This book presents contributions of intelligent management theories and models for a more effective management of sustainable business practices in competitive, profitable and socially responsible organizations. It communicates the latest developments and thinking on the sustainability and intelligent management subjects worldwide, increasing the knowledge and effectiveness of all those involved in these areas whether in the profit or non-profit sectors or in the public or private sectors.

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspects of classical environmental solution techniques to its intelligent counterpart, the book presents a dynamic snapshot on the field that is expected to stimulate new directions and stimulate new ideas and developments.

This book discusses issues related to ICT, intelligent systems, data science, AI, machine learning, sustainable development and overall their impacts on sustainability. It provides an overview of the technologies of future. The book also discusses novel intelligent algorithms and their applications to move from a data-centric world to sustainable world. It includes research paradigms on sustainable development goals and societal impacts. The book provides an overview of cutting-edge techniques toward sustainability and ideas to help researchers who want to understand the challenges and opportunities of using smart management perspective for sustainable society. It serves as a reference to wide ranges of readers from computer science, data analysts, AI technocrats and management researchers.

This book consolidates and summarizes smart technologies like IoT, edge computing, and AI used in different aspects of waste material management, mitigation, and recycling for a sustainable environment. One of the cases explains how IoT-based systems and wireless sensors can be used to continuously detect common pollutants such as volatile organic compounds (VOCs), carbon monoxide, and particulate matter (PM) and how the data collected are used to assess the overall air quality and determine actions for improvements. A collection of practical case studies, this book provides a comprehensive knowledge in smart waste management to readers in universities, research centers, and industries.

Social intelligence is defined as the ability to be aware of relevant social situational contexts; to deal with the contexts or challenges effectively; to understand others' concerns, feelings, and emotional states; and to interact appropriately in social situations and build and maintain positive relationships with others. Intelligence, Sustainability, and Strategic Issues in Management analytically discusses this concept within administrative and entrepreneurial managerial business environments.The volume opens with a study of academic department chairs' social intelligence and faculty members' satisfaction with annual evaluation of teaching and research at a US university. The seven other articles cover a range of topics, including a neurocognitive model of entrepreneurial opportunity, ownership dilution, sustainability in inventory management, the role of status in imitative behaviour, the negative impacts of embeddedness, product quality failures in international sourcing, and employers' use of social media in employment decisions.In addition to the articles, the volume also features a case study, "From Social Entrepreneur to Social Enterprise," a research note, "Reducing Job Burnout through Effective Conflict Management Strategy," five book reviews, and a list of books received.

In the midst of climate change, responsible business practices and ecological modernization become essential tools for the promotion of sustainability. Due to the current level of demand for eco-friendly products and services, there is a need for green training and green human resource development to support green creativity and eco-innovation for sustainability. By incorporating green initiatives into human resource practices, organizations can maintain a positive impact on the environment. With a full understanding of sustainable business practices, positive impacts on the environmental management field become easier to produce. Human Resource Management Practices for Promoting Sustainability is a pivotal reference source that explores the incorporation of green initiatives into all aspects of human resource management practices in a variety of industries. The book delivers a discussion on green human capital, collective green intelligence, and competencies that are essential to cope with the challenges in Industry 4.0. It also provides a basis for green recruitment and selection processes as a way of promoting pro-environmental behavior in the labor markets. While highlighting a broad range of topics including employee relations, knowledge management, and recruitment, this book is ideally designed for executives, entrepreneurs, human resource managers, academicians, researchers, and students. The book is also suitable for conventional and corporate universities looking to meet sustainable development goals as well as policymakers as it provides a guideline in designing and implementing green creativity and eco-innovation based on a wide range of global issues confronting sustainability in the Fourth Industrial Revolution.

Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. Introduces novel intelligent techniques needed to address environmental pollution for the well-being of the global environment Offers perspectives on the design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies surrounding the monitoring and mitigation of environmental pollution Puts forth insights on future generation intelligent pollution monitoring techniques