Determinants of Customer Loyalty among FMCG Consumers in Lahore: A Structural Equation Modelling Approach
Year: 2025
Type: article
Study design: Observational Study
Abstract: The transformation in the FMCG (Fast-Moving Consumer Goods) sector in Pakistan has been quick with the growth of digital markets, improvement of consumer expectations, and the availability of information. The knowledge of the motivating factors of customer empowerment and loyalty has become vital to the firms that compete in the metropolitan markets like Lahore. This paper examines how the perceived risk, seller reputation, and concern on privacy affect the empowerment of customers and, by extension, customer loyalty in the context of consumer behavior in the FMCG. Based on the empowerment and loyalty theories, the quantitative research design was used and 350 FMCG consumers were sampled in Lahore through purposive sampling. The measure of reliability, validity, and structural relations was assessed with Structural Equation Modeling (SEM) with SmartPLS 4.0. The results demonstrate that the reputation of sellers and privacy concern have a significant impact on customer empowerment, whereas perceived risk has a negative impact on the empowerment. Customer loyalty is highly and positively predicted by customer empowerment. The mediation analysis shows that customer empowerment partly mediates the relationships between the seller reputation and loyalty as well as the privacy concern and the loyalty, and completely mediates the relationship between the perceived risk and the loyalty. The model has a high explanatory power (R 2 = 0.64 customer empowerment; R 2 = 0.58 customer loyalty). The research adds to the body of knowledge on FMCG branding by pointing out the issue of consumer empowerment as the key in establishing long-term loyalty. They give practical suggestions that the FMCG marketers can adopt so that they minimize the risks of consumer perceptions, boost the reputation of sellers, and develop trust by having transparent privacy policies.
Institution: Kunming University of Science and Technology
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7123337686