Identifying and prioritizing quantitative and qualitative variables predicting the success of investment projects in modeling perceptron neural network for quality management in free and special economic zones of the country
Volume 7, Issue 3, Autumn 2017, Pages 159-175
Morteza shokrzadeh, Kamaledin Rahmani, Farzin modarres khibani
Abstract The available statistics and information about the free and special economic zones of the country show the fact that these zones, in comparison with the export processing zones of the world, have not been very successful in achieving the goals set for them. The statistical population of this research is 80 experts and experts on free and special economic zones, which are available from Aras and Mako free trade-industrial zones and Salmas special economic zone. In this study, the tool used to measure and measure the desired variables are two types of researcher-made questionnaires, one of which is used to use the Likert scale to assess the effect of each factor and the other questionnaire to compare Pairs have been used to prioritize factors. Using the theoretical foundations of six factors and quantitative and qualitative variables predicting the success or failure of investment projects to manage quality in free and special economic zones of the country to model with a multilayer neural network of perceptron, identify and after describing the variables and test Normality, using PLS software, confirmatory factor analysis of variables was performed, all of which had a good confirmatory factor analysis. Then, using linear regression and analysis of variance (ANOVA) test, the effect of each factor on the success or failure of investment projects was investigated. The results of this test showed the confirmation of the effect of each factor and finally the results of hierarchical analysis That is, product and service specifications came in first, and the rest of the factors came in second.