global-journal-of-human-social-science-h-interdisciplinary Global Journal of Human-Social Science - H: Interdisciplinary 0975-587X 2249-460X Global Journals Publishing Group Incorporated 62189 Evaluating the Factors that Contribute to the Shopping through Social Media, using Exploratory factor Analysis and Partial Least Square Structural Equation Modeling – Insights from Tanzania Consumer Behavior and Social Media E-Commerce GaudanceMartha TANZANIA 13 05 2023 23 H3 69 86

The purpose of this study is to apply exploratory factor analysis and Partial least square Structural equation to analyze the factors contributing thriving of online shopping through social media in Tanzania. Seven areas of Social and Economic factors, social media behavior factors, Buying and Shopping Behavior, Technology Internet Acceptance factors, Security and Risk assessment factors, Customer care, pre-purchasing, and Post Purchasing service and Cost factors were theoretical conceptualized to construct latent factors. An online questionnaire was used as a data collection tool with 344 participants, and data were analyzed using R software for statistical analysis and Smart PLS software for partial least square modeling. Exploratory factor analysis was used to evaluate variable factor loadings, and variables with more than or equal to 0.3 loadings were used in structural equation modeling.

 online shopping behavior social media buying behavior and partial least square structural equation. Full Text

The purpose of this study is to apply exploratory factor analysis and Partial least square Structural equation to analyze the factors contributing thriving of online shopping through social media in Tanzania. Seven areas of Social and Economic factors, social media behavior factors, Buying and Shopping Behavior, Technology Internet Acceptance factors, Security and Risk assessment factors, Customer care, pre-purchasing, and Post Purchasing service and Cost factors were theoretical conceptualized to construct latent factors. An online questionnaire was used as a data collection tool with 344 participants, and data were analyzed using R software for statistical analysis and Smart PLS software for partial least square modeling. Exploratory factor analysis was used to evaluate variable factor loadings, and variables with more than or equal to 0.3 loadings were used in structural equation modeling. Nine hypotheses were created with direct and indirect effect; results reveled social-economic factors, technology, and internet adoption and Security and Risk influence social media shopping behavior. This study also finds multiclonality influence between factors as social and economic and security factors influence technology adoption.