Human decisions, especially in management and personnel selection, are based on making judgments about people analytically and intuitively. Yet in business and scientific contexts, judgments are expected to be based on a rational analysis rather than intuitions or emotions. Intuition is often seen as something mystical that should not be trusted and thus eliminated from human decision-making. Our empirical and theoretical research shows that this is impossible when people are dealing with people. Instead, intuitions and emotions have significant power in the decision-making process. Neuroscience even shows that humans are incapable of switching off their emotions or intuitions when making decisions. Therefore, intuition and emotions as evolutionary achievements of human beings should be looked at more closely to use the wisdom they offer. This book provides an insight into the current state of research on rational-analytical procedures in personnel selection and complements this with research on intuitions and emotions in personnel diagnostics. By integrating scientifically verifiable rational-analytical decision-making procedures with the inner experiential knowledge of people, this book bridges two complementary ways of recognizing and making good decisions. It demonstrates how intuitions are developed and used in different fields of practice and cultures and how scientific research results from rational-analytical and intuitive-emotional selection procedures are successfully integrated by practitioners.

Contains nine papers that address the challenges in organizational change, report the results of change-related research, and advocate methodological advances in the field.

The implementation of waste-to-energy innovations is a shining example of advancement in sustainable tourism, characterized by the intertwining of environmental consciousness and hospitality. Through this transformational approach, businesses not only reduce their adverse effects on the environment by utilizing the potential of waste materials to generate energy, but they also open the way for a more sustainable and efficient operation model. Throughout history, managing this garbage has presented considerable issues, resulting in damage to the environment and the depletion of resources in several essential tourist destinations. These innovations seek to remedy this challenge. Application of Waste-to-Energy Innovations in Tourism offers a complete overview of waste-to-energy technologies that can be used in tourism facilities. It further assesses the environmental, economic, and social repercussions of implementing these technologies within the context of tourism facilities. Covering topics such as circular waste management, sustainability, and tourist experiences, this book is an excellent resource for industry professionals, policymakers, researchers, academicians, investors, non-governmental organizations, graduate and postgraduate students, educators, and more.

Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of IBM's menu-based SPSS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. A valuable resource for all beginning-to-intermediate-level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

Transfer of Training Skills into practice is a challenging endeavor in this dynamic world. This book is based on experience of training more than 1000 educators per year and following up on their experiences as they implernent what they have learnt into practice. The book is based on four school leaders who were showing improverment in the school management and students learning outcome. Their success was tracked to identify what made them transfer their skills into practice. This book offers insights on the barriers trainees should work to overcome on so that they are able to transfer their training skills into practice. The book is based on real school leaders where a detailed high skill research was implemented to understand what the school leaders went through and how they managed the barriers they faced. The book is for school leaders, managers, and school owners, training providers, universities and institutions working on leadership, training and transfer of training into practice. The researched insights are valuable to the readers as they receive guidance on how to implernent what they read into practice. Its a gem worth of applicable knowledge that transcend beyond the book.

Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python introduces readers to the foundational concepts of data analysis, cognitive science, and computational intelligence, including AI and Machine Learning. The book's focus is on fundamental ideas, procedures, and computational intelligence tools that can be applied to a wide range of data analysis approaches, with applications that include mathematical programming, evolutionary simulation, machine learning, and logic-based models. It offers readers the fundamental and practical aspects of cognitive science and data analysis, exploring data analytics in terms of description, evolution, and applicability in real-life problems.The authors cover the history and evolution of cognitive analytics, methodological concerns in philosophy, syntax and semantics, understanding of generative linguistics, theory of memory and processing theory, structured and unstructured data, qualitative and quantitative data, measurement of variables, nominal, ordinals, intervals, and ratio scale data. The content in this book is tailored to the reader's needs in terms of both type and fundamentals, including coverage of multivariate analysis, CRISP methodology and SEMMA methodology. Each chapter provides practical, hands-on learning with real-world applications, including case studies and Python programs related to the key concepts being presented. - Demystifies the theory of data analytics using a step-by-step approach - Covers the intersection of cognitive science, computational intelligence, and data analytics by providing examples and case studies with applied algorithms, mathematics, and Python programming code - Introduces foundational data analytics techniques such as CRISP-DM, SEMMA, and Object Detection Models in the context of computational intelligence methods and tools - Covers key concepts of multivariate and cognitive data analytics such as factor analytics, principal component analytics, linear regression analysis, logistic regression analysis, and value chain applications

Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them. Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use.

In our contemporary era, while diversity is acknowledged, true inclusion remains an elusive goal, as society grapples with multifaceted challenges. The "great resignation" and movements like #MeToo have exposed workplace culture issues, while events like Black Lives Matter protests underscored glaring disparities. Simultaneously, rapid technological advancements introduce new risks, from cyber exploitation to biased AI. These complexities demand innovative solutions that address these challenges, fostering environments of genuine respect, understanding, and collaboration. Applied Research Approaches to Technology, Healthcare, and Business, edited by Dr. Darrell Norman Burrell, emerges as a transformative force. This dynamic anthology presents insights, research, and actionable recommendations from diverse fields and perspectives, taking an interdisciplinary approach to unravel workplace dynamics, health disparities, and technological advancements. Topics include inclusive leadership, equitable technology, bias in AI, and forging collaboration across religious and cultural differences. By harmonizing voices and expertise, this book offers transformative approaches for individuals, educators, and professionals. This rich resource empowers readers to navigate today's societal challenges, equipping them to become architects of a more inclusive, equitable, and harmonious future across technology, healthcare, and business.