Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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.
Martha Gaudance. 2026. \u201cEvaluating the Factors that Contribute to the Shopping through Social Media, using Exploratory factor Analysis and Partial Least Square Structural Equation Modeling – Insights from Tanzania\u201d. Global Journal of Human-Social Science - H: Interdisciplinary GJHSS-H Volume 23 (GJHSS Volume 23 Issue H3): .
Crossref Journal DOI 10.17406/GJHSS
Print ISSN 0975-587X
e-ISSN 2249-460X
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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.
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