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Rapid urbanisation and recent shock events have reiterated the need for resilient infrastructure, as seen in the pandemic. Yet, knowledge gaps in construction robotics and human–robot teams (HRTs) research limit maximising these emerging technologies’ potentials. This paper aims to review the state of the art of research in this area to identify future research directions in HRTs able to aid the resilience and responsiveness of the architecture, engineering and construction (AEC) sector.

A total of 71 peer-reviewed journal articles centred on robotics and HRTs were reviewed through a quantitative approach using scientometric techniques using Gephi and VOSviewer. Research focus deductions were made through bibliometric analysis and co-occurrence analysis of reviewed publications.

This study revealed sparse and small research output in this area, indicating immense research potential. Existing clusters signifying the need for further studies are on automation in construction, human–robot teaming, safety in robotics and robotic designs. Key publication outlets and construction robotics contribution towards the built environment’s resilience are discussed.

The identified gaps in the thematic areas illustrate priorities for future research focus. It raises awareness on human factors in collaborative robots and potential design needs for construction resilience.

Rapid urbanisation and recent shock events have reiterated the need for resilient infrastructure, as seen in the pandemic. Yet, knowledge gaps in construction robotics and HRTs research limit maximising these emerging technologies’ potentials. This paper aims to review the state of the art of research in this area to identify future research directions in HRTs able to aid the resilience and responsiveness of the AEC sector.

Existing literature on algorithmic management practices – defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice and – as a result – workplace well-being. Literature review revealed a significant gap in empirical research on the nature and direction of these relationships. Therefore the purpose of this paper is to analyse how algorithmic management practices directly influence workplace well-being, as well as investigating its relationships with job autonomy and total rewards practices.

Conceptual model of relationships between algorithmic management practices, job autonomy, total rewards and workplace well-being has been formulated on the basis of literature review. Proposed model has been empirically verified through confirmatory analysis by means of structural equation modelling (SEM CFA) on a sample of 21,869 European organisations, using data collected by Eurofound and Cedefop in 2019, with the focus of investigating the direct and indirect influence of algorithmic management practices on workplace well-being.

This research confirmed a moderate, direct impact of application of algorithmic management practices on workplace well-being. More importantly the authors found out that this approach has an indirect influence, through negative impact on job autonomy and total rewards practices. The authors observed significant variation in the level of influence depending on the size of the organisation, with the decreasing impacts of algorithmic management on well-being and job autonomy for larger entities.

While the influence of algorithmic management on various workplace practices and effects is now widely discussed, the empirical evidence – especially for traditional work contexts, not only gig economy – is highly limited. The study fills this gap and suggests that algorithmic management – understood as an automated decision-making vehicle – might not always lead to better, well-being focused, people management in organisations. Academic studies and practical applications need to account for possible negative consequences of algorithmic management for the workplace well-being, by better reflecting complex nature of relationships between these variables.

This paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.

The current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.

We highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers' fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfilment expectations with their AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as facilitating environment, training opportunities and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.

Our paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.

Exoskeletons are mechanical structures that humans can wear to increase their strength and endurance. The purpose of this paper is to explain how exoskeletons can be used to improve performance across five phases of manufacturing.

Multivocal literature review, encompassing scientific literature and the grey literature of online reports, etc., to inform comprehensive, comparative and critical analyses of the potential of exoskeletons to improve manufacturing performance.

There are at least eight different types of exoskeletons that can be used to improve human strength and endurance in manual work during different phases of production. However, exoskeletons can have the unintended negative consequence of reducing human flexibility leading to new sources of musculoskeletal disorders (MSD) and accidents.

Findings are relevant to function allocation research concerned with manual production work. In particular, exoskeletons could exacerbate the traditional trade-off between human flexibility and robot consistency by making human workers less flexible.

The introduction of exoskeletons requires careful health and safety planning if exoskeletons are to improve human strength and endurance without introducing new sources of MSD and accidents.

The originality of this paper is that it provides detailed information about a new manufacturing technology: exoskeletons. The value of this paper is that it provides information that is comprehensive, comparative and critical about exoskeletons as a potential alternative to robotics across five phases of manufacturing.

A growing body of literature shows how intragenerational occupational mobility affects economic dynamics and social stratification. In this article the authors aim to carry out a structured review of this literature, outlining a systemic overview for more comprehensive research and public policies.

The authors use methods from structured literature reviews and network science to reveal the segmented research landscape of occupational mobility literature. The authors made an in-depth analysis of the most important papers to summarize the main contributions of the literature and identify research gaps.

The authors reveal a segmented research landscape around three communities: (1) human capital theory, (2) social stratification theory and (3) migration studies. Human capital research uses microfounded mathematical modeling to understand the relationship between skills and mobility. Nevertheless, it cannot explain social segregation and generally does not focus on the importance of local labor demand. Social stratification research can explain the social and institutional barriers to occupational mobility. Migration research studies the relationship between migration, labor demand and social mobility.

This paper is the first literature review that uses network analysis to perform a systematic review of the intragenerational occupational mobility literature. Moreover, this review identifies opportunities for mutual learning and research gaps in the research landscape.

The purpose of this paper is to investigate the intended and unintended consequences of compliance and auditing pressures in the Bangladeshi garment industry. To explore this issue the authors draw on three medium-sized suppliers. The institutional changes that followed the Rana Plaza accident in April 2013 make Bangladesh in general and the garment industry in particular an interesting and suitable research setting for standards compliance.

The study adopts a multiple case study approach. Face-to-face interviews have been conducted with the owners of three Bangladeshi garment manufacturing firms and several workers. Additionally, organisational documents and local newspaper articles had been collected wherever possible.

The results indicate that the pressure for compliance has led the case companies to prioritise the implementation of measurable standards over the socially grounded needs and priorities of workers. As a consequence certain initiatives instead of adding new social value in fact destroyed previously existing social value. Furthermore, the pressure for compliance created the necessity to find ways to cover the sizable cost of compliance. This prompted firms to pursue process upgrading through technological advancements and increased work pressures on the labour force. These initiatives led to an increased power imbalance and the exclusion of unskilled workers from the job market.

The paper contributes to the understanding of the human rights implications of compliance and auditing pressures and initiatives. Furthermore, in order to further enrich existing knowledge in the critical accounting literature, the study draws on insights from the global value chains (GVC) and international business (IB) literatures.

The paper contributes to the understanding of the human rights implications of compliance and auditing pressures and initiatives. Furthermore, in order to further enrich existing knowledge in the critical accounting literature, the study draws on insights from the GVC and IB literatures.

The purpose of this paper is to analyze the conceptual framework about human resources downsizing and restructuring and how organizations of the public sector can do that effectively and efficiently. These facts drive to the conclusion that the implementation of early retirement incentives requires the most elaborate planning and execution to be effective, predictable and safe in the long term.

This paper adopts an analytical, descriptive methodology approach to describe the basic features of the data by using the descriptive research design. Data have been collected through different sources, which include secondary data, to introduce the theoretical literature of the subject as books, journals, articles, published working papers and referred previous studies related to the same subject.

Downsizing process is a deliberate administrative process that includes, but is not limited to, workforce reduction and is primarily aimed at achieving efficiency in public organizations. The definition of workforce downsizing may be narrowed to reducing the number of workers, or more likely to refer to general efforts to restructuring human resources in public organizations, Early Retirement Incentive Programs (ERIP) represents a viable alternative for organizations seeking to reduce staff. For the ERIP to be successful, the program coordinator must understand the business objectives and goals that the organization is trying to obtain.

Human resources strategies concerning downsizing public administration workforce should be more appropriate to those who leave the organization and those who stay at work, reducing the negative psychological, administrative and economical effects. This could be achieved through a strategy called early retirement incentive programs.

According to Sen's theoretical framework of capability (1985), individuals reach their full potential once they have the freedom, intended as the set of functionings at their disposal, to do so. However, many critiques have been developed against the lack of embeddedness of the capability approach in social and political relations and structures. In this article, the authors investigate the influence of three institutional contexts (Belgium, the Netherlands and France) on the respective work-related functionings of self-employed and regular workers, with a focus on human capital investment and institutional support offered to them.

Data from the European Working Conditions Survey (EWCS) are used to highlight similarities and differences in building work-related functionings for regular and self-employed workers. A regression analysis is provided at the country level.

In the three labour markets, the authors find that the building of work-related functionings is more successful for regular employees, especially as regards institutional support. Self-employed workers, on the other hand, need to rely on their individual capability as regards employment protection and human capital investment. However, the authors find interesting differences between the three institutional contexts. In both Belgium and France, self-employed workers are subject to higher instability in terms of changes in salary and hours worked, whereas atypical work is better positioned in the Dutch labour market. The Netherlands is also characterised by a less significant gap between regular and self-employed workers with respect to participation in training.

In this article, the authors contextualise Sen's (1985) theoretical framework by taking into account the institutional differences of labour markets. In particular, the authors provide a novel application of his capability approach to regular and self-employed workers in an economically relevant European area.

This paper aims to demonstrate how the new generative artificial intelligence (AI) tool ChatGPT changes knowledge work for individuals and what are the implications of this change for companies.

Based on 22 interviews from informants across different industries, the authors conducted an inductive analysis on the use and utility of ChatGPT in knowledge work. Based on this initial analysis, they discovered different ways in which ChatGPT either augments human agency, makes it redundant or lacks capability in that regard.

The authors develop a 2 × 2 framework of algorithmic assistance, which demonstrates four ways in which ChatGPT (and generative AI in general) interacts with knowledge workers, depending on the usefulness of ChatGPT in particular tasks and the type of the task (routine vs creative).

Based on the insights from the interviews, the authors propose a set of actionable questions for individual knowledge workers and companies from four viewpoints: skills and capabilities; team structure and workflow coordination; culture and mindset; and business model innovation.

To the best of the authors’ knowledge, this study is among the first to identify and analyze the use of ChatGPT by knowledge workers across different industries.