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Theil's approach to the measurement of inequality is set in the context of subsequent developments over recent decades. It is shown that Theil's initial insight leads naturally to a very general class of decomposable inequality measures. It is thus closely related to a number of other commonly used families of inequality measures.

We replicate and extend the social history treatment of the Berg, Dickhaut, and McCabe (1995) investment game, to further document how the reporting of financial history influences how laboratory societies organize themselves over time. We replicate Berg et al. (1995) by conducting a No History and a Financial History session to determine whether a report summarizing the financial transactions of a previous experimental session will significantly reduce entropy in the amounts sent by Investors and returned by Stewards in the investment game, as Berg et al. (1995) found. We extend Berg et al. (1995) in two ways. First, we conduct a total of five sessions (one No History and four Financial History sessions). Second, we introduce Shannon’s (1948) measure of entropy from information theory to assess whether the introduction of financial transaction history reduces the amount of dispersion in the amounts invested and returned across generations of players. Results across sessions indicate that entropy declined in both the amounts sent by Investors and the percentage returned by Stewards, but these patterns are weaker and mixed compared to those in the Berg et al. (1995) study. Additional research is needed to test how initial conditions, path dependencies, actors’ strategic reasoning about others’ behavior, multiple sessions, and communication may mediate the impact of financial history. The study’s multiple successive Financial History sessions and entropy measure are new to the investment game literature.

In a computer-based experimental study, we explored intensity of pleasant and unpleasant emotional experiences (affect), following immediate outcomes of risky choices over time under three levels of uncertainty (80%, 50%, 20%). We found that the intensity of pleasant affect initially increased linearly before suddenly reducing after the seventh task, and then resumed the linear upward trend. In contrast, the intensity of unpleasant affect cyclically changed after every five decision tasks, displaying a wave-like pattern. Interestingly, the 50% probability (maximum information entropy) group demonstrated patterns quite different to the other two groups (20%, 80%). For pleasant affect, this group reduced in positive affect significantly more than the other two groups after the seventh decision task. For unpleasant affect, the 50% group displayed an increasing negative affect trend, while the other two groups displayed a reducing negative affect trend. In sum, our findings reveal different temporal patterns of pleasant emotions from correct decisions and unpleasant emotions resulting from wrong decisions. We conclude that, consistent with the self-organization theory, these differences reflect nonlinear changes in the emotional system to cope with the challenge of uncertainty (or entropy).

Transformational learning outcomes of short-term faculty-led international service-learning experiences can by stymied by cultural shock and improperly facilitated programs. Moreover, dissonance in dimensions of the self in contrast to foreign traditions and social interactions can be especially salient in American student encounters in India. How students resolve and make meaning of their own emotional entropy is traced across two institutional programs, two courses (1 undergraduate and 1 graduate), and multiple India community partner sites. An evidence-based pedagogical model and strategies for preparation, praxis, and processing are offered in supporting student reflection of themselves as global beings and in development of global agency which is manifested as intrapersonal, interpersonal, intercultural, academic, and professional competencies.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.