فهرست مطالب bizhan nosrati barandagh

The purpose of this paper is to design small and medium-sized enterprises (SMEs) financing model. The present research is distinct from other papers published on SMEs financing in that it identifies financing criteria using fuzzy screening (FC), considers the relations, and weighs these criteria using Decision Making Trial and Evaluation Laboratory model based on Analytic Network Process (DANP). Statistical population and sample included 23 senior experts of SMEs industries, senior managers of banks, and university professors familiar with the concepts of SMEs financing. The results indicated that 8 dimensions and 20 criteria were identified using FC and expert opinions. Moreover, the results of DANP method showed that attracting new members is the most important criterion of SMEs financing, and loan rate from procuration and proprietary sources of banks is ranked the second. The other criteria were also weighed and ranked. Considering the causal relationships of criteria showed that revaluation of assets is the most effective criterion, and bank loan growth rate is the most affected criterion in SMEs financing. The research findings can enhance decision making and decision taking in financial performance improvement, and experts can be provided with optimal financing practices so as to develop the economy of Iran and growth these enterprises.

The purpose of present article is to design a dynamic model (DM) of financing SMEs according to Decision Making Trial And Evaluation Laboratory (DEMATEL) based on Analytical Network Process (ANP) (DANP) approach. The innovation of this article is to take hybrid of DANP and DM in financing SMEs approach. This article has paid using different scenarios in financing SMEs and model simulation. The dynamic model is formulated therefore, based on previous literature and the fuzzy screening method, extracting effective factors on financing SMEs and causal link identified. Then it was included in the model using the DANP the relationships between them and the amount of impact coefficients are determined. Finally identify new financing methods over a 10 month period in order to test the accuracy of the model and to determine the behavior of the state and rate variables, we collected data from 24 SMEs. The behavior of research variables analyzing by evaluated in the framework of the model as well as sensitivity analysis the validity of the DM is designed. The results showed that SMEs use the designed model and the scenarios can be used to finance their business optimally.