Institutt for kommunikasjon og kultur

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

Emerging Markets Case Studies (EEMCS) 16(3) s. 1-14 Doi: https://doi.org/10.1108/eemcs-11-2025-0747

This case study is set at TokyoLife, a retail chain operating in the fashion and lifestyle sector in Vietnam. Between 2018 and 2025, the company developed and implemented the Angel Project, an initiative focused on integrating people with disabilities into its workforce through structured recruitment, training and workplace support. The initiative expanded from a small factory pilot to selected retail stores and later the House of Angels stores staffed primarily by disabled employees. HongHanh Nguyen, Chief Happiness Officer at TokyoLife, led the design and implementation of the model. By 2025, external organizations had expressed interest in replicating the approach, yet few were able to adopt it successfully. HongHanh now faced a dilemma: how to strategically scale the Angel employment model beyond TokyoLife in a way that ensures impact, feasibility and sustainability, while maintaining the core values that defined its success. Students are asked to advise HongHanh, using knowledge of strategic management and social innovation to analyze the pathway for broader adoption and address the dilemma.

Nature Human Behaviour Doi: https://doi.org/10.1038/s41562-026-02525-1

Abstract Experts widely agree that East Asian cultures are more collectivistic than Western cultures. Yet 76 survey studies found no reliable difference. Our explanation is that the most-used surveys are contaminated with ‘warm fuzzy’ items, which describe warmth and prosociality towards everyone near and far. We argue that collectivism is better understood as ‘responsibilism’, which emphasizes responsibilities in close relationships. A survey found that many cultural psychologists expect collectivistic cultures to agree with warm fuzzy items. Then we developed a responsibilism scale and tested 12,247 people in 100 cultures. Results showed large cultural differences ( d  = 3.98 [2.50, 5.43]) that were previously obscured by flawed measurement. Responsibilism predicted differences across societies (such as family ties and corruption) and individuals (social class and politics) that most earlier scales missed. This study offers a solution to previous puzzling findings by distinguishing warm fuzzy prosociality from responsibilism and introducing a scale with stronger predictive validity.

Visual Pedagogies for the Early Years. Presence, Potential, and Possibility. s. 259-274

Visualisation in digital technology affects learning, education, and being. Multisensory engagement in digital reading, especially in the early years, enhances learning by involving visual, auditory, haptic, and olfactory senses. Recent studies highlight the potential of olfaction to enrich digital reading experiences because of the close links between smell, memory, emotions, and comfort, even in very young children. This chapter is based on my experiences of reading digital books featuring smell to children. The study is part of a project titled Coming Back to Our Senses to Transform Children’s Digital Reading. The study participants are 65 children four and five years of age from five early years settings in southeast Norway. The three main topics I cover in this chapter are (i) visual senses enlivened through smell in digital book reading; (ii) how I, as a researcher, used my senses when collecting data for the digital book reading experiment; and (iii) possibilities of including smell in future visual pedagogies in the early years.

Computers in Human Behavior Reports 24 s. 1-25 Doi: https://doi.org/10.1016/j.chbr.2026.101285

Partisan news media erode cross-partisan trust, but large language models (LLMs) offer a potential means of debiasing such content at scale. Across two pre-registered experiments, we tested whether LLM-generated debiasing of liberal news headlines could improve conservative readers' trust-relevant judgments. Study 1 found that subtle lexical debiasing (replacing emotive words with moderate synonyms) had no effect on any outcome. Study 2 found that a more substantive reframing intervention significantly increased conservatives' perceived trustworthiness, completeness, and willingness to engage with liberal news headlines, without producing a backfire effect among liberals. In Study 1, the intervention produced robust effects across silicon participants simulated with six different models (o3-mini, o3, GPT-4o mini, GPT-4o, GPT-5 mini, and GPT-5), whereas it had no impact on human readers. In Study 2, the intervention's effects among silicon participants generally aligned directionally with human responses but were significantly larger for some outcomes, and three models (o3, GPT-4o mini, and GPT-4o) incorrectly predicted a liberal backfire effect absent in humans. Moderation analyses tentatively suggest that the models' implicit theory of who responds to debiasing diverged from the psychological profile that actually predicted human responsiveness. Most strikingly, in Study 2, participants simulated by each of the six models suggested that debiasing effects would be stronger among participants high in political in-group identification. Yet, no such moderation was observed among human participants. Collectively, these findings suggest that LLM-based debiasing can improve cross-partisan receptivity when the intervention targeted ideological framing but not when it was limited to the minimal surface-level substitutions tested in this research — and that current models lack both the quantitative accuracy and qualitative psychological fidelity to evaluate their own interventions without human oversight.