Customer Loyalty Formation in Sania Cooking Oil Purchases

General Background: Customer loyalty in staple food markets depends on consumer evaluation of value, product performance, brand perception, and post-purchase experience. Specific Background: Sania cooking oil consumers consider price, product quality, and brand image before developing customer trust, purchase intention, purchasing decisions, repurchase behavior, and customer loyalty. Knowledge Gap: The loyalty formation pathway for Sania cooking oil required structural testing across price, product quality, brand image, trust, purchase intention, purchasing decisions, repurchase, and loyalty. Aims: This study aimed to analyze the relationships among price, product quality, brand image, customer trust, purchase intention, purchasing decisions, repurchase, and customer loyalty among Sania cooking oil consumers. Results: Using a descriptive quantitative method, questionnaire data from 140 respondents were analyzed through Structural Equation Modeling with validity, reliability, and significance testing. The results show that price had a positive and significant relationship with customer trust at 0.729, while product quality and brand image showed positive but non-significant relationships at 0.075 and 0.082. Customer trust significantly related to purchase intention at 0.833, purchase intention related to purchasing decisions at 0.820, purchasing decisions related to repurchase at 0.814, and repurchase strongly related to customer loyalty at 0.802. Novelty: This study maps a sequential loyalty formation model for Sania cooking oil consumers. Implications: Management should strengthen value perception and trust-building strategies to support repurchase and loyalty. Highlights: The first exogenous variable recorded a 0.729 significant coefficient. Two other initial predictors were positive but not significant. The strongest final pathway coefficient reached 0.802. Keywords: Sania Cooking Oil, Customer Loyalty, Customer Trust, Purchase Intention, Structural Equation Modeling