Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning
المؤلفون المشاركون
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-07-10
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Agricultural enterprises play a significant role in China’s economic development.
However, compared with other enterprises, agricultural enterprises are facing serious financial problems.
Financing difficulty is essentially a question of financing efficiency.
Based on the DEA method, this paper evaluates the financing efficiency of 39 agricultural listed companies in China from 2013 to 2017.
The results suggest that the financing efficiency is generally low, and the Total Factor Productivity of agricultural enterprises’ financing has a tendency to decrease first and then increase.
The influencing factors of financing efficiency are analyzed using the Tobit regression model and the random forest regression model.
And we find the following: (1) The random forest regression model significantly outperformed the Tobit regression model, with determination coefficients (R2) greater than 0.9 in full sample sets.
(2) Total liability, financial expenses, return on total assets, and inventory turnover rate are important factors affecting financing efficiency of agricultural listed companies.
(3) Return on total assets and inventory turnover rate promote the financing efficiency, while total liability and financial expenses reduce financing efficiency.
Finally, the paper makes some suggestions for the financing of agricultural enterprises.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Lixia& Zhan, Xueli. 2019. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Lixia& Zhan, Xueli. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Lixia& Zhan, Xueli. Analysis of Financing Efficiency of Chinese Agricultural Listed Companies Based on Machine Learning. Complexity. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133158
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1133158
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر