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Cultural friction (CF) was introduced by researchers to overcome the issues and challenges of cultural distance measurement in the context of cross-border mergers and acquisitions (CBMAs). However, this construct has proved itself to be problematic to operationalize. To address this challenge, this paper aims to elaborate on a CF measurement instrument based on individual perceptions in CBMAs. This study used a microfoundation approach to measure CF, relying on managers’ interactions in CBMA settings.

To develop and validate a CF measurement in the context of CBMAs, this study followed a classical procedure including items development, lab tests and one field-study and an assessment of the construct validity.

The final instrument developed for measuring CF is composed of six critical incidents with three associated items each. The factor analysis revealed that the scale used in the field-test measures two factors of CF: internal and external. Reliability and discriminant validity are tested, demonstrating a good discriminant validity of “external” CF. The final measurement can be used as a valid and reliable scale in further studies to assess CF in the context of CBMAs.

This paper’s originality lies in developing and validating a CF measurement instrument that does not rely on cultural distance frameworks. The resulting scale shows the interest in considering micro-individual perceptions – the microfoundation level – for analyzing an organizational phenomenon as culture in CBMA contexts. Using a micro-founded approach, this study offers promising avenues for researchers who wish to study cultural interactions in international settings.

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.

The analysis was carried out drawing on topic modelling, a machine-learning statistical solution that is capable of processing large volumes of text data.

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.

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.

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.

The research provides an interesting perspective of the development of a scientific field as well as of a scientific community.

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.

We empirically assessed the antecedents of subjective well-being at work for French permanent employees.

The methodology includes qualitative and quantitative data analyses. In the first phase, interviews elicited the antecedents of subjective well-being at work among permanent French employees. In the second phase, a questionnaire survey was used to confirm the relevance of the antecedents uncovered in the first phase.

We found 14 distinct elements that influence French employees’ subjective well-being at work: corporate culture, job dissonance, relationships with colleagues, achievement, professional development, relationships with superiors, status, workload, perks, feedback, workspace, diversity and pay. Moreover, we identified discrete antecedents for the three components of subjective well-being at work: work achievement and relationships with superiors and colleagues for positive emotions at work, job dissonance and workload for negative emotions at work and organizational culture and professional development for satisfaction with one’s work.

The original contribution of this study is to have unpacked the black box of the antecedents of subjective well-being in the French workplace and to have uncovered discriminant predictors for each of the three components of subjective well-being at work. Furthermore, we specifically linked each of these three components with their most significant antecedents.