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Collegiality is the modus operandi of universities. Collegiality is central to academic freedom and scientific quality. In this way, collegiality also contributes to the good functioning of universities’ contribution to society and democracy. In this concluding paper of the special issue on collegiality, we summarize the main findings and takeaways from our collective studies. We summarize the main challenges and contestations to collegiality and to universities, but also document lines of resistance, activation, and maintenance. We depict varieties of collegiality and conclude by emphasizing that future research needs to be based on an appreciation of this variation. We argue that it is essential to incorporate such a variation-sensitive perspective into discussions on academic freedom and scientific quality and highlight themes surfaced by the different studies that remain under-explored in extant literature: institutional trust, field-level studies of collegiality, and collegiality and communication. Finally, we offer some remarks on methodological and theoretical implications of this research and conclude by summarizing our research agenda in a list of themes.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

This study aims to develop a model of learning-by-hiring in which knowledge gains may occur at the time of recruitment but also after recruitment when other incumbent organizational members assimilate a recruit’s knowledge. The author’s model predicts that experienced recruits are more likely to catalyze change to their organization’s core technological capabilities.

The continuous-time parametric hazard rate regressions predict core technological change in a long panel (1970–2017) of US biotechnology industry patent data. The author uses over 140,000 patents to model the evolution of knowledge of over 52,000 scientists and over 4,450 firms. To address endogeneity concerns, the author uses the Heckman selection method and does robustness tests using a difference-in-difference analysis.

The author finds that a hire’s prior research and development (R&D) experience helps overcome inertia arising from her or his new-to-an-organization “distant” knowledge to increase the likelihood of core technological change. In addition, while the author finds that incumbent organizational members resist technological change, experienced hires may effectively induce them to adopt new ways of doing things. This is particularly the case when hires collaborate with incumbents in R&D projects. Understanding the effects of hiring on core technological change, therefore, benefits from an assessment of hire R&D experience and its effects on incumbent inertia in an organization.

First, the author does not recommend managers to hire scientists with considerable distant knowledge only as this may be detrimental to core technological change. Second, the author recommends organizations striving to effectuate technological change to hire people with considerable prior R&D experience as this confers them with the ability to influence other members and socialize incumbent members. Third, the author recommends that managers hire people with both significant levels of prior experience and distant knowledge as they are complements. Finally, the author recommends managers to encourage collaboration between highly experienced hired scientists and long-tenured incumbent organizational members to facilitate incumbent learning, socialization and adoption of new ways of doing things.

This study develops a model of learning-by-hiring, which, to the best of the authors’ knowledge, is the first to propose, test and advance KM literature by showing the effectiveness of experienced hires to stimulate knowledge diffusion and core technological change over time after being hired. This study contributes to innovation, organizational learning and strategy literatures.

This paper first analyses the direct effect of quality management practices (QMPs) on organisational ambidexterity (OA). It then analyses the mediating influence of the values of ambidextrous culture (AC). A novel theoretical model is tested in a quantitative study of the organic agri-food sector.

Quantitative methods and an online survey were used to collect and analyse 239 valid questionnaire responses. The data analysis method was partial least squares (PLS).

There is a relationship between QMPs and OA. AC partially mediates this link, strengthening the direct relationship between the two variables.

The proposed model is novel and creates opportunities for new lines of research. The concept of QMPs is considered in all its dimensions (processes, people, customers and suppliers). The study reaffirms the importance of the novel concept of AC in the literature. In this study, OA is defined in terms of the balanced processes of exploitation and exploration. The choice of sector is another original feature of the study.

This study aims to address this unexplored influence of international assignment types on the development, transfer and utilization of career capital by assigned repatriates from host to home country. In response to existing literature gap, it aligns with the need for qualitative case studies that delve into threats to the self-reinforcement of repatriates' career capital.

By mean of a qualitative case study, this paper deepens understanding of linkages and processes in career capital development and clarify the interplay between individual interpretations of career actions and the organizational context in which they unfold. Nineteen qualitative interviews with assigned repatriates explored the impact of exposure to new career contexts.

This study provides valuable insights into the complex dynamics of career capital development and transfer during international assignments. It elucidates the impact of career context on assigned repatriates' career capital, emphasizing challenges in career capital generation, dispersion and absorption within multinational enterprises. It contributes to understanding the complexities of (new) managerial capacity development by revealing varied effects that international assignments can exert on individuals' immediate competencies and career capital.

If the assigned expatriate/repatriate’s understanding of the firm’s assignment motive, and their own motive (understanding/reason) for the assignment corresponds then expectations of outcomes can be better managed. Organizations otherwise run the risk of perpetuating inequities in the career development opportunities of employees.

Studies on career capital emphasize its qualities or examine different globally mobile employee types. Yet there's a gap in understanding how the type of assignment impacts career capital development, transfer and utilization. This research fills this void by investigating the international transfer of career capital from host to home country specifically for assigned repatriates.

The crude oil supply chain (COSC) is one of the most complex and largest supply chains in the world. It is easily vulnerable to extreme events. Recently, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (often known as COVID-19) pandemic created a massive imbalance between supply and demand which caused significant price fluctuations. The purpose of this study is to explore the influential factors affecting the international COSC in terms of consumption, production and price. Furthermore, it develops a model to predict the international crude oil price during disease outbreaks using Random Forest (RF) regression.

This study uses both qualitative and quantitative approaches. A qualitative study is conducted using a literature review to explore the influential factors on COSC. All the data are extracted from Web sources. In addition to COVID-19, four other diseases are considered to optimize the accuracy of predictive results. A principal component analysis is deployed to reduce the number of variables. A forecasting model is developed using RF regression.

The findings of the qualitative analysis characterize the factors that influence international COSC. The findings of quantitative analysis emphasize that production and consumption have a higher contribution to the variance of the data set. Also, this study found that the impact caused to crude oil price varies with the region. Most importantly, the model introduced using the RF technique provides a high predictive ability in short horizons such as infectious diseases. This study delivers future directions and insights to researchers and practitioners to expand the study further.

This is one of the few available pieces of research which uses the RF method in the context of crude oil price forecasting. Additionally, this study examines international COSC in the events of emergencies, specifically disease outbreaks using machine learning techniques.

This essay charts an intellectual journey. Geoffrey M. Hodgson became an institutional economist in the 1980s. He explains how he discovered institutional economics and what strains of institutional thought were attractive for him. Another issue raised in this essay is how institutional researchers organize and move forward. Hodgson argues for an interdisciplinary approach, but this is not without its problems.