Framing knowledge structure of customer engagement: a multimethod review

Abstract

Purpose

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

Design/methodology/approach

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

Findings

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

Originality/value

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.

Citation

Roopak, R. and Chakrabarti, S. (2024), "Framing knowledge structure of customer engagement: a multimethod review", VINE Journal of Information and Knowledge Management Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/VJIKMS-12-2022-0364