Design and validation of the change in the end-user's behavior model from offline to online with a mixed research approach in the FMCGs group

The volume of online shopping compared to offline shopping and the speed of change in consumer behavior from online to offline in Iran is much lower than the world average. Therefore, this research aims to design and validation of the change in the end-user's behavior model from offline to online in the FMCGs group. A mix of qualitative (grounded Theory) and quantitative (structural equation modeling) methods are used to identify components, indicators, and the relationship between them. In the qualitative section, 10 experts were selected by snowball sampling and in the quantitative section by Cochran's formula, 384 people were determined by simple random sampling. Semi-structured interviews were used to collect qualitative data, whereas questionnaires were used to collect quantitative data. Content validity and face validity were confirmed by the Delphi technique, construct validity and questionnaire structure by confirmatory factor analysis, reliability by Cronbach's alpha coefficient, and composite reliability in SmartPLS and SPSS software. MAXQDA software was used to analyze qualitative data. Kolmogorov-Smirnov test for normality, the Friedman test for prioritizing components and indicators, and the structural equation modeling test for path analysis and model validation were used to analyze quantitative data. In the qualitative results, 8 components and 60 indicators were confirmed. Ranking of components based on quantitative results includes consumer decision-making structure, the consequences of consumer behavior in online platforms, FMCGs competitive advantage, consumer behavior models, marketing and advertising communication channels, consumer innovation technology, and e-commerce acceptance and marketing strategies.