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Muslimophobia, or prejudice toward Muslims, results in employment discrimination, social exclusion of Muslims, anti-Muslim hate crimes, and physical and verbal assaults, in the United States and globally. Moreover, anti-Muslim incidents are on the rise in many countries. In this chapter, we provide a review of Muslimophobia and its dynamics and consequences in the workplace. We also make suggestions for reducing prejudice toward Muslim employees, using social psychological perspectives, particularly intergroup contact theory, and research on prejudice reduction. It is also argued that leaders play an important role in the combating of Muslimophobia, including creating opportunities for personalized interactions with Muslim employees and disseminating more information about Muslims and Islam. This chapter concludes with practical implications and suggestions for future research directions. Although there is much work to be done in reducing Muslimophobia and discrimination against Muslims, social psychological research emanating from intergroup contact theory suggests that it is a viable path for researchers and practitioners to pursue.

The thin feminine body ideal in Western society has persisted, despite becoming less representative of the female population, with obesity rates consistently rising since the 1980s. Recently, the COVID-19 pandemic has exacerbated obesity rates, due to curtailed interventions, restricted mobility/enforced physical inactivity and increased reliance on processed food with a longer shelf life due to social isolation (World Obesity Foundation, n.d.). Individuals with obesity report weight discrimination in a broad range of settings, including employment, where researchers have documented weight discrimination in relation to hiring, job assignment, promotion, remuneration and work stability. Weight discrimination may be worse for jobs involving public interaction, particularly for women, because heavier women do not conform to societal body ideals, leading to weight stigmatisation such as anti-fat attitudes and beliefs (e.g. negative stereotypes) and prejudice. This chapter presents a systematic literature review of studies that have examined weight discrimination against women with obesity in jobs involving public interaction, i.e. ‘customer-facing roles’.

Digital technology has had a massive impact on business management procedures, driving modifications. The goal of this study is to figure out how human resource management (HRM) in businesses should change as digital technology develops. Via social, mobile, analytic and cloud technology, businesses can monitor and ensure that preconceptions and assumptions inside the organization drive acceptable behaviour. The outcomes of this study reveal that information transformation has influenced jobs growth, labour supply and the composition of corporate talent. Management and control in management of human resources (HR) should give way to empowerment. The goal of the current review is to examine current technological trends in HRM-related enterprises. Peer-reviewed articles from databases like EBSCO, Emerald and Sage publications provide the foundation of the review. Since there are few academic articles on the subject of the study, which covers technology in HRM and cloud in HRM, references from organizational reports have also been incorporated. Utilizing digital technologies in HR will increase organizational performance through decisions involving talent, forecasting workforce requirements and maximizing talent through planning and development. Informed decision-making will also allow HR to assist an organization in achieving corporate objectives. It also makes it possible to manage staff members through hiring, training, job happiness, productivity and task assignment based on qualifications. Additionally, it aids in determining the cause of attrition and locating high-value individuals who are departing.

The impact of appearance on career development is well-documented. We know with some certainty that those blessed with good looks, a sense of style and a winning smile have an advantage at all stages of the job application process, and throughout their careers, with the most aesthetically pleasing being more likely to be given jobs, higher salaries and promotions (Baert & Decuypere, 2014; Toledano, 2013). What then should those who offer career advice make of this? Should career advisers, coaches, HR professionals and line managers be advising their clients and employees on how to improve their looks? At one level, the answer to this question seems obvious: if the advisers know it can make a difference, of course they should try to help their clients to look more professional or better appropriate for the role, to give them every chance of success in their chosen field. But on closer inspection, this assumption is fraught with challenges. How far should the practitioners go? How can one give advice without causing offence? And most crucially, how could this tacit support of an arguably unfair and superficial value system be justified? In this chapter, I will explore some of these issues, drawing on research conducted with career advisers, counsellors and coaches and will offer some practical guidelines for all those who might find themselves tempted to offer advice.

Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.

Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.

Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.

Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.

The COVID-19 pandemic ushered in multiple challenges for employees, which led to employee turnover, disengagement at work, employees’ mental health issues, etc. The study tries to elucidate how artificial intelligence (AI) herald great promise in human resource management in decreasing cost, attrition level and enhancing productivity. Considering the dearth of studies on recent trends in human resource management (HRM) in the context of AI, the study elucidates the role of AI in facilitating seamless onboarding, diversity and inclusion (D&I), work engagement, emotional intelligence and employees’ mental health. Thus, a conceptual model of recent trends in HRM in the context of AI and its organisational outcomes is proposed. A systematic review and meta-synthesis method are undertaken. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes. The findings of the study suggest that using natural language processing (NLP) and robots has eased the onboarding process. D&I is promoted using data analytics, big data, machine learning, predictive analysis and NLP. Furthermore, NLP and data analytics have proved to be highly effective in engaging employees. Emotional Intelligence is applied through AI simulation and intelligent robots. On the other hand, chatbots, employee pulse surveys, wearable technology, and intelligent robots have paved way for employees’ mental health. The study also reveals that using AI in HRM leads to enhanced organisational performance, reduced cost and decreased intention to quit the organisation. Thus, AI in HRM provides a competitive edge to organisations by enhancing the performance of the employees.