Aura Lydia Riswanto

Social media has become a dominant channel for food marketing, particularly targeting youth through visually engaging and socially embedded content. This study investigates how young adults visually engage with food advertisements on social media and how specific visual and contextual features influence purchase intention. Using eye-tracking technology and survey analysis, data were collected from 35 participants aged 18 to 25. Participants viewed simulated Instagram posts incorporating elements such as food imagery, branding, influencer presence, and social cues. Visual attention was recorded using Tobii Pro Spectrum, and behavioral responses were assessed via post-surveys. A 2 × 2 design varying influencer presence and food type showed that both features significantly increased visual attention. Marketing cues and branding also attracted substantial visual attention. Linear regression revealed that core/non-core content and influencer features were among the strongest predictors of consumer response. The findings underscore the persuasive power of human and social features in digital food advertising. These insights have implications for commercial marketing practices and for understanding how visual and social elements influence youth engagement with food content on digital platforms.

The design of product packaging significantly impacts consumer behavior by attracting attention and influencing purchasing choices within a competitive market environment. This research explores the effects of visual packaging elements, such as branding, imagery, and descriptive text, on consumer preferences and decisions. By examining regular, organic, and character-themed milk packaging, the study seeks to determine which features effectively capture attention and drive engagement. Employing eye-tracking tools (Tobii Pro Spectrum and Tobii Pro Lab) alongside survey analysis, the study evaluates consumer focus through fixation durations and heatmap visualizations. The findings indicate that character-themed packaging draws the most attention, with colorful illustrations and prominently displayed brand names playing a central role. Fixation data highlight brand names as the most consistently engaging feature across all packaging types. Regression analysis further reveals that cultural familiarity influences preferences, as international participants favored designs resembling those from their home regions or familiar global brands. These insights underscore the importance of visually appealing and culturally relevant designs in building consumer engagement and brand loyalty. The study offers valuable guidance for marketers and designers aiming to create packaging that resonates with diverse audiences and market demands.

This study examines the role of Komodo Island in boosting Indonesia’s status as a leading global tourism destination, emphasizing the importance of balancing environmental preservation with visitor satisfaction for sustainable growth. By conducting a comprehensive analysis of online reviews from Google Travel, this study identifies key factors that shape tourists’ experiences on Komodo Island. Specifically, the objectives are to uncover the primary drivers of visitor satisfaction and offer practical recommendations for tourism operators and policymakers. Using text mining and semantic network analysis through RStudio and UCINET 6.0 to analyze word associations, alongside exploratory factor analysis and linear regression in SPSS 29, this study focuses on aspects such as “Value for Money” and “Service Quality”. The results show that natural attractions greatly enhance visitor satisfaction, whereas high expenses and inconsistent service quality are sources of dissatisfaction. These insights highlight the importance of revisiting pricing approaches and enhancing training for frontline staff. The study’s recommendations for sustainable tourism on Komodo Island center on recalibrating pricing and improving service quality, fostering a memorable experience for visitors.

This study aims to bridge the gap between traditional consumer behavior analysis and modern techniques by integrating big data analysis, eye-tracking technology, and survey methods. The researchers considered that understanding consumer behavior is crucial for creating effective advertisements in the digital age. Initially, a big data analysis was performed to identify significant clusters of consumer sentiment from online reviews generated during a recent seasonal promotional campaign. The key factors were identified and grouped into the “Product”, “Model”, “Promo”, and “Effect” categories. Using these clusters as a foundation, an eye-tracking analysis measured visual attention metrics such as the fixation duration and count to understand how the participants engaged with the different advertisement content. Subsequently, a survey assessed the same participants’ purchase intentions and preferences related to the identified clusters. The results showed that the sentiment clusters related to products, promotions, and effects positively impacted the customer satisfaction. The eye-tracking data revealed that advertisements featuring products and models garnered the most visual attention, while the survey results indicated that promotional content significantly influenced the purchase intentions. This multi-step approach delivers an in-depth understanding of the factors that affect customer satisfaction and decision-making, providing valuable information for optimizing marketing strategies in the Korean skincare market. The findings emphasize the importance of integrating consumer sentiment analysis with visual engagement metrics to develop more effective and compelling marketing campaigns.