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The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.

Recruitment to social care roles can be the weakest link in many integrated systems, with vacancy rates being very high compared to other sectors, especially in remote and rural places. Analysis of Employer Value Propositions (EVPs) in social care can capture and challenge perceptions of care work.

This study of EVP in four organisations in a rural setting in Scotland focussed on young people as a target demographic. This study interprets recruitment challenges in social care in three contexts, the technical-instrumental, the hermeneutic and the emancipatory.

EVP articulation is at present not effective. Refreshed and new messaging has potential to attract, employ and nurture young people to the social care sector in remote and rural places.

Recruiting to social care vacancies is crucial for sustainable social care. Improving the recruitment of young people is a key part of the longer-term solution. More studies on recruitment in a variety of remote and rural contexts, with a range of demographics, are needed.

The potential impact is attracting more young people to the social care workforce, enhancing capacity for integrated care improving lives for people who receive care and for paid care workers and unpaid carers.

Remote and rural areas often feature a generational imbalance, with more older people from in-migration and fewer young people from out-migration. Employment in social care has the capacity to redress that to some extent.

This study is original in outlining the messages and methods that can be adopted to boost recruitment to social care.

Drawing on the social identity theory, this paper explores the impact of rider–driver ethnicity match on the driver’s expected ride satisfaction and willingness to perform, and rider’s trust on the driver.

The study relies on scenario-based online experiments with 291 ride-hailing drivers and 282 riders in the USA.

The findings indicate that ethnicity match between ride-hailing drivers and riders positively impact driver’s ride satisfaction and willingness to perform, and rider’s trust in the driver. The study also revealed a significant positive moderation effect of ethnic identity on the relationship of ethnicity match and those constructs.

While it may be challenging to influence an individual’s level of ethnic identity, managers can take steps to educate and train their employees regarding the impact of ethnic identity and discrimination, with a particular focus on those individuals who possess a strong sense of ethnic identity.

The findings of this research provide theoretical contributions to the existing literature on ride-hailing services and adds to the limited stream of logistics research that examines the impact of ethnicity on ride-hailing operations.

Purpose: Significant structural changes are currently occurring in the Indian labour sector. Artificial intelligence (AI) and other emerging technologies are redefining the activities and skill requirements for various jobs in the healthcare sector. These adjustments have been accelerated by the economic crisis brought on by COVID-19, along with other considerations.

Need for the Study: Skills shortages, job transitions, and the deployment of AI at the company level are the three main challenges confronting the Indian labour market. This chapter aims to discuss policy alternatives to address a rising need for health workers and provide an overview of changes to the healthcare sector’s labour market.

Methodology: A review of the available literature was conducted to determine the causes of the widening skill gap despite a vibrant and prodigious young population. The background of the sustainable labour market is examined in this chapter, with a focus on workforce migration and mobility.

Findings: This chapter gives a comparative review of recent policy papers and evidence, as well as estimates of the health workforce and present Indian datasets. Furthermore, it highlights how important it is for all people concerned to invest in today’s workforce to close the skill gap and create better future opportunities.

Practical Implications: This chapter’s findings imply a severe shortage of human intellectual capital in India and a need to bridge this gap in the Indian labour market.

The construction industry in Nigeria, like many others worldwide, grapples with increasing demands for enhanced efficiency, transparency and security. While distributed ledger technology (DLT) offers substantial potential in tackling these issues, its implementation faces numerous obstacles. This study aims to investigate the challenges hindering the adoption of DLT within the Nigerian construction sector, capitalizing on a recognized research gap in this field.

A comprehensive literature review identified 20 challenges to DLT adoption. A structured questionnaire was developed and distributed to 98 construction professionals selected from a pool of 5,330 members using purposive and snowball sampling. Background information was assessed using frequency and percentage, data normality with the Shapiro–Wilk test and nonparametric data compared using the Kruskal–Wallis H-test. Factor analysis was then used to reduce the challenges into a more coherent set.

Findings revealed the top five challenges: power supply issues, data privacy and compliance, an uncertain legal framework, insufficient training and education and a lack of skilled workforce. Further analysis revealed four clusters of challenges, namely, technical and infrastructure barriers, organizational and cultural challenges, financial and economic challenges and regulatory and legal challenges.

Through the evaluation of challenges and potential strategies to overcome them, this study aims to lay a foundation that assists construction entities in effectively harnessing the benefits of DLT while navigating the obstacles inherent in its adoption.

This study contributes to the existing body of knowledge by offering insights into the challenges surrounding the adoption of DLT, specifically within the Nigerian construction sector. By juxtaposing the findings from this study with existing research conducted in other countries such as India, South Africa and the USA, a more comprehensive understanding of the challenges unique to the Nigerian context can be gained.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

American Community colleges are vital to the country's economic mobility and are leaders in developing and facilitating career, technical, and workforce education. This study explored employer perspectives on employees' common and specialized skills across industries in the United States.

Employers were profiled for one year using a case study and content analysis method. They submitted performance records for at least three employees who graduated from community college career, technical, or workforce programs.

Data revealed that overall, employees were successful at work, but employers focused on employability skills across disciplines (common skills); specialized skills employers focused on were associated with business operations and processes and seemed to be something other than industry-specific technical knowledge.

This article and the research it refers to constitute original work that has not been reproduced or published. The value of this article is premised on new longitudinal data, which could be used to improve and progress institutional CTE and WD programs.