Information Technology, Management and Operations Research Practices – serie

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making.The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction.Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

This book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management.Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance. It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements.The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology. The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners.Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India. He has contributed in organising the INSPIRE Science Internship Camp. He is a member of the Institute of Electrical and Electronics Engineers and is a life member of the Computer Society of India. His research interests include the Internet of Things, data mining, cloud computing, image processing and knowledge-based systems. He holds nine patents in Intellectual Property, India. He has authored four books in the areas of data mining, image processing and LaTex.Dr. G. Suseendran is an assistant professor, Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, the Internet of Things, data mining, cloud computing, image processing, knowledge-based systems, and Web information exploration. He has published more than 75 research papers in various international journals such as Science Citation Index, Springer Book Chapter, Scopus, IEEE Access and UGC-referred journals. Prof. Trung-Nghia Phung is an associate professor and Head of Academic Affairs, Thai Nguyen University of Information and Communication Technology (ICTU). He has published more than 60 research papers. His main research interest lies in the field of speech, audio, and biomedical signal processing. He serves as a technical committee program member, track chair, session chair, and reviewer of many international conferences and journals. He was a co-Chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a Session Chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).

Quality of Life: An Interdisciplinary Perspective presents the Quality of Life using a contemporary and interdisciplinary approach. Various socio-cultural, spiritual, technological, and human factors aspects, which have an immense bearing on our lives, are an integral part of this book.This book highlights cultural differences in terms of Quality of Life. It recognizes the presence of cultural differences resulting from the social status attributed to an individual’s age, gender, class, race, and ethnicity. It can be used as a guide in the field of global well-being and for future research. It presents clues to complex problems and empirical materials, and attempts to bring out a more comprehensive picture of global and contemporary Quality of Life and well-being. This book can also fill a gap in teaching and research.Those who will find this book useful are researchers, academicians, practitioners, and students of management, behavioral science, human factors, psychology, health economics, sociology, public health, and politics.

The entrance of fast-paced technology into the workplace necessitates a proper re-look into performance management whether it is in education, marketing, finance, or information technology. Maintaining happiness and wellbeing despite the pressure of performance at work is a serious challenge. Happiness is not only important for work performance, but also for the physical and mental health of human beings. This book provides different concepts, theories, and methods to better understand the relationship between performance and happiness in the context of work in this information and technology era. Various domains of performance management are covered in the context of management and information technology, including topics related to the performance of digital wallets from the customer's point of view; evaluating the sustainability of micro-finance institutions; challenges in employee retention; problems the workforce faces in IT and management; dimensions of happiness for women in the workplace; the role of happiness in building a meaningful life; and the quality of work life.The findings are useful for practical applications in management and business scenarios. They also provide informative insights for researchers, academicians, industry professionals, and scholars.

This book provides different approaches used to analyze, draw attention, and provide an understanding of the advancements in the optimization field across the globe. It brings all of the latest methodologies, tools, and techniques related to optimization and industrial engineering into a single volume to build insights towards the latest advancements in various domains.Applications of Advanced Optimization Techniques in Industrial Engineering includes the basic concept of optimization, techniques, and applications related to industrial engineering. Concepts are introduced in a sequential way along with explanations, illustrations, and solved examples. The book goes on to explore applications of operations research and covers empirical properties of a variety of engineering disciplines. It presents network scheduling, production planning, industrial and manufacturing system issues, and their implications in the real world.The book caters to academicians, researchers, professionals in inventory analytics, business analytics, investment managers, finance firms, storage-related managers, and engineers working in engineering industries and data management fields.

This book provides different approaches used to analyze, draw attention, and provide an understanding of the advancements in the optimization field across the globe. It brings all of the latest methodologies, tools, and techniques related to optimization and industrial engineering into a single volume to build insights towards the latest advancements in various domains.Applications of Advanced Optimization Techniques in Industrial Engineering includes the basic concept of optimization, techniques, and applications related to industrial engineering. Concepts are introduced in a sequential way along with explanations, illustrations, and solved examples. The book goes on to explore applications of operations research and covers empirical properties of a variety of engineering disciplines. It presents network scheduling, production planning, industrial and manufacturing system issues, and their implications in the real world.The book caters to academicians, researchers, professionals in inventory analytics, business analytics, investment managers, finance firms, storage-related managers, and engineers working in engineering industries and data management fields.

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements.The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology. The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners.Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India. He has contributed in organising the INSPIRE Science Internship Camp. He is a member of the Institute of Electrical and Electronics Engineers and is a life member of the Computer Society of India. His research interests include the Internet of Things, data mining, cloud computing, image processing and knowledge-based systems. He holds nine patents in Intellectual Property, India. He has authored four books in the areas of data mining, image processing and LaTex.Dr. G. Suseendran is an assistant professor, Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, the Internet of Things, data mining, cloud computing, image processing, knowledge-based systems, and Web information exploration. He has published more than 75 research papers in various international journals such as Science Citation Index, Springer Book Chapter, Scopus, IEEE Access and UGC-referred journals. Prof. Trung-Nghia Phung is an associate professor and Head of Academic Affairs, Thai Nguyen University of Information and Communication Technology (ICTU). He has published more than 60 research papers. His main research interest lies in the field of speech, audio, and biomedical signal processing. He serves as a technical committee program member, track chair, session chair, and reviewer of many international conferences and journals. He was a co-Chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a Session Chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).

This book describes the uses of different mathematical modeling and soft computing techniques used in epidemiology for experiential research in projects such as how infectious diseases progress to show the likely outcome of an epidemic, and to contribute to public health interventions.This book covers mathematical modeling and soft computing techniques used to study the spread of diseases, predict the future course of an outbreak, and evaluate epidemic control strategies. This book explores the applications covering numerical and analytical solutions, presents basic and advanced concepts for beginners and industry professionals, and incorporates the latest methodologies and challenges using mathematical modeling and soft computing techniques in epidemiology.Primary users of this book include researchers, academicians, postgraduate students, and specialists.

This book shows how to build and maintain a distinctive and credible employer brand and develop a set of relevant success metrics to help measure return on investment (ROI). Starting with the current interest in employer branding, this book looks at the historical roots of brand management and the practical steps to achieve employer brand management success.The book will review the pressures that have generated current interest in employer branding. It goes on to look at the historical roots of brand management and the practical steps necessary to achieve employer brand management success. The book includes the business case, research, positioning, implementation, management and measurement, and case studies of big-named employer brand stories.This book will provide new insights into the field of employer branding and provide directions and tools for organizational brand building. It will be beneficial for research scholars, engineers, practitioners, and management students.

This book shows how to build and maintain a distinctive and credible employer brand and develop a set of relevant success metrics to help measure return on investment (ROI). Starting with the current interest in employer branding, this book looks at the historical roots of brand management and the practical steps to achieve employer brand management success.The book will review the pressures that have generated current interest in employer branding. It goes on to look at the historical roots of brand management and the practical steps necessary to achieve employer brand management success. The book includes the business case, research, positioning, implementation, management and measurement, and case studies of big-named employer brand stories.This book will provide new insights into the field of employer branding and provide directions and tools for organizational brand building. It will be beneficial for research scholars, engineers, practitioners, and management students.

This book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism.Sustainability, Big Data, and Corporate Social Responsibility: Evidence from the Tourism Industry offers a theoretical and empirical framework in the field of digital transformation and applies it to the tourism sector. It discusses Big Data used with CSR and sustainability for the improvement of innovation and highlights the challenges and prospects. It presents a modern insight and approach for use by decision-makers as an application to solve various problems and explores how data collection can shed light on consumer behavior making it possible to account for existing situations and plan for the future.This book is intended to provide a modern insight for researcher, students, professionals, and decision-makers on the application of Big Data to improve CSR and sustainability in the tourism sector.

This book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism.Sustainability, Big Data, and Corporate Social Responsibility: Evidence from the Tourism Industry offers a theoretical and empirical framework in the field of digital transformation and applies it to the tourism sector. It discusses Big Data used with CSR and sustainability for the improvement of innovation and highlights the challenges and prospects. It presents a modern insight and approach for use by decision-makers as an application to solve various problems and explores how data collection can shed light on consumer behavior making it possible to account for existing situations and plan for the future.This book is intended to provide a modern insight for researcher, students, professionals, and decision-makers on the application of Big Data to improve CSR and sustainability in the tourism sector.

This book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management.Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance. It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.

This book describes the uses of different mathematical modeling and soft computing techniques used in epidemiology for experiential research in projects such as how infectious diseases progress to show the likely outcome of an epidemic, and to contribute to public health interventions.This book covers mathematical modeling and soft computing techniques used to study the spread of diseases, predict the future course of an outbreak, and evaluate epidemic control strategies. This book explores the applications covering numerical and analytical solutions, presents basic and advanced concepts for beginners and industry professionals, and incorporates the latest methodologies and challenges using mathematical modeling and soft computing techniques in epidemiology.Primary users of this book include researchers, academicians, postgraduate students, and specialists.

Quality of Life: An Interdisciplinary Perspective presents the Quality of Life using a contemporary and interdisciplinary approach. Various socio-cultural, spiritual, technological, and human factors aspects, which have an immense bearing on our lives, are an integral part of this book.This book highlights cultural differences in terms of Quality of Life. It recognizes the presence of cultural differences resulting from the social status attributed to an individual’s age, gender, class, race, and ethnicity. It can be used as a guide in the field of global well-being and for future research. It presents clues to complex problems and empirical materials, and attempts to bring out a more comprehensive picture of global and contemporary Quality of Life and well-being. This book can also fill a gap in teaching and research.Those who will find this book useful are researchers, academicians, practitioners, and students of management, behavioral science, human factors, psychology, health economics, sociology, public health, and politics.

This book explores the link between entrepreneurship and innovation, providing an understanding of the latest developments in the field. It explores numerous challenges to entrepreneurship, such as failures and socio-economic issues, and presents concepts, models, and implementation strategies for Industry 4.0.Industry 4.0 presents unique challenges and unique opportunities to entrepreneurs. Social, techno, and women’s entrepreneurship, among other business sectors and domains, are discussed in this new context. This book highlights the strategies of successful start-up organizations, focusing on the most critical factors for starting a new enterprise in today’s business environment, and provides efficient remedies for common problems. These strategies and solutions will help build a sustainable development model for developing economies and contribute to a global awareness of the entrepreneurship environment.Entrepreneurial Innovations, Models, and Implementation Strategies for Industry 4.0 is both a practical guide for new entrepreneurs to establishing start-ups and an enlightening collection of research for graduate students, postgraduate students, scholars, and academicians across all disciplines. Policymakers will also benefit from this book’s understanding of entrepreneurial ecosystems and their applications.

This book explores the link between entrepreneurship and innovation, providing an understanding of the latest developments in the field. It explores numerous challenges to entrepreneurship, such as failures and socio-economic issues, and presents concepts, models, and implementation strategies for Industry 4.0.Industry 4.0 presents unique challenges and unique opportunities to entrepreneurs. Social, techno, and women’s entrepreneurship, among other business sectors and domains, are discussed in this new context. This book highlights the strategies of successful start-up organizations, focusing on the most critical factors for starting a new enterprise in today’s business environment, and provides efficient remedies for common problems. These strategies and solutions will help build a sustainable development model for developing economies and contribute to a global awareness of the entrepreneurship environment.Entrepreneurial Innovations, Models, and Implementation Strategies for Industry 4.0 is both a practical guide for new entrepreneurs to establishing start-ups and an enlightening collection of research for graduate students, postgraduate students, scholars, and academicians across all disciplines. Policymakers will also benefit from this book’s understanding of entrepreneurial ecosystems and their applications.

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making.The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction.Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

This handbook contributes to the advanced knowledge of talent management and learning organizations in the post-pandemic era. It provides new insights and contributions to the existing literature on business organizations through the dissemination of information as well as empirical pieces of evidence from various parts of the world. The focus of this handbook is on advancing talent management strategies and learning organizations through knowledge sharing on various platforms, geographical locations, and diverse groups of intellectuals having diversified experience, knowledge, and expertise. It also focuses on innovation and creativity based on global competition, advanced communication, and management technologies and on changing customers’ behaviors and needs in the post-pandemic era.The Handbook of Talent Management and Learning Organizations: A Post-Pandemic Perspective explores theoretical and empirical artifacts and different approaches to enhance the understanding of the relationship between talent management and learning organization. It provides solutions to managers and consultants who are facing problems while managing talent due to workplace changes post-pandemic and shows the connection between innovation and creativity as talent management enhances organizational learning, knowledge-sharing culture, innovation capabilities, and creativity. The handbook also offers strategies and solutions to manage talent virtually and presents future research directions and solutions to contemporary issues related to talent management and learning organizations moving forward.This handbook targets graduate students, research scholars, practitioners, employees, consultants, corporate bodies, and technocrats. It will be very helpful to managers and consultants who are facing problems with managing talent due to workplace changes after the pandemic.

Focusing on the business implications of green innovation, this book describes the sheer impact, spread, and opportunities arising every day, and how business leaders can implement green innovative practices today to realize tangible as well as intangible business advantages in the future. Green Innovations for Industrial Development and Business Sustainability: Models and Implementation Strategies works as a guide for green innovation that focuses on enterprise applications for those tasked with leveraging green practice adoption to enhance the productivity of their organization. The book offers the ability to understand the latest developments in green innovations and their business applications along with their implications in various domains from manufacturing to marketing.Front-line decision-makers can use this book as a practical guide for capitalizing on the latest green practices, adoptions, and transformations. Researchers, business leaders, postgraduate, and graduate students will find this book useful with its presentation of state-of-the-art research together with the current and future challenges of building green practice models and applications for organization and business operations.