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This first chapter provides a general overview of the book. The chapter describes workforce management and the lack of adequate attention to this concept within construction organisations. In the fourth industrial revolution era, where emerging technologies have continued to change how business functions, the need for an effective approach towards managing the construction workforce becomes crucial. Having a construction workforce management practice model was deemed vital at this point, where technological advancement is rapidly changing the construction environment, and skill shortage is evident in the construction industry of most countries around the world. As such, this chapter establishes that the development of a construction workforce management model that will help improve the management of construction workers serves a critical value of the book.

The importance of humans to the successful delivery of construction projects has led to the emergence of research attention on construction workforce management. As such, this chapter uncovers emotional intelligence (EI) and the external environment as critical aspects of workforce management practices that have not gained substantial attention in past workforce management studies. While some theories and models (existing outside the construction domain) have considered the external environment, none of these models is specific to the construction industry. Furthermore, EI has received less attention within existing workforce management models. Through a review of related studies and theories, this chapter noted that the EI of construction workers and their senior management is crucial to the performance of these workers and the ultimate performance of their organisations. In the same vein, since construction organisations do not operate in silos, the external environment significantly influences the operations of organisations in the construction industry. The environment exact pressures that can influence workforce management practices and technological innovations construction organisations adopt.

This study aims to investigate the mediating role of lean management on the relationship between workforce management and value-added time in private hospitals. This study also investigates the direct influences of workforce management and lean management on the value-added time of the hospitals.

This study applied a quantitative approach to obtain data from the private hospitals’ staff in Peninsular Malaysia. A self-administered survey questionnaire was used to collect data from 287 hospital staff using a stratified random sampling method. The partial least squares structural equation modeling (PLS-SEM) approach was used to determine the internal consistency, reliability, validity of the constructs. The PLS-SEM method was also used to test the hypothesised research model via SmartPLS 3.3.4 version.

The findings of the study indicate that lean management has a direct and significant effect on the value-added time of private hospitals. The findings also revealed that lean management significantly mediates the relationship between workforce management and value-added time in private hospitals. The analysis of the results indicates that both workforce and lean management have a significant impact on the value-added time of the hospitals.

This study provides empirical contributions to enhance the quality of workforce management, lean management and value-added time. The findings of this study provide valuable insights into how effectively managing the workforce and providing guidelines to augment the lean management practices can ensure value-added time in Malaysian hospitals and the overall health-care industry. The lean management framework provides useful insights for the policymakers to understand the significance of workforce management, lean management on ensuring value-added time through reducing waiting times, unnecessary delays, generating a higher degree of patient safety, satisfaction and loyalty.

The research findings provide some essential indications for the health-care service providers to understand how the lean management approach can be implemented to enhance value-added time and how lean management can play a mediating role in creating a link between workforce management and value-added time in hospitals. This study also contributes to the theoretical and practical perspectives. The present study contributes to a better understanding of workforce management and lean management in health-care sectors from theoretical and practical perspectives.

In the quest for better construction workforce management, this chapter explored the background of workforce management and related theories, models, and practices. Through a review, the chapter provided meaning to the concept of construction and workforce management. The chapter concluded that while the construction industry worldwide is important to the economic growth of the countries where it operates, the industry’s management of its workforce is challenged by several problems. These problems include the nature of the industry, skill shortage, unhealthy working environment, and poor image of the industry, among others. Also, while the construction industry is rich in diversity, this has been a major source of problems for workforce management. The chapter further revealed that to improve workforce management and attain better-performing construction organisations, careful recruitment, effective training, providing a safe working environment, putting policies to promote diversity, and ensuring innovativeness, among others, are essential.

The construction workforce plays a crucial role in the successful delivery of any construction project and, eventually, the performance of any construction organisation. Effectively managing these workforces becomes crucial. However, past studies have shown that workforce management within the construction industry has been on the back foot, with workers being seen as resources required to deliver construction projects. This situation begs the need for a construction workforce management model that can be tailored to an organisation’s situation and adopted to manage workers and improve organisational performance effectively. To this end, this chapter reviewed existing workforce management theories, models, and practices to develop a suitable approach towards managing the construction workforce. Ultimately, a strategic workforce management with a classical view using a soft workforce management approach that embraces employees’ empowerment and development through trust was proposed. Five major practices that best suit the soft workforce management approach were identified as key constructs in the proposed construction workforce management model.

This book aimed to conceptualise a construction workforce management model suitable for effectively managing workers in construction organisations. To this end, this chapter presents the conceptualised model, which consists of seven workforce management practices with their respective measurement variables. Drawing from existing theories, models, and practices, the chapter concludes that a construction organisation that will attain its strategic objectives in the current fourth industrial revolution era must be willing to promote effective recruitment and selection, compensation and benefits, performance management and appraisal, employee involvement and empowerment, training and development, as well as improving workers emotional intelligence and handling external environment pressure. These practices can promote proactiveness, participation, and improved skills and can lead to effective commitment, better quality, and flexibility within the organisation.

Quality management constructs related to management leadership and workforce involvement have consistently shown strong correlation with firm success for years. However, there is an increasing body of research based on complexity theory (CT) suggesting that constructs such as these should be viewed as variables in a complex system with inter-dependencies, interactions, and potentially nonlinear relationships. Despite the significant body of conceptual research related to CT, there is a lack of methodological research into these potentially nonlinear effects. The purpose of this paper is to demonstrate the theoretical and practical importance of non-linear terms in a multivariate polynomial model as they become more significant predictors of firm success in collaborative environments and less significant in more rigidly controlled work environments.

Multivariate polynomial regression methods are used to examine the significance and effect sizes of interaction and quadratic terms in operations scenarios expected to have varying degrees of complex and complex adaptive behaviors.

The results find that in highly collaborative work environments, non-linear and interaction effects become more significant predictors of success than the linear terms in the model. In more rigid, less collaborative work environments, these effects are not present or significantly reduced in effect size.

This study shows that analytical methods sensitive to detecting and measuring nonlinearities in relationships such as multivariate polynomial regression models enhance our theoretical understanding of the relationships between constructs when the theory predicts that complex and complex adaptive behaviors are present and important.

This study demonstrates that complex adaptive behaviors between management and the workforce exist in certain environments and provide greater understanding of factor relationships relating to firm success than more traditional linear analytical methods.

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.

Workforce planning must answer how many workforces, in which positions, and talents, and when each organization is needed. To find the requirements workforce, organizations need to know the organizational position and talents pools. Clarifying the number of workforces required in each pool requires attention to workforce flows, including hiring, promotion, degradation, horizontal movement, and exiting the organization. It is a dynamic issue and must be addressed over several periods over a specific duration, which adds to the complexity. According to the talent management presented in this research, all the above complex questions are answered by applying the optimal control (OC) model according to talent management presented in this research.

This research presents a dynamic model by using a linear-quadratic optimal control model, which was solved by Pontryagin's maximum principle, to achieve an optimal number of workforce requirements for each of the positions of nursing services manager, supervisor, head nurses and nurses in the health sector according to the required talents in each position.

The results have shown that the target value of workforce numbers has been achieved in the planning period, and the validation test and sensitivity analysis justified the model by reaching the workforce planning targets.

This study provides a dynamic model for achieving quantitative workforce planning targets; the model presented in this manuscript has included an important qualitative factor, namely workforce talents. According to the authors' review, there is no comprehensive research devoted to workforce planning through optimal control models by attention to workforces skills.