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The purpose of this chapter is to investigate the adoption and use of building information modelling (BIM) for residential real estate development in Nigeria (using Lagos as a case study), with a view to providing information towards improving BIM uptake, which could enhance sustainable housing delivery in the country. A quantitative research methodology was adopted involving the use of questionnaire survey to collect primary data. The data were obtained from private real estate developers in Lagos State. The self-administered questionnaire was distributed to all the 72 active real estate developers in the study area, and the response rate was 62.5%. The collected data were analysed using statistical tools such as frequency and percentages, mean rating and chi-square. The results revealed a low level of awareness and usage of the transformative and contemporary BIM technology (6D BIM version) by real estate developers. It was established that the 2D and 3D BIM traditional versions were the most utilised across the phases of real estate development process. It was also found that the level of BIM utilisation has a significant relationship with the age and asset base of the real estate developers. The chapter concludes by advocating increase in the asset base and organisational profile of real estate developers to enhance BIM adoption, especially, the 6D BIM, which could facilitate sustainable real estate development.

New computer-assisted techniques for visualizing data are evolving in a number of areas in transportation. For example, in engineering, 3D visualization and microsimulation techniques are being applied for the identification and evaluation of geometric and operational solutions for improving visually impaired pedestrian access to roundabouts and channelized turn lanes. For planning, visualization is being used for corridor analysis. Data visualization is being used as a tool for improving decision-making within transit agencies, as well as a tool for understanding truck trip generation on highways. Many of these new techniques take advantage of archived intelligent transportation systems (ITS) data. Examples of other innovative data sources include global positioning systems (GPS), geographic information systems (GIS), computer-aided design (CAD), and a variety of visualization tools available for use with travel survey data. As these various techniques and software applications move forward, consideration needs to be given to how the “lessons learned” from these applications can facilitate the use of data visualization techniques for travel survey data analysis and decision-making.

Appreciative Inquiry (AI) has gained prominence as an organizational development approach. For over 15 years, it has had varied use in higher education research as a methodology and as a collection of methods. Perhaps the most consistently used, yet most criticized, aspect of AI is the positive stance that its adherents adopt. In this chapter, we survey the prevalence and use of AI, both in the wider literature and in higher education research. We offer our own case study to illustrate the practicalities of employing it and discuss our findings. We suggest that educational researchers are overlooking relevant AI research published within other disciplines; that our own and other case stories can provide guidance for the use of AI in academic contexts; and that AI’s collaborative and positive standpoint has potential as a research methodology influencing policy.

This chapter discusses the profound and influential impact the construction industry has on the national economy, together with the huge negative effect it has on the environment. It argues that by adopting smart and industrialised prefabrication (SAIP), the Australian construction industry, and the construction industry globally, is well positioned to leverage the circular economy to advance future industries with less impact on our natural environment. It discusses aspects of the application of digital technologies, specifically building information modelling, virtualisation, augmented and virtual reality and 3D printing, coupled with reverse logistics as a proponent for advancing the circular economy through smart, digitally enabled, industrialised prefabrication. It further postulates a framework for SAIP for the circular economy.

The impact of rapidly developing technologies on digitalization of production and planning has affected all sectors in a short period. This impact has led to both positive and negative outcomes. While it is helping the decision-makers to make better and more productive choices, it also can create a cluster of information and data that can put an undue burden on processes. Today, we call this Industry 4.0, which is defined as the use of digital technologies, based on data processing, the end-to-end connection of value chains, and ensuring data fluidity. Industry 4.0 consists of technologies such as cyber-physical systems, internet of things, cloud computing, big data and analysis, autonomous vehicles, and augmented reality. With the digitalization of the entire production and planning processes, data-based applications are made; thus it is important to protect data in this context, pointing to the critical importance of cybersecurity. Companies are constantly working on taking the necessary cybersecurity measures to prevent exposure to any cyberattacks. One of the biggest steps toward the development of production and planning is undoubtedly the integration and adaptation of blockchain technology. The use of blockchain technologies has been a major breakthrough for the sector in order to effectively meet customer needs, ensure information security, reduce costs, and achieve rapid growth. With digital transformation, production and planning must comply with the principle of transparency. In this context, integrating blockchain technologies into the production and planning ecology for data security will provide companies with a serious competitive advantage.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

In this chapter, the authors discuss how visual artifacts may support the analysis and interpretation of qualitative data in organization studies. They draws on their own experience as well as other scholars’ published work to explore the distinctive affordances of visual forms. In particular, the authors identify four roles – namely “mapping,” “analyzing,” “conceptualizing,” and “communicating” – that visual artifacts play to help us move from raw qualitative data to a compelling conceptual product.

Specifically, the use of visuals for “mapping” involves directly coding data into visual forms such as cognitive maps, flow charts or relational diagrams, an approach that may offer a useful complement to traditional verbal coding. Using visuals for “analyzing” implies either comparing, aggregating or decomposing previously constructed visual maps, or drawing directly on verbal data to develop visuals such as analytical flow charts, process replication maps, and trend charts. Using visuals for “conceptualizing” involves rising above the data to develop more abstract representations of concepts and relationships, while maintaining recognizable connections to empirical phenomena. While conceptual models can take a wide variety of forms, the authors illustrate, in particular, the use of visuals to represent linear, dialectic and multi-level process theories. Finally, the authors consider the importance of visualizations for “communicating” insights as well as for developing them, and the inextricable linkages between the two.

The authors conclude by discussing some of the strengths and weaknesses of visualization and by considering how new technologies may offer further possibilities for useful and insightful visual representations of qualitative data that can enhance theory-building.

We develop an interactive framework to model speculation (over regulation) and regulation (of speculation) in a greenhouse gas (GHG) permits market. In our proposed model, big traders engage in speculation by strategically withholding and releasing permits to influence the temporal path of permit prices in order to maximize their profits. The national government/regulator has an incentive to stabilize permit prices by suitably manipulating stocks of permits. Thus, the GHG permits market can typically be characterized by circular interdependence in which big traders will be “gaming” the regulator to generate profits: the state of the market affects speculative behavior of traders that in turn impacts on government's behavior, which in turn impacts on the state of the market. The interactive framework explores the gaming between speculators and a regulator, or government, to shed crucial insights on the nature of equilibrium in possible global emissions trading schemes (GETS). By so doing, we are able to unravel potential pitfalls of any global trading system in pollution permits for arresting global warming. Once policy makers are aware of these pitfalls, for example, a “culture of speculation” as opposed to a culture of safety, they can devise a suitable mechanism to bypass these potential pitfalls.

Service-learning (SL) is an innovative methodology aiming to improve learning while providing students experiences in the community. Consequently, students also develop social and emotional skills many higher education institutions promise to foster. However, few academic enrichment opportunities are implemented to develop these social skills and university teaching staff are limited in their knowledge of SL to promote active citizenship and civic engagement (Belando-Montoro, Jover, Ruiz de Miguel, Blanco, & Carrasco, 2015). This chapter presents an analysis of the presence of direct and indirect indicators related to social responsibility and SL in the degree programs of the Social and Legal Sciences area of the Complutense University of Madrid. These indicators include questions related to the social environment needs diagnosis and the design of projects that meet these needs, the environmental care, among others. The results indicate the lack of presence of courses on the direct indicators in the degrees offered. However, the focus on indirect indicators is relatively common. In particular, those common indirect indicators are related to critical thinking about social reality, the environment needs diagnosis, and the development of social intervention. The findings suggest universities increase their focus on social responsibility and community service in the university curriculum, providing training oriented toward socio-community intervention.