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This work critically investigates online fan responses towards the implementation of the affirmative action policy, the Rooney Rule, within English professional football. It explores systemic and structural racism and the history of the Rooney Rule, before analysing football fans' Twitter comments concerning the policy within English football across an 18-month period.

This research utilised a bespoke search programme to identify and analyse Tweets which focused on the Rooney Rule in English football. A total of 205 posts were thematically analysed and a series of codes were created.

The findings illustrated that fans were generally divided over the Rooney Rule. Over half of the participants welcomed counter measures against structural racism although many caveated responses by critiquing the Rule's approach and scope. For others, however, the policy is yet another example of ‘reverse racism’ and ‘political correctness gone mad’. The findings illustrate that there is an undercurrent of hostility towards anti-racist action and a belief that sport is inherently meritocratic and fair.

While much research has focused on examining online reactions to ‘trigger events’, this chapter provides an empirical insight into contemporary football fan responses towards anti-racist action in the ‘beautiful game’. It demonstrates that there are a series of common misconceptions and misunderstandings towards affirmative action policies in sport. Once we become aware of such misunderstandings, we can attempt to remedy them in order to aid the efficacy of anti-racist action.

The main objective of this chapter is broadening the understanding of anthropomorphic artificial intelligence (AI) (e.g. avatars, humanoid robots, chatbots) in both physical and digital environments. The chapter strives to demonstrate how organisations can curate relationship marketing and enhance customer experience by employing anthropomorphic AI. To achieve this, the chapter extends existing understanding in three ways. First, it explains the interconnectivity between relationship marketing and customer experience. Second, it presents anthropomorphic AI along with its different characteristics and technologies. Third, it offers some real-life uses cases and examples of such AI drawing from practical insights into five selected industries. Overall, the chapter provides some food of thoughts concerning the successful application and deployment of anthropomorphic AI in marketing practices.

The paper sets forth and examines the assumptions underlying two global ideas – world class and best practices – and their application to (higher) education and health organizations. Our basic (ex-ante) assumption is that both sectors are influenced by organizational fields that embody these ideas. However, we also assume that these sectors differ, and thus, that one should find between sector variations in the influence of such ideas. The findings suggest that both sectors have been affected by hegemonic ideas, yet in rather different ways, and that these ideas, particularly the metrics being used, pose different challenges in the two sectors.

Purpose – The aim of this study is to determine the impact of feeling bored on managers' decision-making in the digital age under conditions of increased uncertainty by examining the role of personality trait openness and empirically testing such relationships within the context of retail middle managers.

Design/methodology/approach – Feeling bored was defined within a broader Decision-Making Process Model, which included the personality trait openness. An empirical study with retail middle managers was conducted to examine the relationships between feeling bored and decision-making competence (DMC). Regression models were fit to test whether feeling bored affects DMC and whether the associations were moderated by personality trait openness.

Findings – In the relationship between feeling bored and DMC, the moderating role of the personality trait openness was established. Results showed that feeling bored has a significant negative association with middle managers' confidence levels and risk perceptions when making decisions. Results also provided evidence that the learning component of personality trait openness plays a moderating role in the relationship between feeling bored and DMC. Most notably, the learning component of personality trait openness neutralizes the negative effects of feeling bored on managers' ability to remain appropriately confident when making decisions. In addition, the learning and inquisitive components temper the positive association between mood excited and risk perceptions. Limitations to the study are outlined.

Practical implications – Since trait openness (specifically its learning component) benefits decision-making contexts, it makes trait openness a worthy criterion to include when screening aspirant retail middle managers. The benefits of trait openness (specifically its learning component) for middle managers and their teams (especially when they are feeling bored) are indicated, since learning neutralizes the negative effect feeling bored has on appropriate confidence levels in retail management decision-making contexts.

Scientific research provides a reliable means for developing and accumulating knowledge bases to guide policy and practice. However, evidence from meta-research and large-scale replication projects suggests that the published research base likely reflects bias, which threatens the validity and credibility of research-based recommendations. Moreover, there is limited accessibility to research reports, which limits the impact and application of scientific research. In this chapter, we propose that open-science reforms, which aim to make the research process as open and transparent as possible, can be applied to help address these issues. We describe and discuss four open-science practices – preregistration and Registered Reports, open data and materials, open peer review, and open access and preprints – and propose that they may become one of the next big things in special education research.