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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.

Multinational enterprises (MNEs) are increasingly compelled to consider the United Nation’s sustainable development goals (SDGs). These goals are complex and may cause internal goal conflicts for companies. To stay the course, MNEs will benefit from an ethical compass enabling them to take on leading roles in driving change towards a better future. We argue that ethical leadership in this new business landscape is bolstered by virtue ethics. MNEs with genuine ethical groundings will be equipped to make decisions in complex situations where the needs of a variety of stakeholders must be considered. The purpose of this chapter is to conceptually and empirically explore an MNE’s implementation of a particular SDG, through an ethical leadership lens. We contribute to international management and international business literature by offering a framework to analyse MNEs’ pursuit of SDGs.

This chapter extends the work of Baltagi, Bresson, Chaturvedi, and Lacroix (2018) to the popular dynamic panel data model. The authors investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in two ways. First, the authors consider the ε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε-contamination priors use Zellner’s (1986) g-priors for the variance–covariance matrices. The authors propose a general “toolbox” for a wide range of specifications which includes the dynamic panel model with random effects, with cross-correlated effects à la Chamberlain, for the Hausman–Taylor world and for dynamic panel data models with homogeneous/heterogeneous slopes and cross-sectional dependence. Using a Monte Carlo simulation study, the authors compare the finite sample properties of the proposed estimator to those of standard classical estimators. The chapter contributes to the dynamic panel data literature by proposing a general robust Bayesian framework which encompasses the conventional frequentist specifications and their associated estimation methods as special cases.

This paper addresses revolutionary changes in the education, fertility and market work of U.S. families formed in the 1870s–1920s: Fertility fell from 5.3 to 2.6; the graduation rate of their children increased from 7% to 50%; and the fraction of adulthood wives devoted to market-oriented work increased from 7% to 23% (by one measure).

These trends are addressed within a unified framework to examine the ability of several proposed mechanisms to quantitatively replicate these changes. Based on careful calibration, the choices of successive generations of representative husband-and-wife households over the quantity and quality of their children, household production, and the extent of mother’s involvement in market-oriented production are simulated.

Rising wages, declining mortality, a declining gender wage gap, and increased efficiency and public provision of schooling cannot, individually or in combination, reduce fertility or increase stocks of human capital to levels seen in the data. The best fit of the model to the data also involves: (1) a decreased tendency among parents to view potential earnings of children as the property of parents and (2) rising consumption shares per dependent child.

Greater attention should be given the determinants of parental control of the work and earnings of children for this period.

One contribution is the gathering of information and strategies necessary to establish an initial baseline, and the time paths for parameters and targets for this period beset with data limitations. A second contribution is identifying the contributions of various mechanisms toward reaching those calibration targets.

This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the second objective is to minimize the carbon emission resulting from production, transportation, and disposal processes using carbon cap and carbon tax regularity policies. In the third objective, we maximize the service level of retailers by using maximum covering location as a measure of service level. To model the proposed problem, a physical programming approach is developed. This work contributes to the literature in designing an optimum CLSC network considering the service level objective and product substitution.