Search results

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.

As e-HRM systems move into the ‘smart’ technology realm, expectations and capabilities for both the automational and informational features of e-HRM systems are increasing. This chapter uses the well-established DeLone and McLean (D&M) model from the information systems literature to analyze how a smart workforce management system can create value for an organization.

The chapter is based on an exploratory case study conducted with a North American industrial products firm. We review three systems-level predictors of success from the D&M model (system quality, information quality, and service quality) and evaluate the company’s systems on these attributes.

The company’s e-HRM systems fall short on the information quality dimension, which limits potential for overall system success related to smart workforce management.

The e-HRM literature focuses on individual-level factors of system success, while the D&M model uses more macro factors. Blending these may help researchers and practitioners develop a more complete view of e-HRM systems. Conclusions from this chapter are limited due to the use of a single, exploratory case study.

Companies must pay attention to all three predictors of system quality when developing smart workforce management systems. In particular, implementation of a data governance program could help companies improve information quality of their systems.

This chapter adds to the literature on smart workforce management by using a model from the information systems literature and a practical example to explore how such a system could add value.

The purpose of this research paper is to evaluate and estimate the cybersecurity maturity and awareness risk for workforce management in railway transportation by using Railway-Cybersecurity Capability Maturity Model (R-C2M2) and Information Security Awareness Capability Model (ISACM), respectively.

This research uses a case study strategy, so primary data comprise the majority of data collected. These data were collected through interviews and questionnaires. The secondary data were collected from the literature, technical reports and standards.

The results show that there is a gap in cybersecurity awareness within the workforce and there is a need to improve this gap. This paper provides some of the recommendations and literature to enhance cybersecurity workforce culture within railway organizations.

In this paper, the authors have demonstrated that cybersecurity awareness has positive impact on the overall dependability of the railway system.

This paper describes the importance of cybersecurity awareness and training in building more cyber resiliency across the operation and maintenance of railway.

This paper provides an overview of the national child and adolescent mental health service (CAMHS) mapping exercise, the workforce data reported in the mapping between 2003 and 2006, and how this data relates to current policy. The paper will first outline key issues within current CAMHS workforce policy and provide an introduction to the mapping process itself in order to establish the context in which the findings from the mapping exercises are being presented. The mapping is carried out by Durham University on behalf of the Department of Health. Core trend data is provided on the growth and development of the specialist CAMHS.

In a world where the continual combining of computer applications and the expansion of artificial intelligence is already necessarily changing the world of work for people, an education system that does not adequately respond to these trends and changes will render itself irrelevant. Education policy and regulation may suffer at the hand of such accelerations due to unexpected consequences and developments. However, the rapid, exponential improvements in computer hardware and software that have enhanced the rate and our ability to gather, transform, manipulate, and interpret these data in an ongoing fashion also present myriad educational opportunities. The so-called Fourth Industrial Revolution offers societies data and information capabilities previously unimagined, making it possible to learn how to combine, innovate, and imagine entirely new avenues for building responsive and intelligent education policies and systems that promote the education and wellbeing of citizens as well as improving their economic participation. These advances necessitate a growing number of educators and education systems who can intelligently respond to Industry 4.0 trends. In this chapter, some considerations regarding the use of large-scale, international datasets and emerging data analytics for analyzing policy for the governance of education are offered, and a discussion of the need for the more systematic use of data analytics as a mechanism for developing socially responsive adult learning and workforce education policy and programing.

The purpose of this study is to examine the role of digital infrastructure in supporting compliance with travel restrictions. The purpose of this study is to examine the role of digital infrastructure in supporting compliance with travel restrictions. In response to the COVID-19 pandemic, countries around the world have issued “stay-at-home” orders and curtailed a variety of economic activities. As countries have adopted aggressive policies to limit the spread of COVID-19, varying levels of national infrastructure to provide internet access have limited some nations’ ability to reduce travel requirements. As national policies struggle to address public health issues, location analytics enabled by big data provide unique insights regarding the efficacy of digital infrastructure. These insights can provide valuable tools to public health officials and regulators in understanding how health recommendations are implemented within an economy.

This study analyzes mobile phone movement data during the first half of 2020 and finds that countries that provided greater access to internet capabilities were better able to reduce work-related mobility.

This study’s findings indicate that greater levels of digital infrastructure may better prepare countries to adapt to societal disruptions such as COVID-19.

This study’s findings demonstrate that public health controls regarding movement and person-to-person interaction are less likely to be effective in nations with weaker digital infrastructure, even after accounting for variation attributable to gross domestic product (GDP) and pandemic severity. This could limit public health options in developing countries when faced with future socially disruptive events and encourage national investment in digital infrastructure.

This study’s findings highlight positive externalities associated with reducing the digital divide. Developing better digital business infrastructure globally may reduce human exposure to future pandemic risks.

This research demonstrates the practical development implications of analysis of aggregate data widely available through mobile technology. As institutions develop techniques to ethically and effectively analyze this data, greater opportunities to support economic development may be revealed.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

This paper aims to contribute to the literature on human resources (HR) digitalization, specifically on HR analytics, disentangling the concept of analytics applied to HR and explaining the factors that hinder companies from moving to analytics. Therefore, the central research questions addressed in this study are: what does HR analytics encompass? What impedes the adoption of analytics in HR within organizations?

The authors performed a comprehensive literature review on analytics as applied in HR. The authors relied on two of the major multidisciplinary publication databases (i.e. Scopus and WoS). A total of 64 manuscripts from 2010 to 2019 were content analyzed.

The results reveal that there is an ongoing confusion on HR analytics conceptualization. Yet, it seems that there is an emerging consensus on what HR analytics encompasses. The authors have identified 14 different barriers for HR analytics adoption grouped into four categories, namely, data and models, software and technology, people and management. Grounding on them the authors propose a set of 14 key factors to help to successfully adopt HR Analytics in companies.

This paper brings clarity over the conceptualization of HR analytics by offering a comprehensive definition. Additionally, it facilitates business and HR leaders in making informed decisions on adopting and implementing HR analytics. Moreover, it assists HR researchers in positioning their paper more explicitly in current debates and encouraging them to develop some future avenues of research departing from some questions posed.

Workforce shortages and maldistribution in the health care sector are the outcome of poor planning processes, entrenched power relations, jurisdictional boundaries and professional silos. In seeking to redress these problems, countries are moving toward establishing independent agencies to monitor, regulate and shape the health workforce. In Australia, for example, Health Workforce Australia (HWA) has been established to provide data on workforce numbers and fund clinical education. The purpose of this paper is to examine whether this strategy is likely to work. By locating HWA within the framework of an Independent Regulatory Agency, the implicit strengths and weaknesses of using HWA to manage workforce planning are highlighted.

A theoretical discussion on regulatory capitalism and Independent Regulatory Authorities provides the context for the case study: the gynaecological cancer workforce – a niche health workforce that is complex and multidisciplinary. Data are from a mixed method study commissioned by Cancer Australia.

The analysis of the gynaecological cancer workforce illustrates the difficulties that HWA will face in defining the health workforce, in measuring supply and demand and in setting targets for training and education.

Findings are limited by the fact that HWA was only established in mid 2009.

The establishment of independent agencies to oversee and implement government policy is a new form of control over universities and health professionals that challenges their professional autonomy.

This paper points to the creation of new agencies of government control in the wake of an international health workforce crisis.

Drawing on human capital theory and the human capital resources framework, this study explores the knowledge, skills, abilities and other characteristics (KSAOs) required by the emerging role of human resource (HR) analysts. This study aims to systematically identify the key KSAOs and develop a competency model for HR Analysts amid the growing digitalization of work.

Adopting best practices for competency modeling set out by Campion et al. (2011), this study first analyzes 110 HR analyst job advertisements collected from five countries: Australia, Canada, Ireland, the United Kingdom and the USA. Second a thematic analysis of 12 in-depth semistructured interviews with HR analytics professionals from Canada and Ireland is then conducted to develop a novel competency model for HR Analysts.

This study adds to the developing and fast-growing field of HR analytics literature by offering evidence supporting a set of six distinct competencies required by HR Analysts including: consulting, technical knowledge, data fluency and data analysis, HR and business acumen, research and discovery and storytelling and communication.

The research findings have several practical implications, specifically in recruitment and selection, HR development and HR system alignment.

This study contributes to the evolving HR analytics literature in two ways. First, the study links the role of HR Analysts to human capital theory and the human capital resource framework. Second, it offers a timely and empirically driven competency model for the emerging role of HR Analysts.