Customer satisfaction in service delivery with artificial intelligence: A meta-analytic study

Abstract

Purpose: This study intends to identify the main background and consequent constructs that form consumer satisfaction in providing services using artificial intelligence (AI) and their magnitudes. Originality/value: This work seeks to fill a gap arising from the scarcity of meta-analytic research on service delivery with AI and also its relationship to consumer satisfaction. Design/methodology/approach: The study adopted the meta-analytic method, and its development followed three phases: 1. research; 2. collection; and 3. coding and data analysis. We analyzed 19 articles published in journals of international relevance from January 2000 to December 2020, present on the Web of Science and Science Direct platforms, totaling 128 observations and 28 topic-related. Findings: Five background constructs and one consequent construct were identified, from which an integrated model was built to illustrate the relationships between consumer satisfaction in intelligent services. The results show that consumer satisfaction in the provision of services is significantly correlated to the adoption of artificial intelligence. Then, the integrated quantitative evaluation that was performed in this study aims to contribute to future empirical evidence in such a way that an increase in the scope of studies on artificial intelligence and consumer satisfaction occurs, based on the analysis of the following constructs: perceived value, perceived features, perception of quality, marketing orientation, identification with the service and behavior of using AI in services.