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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.

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 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.

In Chapter 1, we critically reviewed the foundations of the free enterprise capital system (FECS), which has been successful primarily because of its wealth and asset accumulation potentiality and actuality. In this chapter, we critically argue that this capacity has been grounded upon the profit maximization (PM) theories, models, and paradigms of FECS. The intent of this chapter is not anti-PM. The PM models of FECS have worked and performed well for more than 200 years of the economic history of the United States and other developed countries, and this phenomenon is celebrated and featured as “market performativity.” However, market performativity has not truly benefitted the poor and the marginalized; on the contrary, market performativity has wittingly or unwittingly created gaping inequalities of wealth, income, opportunity, and prosperity. Critical thinking does not combat PM but challenges it with alternative models of profit sharing that promote social wealth, social welfare, social progress, and opportunity for all, which we explore here. Economic development without social progress breeds economic inequality and social injustice. Economic development alone is not enough; we should create a new paradigm in which economic development is the servant of social progress, not vice versa. Such a paradigm shift involves integrating the creativity and innovativity of market performativity and the goals and drives of social performativity together with PM, that is, from market performativity to social performativity.

This chapter aims to discuss the challenges facing these countries building productive capacity for development. This chapter makes use of data published by international organizations as indicators for measuring the state of development in the Arab region. Several indicators are presented to compare Arab countries with other world regions. The use of data identifies some of the gaps that countries in the Arab region need to close to strengthen capacity building for development and fostering economic growth. The findings from the data presented reveal that the productive structure in most Arab countries remains weak to generate production linkages and provide incentives for investment in nonenergy sectors. The failure of the export-led growth model to diversify output and promote development in energy producing countries has increased the dependence of these countries on global trade. Fluctuations in commodity prices and uncertainty about global demand for energy have influenced the ability of the state to construct strategies for rapid transformation. Except for the energy sector, the productivity of nonoil sectors remains low reflecting inadequate incentives and ineffective entrepreneurial capabilities. The study examines the challenges for building productive capacity in the Arab world. It illustrates the failure of the led-export model and its inability to prompted economic diversification, especially in the Gulf countries. The study contributes to the literature on capacity building in the Arab world so that to encourage researchers and students of development conducting studies concerning the main development challenges facing these countries.

“First principles” of international business (IB) thinking should be applied systematically when assessing the functioning of internationally operating firms. The most important first principle is that entrepreneurially oriented firms seek to create, deliver and capture economic value through cross-border linkages. Such linkages invariably require complementary resources from a variety of parties with idiosyncratic vulnerabilities to be meshed. Starting from first principles allows bringing to light evidence-based insight. For instance, most companies are not global and even the world’s largest firms rarely change the location of key strategic functions. International new ventures (INVs), emerging economy multinational enterprises (MNEs) and family firms face unique vulnerabilities but also command resources that can be used to create value across borders. The quest for “optimal” international diversification appears to be a futile academic exercise, and in emerging economies with institutional voids, relational networks – and more broadly, informal institutions – are unlikely to function as scalable substitutes for formal institutions. In global value chains (GVCs), many lead firms and their partners have been able to craft governance mechanisms that reduce bounded rationality and bounded reliability challenges, and it is also critical for them to use governance as a tool to create entrepreneurial space. Finally, many of the world’s largest companies have been on successful trajectories toward reducing their climate change footprint for a few decades. But these firm-specific trajectories are fraught with challenges and cannot just be imposed via unilateral, macro-level targets decided upon by individuals and institutions lacking a clear understanding of innovation and capital expenditure processes in business.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

China’s foreign aid efforts in Africa remain contentious. Chinese foreign aid tends to be different from “traditional” development assistance in that it frequently involves firms as the implementing agents of projects. Firms bring unique resources to public–private partnerships (PPPs) formed with government agencies, but their possible self-interested nature also gives rise to concerns over their development impact. Yet, on a larger scale, little is known about the characteristics of Chinese PPPs in foreign aid. Using project-level data available for 1,308 Chinese aid projects in 50 countries across Africa, the author characterizes the projects undertaken by firms and government agencies in a PPP and contrasts them to those executed by Chinese government agencies without firm involvement. This exploratory data analysis suggests that important differences apply, as Chinese PPPs tend to target different sustainable development goals (SDGs), work on the basis of distinct aid conditions, and implement projects that tend to be larger than those that are solely run by government agencies. Such observations raise important questions of an ethical, theoretical, and international nature, and warrant further research. The author develops a research agenda that aims at issues particularly important for business ethics scholars, organization theorists, and international business scholarship.