The evolution of IB research: a topic model analysis of EIBA conference papers (1975-2020)

Purpose This paper comes in the context of the European International Business Academy (EIBA) History project, and the long period analysed was broken down in six time windows (1975–1981, 1982–1988, 1989–1995, 1996–2002, 2003–2012; and 2013–2020), in line with the periodisation followed in writing such history. The main purpose was to identify the key themes of the papers presented at EIBA conferences between 1975 and 2020. Design/methodology/approach The analysis was carried out drawing on topic modelling, a machine-learning statistical solution that is capable of processing large volumes of text data. Findings A set of 5,296 Competitive and Workshop papers was processed with the use of topic modelling. The method enabled to identify 24 underlying research topics. These were then grouped into nine higher-level categories. The results show a consistent growth in the number of papers presented, especially in the periods going from 1989–2012. This is a sign of an increasing attractiveness, openness and attendance in EIBA’s annual conferences. Overall, the topics with the highest probabilities were topic 22 (Measuring and Assessing IB performance), followed ex-aequo by topics 13 (Evolutionary Approaches, Matrix Structures and Managerial Challenges) and 20 (Comparative Management Education and Behaviour) and then by topic 4 (Born Globals and International New Ventures). A key finding was the change in methodological approaches over time, with a significant increase in the use of sound quantitative and qualitative methods, instead of broad narratives mostly based on descriptive statistics. Research limitations/implications Latent Dirichlet Allocation (LDA), as a quantitative approach to analyse text data, has some limitations. LDA, along with other distributional models, may identify degrees of semantic relations between words, but is not able by itself to specify the kind of relation, entailing a possible loss of contextual information which might have been able to further assist in the study. Another limitation stems from the use of very old paper proceedings, whose quality was sometimes low, making reading difficult. Practical implications This research provides a longitudinal perspective of the evolution of the key research topics in international business over about 45 years. Its findings are very important for all those who are interested on the evolution of the IB field. Social implications The research provides an interesting perspective of the development of a scientific field as well as of a scientific community. Originality/value The main contributions of this research are fourfold. Firstly, to the best of the authors' knowledge, it provides the most complete longitudinal analysis about the evolution of IB research topics published so far. Secondly, it extracts relevant information about the evolution of the IB research issues addressed at EIBA’s annual conferences, enabling a 46-year longitudinal perspective on research interests as they emerged. Thirdly, it provides a successful application of topic modelling for the analysis of large volumes of textual data. Fourthly, it addresses the entirety of the text documents, as opposed to specific sections or keywords only, ensuring increased analytical depth.

Authors

Institutions

Publication Details

Journal
Competitiveness Review An International Business Journal incorporating Journal of Global Competitiveness
Published
2024-12-27
DOI
https://doi.org/10.1108/cr-07-2024-0132
Citations
1
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
1.89
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The evolution of IB research: a topic model analysis of EIBA conference papers (1975-2020)

John Cantwell, Vítor Corado Simões, Philippe Gugler, Anke Piepenbrink et al.
1 citations
Competitiveness Review An International Business Journal incorporating Journal of Global Competitiveness
Computational and Text Analysis Methods
1.89
article

The evolution of IB research: a topic model analysis of EIBA conference papers (1975-2020)

John Cantwell, Vítor Corado Simões, Philippe Gugler, Anke Piepenbrink, João Pedro Rocha
article en
1 citations

Abstract

Purpose This paper comes in the context of the European International Business Academy (EIBA) History project, and the long period analysed was broken down in six time windows (1975–1981, 1982–1988, 1989–1995, 1996–2002, 2003–2012; and 2013–2020), in line with the periodisation followed in writing such history. The main purpose was to identify the key themes of the papers presented at EIBA conferences between 1975 and 2020. Design/methodology/approach The analysis was carried out drawing on topic modelling, a machine-learning statistical solution that is capable of processing large volumes of text data. Findings A set of 5,296 Competitive and Workshop papers was processed with the use of topic modelling. The method enabled to identify 24 underlying research topics. These were then grouped into nine higher-level categories. The results show a consistent growth in the number of papers presented, especially in the periods going from 1989–2012. This is a sign of an increasing attractiveness, openness and attendance in EIBA’s annual conferences. Overall, the topics with the highest probabilities were topic 22 (Measuring and Assessing IB performance), followed ex-aequo by topics 13 (Evolutionary Approaches, Matrix Structures and Managerial Challenges) and 20 (Comparative Management Education and Behaviour) and then by topic 4 (Born Globals and International New Ventures). A key finding was the change in methodological approaches over time, with a significant increase in the use of sound quantitative and qualitative methods, instead of broad narratives mostly based on descriptive statistics. Research limitations/implications Latent Dirichlet Allocation (LDA), as a quantitative approach to analyse text data, has some limitations. LDA, along with other distributional models, may identify degrees of semantic relations between words, but is not able by itself to specify the kind of relation, entailing a possible loss of contextual information which might have been able to further assist in the study. Another limitation stems from the use of very old paper proceedings, whose quality was sometimes low, making reading difficult. Practical implications This research provides a longitudinal perspective of the evolution of the key research topics in international business over about 45 years. Its findings are very important for all those who are interested on the evolution of the IB field. Social implications The research provides an interesting perspective of the development of a scientific field as well as of a scientific community. Originality/value The main contributions of this research are fourfold. Firstly, to the best of the authors' knowledge, it provides the most complete longitudinal analysis about the evolution of IB research topics published so far. Secondly, it extracts relevant information about the evolution of the IB research issues addressed at EIBA’s annual conferences, enabling a 46-year longitudinal perspective on research interests as they emerged. Thirdly, it provides a successful application of topic modelling for the analysis of large volumes of textual data. Fourthly, it addresses the entirety of the text documents, as opposed to specific sections or keywords only, ensuring increased analytical depth.

Competitiveness Review An International Business Journal incorporating Journal of Global CompetitivenessVol. 35(1)
Rutgers, The State University of New Jersey (US), University of Lisbon (PT), University of Fribourg (CH), École Supérieure de Commerce de Rennes (FR)
Openalex Percentile: Top 9%
Computational and Text Analysis Methods
1.89
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.