Thirty years of product and brand management research: a retrospective review of the Journal of Product and Brand Management using bibliometric analysis

Abstract

Purpose The Journal of Product and Brand Management (JPBM) has a 30-year long history. To commemorate the journal’s 30th anniversary, this research paper aims to present a retrospective overview of JPBM. Design/methodology/approach This research examines the performance of the research constituents, social structure and intellectual structure of scholarly publications produced by JPBM between 1992 and 2021 using bibliometric analysis. Findings This research sheds light on the growing influence of JPBM through four major knowledge clusters (themes): strategic brand management; consumer behavior; product development and innovation management; and brand engagement. A temporal analysis of decade-by-decade cataloguing of the JPBM corpus revealed another set of three distinct knowledge clusters (themes): retailing and pricing strategies; marketing communications; and relationship marketing. Research limitations/implications Though the state-of-the-art overview herein offers seminal and useful insights about product and brand management research curated by JPBM, which can be used by the editorial board and prospective authors to curate and position the novelty of future contributions, it remains limited to the accuracy and availability of bibliographic records acquired from Scopus. Originality/value This research advances the internal review and subjective evaluation of the evolution of brand management thinking in JPBM by Veloutsou and Guzmán (2017) with an objective retrospection on the performance and scientific evolution of product and brand management research in JPBM.

Asian business and management: review and future directions

“…The popularity of the journal among academia may be gauged using established journal-related performance indicators such as CiteScore (CS) and impact factor (IF). Scopus reports the CS of journals based on the last 4 years of bibliographic records from the Scopus database, while Clarivate Analytics reports the IF of journals based on the latest 2 years of bibliographic records from the Web of Science (WoS) database (Donthu et al, 2022 ; Waris et al, 2021 ). ABM was included in Clarivate Analytics (its predecessor) in 2007 and Scopus in 2008.…”

“…To assess ABM’s performance, several metrics were used (“ Appendix ”), including total publications (TP), total cited publications (TCP), total citations (TC), citations per publications (TC/TP), citations per cited publications (TC/TCP), citations per active year since publication (C/Y), h-index , and IF and CS. The quantitative existence of research constituents such as authors, institutions, and countries is defined by TP, whereas the quantifiable scholarly influence of these elements is designated by TC (Donthu et al, 2021 , 2022 ; Gammelgaard et al, 2020 ; Pattnaik et al, 2021 ). TCP counts influential or referenced articles, providing a logical justification for using TC/TCP rather than TC/TP (Donthu et al, 2022 ; Kataria et al, 2021 ; Varma et al, 2022 ).…”

“…The quantitative existence of research constituents such as authors, institutions, and countries is defined by TP, whereas the quantifiable scholarly influence of these elements is designated by TC (Donthu et al, 2021 , 2022 ; Gammelgaard et al, 2020 ; Pattnaik et al, 2021 ). TCP counts influential or referenced articles, providing a logical justification for using TC/TCP rather than TC/TP (Donthu et al, 2022 ; Kataria et al, 2021 ; Varma et al, 2022 ). The h-index , like IF and CS, is a similar impact-measuring metric defined as the maximum value of h such that the given author/journal has written at least h articles, each of which has been cited at least h times (Gammelgaard et al, 2020 ; Waris et al, 2021 ).…”

“…Network visualization was utilized in scientific mapping to uncover the main knowledge clusters that constitute ABM’s social and intellectual structure. Drawing on previous research (Donthu et al, 2022 ; Kataria et al, 2021 ; Varma et al, 2022 ), the collaboration pattern among research constituents was found using co-authorship analysis, while the knowledge cluster was established using the co-occurrence of the author keyword method. It is fairly obvious that authors select keywords to represent the topics and themes that lie at the heart of their academic work and also to increase their exposure among interested researchers (Sureka et al, 2020 ; Viglia et al, 2022 ).…”

“…ABM is celebrating its twentieth anniversary in 2022; to commemorate the event, we conducted a bibliometric analysis of the journal, which also serves as an excellent reflection of the research landscape in the area of business and management in Asia. Bibliometric methodology provides an unbiased review of the journal through quantitative assessment in a variety of areas (Donthu et al, 2022 ; Gammelgaard et al, 2020 ; Kataria et al, 2021 ), including content and pattern relating to publications, citations, contributors (i.e., authors, institutions, countries, and publishing outlets), geographical focuses, and scholarly contributions (themes and topics). Given ABM’s accomplishments and reputation over the preceding two decades, the current investigation attempts to answer the following research questions (RQs):…”