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Improving Service Quality and Customer Engagement With Marketing Intelligence
To succeed, businesses must keep up with the ever-changing technological landscape and constantly introduce new advancements. The rise of digitalization has wholly transformed how companies interact with their customers, presenting both opportunities and challenges. Marketing professionals are inundated with data and need guidance on leveraging it effectively to craft successful marketing strategies. Additionally, the ethical and privacy concerns surrounding the collection and use of customer data make the marketing landscape even more complex. Improving Service Quality and Customer Engagement With Marketing Intelligence is a groundbreaking book that offers a comprehensive solution to these ...
Future of Customer Engagement Through Marketing Intelligence
In the competitive world of contemporary business, the challenge of developing marketing strategies that bridge the gap between traditional and innovative techniques has become more critical than ever. As marketing shifts between physical and digital realms, companies grapple with the central question of how to navigate this evolution successfully. The key lies in data the linchpin that can unravel vital problems in modern marketing. The need for sustainable and effective marketing strategies permeates all sectors, emphasizing the urgency for businesses to combine traditional methods with innovative approaches, such as harnessing alternative data and leveraging AI-based solutions. Future ...
HR Analytics in an Era of Rapid Automation
Human Resources (HR) departments often have significant data sets related to employees and positions within their organizations, but optimizing use of this data can present challenges. As the business world rapidly transforms due to technological advancements, experts within the HR domain must learn to effectively use data to improve workforce performance and assist with strategic decisions. A comprehensive understanding of HR analytics and its multiple levels, ranging from descriptive to perspective, can emphasize how the data can support, track, and monitor employee performance, culture, turnover rate, and absenteeism. HR Analytics in an Era of Rapid Automation is a valuable guide for acad...
Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.
Financial Inclusion in Emerging Markets
This book discusses ideas for stakeholders to develop strategies to access and use financial products and services such as deposits, loans, and fund transfer mechanism, insurance, payment services, and intermediaries, distribution channels at economical prices in order to cater to the needs of the poor and underprivileged people. Financial inclusion ensures ease of access, availability, and usage of the financial products and services to all the sections of the society. The book will help in recognizing the role of financial inclusion as one of the main drivers in reducing income inequality and thus supporting sustainable economic growth of the countries, especially of an emerging economy. The book provides conceptual and practical ideas from the practitioners, best practices from the experts, and empirical views from the researchers on the best practices and how to mitigate the challenges and issues plaguing the development of the financial inclusion.
The Science behind the COVID Pandemic and Healthcare Technology Solutions
This book offers a timely review of modern technologies for health, with a special emphasis on wireless and wearable technologies, GIS tools and machine learning methods for managing the impacts of pandemics. It describes new strategies for forecasting evolution of pandemics, optimizing contract tracing, and for detection and diagnosis of diseases, among others. Written by researchers and professionals with different backgrounds, this book offers a extensive information and a source of inspiration for physiologists, engineers, IT scientists and policy makers in the health and technology sector.
Industry and Academic Research Review
Industry and Academic Research Review (IARR) is the official conference proceedings publication of the International Conference on Multidisciplinary Industry and Academic Research (ICMIAR). It focuses on four broad themes: education and development studies; humanities and social sciences; science, technology, engineering and mathematics; and business, management and accounting. This publication provides a platform for experts and practitioners from various fields in the dissemination of their research works that address industry trends and needs, scientific findings and international concerns. Both the conference and proceedings publication promote a wider horizon for researchers through open-access paradigm.
Integration Challenges for Analytics, Business Intelligence, and Data Mining
As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
Green Technological Innovation for Sustainable Smart Societies
This book discusses the innovative and efficient technological solutions for sustainable smart societies in terms of alteration in industrial pollution levels, the effect of reduced carbon emissions, green power management, ecology, and biodiversity, the impact of minimal noise levels and air quality influences on human health. The book is focused on the smart society development using innovative low-cost advanced technology in different areas where the growth in employment and income are driven by public and private investment into such economic activities, infrastructure and assets that allow reduced carbon emissions and pollution, enhanced energy, and resource efficiency and prevention of the loss of biodiversity and ecosystem services. The book also covers the paradigm shift in the sustainable development for the green environment in the post-pandemic era. It emphasizes and facilitates a greater understanding of existing available research i.e., theoretical, methodological, well-established and validated empirical work, associated with the environmental and climate change aspects.
