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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.

Fuzzy numbers are often used to represent non-probabilistic uncertainty in engineering, decision-making and control system applications. In these applications, fuzzy arithmetic operations are frequently used for solving mathematical equations that contain fuzzy numbers. There are two approaches proposed in the literature for implementing fuzzy arithmetic operations: the α-cut approach and the extension principle approach using different t-norms. Computational methods for the implementation of fuzzy arithmetic operations in different applications are also proposed in the literature; these methods are usually developed for specific types of fuzzy numbers. This chapter discusses existing methods for implementing fuzzy arithmetic on triangular fuzzy numbers using both the α-cut approach and the extension principle approach using the min and drastic product t-norms. This chapter also presents novel computational methods for the implementation of fuzzy arithmetic on triangular fuzzy numbers using algebraic product and bounded difference t-norms. The applicability of the α-cut approach is limited because it tends to overestimate uncertainty, and the extension principle approach using the drastic product t-norm produces fuzzy numbers that are highly sensitive to changes in the input fuzzy numbers. The novel computational methods proposed in this chapter for implementing fuzzy arithmetic using algebraic product and bounded difference t-norms contribute to a more effective use of fuzzy arithmetic in construction applications. This chapter also presents an example of the application of fuzzy arithmetic operations to a construction problem. In addition, it discusses the effects of using different approaches for implementing fuzzy arithmetic operations in solving practical construction problems.

The ability to analyze social action as it unfolds on micro time scales – particularly the 24-hour day – is central to understanding group processes. This chapter describes a new approach to this undertaking, which treats individuals’ involvement in specific activities at specific times as bases for: (1) sequential linkages between activities; as well as (2) connections to others who engage in similar action sequences. This makes it possible to examine the emergence and internal functioning of groups using existing network analysis techniques.

We illustrate this approach with a specific application – a quantitative and visual comparison of the daily activity patterns of employed and unemployed people. We use data from 13,310 24-hour time diaries from the 2010–2013 American Time Use Surveys.

Employed and unemployed people engage in significantly different types of activities and at different times. Beyond this, network analyses reveal that unemployed individuals experience much lower levels of synchrony with each other than do employed individuals and have much less organized action sequences. In short, there is a chronic lack of prevailing norms regarding how unemployed people organize the 24-hour day.

Future research that uses time-stamped data can employ network methods to analyze and visualize how group members sequence and synchronize social action. These methods make it possible to study how the structure of social action shapes group and individual-level outcomes.

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

The current chapter is a tentative step toward investigating the allocation of advertising budget between the internet platform and the entity platform according to the long-term and short-term achievement of advertising investment. We provide a decision-making framework on how to allocate the advertising budget to the two platforms for the best results. The integrated effect of advertising investment consists of two parts. Goodwill and customer scale reflect the long-term achievement, and sale profit represents the short-term achievement. We selected some representative feasible investment plans as decision-making units (DMUs), and calculated the values of sale profit, goodwill, and customer scale as three outputs. To determine the best advertising investment plan, we use data envelopment analysis (DEA) model to seek efficient plans, and then determine the best one from those efficient plans through preference investigation and super-efficiency technique.

We contribute to the emerging literature on strategic corporate social responsibility (CSR) and its antecedents by undertaking a systematic analysis of the effect of rivalry on firm and industry CSR. We deal with the codetermination of competition and CSR by using instrumental variables in the firm-level analysis and by modeling it directly in the industry-level analysis. We find that higher intensity of rivalry and CSR of competitors increase firm CSR, ceteris paribus; however, in a more dynamic setting when firms can change their production output, more competition in fact decreases aggregate industry CSR. While seemingly contradictory, these findings suggest interesting implications for both managers and public policy makers.

Portfolios of mortgage loans played an important role in the Great Recession and continue to compose a material part of bank assets. This chapter investigates how cross-sectional dependence in the underlying properties flows through to the loan returns, and thus, the risk of the portfolio. At one extreme, a portfolio of foreclosed mortgage loans becomes a portfolio of real estate whose returns exhibit substantial cross-sectional and spatial dependence. Near the other extreme, almost all loans perform and yield constant returns, which do not correlate with other performing loan returns. This suggests that loan performance effectively censors the random returns of the underlying properties. Following the statistical properties of the correlations among censored variables, the authors build off this foundation and show how the loan return correlations will rise as economic conditions deteriorate and the defaulting loans reveal the underlying housing correlations. In this chapter, the authors (1) adapt tools from spatial statistics to document substantial cross-sectional dependence across house price returns and examine the spatial structure of this dependence, (2) investigate the nonlinear nature of correlations among loan returns as a function of the default rate and the underlying house price correlations, and (3) conduct a simulation exercise using parameters from the empirical data to show the implications for holding a portfolio of mortgages.

Tooling is a common component of an industrial product’s manufacture. Specific tooling is devised to serve the fabrication of a particular product, while generic tooling can be used in the manufacture of multiple products. In the latter case, companies are confronted with the problem of fairly allocating the indirect costs of the tooling. This article studies how to allocate costs of generic tooling to single production orders.

Ten allocation methods (AMs) are described that are in principle suited to the distribution of generic tooling costs to production orders. Since the presented methods have for the most part been discussed in differing contexts, we apply them to a specified generic tooling problem for comparison. Evaluation of the various methods is based on 16 criteria. Reasoning is supported by a computational Monte Carlo simulation. Furthermore, we suggest using the Analytical Hierarchy Process (AHP) to elaborate one final proposition concerning the most preferable allocation scheme.

The article reports the single allocation rules’ performances for different allocation scenarios. The described characteristics refer to fairness, efficiency, and simplicity as well as to empty-core performance. Using AHP analysis allows for the aggregation of the rules’ criteria ratings. Thus, especially suitable allocation schemes for the problem at hand are identified.

An allocation is required for budgeting reasons and also for the definition of projects’ bottom-up sales prices. Selecting the “right” AM is important, as a suboptimal AM can result in unfair allocation vectors, which will act as incentives to stop using the common resource, potentially leading to higher total costs.

Research on the comparison of AMs is typically performed for certain purposes, such as enterprise networks, horizontal cooperative purchasing scenarios, or municipal service units. This article will augment the research evaluating AMs by introducing a novel set of evaluation criteria and by providing an in-depth comparison of AMs suited for the allocation of generic tooling costs.