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This chapter discusses the proposed integrated sustainable road infrastructure project implementation (ISRIPI) model and its constructs and sub-constructs, as well as public participation (PP), climate change response (CCR), and stakeholder management (SM). CEEQUAL was the most comprehensive rating system, with 11 criteria. Lim (2009) and Ugwu and Haupt (2007) were the most thorough studies examining sustainability models for infrastructure projects, focussing on social and cultural sustainability (SCS), economic sustainability (ES), environmental sustainability (EnS), institutional sustainability (IS), health and safety (HS), project management (PM), resource utilization and management (RUM), and engineering performance (EP). The Brundtland Report and Rio Summit defined social sustainability as the right to a decent standard of living, social justice between generations, within generations, and around the world. Thin (2002) showed social justice, unity, investment, and safety as aspects of society. Rosenström et al. (2006) defined social qualities as objects that make people happy. Cultural sustainability is access to cultural assets for current and future generations, and cultural legacy is the collection of physical signals passed on from the past to each civilization and, by extension, to all humans. EnS seeks to reduce the environmental impact of road infrastructure projects. Sustainable road infrastructure project implementation (SRIPI) must consider PM issues such as delivery system, risks, duration, performance assessment, sustainability clauses, and contract type. Quality control systems must be set up to ensure the optimum utilization and management of resources in SRIPI. EP criteria measure sustainable road infrastructure projects’ (SRIP) durability, quality, resilience, adaptability, functionality, carrying capacity, and robustness. This research developed an SRIPI model based on the models of CEEQUAL, Lim (2009), and Ugwu and Haupt (2007). The hypothesized framework consists of 37 SRIPI factors, including SCS, ES, IS, HS, PM, RUM, EP, CCR, PP, and SM. It projected the analytical authority of these constructs in the success of SRIPs to test whether the realization of SRIPI outcomes depends on the supposed indicators of the variables. SRIPI is a multidimensional structure composed of 11 latent variables, derived from literature review and Delphi study findings.

The CEEQUAL certification system promotes sustainable development (SD) principles in infrastructure construction, with 12 categories of criteria and indicators. ENVISION assigns 60 points to five categories, while Green Guide is divided into seven classifications. SD certification requires 11 requirements, including an ecological assessment procedure, life-cycle costing assessment, quality control plan, noise mitigation plan, waste management plan, pollution prevention plan, low impact development, pavement management system, site maintenance plan, and educational outreach. SD certification technique provides 8 critical criteria, 153 standards, 17 stringent prerequisites, and 8 categories of points. Culp (2011) developed a grading system to incorporate SD principles into infrastructure projects; Shen et al. (2011) explored significant assessment parameters for the SD of infrastructure projects using the fuzzy set method; Lui and Cui (2012) studied SD frameworks for building projects, Montgomery et al. (2014) and Lim (2009) identified 77 major SD indicators based on a comprehensive review of the relevant literature, and the Transport Division of New South Wales established a Transportation Project Sustainability Framework to ensure the long-term viability of their transportation network and the continuous improvement of their environmental and sustainability performance. Assah Amiril (2014) revealed a global network of 27 SD criteria produced by professionals, for-profit and non-profit organizations, divided into five groups: ecological, financial, sociological, engineering, asset use, and project management. The most important details in this study are that 57 indicators were categorized into eight types, weighted according to their respective impacts, and the influence of each component on SD was evaluated using a 100-dimensional scale. This study investigated the eight criteria and the impact of three additional criteria (public participation, climate change response, and stakeholder management). This chapter examined the criteria and indicators of SD criteria and indicators for road infrastructure development in developing countries. The most important findings are that the CEEQUAL, Ugwu, Haupt, and Lim models are the most comprehensive theoretical models of SD requirements for infrastructure design, and that all frameworks and models promote the sharing, promotion, and acknowledgement of SD concepts.

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.

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.

This chapter examines the impact and influence of the visual and performing arts in sustaining thriving communities and highlights the essential role of libraries in providing access to arts and cultural programming and services. Creative and artistic intervention has become the imperative of our time. Creativity is required not only in design studios and workshops, but in all areas of work and life, both professional and personal. Places of artistic and cultural production are strongly correlated with strong local economies and sustainable communities. Libraries are public spaces that promote and maintain community, not only civic institutions. As such, the library plays a key role as incubator for the arts. Libraries advocate freedom: of ideas, communication, and information. Arts programming in libraries provides an avenue for people to communicate ideas and feelings through visual, auditory, or kinesthetic forms. But more than that, libraries are also about education, safe and welcoming spaces, community, and entertainment. Libraries support and promote the value of multiple perspectives and voices. Libraries can shape patronage of the arts and engage future generations by addressing social diversity and inciting inclusive participation in the arts. Many libraries are participating in the creation of new forms of understanding through arts programming, services, and resources. In an age where many of society’s most important challenges are related to our relationship with information, it is vitally important to include visual and performing arts professionals in the intersection between artistic practice and critical engagement with information.

Purpose — This study proposes an optimal survey design method for multi-day and multi-period panels that maximizes the statistical power of the parameter of interest under the conditions that non-linear changes in response to a policy intervention over time can be expected.

Design/methodology/approach — The proposed method addresses balances among sample size, survey duration for each wave and frequency of observation. Higher-order polynomial changes in the parameter are also addressed, allowing us to calculate optimal sampling designs for non-linear changes in response to a given policy intervention.

Findings — One of the most important findings is that variation structure in the behaviour of interest strongly influences how surveys are designed to maximize statistical power, while the type of policy to be evaluated does not influence it so much. Empirical results done by using German Mobility Panel data indicate that not only are more data collection waves needed, but longer multi-day periods of behavioural observations per wave are needed as well, with the increase in the non-linearity of the changes in response to a policy intervention.

Originality/value — This study extends previous studies on sampling designs for travel diary survey by dealing with statistical relations between sample size, survey duration for each wave, and frequency of observation, and provides the numerical and empirical results to show how the proposed method works.

Business simulation games (BSGs) are gaining popularity in higher education as tools for entrepreneurial education. However, there are challenges in using BSGs for large classes of students in historically disadvantaged institutions (HDIs). The challenges include limited resources and digital literacy skills.

The living standards measure (LSM) indicates socioeconomic status by measuring the degree of urbanisation, access to services and possession of assets, such as mobile phones. This research investigated the impact of students' living standards on their intention to use BSGs, as there is limited research.

This study used positivism and added LSM to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Quantitative data from 224 third-year information system students at an HDI were collected through an online survey. Structured Equation Modelling was used to analyse the data.

Results indicated that performance expectancy and social influence significantly influenced the intention to use BSGs. However, the relationship between effort expectancy and behavioural intention facilitating conditions was not significant. The introduction of LSM as a moderator for the relationships between all variables and behavioural intention also proved to be insignificant.

The result was unexpected, as we posited that a lower LSM would affect students' intention to use BSGs. This was not proven in this study and could be related to students accessing campus resources. However, during times when access to campus is restricted, such as protest action, the result may change for students with lower LSM.