摘要
采用BP神经网络模型与DEA-BCC模型对洛阳市农村信用联社的财务绩效和财务效率进行了评估。结果表明:洛阳市农村信用联社财务绩效整体偏低,且各联社之间存在显著差距;财务效率处于非DEA有效状态,但纯技术效率都接近于1,非DEA有效的评价单元均处于规模报酬递增状态;农村信用联社存在投入冗余和产出不足。提出了扩大运营规模、缩减人力成本投入等政策建议,以期提高农村信用联社的财务绩效及运行效率。
Financial performances and efficiency of rural credit cooperatives association(RCCA) in Luoyang are evaluated by means of BP neural networks model and DEA-BCC model.The results show that the financial performance of RCCA in Luoyang is integrally low and there are significant gaps among RCCA; the financial efficiency is in non-DEA effective state,but the pure technical efficiency are close to 1,and the non-DEA effective evaluation units are in a state of increasing returns to scale; RCCA has both input redundancy and output deficiency.Finally,some policy suggestions like enlarging the operational scale,reducing the human costs and so on are offered so as to improve the financial performance and efficiency of RCCA.
出处
《西安石油大学学报（社会科学版）》
2018年第1期34-42,共9页
Journal of Xi’an Shiyou University:Social Science Edition
基金
国家社会科学基金项目(14BJY217)
国家社会科学基金项目(11XJY029)
关键词
农村信用联社
BP神经网络
财务绩效
财务效率
rural credit cooperatives association
BP neural networks
financial performance
financial efficiency
