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This chapter overviews organizational neuroscience (ON), covering the past, present, and future of this growing field of inquiry. First, we define ON and clarify the boundaries of the field. Second, we describe the evolution of ON by starting with early papers that tended to discuss the potential of ON to benefit both research and practice. Throughout its development, debates have abounded about the value of ON. Such debates are often related to challenges in collecting, integrating, interpreting, and using information from the brain-level of analysis. It is time for the field to move beyond these debates to focus on applying neuroscience to further theory development and reveal more comprehensive answers to research questions of importance to both academics and practitioners. Third, we propose and describe future research directions for ON. The research directions that we propose are merely a sample of the many paths along which ON inquiry can move forward. Fourth, we outline potential practical implications of ON, including: training and development, job design, high-performance assessment, motivating communications, and conflict prevention. Finally, we draw conclusions about ON as it stands today, address challenges in developing ON, and point out opportunities. We conclude with takeaways and highlight the importance of ON for both academics and practitioners.

Mobile devices, through their capacity to enable anytime-anywhere learning as well as capture, annotate and share multimedia, offer entirely new ways for students to learn. This chapter provides review of mobile learning with a particular focus on learning design. First various definitions and characteristics of mobile learning are examined in order to establish a common understanding of its boundaries and meaning. Example uses of mobile learning in schools and higher education are described as a way to provide a more concrete understanding of design possibilities. Benefits of mobile learning are unpacked, as distilled from the literature, including the ability to provide flexible, accessible, authentic, personalized, ubiquitous and seamless learning. Mobile learning issues are also examined, including technical problems, cognitive load issues, distraction, equity and safety. A primary school science and a university pre-service teacher education vignette are described so as to offer a more in-depth illustration of what mobile learning can look like and achieve in practice. Finally, mobile learning research findings and observations are synthesized into recommendations, to inform and guide evidence-based mobile learning design practices. Opportunities for future research and investigation are also discussed.

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.