Handbook Of Research On Applied Ai For International Business And Marketing Applications

Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

This handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.

Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.

Interactive marketing, as one of the fastest growing academic fields in contemporary business world, is the multi-directional value creation and mutual-influence marketing process through active customer connection, engagement, participation and interaction. Contemporary interactive marketing has moved beyond the scope of direct marketing or digital marketing, as the market is becoming a forum for conversations and interactions among connected actors or participants in platform ecosystems. The advancement of mobile technology with interactive content and personalized experience makes interactive marketing the new normal in the business world. This handbook contains the most comprehensive and cutting-edge knowledge in the interactive marketing field. The 41 chapters that are divided into eight sections cover all aspects of contemporary interactive marketing realm, including social media and influencer marketing, big data and machine learning in predictive analytics, mobile marketing and proximity marketing, interactive digital marketing and Omnichannel marketing, AI, VR and AR in business applications. With a focal point on interactive marketing, this handbook takes a multidiscipline perspective, from new technology innovations, social media and platform application, economic and cultural impacts, social and psychological analysis, and management and information system. This book provides a timely and comprehensive textbook companion and/or course project resource for college educators and students used for variety of graduate and undergraduate marketing courses, such as Digital Marketing, Internet Marketing, Social Media Marketing, New Media Communication, Marketing Analytics and Marketing Management, etc. It offers valuable references for academic researchers who are interesting conducting and publishing in interactive marketing research. The state-of-art review and emerging new trends presented in the book are particularly useful for research idea generation and conceptual development. The book also putts forward insightful guidelines and practical tools for business management in the application of new interactive marketing strategies and applications in the real world practices. Chapter 41 “Ethical Considerations in Gamified Interactive Marketing Praxis” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book investigates the growing influence of artificial intelligence in the marketing sphere, providing insights into how AI can be harnessed for developing more effective and efficient marketing strategies. In addition, the book will also offer a comprehensive overview of the various digital marketing tools available to entrepreneurs, discussing their features, benefits, and potential drawbacks. This will help entrepreneurs make well-informed decisions when selecting the tools most suited to their needs and objectives. It is designed to help entrepreneurs develop and implement successful strategies, leveraging the latest tools and technologies to achieve their business goals. As the digital landscape continues to evolve rapidly, this book aims to serve as a valuable resource for entrepreneurs looking to stay ahead of the curve and capitalize on new opportunities. The book's scope encompasses a wide range of topics, including customer experience, content marketing, AI strategy, and digital marketing tools.

Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.

In the throes of a global skills gap and relentless labor market disruptions, organizations grapple with the pressing challenge of aligning workforce skills with the demands of a hypercompetitive economy. Reports from influential entities like the World Economic Forum and McKinsey & Company underscore the urgency for strategic interventions to bridge this divide. Despite the pivotal role of higher education and corporate training, recent findings from the Society for Human Resource Management (SHRM) reveal a persistent struggle in finding candidates equipped with the requisite skills for a multitude of available jobs. The deficiencies span from foundational communication skills to complex problem-solving abilities, posing a formidable hurdle for organizations seeking qualified talent. Prioritizing Skills Development for Student Employability emerges as a solution to the skills misalignment conundrum by delving into the heart of the issue, dissecting the intricacies of global workforce dynamics, education-industry collaborations, and the evolving landscape of corporate training. By exploring topics such as learning analytics, educational artificial intelligence (AI), and effective leadership in the context of present-day human resource management, the book provides a comprehensive roadmap for both academic scholars and professionals to navigate the complex terrain of skills development.