判法具有结果清晰、系统性强的特点,该方法能够在定性分析的基础上对受评对象进行数学化、定量化的多层次综合评判,很好地适应了施工企业信用评价指标体系的特点。本文将两种方法结合起来用于施工企业信用评价,能够更加科学、客观的确定其信用等级。
本文最后选取某施工企业对该模型的进行了实例检验。从评价结果可以看出,该模型能够对施工企业信用进行有效的分级,同时为建设单位择优选择承包商提供一定的参考,具有较好的可操作性和有效性。
The credit of construction enterprises is an important part of social credit system, which is also a key factor effecting construction enterprise's core competitiveness. Due to the incomplete credit system in current construction market of China, some construction companies have severe problem of lacking credit, which not only distorts the relation between both sides, but also hinders the healthy development of construction market. It is urgent to build an optimized credit rating system for construction enterprises. In this paper, the indicators and methods of credit evaluation were studied, then a scientific and rational credit evaluation model for construction enterprises was established, which could provide some reference for the owner to choose building contractor and prevent credit risk.
The credit evaluation of construction enterprises includes two aspects of core content, which are the establishment of index system and the selection of evaluation method. Firstly the principles of building credit evaluation index system were explained, including the comprehensiveness, hierarchy, applicability, as well as combining qualitative and quantitative indexes. Based on the credit rating theory for general business and combined with the specific characteristics of construction enterprise, it was proposed that the credit level should be analyzed from aspects of contract performing capacity and willingness. Meanwhile, the evaluation elements were selected to establish the credit evaluation index system for construction enterprises.
Through the analysis and comparison of corporate credit rating methods, the fuzzy evaluation theory and grey relational analysis were applied to establish the credit evaluation model for construction enterprises. Firstly the weight of each index was determined with gray relational analysis, based on that the construction company's credit was apprised using fuzzy evaluation method. Grey relational analysis has no excessive requirements in sample's amount and distribution pattern, and its qualitative analysis results are consistent with that of quantitative analysis. This method is suitable to determine the primary or secondary degree of each factor. The fuzzy evaluation method has strong systematicness and can obtain clear results, which evaluates the object comprehensively and quantitatively based on qualitative analysis. This method is well adapted to the characteristics of credit evaluation index system for construction enterprises. In this paper, these two methods were used together for construction business credit evaluation, which could determine its credit rating more scientifically and objectively.
Finally, a construction company was selected to verify the established model. It was indicated that this model had good maneuverability and effectiveness, which could objectively determine the credit rating of construction enterprise, and provide certain information for the owner to choose better contractor.
施工企业信用评价主要包括两方面的核心内容,即指标体系的构建和评价方法的选择。本文首先阐述了信用评价指标体系的构建原则,包括全面性、层次性、适用性、定性与定量相结合等；然后根据一般企业信用评价理论,结合施工企业的具体特点,提出从企业的履约能力和履约意愿两方面进行考察以确定其信用水平,并据此对评价要素进行筛选,进而建立施工企业信用评价指标体系。
通过对各种企业信用评价方法的分析和比较,本文选用模糊评判理论和灰色关联分析建立了施工企业信用评价模型,即在运用灰色关联分析确定指标权重的基础上对施工企业信用进行模糊综合评判。灰色关联分析对样本的数量和分布规律没有过多要求,其定量分析结果与定性分析结果比较一致,适合于确定多个影响因素的主次关系；模糊综合评判法具有结果清晰、系统性强的特点,该方法能够在定性分析的基础上对受评对象进行数学化、定量化的多层次综合评判,很好地适应了施工企业信用评价指标体系的特点。本文将两种方法结合起来用于施工企业信用评价,能够更加科学、客观的确定其信用等级。
本文最后选取某施工企业对该模型的进行了实例检验。从评价结果可以看出,该模型能够对施工企业信用进行有效的分级,同时为建设单位择优选择承包商提供一定的参考,具有较好的可操作性和有效性。
The credit of construction enterprises is an important part of social credit system, which is also a key factor effecting construction enterprise's core competitiveness. Due to the incomplete credit system in current construction market of China, some construction companies have severe problem of lacking credit, which not only distorts the relation between both sides, but also hinders the healthy development of construction market. It is urgent to build an optimized credit rating system for construction enterprises. In this paper, the indicators and methods of credit evaluation were studied, then a scientific and rational credit evaluation model for construction enterprises was established, which could provide some reference for the owner to choose building contractor and prevent credit risk.
The credit evaluation of construction enterprises includes two aspects of core content, which are the establishment of index system and the selection of evaluation method. Firstly the principles of building credit evaluation index system were explained, including the comprehensiveness, hierarchy, applicability, as well as combining qualitative and quantitative indexes. Based on the credit rating theory for general business and combined with the specific characteristics of construction enterprise, it was proposed that the credit level should be analyzed from aspects of contract performing capacity and willingness. Meanwhile, the evaluation elements were selected to establish the credit evaluation index system for construction enterprises.
Through the analysis and comparison of corporate credit rating methods, the fuzzy evaluation theory and grey relational analysis were applied to establish the credit evaluation model for construction enterprises. Firstly the weight of each index was determined with gray relational analysis, based on that the construction company's credit was apprised using fuzzy evaluation method. Grey relational analysis has no excessive requirements in sample's amount and distribution pattern, and its qualitative analysis results are consistent with that of quantitative analysis. This method is suitable to determine the primary or secondary degree of each factor. The fuzzy evaluation method has strong systematicness and can obtain clear results, which evaluates the object comprehensively and quantitatively based on qualitative analysis. This method is well adapted to the characteristics of credit evaluation index system for construction enterprises. In this paper, these two methods were used together for construction business credit evaluation, which could determine its credit rating more scientifically and objectively.
Finally, a construction company was selected to verify the established model. It was indicated that this model had good maneuverability and effectiveness, which could objectively determine the credit rating of construction enterprise, and provide certain information for the owner to choose better contractor.
引文
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[29]董振玉.基于BP神经网络的施工企业信用评价[J].水利与建筑工程学报,2008(4)：115-117.
[30]段蝉.建筑业企业信用评价研究[D].武汉理工大学,2008.
[31]沈杰.西方发达国家个人诚信制度及其运行机制[J].社会科学管理与评论,2006(2)：54-67.
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[36]Li Wenyi. Financial performance evaluation of China's listed steel companies from creditors'perspective[C]. Proceedings of the 2nd International Conference on Interaction Sciences:Information Technology, Culture and Human,2009:337-341.
[37]D J Hand, W E Henley. Statistical Classification Methods in Consumer Credit Scoring:A Review [J]. Journal of the Royal Statistical Society:Series A (Statistics in Society),1997, 160(3):523-541.
[38]Lyn C Thomas. A survey of credit and behavioural scoring:forecasting financial risk of lending to consumers [J]. International Journal of Forecasting,2000,16(2):149-172.
[39]Edward I Altman. A Further Empirical Investigation of the Bankruptcy Cost Question [J]. The Journal of Finance,1984,39(4):1067-1089
[40]Vijay S Desai, Jonathan N Crook, George A Overstreet Jr. A comparison of neural networks and linear scoring models in the credit union environment [J]. European Journal of Operational Research,1996,95(1):24-37.
[41]宋程鹏,王孟钧,常燕.施工企业信用评价体系构建[J].铁路工程造价管理,2007,22(2)：44-47.
[42]张玲,张佳林.信用风险评估方法发展趋势[J].预测,2000,19(4)：72-75.
[43]王靖,张金锁.综合评价中确定权重微量的几种方法比较[J].河北工业大学学报,2001,30(2)：52-57.
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[2]盛春奎,王旭峰,徐伟.中国推行工程担保制度的探讨[J].建筑技术,2004,35(8)：620-622.
[3]Edward I Altman. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy [J]. The Journal of Finance,1968,23(4):589-609.
[4]Edward I Altman, Robert G Haldeman, P Narayanan. ZETA analysis:A new model to identify bankruptcy risk of corporations [J]. Journal of Banking & Finance,1977,1(1): 29-54.
[5]Samprit Chatterjee, Seymour Barcun. A Nonparametric Approach to Credit Screening [J]. Journal of the American Statistical Association,1970,65:150-154.
[6]Patricia M Rudolph, Marvin Karson. The effect of unequal priors and unequal misclassification costs on MDA [J]. Journal of Applied Statistics,1988,15(1):69-83.
[7]Pieter H Streefland, Hasina Ahmed, Marium Nafisa, et al. Credit and conscientization: Effects of different development approaches in Bangladesh [J]. Public Administration and Development,2006,13(2):153-169.
[8]Fredrik Andersson, Helmut Mausser, Dan Rosen, et al. Credit risk optimization with Conditional Value-at-Risk criterion [J]. Mathematical Programming,2001,89(2):273-291.
[9]David West. Neural network credit scoring models [J]. Computers & Operations Research, 2000,27(11-12):1131-1152.
[10]Jin-Chuan Duan, Andras Fulop. Estimating the structural credit risk model when equity prices are contaminated by trading noises [J]. Journal of Econometrics,2009,150(2): 288-296.
[11]徐宪平.关于美国信用体系的研究与思考[J].管理世界,2006(5)：1-9.
[12]Lendol Callder.美国金融梦——有关消费者信用的历史[M].上海：上海人民出版社,2007.
[13]庞建敏.国内外企业资信评级的分析与思考[J].山东社会科学,2006(2)：149-151.
[14]王培龙,孙佳.对资信评估体系的中外比较分析[J].哈尔滨商业大学学报(社会科学版),2003(2)：104-107.
[15]张玲,曾维火.基于Z值模型的我国上市公司信用评级研究[J].财经研究,2004(6)：5-13.
[16]严太华,程映山,李传昭.商业银行信用风险量化和管理模型的应用分析[J].重庆大学学报(自然科学版),2004(7)：109-113.
[17]王小明.商业银行信用风险评级测度方法研究[J].财经研究，2005,31(5)：73-82.
[18]邹蕾,叶华平.基于二元Logistic模型的国内上市企业信用评级展望的影响因素研究[J].特区经济,2007(5)：128-129.
[19]刘淑莲,王真,赵建卫.基于因子分析的上市公司信用评级应用研究[J].财经问题研究,2008(7)：53-60.
[20]马自强,旷开萃,方建慧.建筑企业诚信评估指标体系的分析[J].同济大学学报(社会科学版),2003,14(4)：57-63.
[21]孙鹏,施海球,倪立芬.基于AHP的施工企业信用标准体系研究[J].建筑经济,2006(S1)：40-42.
[22]唐茜.建筑施工企业信用评估指标体系的研究[D].哈尔滨工业大学,2006.
[23]刘晓峰,齐二石.建筑企业信用评价系统研究[J].西安电子科技大学学报(社会科学版),2006,16(2)：62-66.
[24]黄文杰,雷泽丽.基于模糊多属性决策法的施工企业信用评价[J].建筑经济,2008(S2)：18-21.
[25]邵丽芳.浙江省公路施工企业信用评价研究[D].长安大学,2006.
[26]曲春慧.建筑企业信用评价研究[D].浙江大学,2006.
[27]王开凤,张谢东,王小璜等.基于AHP的施工企业安全生产评价指标体系的研究[J].武汉理工大学学报(交通科学与工程版),2009,33(1)：169-172.
[28]姚玉玲,李婷婷.公路施工企业信用评价[J].长安大学学报(社会科学版),2007,9(3)：31-33.
[29]董振玉.基于BP神经网络的施工企业信用评价[J].水利与建筑工程学报,2008(4)：115-117.
[30]段蝉.建筑业企业信用评价研究[D].武汉理工大学,2008.
[31]沈杰.西方发达国家个人诚信制度及其运行机制[J].社会科学管理与评论,2006(2)：54-67.
[32]刘颖.西方发达国家政府诚信制度的演变[J].广西社会科学,2004(4)：25-27.
[33]夏敏仁,林汉川.企业信用评级——基于国外经验的中国体系研究[M].上海：上海财经大学出版社,2006.
[34]朱荣恩.资信评级[M].上海：上海财经大学出版社,2006.
[35]F V Krumm, C F Rolle. Management and Application of Decision and Risk Analysis in Du Pont [J]. Interfaces,1992,22(6):84-93.
[36]Li Wenyi. Financial performance evaluation of China's listed steel companies from creditors'perspective[C]. Proceedings of the 2nd International Conference on Interaction Sciences:Information Technology, Culture and Human,2009:337-341.
[37]D J Hand, W E Henley. Statistical Classification Methods in Consumer Credit Scoring:A Review [J]. Journal of the Royal Statistical Society:Series A (Statistics in Society),1997, 160(3):523-541.
[38]Lyn C Thomas. A survey of credit and behavioural scoring:forecasting financial risk of lending to consumers [J]. International Journal of Forecasting,2000,16(2):149-172.
[39]Edward I Altman. A Further Empirical Investigation of the Bankruptcy Cost Question [J]. The Journal of Finance,1984,39(4):1067-1089
[40]Vijay S Desai, Jonathan N Crook, George A Overstreet Jr. A comparison of neural networks and linear scoring models in the credit union environment [J]. European Journal of Operational Research,1996,95(1):24-37.
[41]宋程鹏,王孟钧,常燕.施工企业信用评价体系构建[J].铁路工程造价管理,2007,22(2)：44-47.
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