Industrial-buying research 1965-2015: review and analysis

Abstract

Purpose The purpose of this paper is to investigate the underlying knowledge structure and evolution of industrial-buying research published between 1965 and 2015. Design/methodology/approach Bibliometric analysis is performed on 357 relevant papers (using principal component analysis and natural language processing, using VantagePoint® tools, used to generate bubble maps, auto-correlation maps and Aduna cluster maps), demonstrating how various factors involved in industrial buying have evolved, their degree of correlation with each other and the interrelationships of multiple factors concerning their co-occurrences. Findings The systematic mapping of industrial-buying research would illustrate the development of the significant factors in industrial-buying research. This paper provides both a global perspective on the leading countries and journals in the field and a robust roadmap for further investigation in this field. Research limitations/implications This paper is limited to the data considered for analysis and may, therefore, overlook or underestimate some work that has not been captured while filtering databases related to industrial buying. Practical implications This paper facilitates near-future projection and trend analysis in industrial-buying research. Originality/value The methodology used is unique to the field of business-to-business marketing.

Research constituents and citation analysis of theJournal of Business and Industrial Marketing(1986–2019)

“…provide a bibliometric analysis on 30 years of JBIM concentrating mainly on the most published topics and the most prolific authors, their affiliated institutions and countries. The current retrospective evaluation extends the work of and Chavan et al, 2019, and also, at the same time, differs in many respects. First, the present study uses both bibliometric and empirical methods to evaluate the JBIM corpus covering 1986-2019.…”

“…In recent years, JBIM has published ample of narrative and SLRs such as Dobrucalı (2019), Novais et al (2019), Altuntas Vural (2017), ), McDonald (2010. Bibliometric studies published by the journal includes Chavan et al (2019), Valenzuela-Fernandez et al (2019), and Dagnino et al (2015). Narrative reviews provide a comprehensive description of the previously published literature.…”

“…Rosenstreich and Wooliscroft (2009) developed "g" scores and other ways of measuring an article's impact. Chavan et al (2019) presented a retrospective of the existing body of knowledge on industrial buying research between using bibliometrics. The study explored major works, authors, contributing countries, trends, intellectual evolution and emerging areas in industrial busing field.…”

“…This study addresses the following six research questions: Literature review is the majorly used technique in management research for managing the diversity of scientific knowledge for a definite academic inquiry (Tranfield et al, 2003). Several studies have reviewed industrial buying and B2B marketing research (Reid and Plank, 2000;LaPlaca and Katrichis, 2009;Chavan et al, 2019). In addition, LaPlaca and Johnston (2006) provide a case study of JBIM offering a brief history of the journal and its advancement.…”

Research on the Natural Language Recognition Method Based on Cluster Analysis Using Neural Network

“…e basic step is to divide a sentence into a sequence of several sentence elements through a word segmentation algorithm and then use a nonmonotonic optimal part-of-speech analysis model to determine each sentence subjected to the functional attributes of the element. Obviously, the dimension of the sentence element attribute vector obtained in this way is equal to the length of the sentence element sequence generated by the word segmentation, but some elements in this vector can also be combined to a certain extent [27][28][29]. Sentences are a kind of division.…”