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Two different systems for streaming patients were considered to improve efficiency measures such as waiting times (WTs) and length of stay (LOS) for a current emergency department (ED). A typical fast track area (FTA) and a fast track with a wait time threshold (FTW) were designed and compared effectiveness measures from the perspective of total opportunity cost of all patients’ WTs in the ED. The paper aims to discuss these issues.

This retrospective case study used computerized ED patient arrival to discharge time logs (between July 1, 2009 and June 30, 2010) to build computer simulation models for the FTA and fast track with wait time threshold systems. Various wait time thresholds were applied to stream different acuity-level patients. National average wait time for each acuity level was considered as a threshold to stream patients.

The fast track with a wait time threshold (FTW) showed a statistically significant shorter total wait time than the current system or a typical FTA system. The patient streaming management would improve the service quality of the ED as well as patients’ opportunity costs by reducing the total LOS in the ED.

The results of this study were based on computer simulation models with some assumptions such as no transfer times between processes, an arrival distribution of patients, and no deviation of flow pattern.

When the streaming of patient flow can be managed based on the wait time before being seen by a physician, it is possible for patients to see a physician within a tolerable wait time, which would result in less crowded in the ED.

A new streaming scheme of patients’ flow may improve the performance of fast track system.

Overcrowding in emergency departments (EDs) leads to longer waiting times and results in higher number of patients leaving the ED without being seen by a physician. EDs need to improve quality for patients’ waiting time and length of stay (LoS) from the perspective of process and flow control management. The paper aims to discuss these issues.

The retrospective case study was performed using the computerized ED patient time logs from arrival to discharge between July 1, 2009 and June 30, 2010. Patients were divided into two groups either adult or pediatric with a cutoff age of 18. Patients’ characteristics were measured by arrival time periods, waiting times before being seen by a physician, total LoS and acuity levels. A discrete event simulation was applied to the comparison of quality performance measures.

Statistically significant differences were found between the two groups in terms of arrival times, acuity levels, waiting time stratified for various arrival times and acuity levels. The process quality for pediatric patients could be improved by redesign of patient flow management and medical resource.

The results are limited to a case of one community and ED. This study did not analyze the characteristic of leaving the ED without being seen by a physician.

Separation of pediatric patients from adult patients in an ED can reduce the waiting time before being seen by a physician and the total staying time in the ED for pediatric patients. It can also lessen the chances for pediatric patients to leave the ED without being seen by a physician.

A process and flow control management scheme based on patient group characteristics may improve service quality and lead to a better patient satisfaction in ED.

This article argues that critical realism (CR) offers an ontological position suited to understanding the dynamic relations between multinational companies (MNCs) and the complex political spaces within which they operate. After outlining the core assumptions of CR, the key arguments are elaborated through two case studies which focus on issues of staffing and expatriation. The first case concerns recent developments in the Middle East, highlighting the shifting reality of nationality-based definitions of staffing the MNC, and the second examines the internationalisation of Chinese firms, exploring the way MNCs restructure space to retain access to home-country advantages.

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.

Looks at the 2000 Employment Research Unit Annual Conference held at the University of Cardiff in Wales on 6/7 September 2000. Spotlights the 76 or so presentations within and shows that these are in many, differing, areas across management research from: retail finance; precarious jobs and decisions; methodological lessons from feminism; call centre experience and disability discrimination. These and all points east and west are covered and laid out in a simple, abstract style, including, where applicable, references, endnotes and bibliography in an easy‐to‐follow manner. Summarizes each paper and also gives conclusions where needed, in a comfortable modern format.

Various forms of precarious employment create barriers to the integration and inclusion of migrant workers in receiving countries. The purpose of this paper is to review extant research in employment relations and management to identify key factors that contribute to migrant workers' precarious employment and highlight potential avenues for future research.

The authors conducted a narrative literature review drawing on 38 academic journal articles published between 2005 and 2020.

The authors’ review suggests that macro- and meso-level factors contribute to the precarious employment conditions of migrant workers. However, there is a limited articulation of successful practices and potential solutions to reduce migrant work precarity and exclusion. The literature on migrant workers' precarious employment experience is primarily focused on low-skilled sector (e.g. agriculture, hospitality, domestic care) jobs. In addition, few studies have explored the role of worker characteristics, such as gender, class, ethnicity, race and migration status, in shaping the experience of migrant workers in precarious employment.

The results of this research highlight the importance of engaging multilevel actors in addressing migrant employment precarity, including policymakers, employers and employment agencies.

This research contributes to a growing conversation of migrant employment precarity by highlighting the heterogeneity of migrant groups and calling for the use of intersectional lenses to understand migrant workers' experiences of precarious employment.