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The Scottish Government hope to pilot judge only rape trials to increase the woefully low rape conviction rates in Scotland. The reasoning is that by removing jurors, the court will be attenuating the role that rape myths and other cognitive and social biases have on conviction rates. However, a plethora of research from cognitive and social psychology, legal literature and decision-making science has shown that experts, including judges and other legal professionals, may be no less biased than laypeople. This paper aims to outline the research highlighting that experts may also be biased, why biases in judges can be elicited, and potential alternative recommendations (i.e. deselecting jurors who score highly on rape myths and providing training/education for jurors). Furthermore, piloting with real judges, in real trials, may not be best practice. Therefore, the authors recommend that any piloting is preceded by experimental research.

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Furthermore, piloting with real judges, in real trials, may not be best practice; therefore, the authors recommend that any piloting is preceded by experimental research.

To the best of the authors’ knowledge, this research is the first of its kind to directly compared the decision-making of jurors and judges within the current Scottish legal context.

The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry.

Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1, consolidating the established effect.

Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent.

The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals.