Providing a crowdsourcing model for developing automotive industry strategies

This paper presents a crowdsourcing model for developing automotive industry strategies using the partial least squares method. The implementation method of this research is descriptive-survey and the correlational research design is of the type of structural equations using the method of partial least squares. The selected options to answer the questions of this research included the employees and experts of automobile industry in Tehran. In addition, stratified random sampling method has also been used in some cases. Based on standard statistical models, the number of statistical samples in this research is considered to include 220 samples according to the "Cochran" formula. The selected statistical samples of the article responded to the research questionnaire. Data analysis was done using structural equation model and using SMARTPLS software. The results of this research show that information intelligence and strategy adoption on value creation, customer acceptance and cost reduction are significant at the 0.01 level. The numbers inside the circle are the explained variance of the research variables. 47% of information intelligence variance, 62% of strategy adoption, 46% of value creation, 38% of customer acceptance and 52% of cost reduction were explained by the research model.