Identifying and Validating the Factors Affecting Online Social Media Marketing about Consumer Buying Behavior
Subject Areas : Business StrategyReyhaneh Toudeh Bahambari 1 , Hossein Hakim pour 2 , Mehdi Mahmoudzadeh Vashan 3 , Hamid Rezaeifar 4
1 - Department of Management, Birjand Branch, Islamic Azad University, Birjand, Iran
2 - Department of Management, Birjand Branch, Islamic Azad University, Birjand, Iran
3 - Department of Management, Birjand Branch, Islamic Azad University, Birjand, Iran
4 - Department of Management, Birjand Branch, Islamic Azad University, Birjand, Iran
Keywords: MICMAC Analysis, Interpretive Structural Modeling (ISM), consumer buying behavior, Online social media marketing,
Abstract :
Online social media is an important innovation that has attracted individuals and companies. The purpose of this study is to "develop an online social media marketing model about consumer buying behavior". This utilizes a mixed-method (qualitative and quantitative). This study uses the research literature to extract the indicators, then, finalizes them by the Delphi technique in three different rounds. The study develops the qualitative model of the research based on the opinions of 20 experts as well as the application of Interpretive Structural Modelling (ISM) and MICMAC analysis. In the quantitative part, the study uses the Partial Least Squares (PLS) technique to implement SEM, validate, and test the predictive relevance of the initial model. This study applies Cohen's formula and determines 460 individuals as sample. The sampling method is non-probability. Furthermore, the statistical population of the study consists of online social media users from all over Iran. In this study, 9 key factors have been identified, modeled and analyzed. According to the MICMAC analysis results, perceived security (with the highest driving power) is identified as the driving indicator, and value co-creation (with the highest dependence) is identified as the result or target indicator. The ISM based model is validated using SEM and 15 hypotheses were checked using SEM-PLS technique, also all hypotheses except the second hypothesis were confirmed. Finally The findings confirmed Goodness of Fitness and ideal predictive relevance of the model.
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