predicting components of consumer shopping behavior

The duties of university graduates in the field of marketing management are to present a strategic plan with a forward-looking perspective on consumer behavior as a model for empowering marketers and consumers in particular.

In this research paper, it is attempted to investigate the models of predicting consumer buying behavior with macro analysis in physical and virtual space. First, the rules and process of purchasing decision models, and then the formulation of a variety of decision models with the prevailing antimatter in the physical and virtual global competitive environment, with the help of interaction and exchange science and information science and technology.

In order to achieve the results of the research, by designing a questionnaire with a statistical population of 346 people and a five-point Likert scale with 5 subscales, also a questionnaire with Cronbach's alpha of 0.754, using SPSS statistical software and two statistical tests. Significance, standardization and appropriate fit of the selected questions model for the factors under investigation were confirmed by the LISREL Confirmatory Factor Analysis indices of 2.22 df / 2x.

For this purpose, the data of exploratory factor analysis using chi-square test with significance level of 0.000 and KMO index for sample adequacy is 0.765.

By using From equity statistics, And the matrix of agent rotation, two main factors with two-factor behavioral agents, and three-factor stimuli, with more than 63% of the variance were identified and extracted.