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While the economic literature mostly tackled discrimination looking at labour costs, this work focuses on its relation to labour productivity, arguing that discrimination may worsen the performance of female employees. In this view, it represents a source of allocative inefficiency, which contributes to reducing output.

Female discrimination is both a social and an economic problem. In social terms, consolidated gender stereotypes impose constraints on women’s behaviour, worsening their overall well-being. In economic terms, women face generally worse labour market conditions. Using long-run Italian data spanning from 1861 to 2009, the authors propose a novel measure of female discrimination based on the observed frequency of discriminating epithets. Following social capital theory, the authors distinguish between structural and voluntary discrimination, and use Data Envelopment Analysis for time series data to assess the extent of inefficiency that each component of discrimination induces in the production process.

The results draw the trajectory of female discrimination in Italy and provide evidence in favour of the idea that female discrimination reduces productive efficiency. In particular, the structural component of female discrimination, although less sizeable than the voluntary component, plays a major role, especially in recent years, where more stringent beauty standards fuel looks-based discrimination.

The contribution of this work is twofold. First, based on contributions from social sciences different from economics, it proposes a novel theoretical framework that explores the effect of discriminatory language on labour productivity. Second, it introduces a novel and direct measure of female discrimination at the country level, based on the bidirectional link between language and culture. The indicator is easily understood by policymakers and may be used to evaluate the effectiveness of anti-discrimination policies.

We conceptualized the novel phenomenon of COVID-induced virtual teams and its implications and provided researchers with the required information on how to conduct a phenomenon-based study for conceptualizing novel phenomena in relevant ways.

This article stems from phenomenon-based and, thus, theory-building and grounded qualitative research in the German industrial sector. We conducted 47 problem-centered interviews in two phases (February–July 2021 and February–July 2022) to understand how team members and team leaders experienced COVID-induced virtual teamwork and its subsequent developments.

Empirically, we found COVID-induced virtual teams to be characterized by a high relevance of shaping positive team dynamics via steering internal moderators; crisis is a novel external moderator and transformation becomes the key output factor to be leveraged. Work-from-home leads to specific configuration needs and interrelations between work-from-home and on-site introduce additional dynamics. Methodologically, the phenomenon-based approach is found to be highly suitable for studying the effects of such novel phenomena.

This article is explorative. Thus, we advocate further research on related novel phenomena, such as post-COVID-hybrid and work-from-home teams. A model of how to encourage positive dynamics in post-COVID-hybrid teams is developed and lays the groundwork for further studies on post-COVID teamwork. Concerning methodology, researchers are provided with information on how to conduct phenomenon-based research on novel phenomena, such as the COVID-induced virtual teams that we studied.

Companies receive advice on how to encourage positive dynamics in post-COVID teamwork, e.g. on identifying best practices and resilient individuals.

In a country such as Germany that faces labor shortages, our insights might facilitate better labor-market integration for those with care-work obligations and international workers.

We offer a first conceptualization of a relevant novel phenomenon, namely COVID-induced virtual teams. We exemplify the phenomenon-based approach as a suitable methodology that serves to build relevant theory using active categorization.

Small business owners require objective solutions to deal with threats of labour unionisation. This study aims to centre on a novel exploration for improving the leadership acumen of small business owners to address labour unionisation. Specifically, small business owners need a theoretical framework that uses best practices from human resource management (HRM) and industrial relations to provide solutions.

The design, methodology and approach reflect post-modernist epistemological and ontological perspectives for conducting systematic literature reviews. A systematic literature review revealed the relationship between small business owners’ leadership, positive industrial relations and HRM policies and procedures. To identify relevant studies in the review, the utilisation of several databases (EBSCO Database, including PsycINFO and Psych studies; Web of Science) and a mix of ranked journals from entrepreneurship, human resources, leadership and organisational behaviour.

The findings and results in this paper reflect the purpose, methodology and literature analysis culminating in 162,132,000 peer-reviewed studies. A total of 142 peer-reviewed studies met criterion for review. For example, the purpose of this review focused on labour unionisation mitigation for small businesses and HRM solutions. In doing so, the methodology allowed for identification of a novel research topic (i.e. how small business owners mitigate labour unionisation) worthy of further investigation. The sparse findings on labour unionisation mitigation represent small business owners' reticence in creating HRM policies and procedures.

This study contributes research implications for theory and practice by offering small business owners a theoretical framework to address labour unionisation. The framework, centring on HRM solutions, is grounded in social exchange theory to address the novel topic of labour unionisation mitigation in small businesses. This study results suggest that HRM solutions for small business owners provide competitive advantages for employee job satisfaction through a holistic industrial relations approach. In future research, examining other issues discussed in this study can influence the understanding of the relationship between small business owners and industrial relations to increase employee job satisfaction.

The introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.

A systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.

Based on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.

The findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.

The authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

The paper takes the lead from Forsgren and Yamin (2022), “The MNE as the ‘crown of creation’?: A commentary on mainstream theories of multi-national enterprises”, and accepts that the MNE can, indeed, be seen as the “crown of creation” in the world of business. The purpose of the paper is to show that this is due to advantages of multi/transnationality that must be sought outside rather than within the firm itself.

The paper argues that the advantages of multi-nationality derive from the differences in regulatory regimes between nation-states and, specifically, from laws and regulations regarding the following: labour and social security, industrial policy, taxation and environmental regulations. Some examples are given.

It is claimed that the transnational company (TNC) has the ability to operate as a unified centre of strategic decision-making, and this gives it an advantage compared to operators it bargains with who do not possess such ability. Three such operators are discussed: labour, governments of nation-states and suppliers. In TNCs’ operations with foreign countries, a distinction is made between the spatial dimension and the regulatory regimes dimension. The interaction between these two dimensions leads to discussions on: regions within nation-states and their regulatory regimes, global value chains (GVCs) and free/investment zones (F/IZs). The conclusions draw policy implications and research agenda implications touching also on issues of TNCs as creator/destructors of social values.

The paper refers to other published work by the author – solo or as co-author – where the arguments are further developed, including the finding of a detailed case study. There are policy implications regarding labour and its trade unions (TUs) as well governments and their taxation and industrial policies. Details of such policies need further development.

There are implications for theory development, policies and for research agendas.

Governments of nation-states and institutions within them – such as TUs – should try to co-ordinate rather than compete with each other in their bargaining with transnational companies. The breakaway of regions within nation-states further increases the power of TNCs.

In the development of theories of the TNC, this work shifts the focus from internal characteristics within the firm and its markets to external ones: to the nation-states as jurisdictional loci. The distinction between spatial and regulatory regimes dimensions in dealing with transnational activities allows a novel viewpoint on: regions, GVCs and IZs. A novel viewpoint is also given in relation to the role of TNCs in social value.

The authors provide a novel interpretation of the relationship between skill demand and labour market concentration based on the training rationale.

The authors use a novel data set on Italian online job vacancies during 2013–2018 to analyse the relationship between labour market concentration and employers' skill demand. The authors construct measures of market concentration and skill intensity in the local labour market. The authors regress the measures of skill demand on market concentration, controlling for sector, occupations and other features of the labour market. The authors also use the Hausman–Nevo instrument for market concentration.

The authors show that employers in a highly concentrated labour market demand competencies associated with the ability of workers to learn faster (e.g. social skills) rather than actual knowledge. They also require less experience but higher education. These results are consistent with the hypothesis that employers in more concentrated labour markets are more prone to train their employees. Instead of looking for workers who already have job-specific skills, they look for workers who can acquire them faster and efficiently. The authors provide a theoretical framework within which to analyse these aspects as well as providing a test for the relevant hypotheses.

In addition to cross-countries differences in labour market regulations, the authors' findings suggest that policy authorities should consider the local labour market structure when studying workforce development programmes aimed at bridging the skill gap of displaced workers. Moreover, the authors show that market concentration can have relevant implications for human resource (HR) managers by affecting their recruitment behaviour through the demand for skills. In fact, concentrated markets tend to favour firms' collusion and anti-competitive behaviour that could strongly affect HR management practices.

The authors' paper innovates on the literature in a number of ways. First, the authors provide evidence of local labour market concentration in Italy. Second, the authors provide evidence of skill demand at the local level using a detailed skill taxonomy that goes beyond the classical distinction between high and low skills. Third, and most importantly, the authors provide evidence of the relationship between skill demand and labour market concentration. By analysing detailed skills and competencies, the authors take one step beyond understanding the features of labour demand in monopsonistic markets.

Forced labour is one of the most exploitative practices in supply chains, generating serious human right abuses. The authors seek to understand how relationships for reducing forced labour are influenced by institutional logics. The emerging supply chain efforts of social enterprises offer particularly intriguing approaches, as their social mission can spur creative new approaches and reshape widely adopted management practices.

The authors study supplier relationships in the smartphone industry and compare the evolving practices of two cases: the first, a growing novel social enterprise; and the second, a high-profile commercial firm that has adopted a progressive role in combating forced labour.

The underlying institutional logic influenced each firm's willingness to act beyond its direct suppliers and to collaborate in flexible ways that create systematic change. Moreover, while both focal firms had clear, well-documented procedures related to forced labour, the integration, rather than decoupling, of forced labour and general supply chain policies provided a more effective way to reduce the risks of forced labour in social enterprises.

As authors’ comparative case study approach may lack generalizability, future research is needed to broadly test their propositions.

The paper identifies preconditions in terms of institutional logics to successfully reduce the risk of forced labour in supply chains.

This paper discusses how social enterprises can provide a learning laboratory that enables commercial firms to identify options for supplier relationship improvement.

Small and medium-sized contractors are critical to micro and macroeconomic performance. These contractors in South Africa have long been confronted with the problem of business failure because of a plethora of factors, including poor productivity. The purpose of this study is to investigate salient issues undermining the productivity of small and medium-sized contractors in South Africa. This study proposes alternative possibilities to engender productivity improvement.

Qualitative data were collected using semi-structured interviews with 15 contractors in Gauteng Province, South Africa. The research data were analysed using content and causal layered analyses.

Challenges to contractors’ productivity were associated with inadequately skilled workers, management competence and political factors. Skills development, construction business and political factors were dominant stakeholders’ perceptions. Metaphors for construction labour productivity are presented and reconstructed as alternative directions for productivity improvement.

Contractors lose a substantial amount of South African Rand to poor productivity. Alternative directions provided in this study can be leveraged to increase profitability in construction organizations, enhance the social well-being of South Africans and ultimately improve the contribution of contractors to the South African economy.

The causal layered analysis (CLA) applied in this study is novel to construction labour productivity research. The four connected layers of CLA, which make a greater depth of inquiry possible, were explored to investigate labour productivity in construction organizations.