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This book contains the refereed proceedings of the 2nd Advances in Business Research International Conference (ABRIC2016). Chapters in the book address the theme of Advancing Knowledge, Connecting the World, reflecting on the emerging issues in various business management fields and the interconnections of multiple disciplines for creating knowledge advancement. Papers were carefully reviewed and selected and grouped into four main themes: economic and finance, marketing and communications, management, and information technology in business. The book serves as a helpful resource for students and researchers of business management, especially in understanding issues and cases of business in emerging economies and markets.
From traditional brick and mortar to new start-ups, businesses are harnessing the power of digital enterprise as a cost-effective model to deliver goods and services online. Digital enterprise strategy is adopted for transforming business, streamlining processes, and making the best use of online technologies to enhance interaction with customers and employees and deliver excellent customer experience in real time. Digital enterprises increasingly need digital workers to establish greater digital skills to bear on every activity and to drive management, strategy, and innovation, which are key for digital enterprise transformation. The Handbook of Research on Management and Strategies for Digital Enterprise Transformation is a crucial reference source that discusses leveraging technology for the customers’, employees’, and suppliers’ benefit, as well as integrating complex processes to management, marketing, production, manufacturing, and financial systems. Combining management, strategy, technology, and digital enterprise topics into one book provides the reader with a holistic understanding of the new developments in these emerging fields. This study will also include key topics of interest on how to address structural changes underway in the local and global business environment for digital enterprise transformation. Featuring research on topics such as e-commerce, organizational learning, and agile management, this book is ideally designed for business professionals, policymakers, researchers, students, and managers.
In today’s rapidly evolving society, there has been an increase in technologies and systems available to support the elderly throughout various aspects of life. We have come a long way in the quality of life we can offer our aging populations in recent years due to these technological innovations, medical advancements, and research initiatives. However, further study of these developments is crucial to ensure they are utilized to their utmost potential in securing a healthier elderly population. The Research Anthology on Supporting Healthy Aging in a Digital Society discusses the current challenges of aging in the modern world as well as recent developments in medicine and technology that can be used to improve the quality of life of elderly citizens. Covering a wide range of topics such as smart homes, remote healthcare, and aging in place, this reference work is ideal for healthcare professionals, gerontologists, therapists, government officials, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.
Service organizations are grappling with unprecedented challenges in maintaining and enhancing productivity. As the landscape evolves, traditional approaches to service operations become obsolete, necessitating a deep understanding of the intricate dynamics at play. Innovative Technologies for Increasing Service Productivity delves into this urgent issue, offering a comprehensive exploration of the trends and challenges confronting service industries. The book sheds light on the impact of digital transformation, emerging technologies, and disruptive business models, serving as a guide for navigating the complexities of service productivity in an ever-changing environment. As a groundbreaking solution, this book not only identifies challenges but provides various solutions for service organizations to thrive amidst technological disruption. Its unique selling points lie in the breadth of its coverage, spanning diverse service industries and dissecting the symbiotic relationship between technology and productivity. Offering practical strategies and tools, the book equips service professionals with the means to enhance productivity, quality, and customer experience. By connecting the gap between theoretical insights and practical implementation, it stands as a valuable resource for academics, researchers, and service managers seeking innovative solutions to the evolving landscape of service productivity.
In today’s modern business world, the dominant factor of any organization's success is human capital. Appropriately acquiring and managing talented staff is crucial to the growth and development of companies and provides them with a considerable competitive advantage in the industry. Further study on the importance of talent management is required to ensure businesses are able to thrive in the present environment. Post-Pandemic Talent Management Models in Knowledge Organizations discusses strategic human resource management and the talent management of post-modern knowledge-based organizations during the COVID-19 pandemic and post-pandemic paradigm. Covering critical topics such as organizational performance and creative work behavior, this major reference work is ideal for managers, business owners, entrepreneurs, academicians, researchers, scholars, instructors, and students.
Pricing or benchmarking is a process of evaluating the performance of a financial company’s products and services or systems, against other businesses, considered to be at the top of their field, by applying a measurement of “best in performance.” This book includes contributions from the leading global experts in the field who tackle topics such as whether the Islamic financial system has been dependent on the LIBOR / EURIBOR in its benchmarking exercises to date, and thus, whether it will be affected negatively by the predicted non-existence of the LIBOR / EURIBOR from 2021 onwards. They also address the question of whether the Islamic financial system requires benchmarking of its products and services and consider the emergence of Sharī ͑ah-justified benchmarking in today’s Islamic financial system. Additionally, they look at how benchmarking formulas should be adapted to ensure the satisfaction of customers within the principles of Maqasid al-Sharī ͑ah. It takes a legal and institutional approach to the subject, which readers will find particularly valuable, as there are various forms of Islamic finance institutions that do not conform to established models in the finance industry. Furthermore, there are emerging business models that will benefit from this line of investigation. This book offers a timely analysis of these issues and redresses the existing misconceptions and misinterpretations pertaining to benchmarking, in an Islamic finance context, and, as such, provides guidance and strategies for future directions. It will appeal to researchers of Islamic banking, finance, and insurance, as well as, practitioners, particularly standard setting bodies, regulators, and policy makers.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
This book brings together real-world cases illustrating how to analyse volatile financial time series in order to provide a better understanding of their past behavior and robust forecasting of their future behavioural patterns. Using time series data from diverse financial sectors, it shows how the concepts and techniques of statistical analysis, machine learning, and deep learning are applied to build robust predictive models, as well as the ways in which these models can be used for forecasting the future prices of stocks and constructing profitable portfolios of investments. All the concepts and methods used in the book have been implemented using Python and R languages on TensorFlow and Keras frameworks. The volume will be particularly useful for advanced postgraduate and doctoral students of finance, economics, econometrics, statistics, data science, computer science, and information technology.
This comprehensive edited volume showcases the latest breakthroughs and innovative research in the rapidly evolving field of data science, and brings together contributions from leading experts and researchers who push the boundaries of the field, offering readers a deep insight into the diverse facets of this transformative discipline. Spanning a wide spectrum of topics, the chapters in this volume cover key areas such as machine learning, artificial intelligence, statistical analysis, and ethical considerations in data science. Each chapter is a testament to the ongoing quest for knowledge and the relentless pursuit of excellence in harnessing the power of data for meaningful insights and actionable intelligence. Whether you're an experienced data scientist, a researcher exploring the frontiers of the field, or a novice eager to grasp the fundamentals, this edited volume serves as a valuable resource. The compilation not only highlights the current state of data science but also anticipates future trends, paving the way for continued advancements and paradigm shifts in the way we approach, analyze, and leverage data.
Businesses consistently work on new projects, products, and workflows to remain competitive and successful in the modern business environment. To remain zealous, businesses must employ the most effective methods and tools in human resources, project management, and overall business plan execution as competitors work to succeed as well. Advanced Methodologies and Technologies in Business Operations and Management provides emerging research on business tools such as employee engagement, payout policies, and financial investing to promote operational success. While highlighting the challenges facing modern organizations, readers will learn how corporate social responsibility and utilizing artificial intelligence improve a company’s culture and management. This book is an ideal resource for executives and managers, researchers, accountants, and financial investors seeking current research on business operations and management.