Deconstructing customer satisfaction recipes: A dynamic configurational framework leveraging the power of online reviews in tourism contexts

Abstract

The complex relationship between product or service attribute performance and customer satisfaction in online review environments has been widely discussed. However, attribute configuration for enhancing customer satisfaction under holistic thinking, particularly considering temporal interactions among attributes, remains underexplored. To address this gap, this study develops a dynamic configurational framework based on complexity and three-factor theories to deconstruct attribute recipes and their temporal evolution for improving customer satisfaction in tourism contexts. By extracting key service attributes and affects directly from tourist reviews, it identifies patterns that consistently achieve high satisfaction over time. This is the first study to integrate online review mining with panel fuzzy-set qualitative comparative analysis from a customer experience perspective. Findings reveal the existence of multiple equivalent causal pathways, with distinct satisfaction pathways for different tourist segments. Practically, normative causal recipes assist policymakers in optimizing tourism resource allocation and providing strategic insights to dynamically respond to tourist demands.