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Top, mid-tier, and predatory alike? The lexical structure of titles and abstracts of six business and management journals

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Abstract

There is an established agenda seeking to disentangle the relationship between journal articles’ title, keywords, or abstract attributes and their association with bibliometric performance. To date, however, there have been few comparative, benchmarking studies in MBR (management-business research), particularly between top-tier, mid-tier, and periodicals with predatory features. This study aims to provide such a benchmark by identifying significant differences/similitudes in the lexical structure of article titles and abstracts of six MBR journals: Academy of Management Journal and Strategic Management Journal, both distinguished journals in the discipline; Corporate Reputation Review and Journal of Global Information Management, two mid-tier journals; and WSEAS Transactions on Business and Economics and Problems and Perspectives in Management, both identified as journals with predatory features. Three content analysis methods were used: (i) semantic networks; (ii) text readability; (iii) and lexical diversity indices (i.e., Flesch-Kincaid grade level and Yule’s K). Kruskal–Wallis tests were also implemented to identify differences between groups. The findings showed no significant differences in article length, irrespective of groups. Significant differences were found, however, in the readability and lexical diversity of the abstracts, with those in the top-tier group having a lower median readability and higher median lexical diversity. Key-terms with higher betweenness were also found to be similar to those central to MBR in developing countries and top-tier journals on strategy.

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Fig. 1

Source: the author drew on Scopus (2020), Kincaid et al. (1975), Yule (1944), and processed with Quanteda (Benoit et al. 2020)

Fig. 2

Source: the author drew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

Fig. 3

Source: the author drew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

Fig. 4

Source: the author drew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

Fig. 5

Source: the author drew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

Fig. 6

Source: the author dew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

Fig. 7

Source: the author drew on Scopus (2020). Processed with quanteda, igraph, and Gephi (Bastian et al. 2009; R Core Team 2014; The igraph core team 2019; Benoit et al. 2020). Node size is proportional to its betweenness score. The node in aqua tone has the highest betweenness score. Labels: top-ten key-terms with the highest betweenness. Layout: Fruchterman and Reingold (1991)

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  1. School of Management and Business, Universidad del Rosario, Bogotá, Colombia

    Julián D. Cortés

  2. Fudan Development Institute, Fudan University, Shanghai, China

    Julián D. Cortés

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Cortés, J.D. Top, mid-tier, and predatory alike? The lexical structure of titles and abstracts of six business and management journals. Manag Rev Q 73, 297–316 (2023). https://doi.org/10.1007/s11301-021-00240-x

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  • DOI: https://doi.org/10.1007/s11301-021-00240-x

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