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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.

Currently, waste is regarded as a symptom of inefficiency. The generation of waste is a human activity, not a natural one. Currently, landfilling and incinerating wastes are common waste management techniques; but the use of these methods, in addition to wasting raw materials, causes damage to the environment, water, soil, and air. In the new concept of “Zero Waste” (ZW), waste is considered a valuable resource. A vital component of the methodology includes creating and managing items and procedures that limit the waste volume and toxicity and preserve and recover all resources rather than burning or burying them. With ZW, the end of one product becomes the beginning of another, unlike a linear system where waste is generated from product consumption. A scientific treatment technique, resource recovery, and reverse logistics may enable the waste from one product to become raw material for another, regardless of whether it is municipal, industrial, agricultural, biomedical, construction, or demolition. This chapter discusses the concept of zero landfills and zero waste and related initiatives and ideas; it also looks at potential obstacles to put the ZW concept into reality. Several methods are presented to investigate and evaluate efficient resource utilization for maximum recycling efficiency, economic improvement through resource minimization, and mandatory refuse collection. One of the most practical and used approaches is the Life Cycle Assessment (LCA) approach, which is based on green engineering and the cradle-to-cradle principle; the LCA technique is used in most current research, allowing for a complete investigation of possible environmental repercussions. This approach considers the entire life cycle of a product, including the origin of raw materials, manufacturing, transportation, usage, and final disposal, or recycling. Using a life cycle perspective, all stakeholders (product designers, service providers, political and legislative agencies, and consumers) may make environmentally sound and long-term decisions.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

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 UK government’s support for sustainable construction involves an explicit attempt to introduce a new institutional logic into the construction sector, while the use of Building Research Environmental Assessment Method (BREEAM) as a preferred policy mechanism exemplifies neoliberal use of voluntary self-regulation to promote policy goals. This paper uses the case of BREEAM to examine the role of science and scientific expertise in the exercise of neoliberal governance. More specifically, it combines a neo-institutional analysis of change with Foucault’s theory of governmentality to explore the effect of BREEAM on eight construction projects. The concepts of visibility, knowledge, techniques, and identity provide an analytic grid to explore the effect of BREEAM on understandings and practices of “green building.” Appeals to science and scientific authority are found to be most important in those instances where institutional logics clash and the legitimacy of BREEAM as a carrier of sustainable construction is challenged. From a theoretical perspective, the case studies highlight the role of instruments in the micro-dynamics of institutionalization. Empirically, it underlines the limited, but nonetheless significant, effect of weakly institutionalized neoliberal policy mechanisms.

Production-related industrial zones, super structures and infrastructures are constructed by the construction industry. Nearly all industries and their environmental emissions are influenced by the construction industry including its sub-industries, companies and their supply chains. Furthermore, cities play an important role in economic growth. Cities are hubs for productivity, production, supply and demand, and innovation with the help of their human capital and built environment (e.g. offices, factories, industrial zones, infrastructures, etc.).

Industrial growth fosters urbanisation which is vital for the supply side in the economy to reach to the human resources. Urbanisation which supports industrial growth obstacles industries’ efficiency due to urbanisation problems (e.g. traffic, air and water pollution, health problems).

Construction industry and its sub-industries affect total factor productivity growth in nearly all industries. Construction industry can be a facilitator industry for economic growth and industrial growth considering total factor productivity growth and environment aspects. All industries’ green and sustainable total factor productivity growth can be supported by rethinking construction industry, its sub-industries and their outputs (e.g. construction materials, built environment, cities) as well as construction project management processes.

This chapter aims to introduce carbon capturing smart construction industry model to foster green and sustainable total factor productivity growth of industries. This chapter emphasises current and potential roles of construction industry, its sub-industries and their outputs in fostering other industries’ growth through green and sustainable total factor productivity growth. It focusses on carbon capturing technologies and design at different levels. Furthermore, this chapter emphasises cities’ role in green and sustainable total factor productivity growth. This chapter provides recommendations for construction industry policies and carbon capturing cities/built environment model to solve urbanisation problems and to foster industrial growth and green and sustainable total factor productivity growth. This chapter is expected to be useful to all stakeholders of the construction industry, policy makers, and researchers in the relevant field.