Abstract
PurposeThis paper aims to take stock of research done in the domain of relationship marketing (RM). Additionally, this article aims to identify the potential areas of future research.Design/methodology/approachThe authors have used machine learning-based structural topic modelling using R-software to analyse the dataset of 1,905 RM articles published between 1978 and 2020.FindingsStructural topic modeling (STM) analysis led to identifying 14 topics, out of which 7 (viz. customer loyalty, customer relationship management systems, interfirm and network relationships, relationship selling, services and relationship management, consumer brand relationships and relationship marketing research) have shown a rising trend. The study also proposes a taxonomical framework to summarize RM research.Originality/valueThis is the first comprehensive review of RM research spanning over more than four decades. The study’s insights would benefit future scholars of this field to plan/execute their research for greater publication success. Additionally, managers could use the practical implications for achieving better RM outcomes.
Published Version
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