Drivers of consumer emotion and recommendation in mobile grocery applications

Purpose This article attempts to understand consumer sentiments and emotions toward mobile grocery shopping applications (MGSA). Additionally, from a technology standpoint, the study examines the influence of different versions of mobile apps on consumer sentiments. Design/methodology/approach We employ a big data-based natural language processing approach using online reviews to identify the positive and negative consumer emotions that drive mobile grocery shopping applications adoption and explore new possibilities for market expansion through consumer-driven recommendations and electronic word-of-mouth (eWOM) triggers. Findings The analysis highlights key drivers of positive and negative emotions (trust, anticipation, surprise, joy, disgust, fear, anger and sadness) influencing consumers' intention to recommend MGSA. The study further emphasizes the impact of technological upgrades on consumer sentiments, underscoring the importance of mobile app management for effective customer engagement, adoption and long-term market performance. Originality/value This study fills a research gap in the growing m-commerce grocery market by assessing the sentiments of early adopters using a large, unbiased dataset to ensure generalizable insights.