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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.

Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant environmental harm. This decision rule is conceptually unsound and would diminish social welfare. Uncertainty as such does not justify regulatory precaution. While they should reject PP, regulators should take appropriate account of societal aversion to risks of large harm and the value of obtaining additional information before allowing environmentally risky activities to proceed.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

In recent years Professor Shackle's numerous, highly imaginative and original works on the role of expectation and uncertainty in the modelling of economic behaviour have at last become more widely acknowledged. However, still relatively little attention is paid to one of his seminal and earliest studies, that concerned with his own theory of expectations and individual decision making under uncertainty, work on which was begun and published in the 1930s and completed in 1949 with the appearance of the first edition of Expectation in Economics. Thereafter, until the early 1960s, his theory received a modest amount of interest. However, it tended to become neglected; reference rarely appears to it in books or papers on expectation, even in those papers discussing decision making under uncertainty (see, as one of the latest examples, G. O. Schneller and G. P. Sphicas, 1983). The literature has been dominated by the risk‐based, expected utility approach to decision taking.

Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations.

The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general.

The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical.

The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

Purpose – The aim of this study is to determine the impact of feeling bored on managers' decision-making in the digital age under conditions of increased uncertainty by examining the role of personality trait openness and empirically testing such relationships within the context of retail middle managers.

Design/methodology/approach – Feeling bored was defined within a broader Decision-Making Process Model, which included the personality trait openness. An empirical study with retail middle managers was conducted to examine the relationships between feeling bored and decision-making competence (DMC). Regression models were fit to test whether feeling bored affects DMC and whether the associations were moderated by personality trait openness.

Findings – In the relationship between feeling bored and DMC, the moderating role of the personality trait openness was established. Results showed that feeling bored has a significant negative association with middle managers' confidence levels and risk perceptions when making decisions. Results also provided evidence that the learning component of personality trait openness plays a moderating role in the relationship between feeling bored and DMC. Most notably, the learning component of personality trait openness neutralizes the negative effects of feeling bored on managers' ability to remain appropriately confident when making decisions. In addition, the learning and inquisitive components temper the positive association between mood excited and risk perceptions. Limitations to the study are outlined.

Practical implications – Since trait openness (specifically its learning component) benefits decision-making contexts, it makes trait openness a worthy criterion to include when screening aspirant retail middle managers. The benefits of trait openness (specifically its learning component) for middle managers and their teams (especially when they are feeling bored) are indicated, since learning neutralizes the negative effect feeling bored has on appropriate confidence levels in retail management decision-making contexts.

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.