Department of Communication and Culture

Journal of Retailing and Consumer Services 94 p. 104981-104981 Doi: https://doi.org/10.1016/j.jretconser.2026.104981

Cambridge University Press Doi: https://doi.org/10.1017/9781009590297

This Element focuses on interactions between international assignees (IAs) and host country nationals (HCNs) by synthesizing three decades of empirical research using a combination of bibliometric, thematic, and content analyses. It delineates three major research streams in the field: language and communication; cultural adjustment; and IA-HCN relationships. Utilizing innovative mixed-methods review and analytical techniques, we shed light on the effects of language, communication, and cultural issues on IAs' and HCNs' adjustment, performance, learning, and career development. This Element reveals mixed effects of IA-HCN interactions, calling for further research to contribute to a more comprehensive understanding of IA-HCN interactions. It offers valuable insights into effective cultural adjustment strategies and guides the development of practices for managing international assignments and cultivating positive IA-HCN relationships.

SocArXiv Doi: https://doi.org/10.31235/osf.io/cjkwy_v1

The emergence of coordinated autonomous AI agents is fundamentally altering human belief systems and public discourse at scales and speeds that outpace existing characterization methods. This paper argues that AI swarm intelligence, the coordinated influence of autonomous agents on human populations, represents a phase shift that cannot be understood by simply scaling single-agent analysis. Instead, it must be analyzed as a sociotechnical system where societal impact emerges from the tight coupling of individual agent capabilities, multi-agent coordination, and population dynamics. Because the shift from single- to multi-agent systems corresponds to a psychological transition between single- and multiple-source influence, we propose a unified framework and evaluate these systems across operational, individual, and population-level dynamics. We identify concrete research agendas and call on the community to build the evaluation methods, countermeasures, and governance approaches needed to address the long-term societal impact of these coordinated autonomous AI populations.AI assistance disclosure: Claude (Anthropic) was used solely to polish the language of the manuscript. No other AI assistance was used.

BI Business Review

A study of 22 996 people across 42 countries and 30 languages shows that subtle language interventions alone are not enough to fix gender stereotypes in politics.

Journal of Business Research 218 Doi: https://doi.org/10.1016/j.jbusres.2026.116573