This volume collects the contributions presented at the conference “Data-driven Decision Making” organized by the Italian Association for Applied Statistics, held in Genoa from 12 to 14 September 2022. The papers cover a broad range of topics, with a common thread: the use of statistical methods to support decision-making both in public administrations and in private companies.
In the rapidly evolving digital landscape, businesses today face an imperative to adapt and innovate continuously. Digital transformation is at the core of this evolution. It enables organizations to rethink and redesign their operations, processes, and customer interactions. Within this context, marketing has seen a profound shift, with agile methodologies and advanced technologies redefining traditional practices. It is imperative to explore the intersection of these critical areas. Digital Transformation Initiatives for Agile Marketing explores the various aspects of marketing and digital transformation, including how technology is changing the way marketers operate, how businesses can leverage data to improve customer engagement, and the challenges and opportunities that com with implementing digital transformation initiatives. It also discusses new marketing tendencies related to technology, people, and processes. Covering topics such as artificial intelligence, customer experience, and omnichannel marketing, this book is an excellent resource for marketers, business leaders, academicians, researchers, educators, graduate and postgraduate students, and more.
"At what point does the sacrifice to our personal information outweigh the public good? If public policymakers had access to our personal and confidential data, they could make more evidence-based, data-informed decisions that could accelerate economic recovery and improve COVID-19 vaccine distribution. However, access to personal data comes at a steep privacy cost for contributors, especially underrepresented groups. Protecting Your Privacy in a Data-Driven World is a practical, nontechnical guide that explains the importance of balancing these competing needs and calls for careful consideration of how data are collected and disseminated by our government and the private sector. Not addressing these concerns can harm the same communities policymakers are trying to protect through data privacy and confidentiality legislation. Claire McKay Bowen is the Lead Data Scientist for Privacy and Data Security at the Urban Institute. Her research focuses on assessing the quality of differentially private data synthesis methods and science communication. In 2021, the Committee of Presidents of Statistical Societies identified her as an emerging leader in statistics for her technical contributions and leadership to statistics and the field of data privacy and confidentiality"--
Data plays a vital role in different parts of our lives. In the world of big data, and policy determined by a variety of statistical artifacts, discussions around the ethics of data gathering, manipulation and presentation are increasingly important. Ethics in Statistics aims to make a significant contribution to that debate. The processes of gathering data through sampling, summarising of the findings, and extending results to a population, need to be checked via an ethical prospective, as well as a statistical one. Statistical learning without ethics can be harmful for mankind. This edited collection brings together contributors in the field of data science, data analytics and statistics, to share their thoughts about the role of ethics in different aspects of statistical learning.
This book gathers selected high-quality research papers presented at the Eighth International Congress on Information and Communication Technology, held at Brunel University, London, on 20–23 February 2023. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.
The American Statistical Association (ASA) and the Association of Computing Machinery (ACM) have longstanding ethical practice standards that are explicitly intended to be utilized by all who use statistical practices or computing, or both. Since statistics and computing are critical in any data-centered activity, these practice standards are essential to instruction in the uses of statistical practices or computing across disciplines. Ethical Reasoning For A Data-Centered World is aimed at any undergraduate or graduate students utilizing data. Whether the career goal is research, teaching, business, government, or a combination, this book presents a method for understanding and prioritizing ethical statistics, computing, and data science – featuring the ASA and ACM practice standards. To facilitate engagement, integration with prior learning, and authenticity, the material is organized around seven tasks: Planning/Designing; Data collection; Analysis; Interpretation; Reporting; Documenting; and Engaging in team work. This book is a companion volume to Ethical Practice of Statistics and Data Science, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the American Statistical Association (ASA) and Association of Computing Machinery (ACM) ethical guideline documents.
Tracing its roots back to World War II, operations research (OR) has become a vital tool in military and defense strategy. The second edition of the Handbook of Military and Defense Operations Research highlights this evolution, showcasing how OR integrates with cutting-edge areas like artificial intelligence, cybersecurity, and big data analytics. This volume is more than a historical account; it is a practical guide. The volume features expert voices and offers insights into OR applications in modern security challenges. Readers will discover a blend of theory and real-world case studies, making it an essential resource for both newcomers and seasoned defense analysis professionals. Dive into this handbook to explore the rich, dynamic field of military and defense operations research, a discipline at the heart of global security and strategic decision-making. New to the second edition: Reorganized into a three-part structure Extensive revisions throughout Numerous new exercises, examples, and case studies Several new chapters
This book is derived from selected papers from the Fourteenth International Congress on Mathematical Education Topic Study Group 12, Teaching and Learning Statistics. It describes recent research on curriculum, pedagogy and outreach initiatives from countries as diverse as Brazil, Chile, Columbia, Denmark, Germany, the Netherlands, Spain, Sweden, Thailand, Turkey, the United Kingdom, and the United States. The book has a focus on the use of data in the teaching and learning of statistics across grade levels and begins with an overview of the status of statistics education and the use of data from seven different countries across the continents and the link between research and practice in those countries. Because it contains specific examples of the research, for example, on the ways children learn, the choice and implementation of tasks, or the role of informal inference, the book will be a great resource to those interested and involved in the teaching of statistics, curriculum developers, and statistics education researchers.
This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.
