Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.

Reimagining Digital Learning for Sustainable Development is a comprehensive playbook for education leaders, policy makers, and other key stakeholders leading the modernization of learning and development in their institutions as they build a high value knowledge economy and prepare learners for jobs that don't yet exist. Currently, nearly every aspect of human activity, including the ways we absorb and apply learning, is influenced by disruptive digital technologies. The jobs available today are no longer predicators of future employment, and current and future workforce members will need to augment their competencies through a lifetime of continuous upskilling and reskilling to meet the demands of the Fourth Industrial Revolution. This book features curated insights and real-world cases from thought leaders throughout the world and identifies major shifts in content formats, pedagogic approaches, technology frameworks, user and design experiences, and learner roles and expectations that will reshape our institutions, including those in emerging economies. The agile, lean, and cost-effective strategies proposed here will function in scalable and flexible bandwidth environments, enabling education leaders and practitioners to transform brick-and-mortar learning organizations into digital and blended ecosystems and to achieve the United Nation’s ambitious Sustainable Development Goals by 2030. Chapter 18 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

This book offers a unique view of how innovation and competitiveness improve when organizations establish alliances with partners who have strong capabilities and broad social capital, allowing them to create value and growth as well as technological knowledge and legitimacy through new knowledge resources. Organizational intelligence integrates the technology variable into production and business systems, establishing a basis to advance decision-making processes. When strategically integrated, these factors have the power to promote enterprise resilience, robustness, and sustainability. This book provides a unique perspective on how knowledge, information, and data analytics create opportunities and challenges for sustainable enterprise excellence. It also shows how the value of digital technology at both personal and industrial levels leads to new opportunities for creating experiences, processes, and organizational forms that fundamentally reshape organizations.

We are living at the dawn of what has been termed 'the fourth paradigm of science, ' a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power-manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data-intensive science and its application, particularly in relation to sustainability.

Global Environmental Sustainability: Case Studies and Analysis of the United Nations' Journey toward Sustainable Development presents an integrated, interdisciplinary analysis of sustainable development, addressing global environmental problems in the contemporary world. It critically examines current actions being taken on global and local scales, particularly in relation to the UN's efforts to promote sustainable development. This approach is supported by empirical analysis, drawing upon a host of interweaving insights spanning economics, politics, ecology, environmental philosophy, and ethics, among others. As a result, it offers a comprehensive and well-balanced assessment of the overall perspective of sustainable development supported by in-depth content analysis, theoretical evaluation, empirical and actual case studies premised on solid data, and actual field work. Also, the book marks a milestone in placing the Covid-19 pandemic into a perspective for understanding the universality of human collective environmental behavior and action.By utilizing in-depth analysis, both quantitative and qualitative, and challenging the status quo of what is expected in the global approach to sustainable development, Global Environmental Sustainability provides the theory and methodology of empirical sustainable development which is especially germane to our advanced society today, which is deeply entrenched in a crisis of environmental morality. More particularly, it serves as a salient source of moral reconstitution of society grounded in empirical reality to liberate man's excessive spirit of individualism and self-aggrandizement to the detriment of the environment. Epistemologically, the book furnishes a remarkable tour de force with a new level of analytical insight to help researchers, practitioners, and policymakers in sustainability and environmental science, as well as the many other disciplines involved in sustainable development, to better understand sustainability from a new perspective and provides a methodological direction to pursue solutions going forward. - Provides a systematic exposition of sustainable development in all its complexity, with all the chapters complementing each other in an integral way - Presents extensive empirical evidence of various environmental problems across the world including China, the United States, Canada, Southeast Asia, South America and Africa, and the extent to which the United Nations has succeeded in driving toward global environmental sustainability - Provides a cogent examination of the treatment of our global commons by some of the world's most powerful leaders - Includes data from field studies and in-depth interviews with indigenous people in Borneo's rainforests of the Malaysian state of Sarawak most affected by environmental change

This book provides insight for researchers and decision-makers on the application of data in the entrepreneurship and sustainable development sector. This book covers how Big Data for Industry 4.0 and entrepreneurship are effective in resolving business, social, and economic problems. The book discusses how entrepreneurs use Big Data to cut costs and minimize the waste of time. It offers how using Big Data can increase efficiency, enables the studying of competitors, can improve the pricing of products, increase sales and loyalty, and can ensure the right people are hired. The book presents how decision-makers can make use of Big Data to resolve economic and social problems. Analyze the development of the economy and enhance the business climate. This book is for researchers, PhD students, and entrepreneurs and can also be of interest for transforming governments as well as businesses.

This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.