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.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

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.

Modular construction is considered a well-established construction method for improving the efficiency of the construction industry worldwide. However, the industry struggles to achieve higher levels of modularisation in urban areas. Previous studies on decision-making for modularisation have, so far, not focussed much on its application in urban areas. As modular construction could bring lots of advantages such as speed of construction, This study aims to develop a decision-making tool that can assist the project planners in deciding whether the modular construction techniques should be applied in their urban area project.

Based on the literature review, a total of 35 decision-making factors of modularisation were identified for this study. The decision-making model is then developed to evaluate the significance of each factor using the analytic hierarchy process (AHP) approach. A total number of 72 valid responses were obtained and analysed. The geometric mean of priorities is adopted to obtain the par-wise comparison between the critical factors in which each factor’s weighting in the decision-making model is calculated. Afterwards, the robustness of the decision-making model is demonstrated by the real-life projects in China, Hong Kong and the UK, respectively.

A total of 35 decision-making factors allocated in five criteria for modular construction selection in urban areas were identified. The criteria include site attributes, project characteristics, labour consideration, environmental and organisation and project risk. Their impact was calculated using the AHP to indicate the relative importance with respect to the adoption of modularisation in urban areas. Afterwards, a two-level decision-making model was developed that can be used as a decision-making tool for the adoption of modular construction.

The outcome of this research will be beneficial to industrial practitioners and academics in understanding the critical attributes that affect the adoption of modular construction in an urban area. It further enables the building professionals to assess the feasibility of using modular construction in their projects, especially at the early stage, so as to facilitate its use.

There is a number of literature on the decision-making model on the adoption of modular construction. However, previous studies did not provide specific concerns related to urban areas, whereas there is an urgent need to have an updated analysis that can be catered to the modular construction in the urban area. In this research study, the 35 decision-making factors were ranked by the experienced project managers and then a pair-wise comparison was conducted. With this information, the robust decision-making model is formulated to offer a kept promised indicator in adopting modularisation in the urban area.

This study aims to empirically examine the effect of employee commitment (EC) (affective, normative and continuance) and emotional intelligence (EI) on work engagement (WE) (vigor, dedication and absorption). Furthermore, the moderating effects of psychological capital (PsyCap) and EI on strengthening WE are investigated.

A carefully crafted survey instrument was developed, and data were collected from 511 employees working in the banking sector in southern India. First, the psychometric properties of the measures were checked. Second, the results were analyzed using Hayes’ PROCESS macros.

The results indicate EC and EI positively predict WE; EI moderates the relationship between EC and WE; and PsyCap (second moderator) moderates the relationship between EI (first moderator) and EC influencing WE.

This study’s limitations include the common method and social desirability biases inherent in any social science research based on surveys. However, the authors have taken adequate care to minimize these limitations. In addition, this study has several implications for practicing managers interested in enhancing WE.

The three-way interaction between EC, EI and PsyCap, which is investigated in this study, represents an original and unique contribution to this study. To the best of the authors’ knowledge, previous researchers have not done the moderated-moderation, especially in the context of a developing country such as India. This research advances the growing literature on EC and WE. Implications for theory and practice are discussed.

Globally, higher education institutions have become reliant on a quality assurance (QA) system over the past four decades. QA is considered to be one of the most important drivers of continuous improvement and an essential tool for promoting excellence in teaching, learning, and research. It provides a framework for establishing and maintaining standards, and for assuring stakeholders that programs and services meet or exceed these standards. Despite the wide range of quality assurance models available to higher education institutions, there remains considerable debate over which model is the most effective, as well as what criteria should be used for evaluating the effectiveness of these models. Universities in the Middle East have tried to adopt different models of QA that can meet their needs and expectations and provide a framework for continuous improvement. A major objective of this book is to provide an overview account of the QA process as implemented in the higher education systems of a number of Middle East countries, including Egypt, Iraq, Lebanon, Saudi Arabia, and the United Arab Emirates. This book lays out essential theoretical and practical insights into the role of QA policies and practices in higher education in the Middle East countries and builds upon this idea to provide a blueprint for future academic leaders in these countries and other Middle Eastern countries to enhance their QA policies and practices and drive higher education in those countries forward.