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The job of ding man is very highly skilled: it contains a large number of advanced sensori‐motor skills and much decision‐making. For many years different car‐builders have wrestled with the training of this key worker, for a long time without success. Ray Basey, Skills Analyst at Fords, Dagenham, has studied this job in depth and developed highly effective training in it. His article is a study in how to approach the business of training for complex manual skills.

The victim’s rights movement and restorative justice (RJ) have gained momentum around the world. More laws and policies have focused on crime victims and their families. Western literature suggests that the victim’s family suffers physical, emotional, and financial tolls and that the power of the victim’s family in pursuing justice for their loved ones remains limited. This is particularly concerning within the political and legal context of the abolitionist movement, innocence project, and human rights groups’ campaigns against police torture. Grounded in the perspectives of RJ and Chinese legal culture, this study examines the victim’s family, represented by Ding and senior Yu, of the Nian Bin capital murder case. Drawing on published reports and using the thematic content analysis method, this study examines the following aspects of victim’s family in a death penalty case: 1) victim family’s physical, emotional, and financial tolls; 2) victims’ family and the criminal justice system; 3) victims’ family and the media; and 4) the relationship between the victims’ and the accused’s families. This study concludes with discussions of the competing goals of families impacted by a crime and RJ practices that would help mitigate the loss of the victim’s family and enhance their confidence in the criminal justice system.

Enterprise social media (ESM) are frequently used in enterprises for daily operation. Although many researchers have attempted to understand the antecedents and consequences of ESM use, the integrated model, boundary conditions and mechanism of the impact of ESM use on performance are still unclear. This study fill this research gap by adopting a grounded theory approach to study how ESM use affects employee performance.

Choosing representative cases, the authors collected interview data and analyzed the data using open coding, axial coding and selective coding.

The results showed four main categories including ESM use, work efficiency, emotional maintenance and work performance, as well as 14 sub-categories. This paper also constructs a model of the impact of ESM use on work performance. In addition, results showed that ESM use affects employees' work performance through work efficiency and emotional maintenance, and frequency of use and individual characteristics may moderate this process.

This study’s results contribute to the existing ESM literature by finding the integrated model, boundary conditions and mechanism of the impact of ESM use on performance. The authors also contributed to the social media literature by finding 14 sub-categories and four main categories including ESM use, work efficiency, emotional maintenance and work performance. The conclusion of this paper provides guidance and reference for the use and management of internal social media in enterprises.

The purpose of this paper is to study the identification methods for multivariable nonlinear Box‐Jenkins systems with autoregressive moving average (ARMA) noises, based on the auxiliary model and the multi‐innovation identification theory.

A multi‐innovation generalized extended least squares (MI‐GELS) and a multi‐innovation generalized ex‐tended stochastic gradient (MI‐GESG) algorithms are developed for multivariable nonlinear Box‐Jenkins systems based on the auxiliary model. The basic idea is to construct an auxiliary model from the measured data and to replace the unknown terms in the information vector with their estimates (i.e. the outputs of the auxiliary model).

It is found that the proposed algorithms can give high accurate parameter estimation compared with existing stochastic gradient algorithm and recursive extended least squares algorithm.

In this paper, the AM‐MI‐GESG and AM‐MI‐GELS algorithms for MIMO Box‐Jenkins systems with nonlinear input are presented using the multi‐innovation identification theory and the proposed algorithms can improve the parameter estimation accuracy. The paper provides a simulation example.

This study investigated the relationship of strengths-based leadership with nurses’ turnover intention and the mediating roles of job crafting and work fatigue in the relationship.

Data comprising 318 valid participants from three hospitals in Beijing were gathered at two points in time, spaced by a two-month interval. Structural equation modeling with a bootstrapping analysis was applied to test hypotheses.

This study found that strengths-based leadership negatively relates to nurses’ turnover intention, and job crafting and work fatigue mediate the relationship of strengths-based leadership with turnover intention, respectively.

The findings of this study highlight the importance of strengths-based leadership in decreasing nurses’ turnover intention and reveal two potential mechanisms through which strengths-based leadership is related to nurses’ turnover intention. In order to retain nursing staff better, nurse leaders should execute more strengths-based leadership behaviors and make more efforts to promote nurses’ job crafting and to reduce nurses’ experience of work fatigue.

Drawing on conversation of resources theory, the present paper aimed to investigate the effect of strengths-based leadership on follower career satisfaction and the mediating role of follower strengths use as well as the moderating role of emotional exhaustion in the relationship.

Research data were gathered at 3 time points with a sample of 210 participants working in various organizations in China. Structural equation model (SEM) was applied to examine the authors' hypotheses.

The results indicated that strengths-based leadership has a positive impact on follower career satisfaction and follower strengths use fully mediates the effect of strengths-based leadership on follower career satisfaction. More importantly, emotional exhaustion enhanced the direct relationship between strengths use and career satisfaction and the indirect association of strengths-based leadership with follower career satisfaction through follower strengths use.

The main limitation of the present paper was the single source of research data.

The present paper advances strengths-based leadership theory and research and provides a new insight into cultivating employee career satisfaction.

Based on the governing equations of magneto‐electro‐elastic media, the general solutions in the case of distinct eigenvalues and is introduced and expressed in four harmonic functions. Then, the Green’s functions for point forces, point charge and point current acting in the interior of a two‐phase infinite magneto‐electro‐elastic plane in the case of distinct or multiple eigenvalues are given using the method of mirror image source.

This paper examines radical reform of the Chinese public accounting profession in the 1990s. In particular, the paper seeks to provide a more nuanced understanding of the sources, responses and processes of this radical institutional change that effectively paved the way for development of the Chinese accounting profession into the twenty-first century.

The empirical data that inform this study come from both archival materials (mostly in Chinese) and in-depth interviews. These data are analysed and interpreted from a neo-institutionalist perspective, drawing, in particular, on the concept of institutional logics and the concept of institutional work.

A state logic initially guided the development of the Chinese accounting profession but was seriously challenged in the 1990s following a series of high profile financial scandals. The findings reveal a shift to a new professional logic, which was made possible through multiple forms of institutional works instigated by various state actors.

Research into the radical reform of the Chinese public accounting profession in the 1990s was mostly quantitative in nature, focussing mainly on one reform programme, i.e. the disaffiliation of the accounting firms from their sponsoring agencies. This paper adopts a qualitative approach and is aimed at providing a deeper and more nuanced understanding of the institutional change process within its political and economic contexts.

Managing diverse talents has become a necessary part of the human resource management of contemporary organizations. The growing diversity of organizations' workforce makes companies reassess their conventional HRM approaches. State-owned enterprises get the increasing attention of talent management scholars since state firms enthusiastically compete for talents. These companies have some particularities that distinguish them from private firms, and there is a need to analyse the existing research on the HRM in state companies which has the potential to add a missing part to the puzzle of managing diverse talents. We study the major topics in the literature on human resource management and talent management in state-owned enterprises, the key findings researchers provide and the gaps in the literature that need to be covered and the resulting research directions for future studies.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.