Structural Equation Modeling of Social Media Influences: How Visual Appeal and Product Information Shape Positive Word of Mouth
Abstract
Social media has become an essential tool in contemporary marketing strategies, allowing brands to enhance consumer engagement and foster trust. This study examines the direct effects of visual appeal and product information on brand satisfaction and positive Word of Mouth (WOM) in the context of Samsung’s social media campaigns. The research aims to provide empirical insights into how specific content elements drive consumer satisfaction and WOM, which are critical factors in expanding a brand’s digital influence. Data were collected from 132 active social media users frequently exposed to Samsung’s advertisements. Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) approach was employed to analyze the relationships between variables. The results indicate that visual appeal significantly impacts brand satisfaction (path coefficient = 0.419, T-statistic = 3.765, P-value = 0.000) and WOM (path coefficient = 0.221, T-statistic = 2.437, P-value = 0.015). Product information also shows a significant influence on brand satisfaction (path coefficient = 0.337, T-statistic = 3.126, P-value = 0.002) and WOM (path coefficient = 0.320, T-statistic = 3.795, P-value = 0.000). Additionally, brand satisfaction strongly contributes to positive WOM (path coefficient = 0.458, T-statistic = 7.191, P-value = 0.000). The findings emphasize the critical role of high-quality visual and informational content in fostering brand satisfaction and promoting WOM. The novelty of this research lies in its detailed examination of how visual appeal and product information independently influence consumer outcomes, offering actionable insights for marketers. This study contributes to the growing literature on digital marketing by providing evidence-based recommendations for optimizing social media strategies in highly competitive and digitally connected marketplaces.
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Journal of Applied Data Sciences
ISSN | : | 2723-6471 (Online) |
Organized by | : | Computer Science and Systems Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia. |
Website | : | http://bright-journal.org/JADS |
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