Data Analytics Applications In Emerging Markets

This book analyzes the impact of technology in emerging markets by considering conditions and the history of how it has changed the way of working and market development in such contexts. The book delves into key areas such as fintech enterprises, artificial intelligence, pension funds, stock markets, and energy markets though applied studies and research. This book is a useful read for practitioners and scholars interested in how technology has and continues to change the way in which development is defined and achieved, particularly in emerging markets.

This book focuses on understanding the analytics knowledge management process and its comprehensive application to various socioeconomic sectors. Using cases from Latin America and other emerging economies, it examines analytics knowledge applications where a solution has been achieved. Written for business students and professionals as well as researchers, the book is filled with practical insight into applying concepts and implementing processes and solutions. The eleven case studies presented in the book incorporate the whole analytics process and are useful reference examples for applying the analytics process for SME organizations in both developing and developed economies. The cases also identify multiple tacit factors to deal with during the implementation of analytics knowledge management processes. These factors, which include data cleaning, data gathering, and interpretation of results, are not always easily identified by analytics practitioners. This book promotes the understanding of analytics methods and techniques. It guides readers through numerous techniques and methods available to analytics practitioners by explaining the strengths and weaknesses of these methods and techniques.

This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications. The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management. This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.

​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization. This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

This book presents a collection of interrelated research advances in the field of technological entrepreneurship from the perspective of competition in emerging markets. Featuring contributions by scholars from different fields of interest, it provides a mix of theoretical developments, insights and research methods used to uncover the unexplored aspects of competitiveness in emerging markets in an age characterized by disruptive technologies.

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This volume of the International Symposia in Economic Theory and Econometrics explores the latest economic and financial developments in Africa and Asia.

Innovation is sweeping the globe at breakneck speed, and emerging markets are where tremendous growth and opportunity reside. Jerry Haar and Ricardo Ernst delve into the forces and drivers that shape innovation in emerging markets and present case studies, along with a summation of the key features and outlook for innovation over the next decade.

Emerging markets are increasingly facing significant challenges, from a slowdown in productivity, rising debt, and trade tensions to the adverse effects of proliferating global uncertainty on domestic financial systems. This incisive Handbook examines the ongoing dynamics of global financial markets and institutions within the context of such rising uncertainty and provides a comprehensive overview of innovative models in banking and finance.

It seems that when businesses were finally understanding, implementing, and getting used to industry 4.0, the term 5.0 came about. Industry 5.0 takes human touch, innovation, and efficiency a step further in creating a turnaround strategy for corporate governance. This transformation has brought many questions to the minds of stakeholders such as when and why this happened. In order to explore the answers to these questions, further study is required to understand the prospects and challenges. Opportunities and Challenges of Business 5.0 in Emerging Markets discusses the present state and future outlooks of Business 5.0 and aims to achieve comprehensive insights on the implications of Business 5.0 in the emerging markets. The book also provides insights to marketers, entrepreneurs, and practitioners to unravel the opportunities and mitigate the challenges in the competitive world. Covering key topics such as big data, e-commerce, and value creation, this reference work is ideal for policymakers, business owners, managers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.

This book presents a wide range of tools and techniques used in entrepreneurial finance in emerging markets. Among them, venture capital is perhaps the best known, understood, and researched mode of entrepreneurial finance. However, a significant focus of the book is dedicated to other modes of entrepreneurial finance such as ‘bootstrapping,’ angel financing, bank financing, and other alternative means of financing, which could include government assistance programs, business incubation, technology parks, or family financing. In addition, the book highlights how new and innovative financial technologies (comprised of software, business processes, and other modern technologies), known under the term of FinTech, may support, enable, and enhance the provision of different modes of entrepreneurial finance in emerging markets. The book also discusses entrepreneurial finance in emerging markets in the context of women entrepreneurs. A comprehensive analysis of entrepreneurial finance in emerging market countries, this book will appeal to academics, researchers, and students of entrepreneurial finance, venture capital and private equity, entrepreneurship, and international business.

This proceedings book is divided in 2 Volumes and 8 Parts. Part I is dedicated to Decision Support System, which is about the information system that supports business or organizational decision-making activities; Part II is on Computing Methodology, which is always used to provide the most effective algorithm for numerical solutions of various modeling problems; Part III presents Information Technology, which is the application of computers to store, study, retrieve, transmit and manipulate data, or information in the context of a business or other enterprise; Part IV is dedicated to Data Analysis, which is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making; Part V presents papers on Operational Management, which is about the plan, organization, implementation and control of the operation process; Part VI is on Project Management, which is about the initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time in the field of engineering; Part VII presents Green Supply Chain, which is about the management of the flow of goods and services based on the concept of “low-carbon”; Part VIII is focused on Industry Strategy Management, which refers to the decision-making and management art of an industry or organization in a long-term and long-term development direction, objectives, tasks and policies, as well as resource allocation.

Beyond Fintech: Technology Applications for the Islamic Economy is a follow-up to the first-ever Islamic Fintech book by the author (published in 2018) that provided linkages between Islamic Finance and disruptive technologies like the blockchain. In the wake of fintech as a new trend in financial markets, the ground-breaking book stressed the relevance of Islamic finance and its implications, when enabled by fintech, towards the development of the Islamic digital economy. While the earlier work discussed the crucial innovation, structural, and institutional development for financial technologies in Islamic Finance, this new research explores the multiple applications possible in the various sectors of the economy, within and beyond finance, that can be significantly transformed. These revolutionary applications involve the integration of AI, blockchain, data analytics, and Internet-of-Things (IoT) devices for a holistic solution to tackle the bottlenecks and other issues in existing processes of traditional systems. The principles of accountability, duty, justice, and transparency are the foundation of shaping the framework in achieving good governance in all institutions — public or private, Islamic or otherwise. Technologies like AI, blockchain, and IoT devices can operationalize the transparency and accountability that is required to eradicate poverty, distribute wealth, enhance micro-, small- and large-scale initiatives for social and economic development, and thus share prosperity for a moral system that enables a more secure and sustainable economy.