基于改进TOPSIS模型的物流业上市公司融资效率
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摘要
基于改进TOPSIS模型,对2016年我国物流业上市公司进行融资效率评价,对比2015年评价结果进一步探究影响融资效率的主要因素。结果表明:影响物流业上市公司融资效率的主要因素集中在利息保障倍数、存货周转率及筹资活动现金流入流出比等方面; 2016年物流业上市公司融资效率整体较低,且行业间差距较大;2016年物流业融资整体效率低于2015年,且下降幅度较大。提出相关建议:物流业企业应进一步优化筹资结构,提高筹资效率,增强公司治理能力,强化自身竞争力。
Based on the improved TOPSIS model, the financing efficiency of listed companies in China's logistics industry in 2016 is evaluated, and compared with the 2015 evaluation results, the main factors affecting the efficiency of financing are further explored. The results are as follows:the main factors affecting the financing efficiency of listed companies in the logistics industry are concentrated in the interest guarantee multiples, inventory turnover rate and cash inflow and outflow ratio of financing activities;the financing efficiency of listed companies in the logistics industry was generally low in 2016, and the gap between industries was large;the overall efficiency of logistics industry financing was lower in 2016 than that in 2015, and the decline was larger. Relevant suggestions have been proposed that logistics enterprises should further optimize the financing structure, improve fundraising efficiency, enhance corporate governance capabilities, and strengthen their competitiveness.
Based on the improved TOPSIS model, the financing efficiency of listed companies in China's logistics industry in 2016 is evaluated, and compared with the 2015 evaluation results, the main factors affecting the efficiency of financing are further explored. The results are as follows:the main factors affecting the financing efficiency of listed companies in the logistics industry are concentrated in the interest guarantee multiples, inventory turnover rate and cash inflow and outflow ratio of financing activities;the financing efficiency of listed companies in the logistics industry was generally low in 2016, and the gap between industries was large;the overall efficiency of logistics industry financing was lower in 2016 than that in 2015, and the decline was larger. Relevant suggestions have been proposed that logistics enterprises should further optimize the financing structure, improve fundraising efficiency, enhance corporate governance capabilities, and strengthen their competitiveness.
引文
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[13] 周文坤,王成付.供应链融资模式下中小企业信用风险评估研究:基于左右得分的模糊TOPSIS算法[J].运筹与管理,2015(1):209-215.
[14] 刘东,龚方华,付强,等.基于博弈论赋权的灌溉用水效率GRA-TOPSIS评价模型[J].农业机械学报,2017(5):218-226.
[15] 朱乾隆,栾敬东.基于改进TOPSIS模型的土地生态安全评价:以安徽省为例[J].安徽农业大学学报(社会科学版),2018(3):36-41.
[ 2 ] 吴娜.基于DEA的山西省物流产业效率研究[D].太原:太原理工大学,2014.
[ 3 ] 倪志敏.对河南省物流效率及其影响因素的实证研究[J].河南理工大学学报(社会科学版),2017(2):20-24.
[ 4 ] 刘丹,巩彦峰,潘晓.海丝路沿线地区物流业的运行效率评价:基于视窗网络SBM模型[J].华南理工大学学报(社会科学版),2018(1):30-39.
[ 5 ] 王海荣,耿成轩.新能源汽车产业融资效率:基于SUPER-SBM DEA及TOBIT模型[J].社会科学家,2016(11):83-87.
[ 6 ] 蒋惠凤.基于数据包络分析的农业上市公司融资效率研究[J].江苏农业科学,2016(11):501-504.
[ 7 ] 张孟威.科技型中小企业挂牌新三板融资效率研究[D].贵阳:贵州财经大学,2017.
[ 8 ] 段从海.云南省医药制造业上市公司投融资效率分析[D].昆明:昆明理工大学,2017.
[ 9 ] 田刚,梁雪,吴天博.基于DEA模型的我国林业上市公司融资效率研究[J].林业经济,2017(3):73-77.
[10] 巩世广,李雯君.中小企业融资难的“蝴蝶效应”机制[J].沈阳大学学报(社会科学版),2014(3):321-324.
[11] 李灿,张凤荣,朱泰峰,等.基于熵权TOPSIS模型的土地利用绩效评价及关联分析[J].农业工程学报,2013(5):217-227.
[12] 杜挺,谢贤健,梁海艳,等.基于熵权TOPSIS和GIS的重庆市县域经济综合评价及空间分析[J].经济地理,2014(6):40-47.
[13] 周文坤,王成付.供应链融资模式下中小企业信用风险评估研究:基于左右得分的模糊TOPSIS算法[J].运筹与管理,2015(1):209-215.
[14] 刘东,龚方华,付强,等.基于博弈论赋权的灌溉用水效率GRA-TOPSIS评价模型[J].农业机械学报,2017(5):218-226.
[15] 朱乾隆,栾敬东.基于改进TOPSIS模型的土地生态安全评价:以安徽省为例[J].安徽农业大学学报(社会科学版),2018(3):36-41.