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This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.

This book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.

The two-volume set LNBIP 518 and 519 constitutes the refereed post-conference proceedings of the 25th International Conference on Enterprise Information Systems, ICEIS 2023, which was held in Prague, Czech Republic, during April 2023. The 30 full papers included in these proceedings were carefully reviewed and selected from a total of 213 submissions. They are organized in topical sections as follows: Part One : Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; and Information Systems Analysis and Specification. Part Two : Software Agents and Internet Computing; Human-Computer Interaction; and Enterprise Architecture.

This two-volume set constitutes the refereed post-conference proceedings of the 25th International Conference on Enterprise Information Systems, ICEIS 2023, which was held in Prague, Czech Republic, during April 2023. The 41 full papers and 66 short papers presented were carefully reviewed and selected from 213 submissions. They are organized in topical sections as follows: Part One : Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; and Information Systems Analysis and Specification. Part Two : Software Agents and Internet Computing; Human-Computer Interaction; and Enterprise Architecture.

This open access book presents a rich set of innovative solutions for artificial intelligence (AI) in manufacturing. The various chapters of the book provide a broad coverage of AI systems for state of the art flexible production lines including both cyber-physical production systems (Industry 4.0) and emerging trustworthy and human-centered manufacturing systems (Industry 5.0). From a technology perspective, the book addresses a wide range of AI paradigms such as deep learning, reinforcement learning, active learning, agent-based systems, explainable AI, industrial robots, and AI-based digital twins. Emphasis is put on system architectures and technologies that foster human-AI collaboration based on trusted interactions between workers and AI systems. From a manufacturing applications perspective, the book illustrates the deployment of these AI paradigms in a variety of use cases spanning production planning, quality control, anomaly detection, metrology, workers'training, supply chain management, as well as various production optimization scenarios. This is an open access book.

This book explores AI technology in wealth management, including what it is, how it changes the wealth management and private banking landscape, its advantages, and how it democratizes wealth management. Specifically, this book investigates topics such as Hyper-personalized investment strategies Combined quantitative analysis with sentiment analysis to create prescriptive and predictive scenarios Expandable and transparent AI algorithms in wealth management Customer experience and client engagement Tailored financial content Providing a clear and concise description of how AI driven wealth management differs from traditional investing, asset management, and wealth management offering new opportunities for investing, this book is ideal for students, scholars, researchers and professionals interested in accessible wealth management applications for investing in the 21st century.

The two-volume set LNCS 15271 and 15272 constitutes the proceedings of the 4th Energy Informatics Academy Conference, EI.A 2024, held in Kuta, Bali, Indonesia, during October 23–25, 2024. The 40 full papers and 8 short papers included in these proceedings were carefully reviewed and selected from 64 submissions. They are categorized under the topical sections as follows: Part I: IoT Edge Computing, and Software Innovations in Energy, Big Data Analytics and Cybersecurity in Energy, Digital Twin Technology and Energy Simulations, Energy data and consumer behaviors, and Digitalization of District Heating and Cooling Systems. Part II: Smart Buildings and Energy Communities, Energy Pricing, Trading, and Market Dynamics, Demand Flexibility and Energy Conservation Strategies, Optimization of Energy Systems and Renewable Integration and Energy System Resilience and Reliability.

Embark on a journey into the future of business with a groundbreaking book that explores the dynamic interplay between data and business, unlocking its transformative power in strategy, decision-making, and application development. Dive deep into cutting-edge topics such as data governance, analytics, knowledge discovery, and AI, and gain an in-depth understanding of managing, analyzing, and extracting insights from complex data sets. This book's holistic approach sets this book apart, seamlessly integrating the latest information and knowledge management concepts. From integrating data-centric approaches into business models to addressing considerations in data-driven decisions, the diverse topics covered will provide invaluable insights into the central role of data in shaping the future of business and applications. This book sheds light on the ongoing advances in structural management, demonstrating how previously understood knowledge, technologies, and data can pave the way for sustainable solutions in the face of innovation, meet insight, and allow businesses to thrive in the digital age.

The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI's impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.

As civilization rapidly evolves into a new radical post-pandemic era, organizations and leaders need to adapt, innovate, and reimagine the future. This guidebook offers insights and strategies for leaders to thrive in this new era, empowering them to embrace their roles as Neo-Innovators, Neo-managers, and Neo-futurists. It is a concise “how-to” guide for anyone who is (or wants to be) involved in the development of radical innovations that solve problems and exploit opportunities in the post-pandemic world. Featuring actionable advice and examples from generative AI and the influencer culture to humanoid robots, self-driving cars and age-slowing therapies, this book equips young and experienced innovators, innovation leaders, and practitioners with the essential tools and mindset to tackle challenges and explore opportunities in a dynamic innovative landscape.

This book focuses on the personalisation of the user interface in e-commerce based on collected data on customer behaviour. While product recommendation systems are widely used for this purpose today, they do not allow for a comprehensive adaptation of the layout to different user groups. The proposed approach is based on the conclusion that since e-commerce customers are different, the user interface should also be different. To make this possible, several components need to be combined, which together allow the design of the online shop to be automatically or expertly adapted to the customer's choices and behaviour. It presents and discusses a framework that allows data to be collected, processed and used to optimise UI variants for generated customer segments. The proposed approach has been verified in practice and further developed on this basis, so that the reader is presented with a solution that is not riddled with'baby age'problems, and the limitations and challenges identified are described and commented on in detail. Typical e-commerce systems currently have a single UI for all customers. The implementation of multi-variant UIs therefore represents an opportunity for companies to create a marketing advantage by addressing the personalisation trends in e-commerce.The book is intended for those responsible for developing e-commerce platform and user interfaces for web-based systems, as well as individuals interested in practical applications of machine learning in business.

This book constitutes the proceedings of the 23rd International Conference on Perspectives in Business Informatics Research, BIR 2024, which took place in Prague, Czech Republic, in September 2024. The central theme of BIR 2024 was “Artificial Intelligence (AI) in Business Informatics: Opportunities and Challenges”. The 15 full papers and 1 short paper included in these proceedings were carefully reviewed and selected from 43 submissions. They cover different aspects of the discipline and are organized in sections on AI opportunities and challenges; AI applications and use cases in business; business intelligence; business and information systems development; and knowledge and traceability management.

This book examines the fundamental concepts and principles of digital transformation and AI, including their historical development, and underlying technologies, and analyzes the opportunities arising from digital transformation and AI in different sectors, such as healthcare, finance, education, transportation, and governance. It provides a comprehensive overview of digital transformation and AI technologies and their current state of implementation. It also explores the potential challenges and risks associated with digital transformation and AI, including ethical considerations, job displacement, privacy concerns, biases, impact on inequality, social interactions, and the overall well-being of individuals and communities. Additionally, the books provides and discusses policy and regulatory frameworks that can effectively address the opportunities and challenges posed by digital transformation and AI leading to responsible AI. It also delves into impact of automation on the job market and workforce. The book concludes by proposing potential strategies for navigating opportunities and challenges of digital transformation and AI integration. It emphasizes the need for interdisciplinary collaboration among stakeholders, including policymakers, industry leaders, academia, and civil society, to develop a comprehensive approach towards harnessing the full potential of digital transformation and AI and associated technologies. The book employs a multidisciplinary approach, drawing from various fields such as computer science, sociology, philosophy, political science, economics, law and governance. It combines theoretical analysis, empirical case studies, and expert perspectives to provide a holistic view of the subject matter. This book caters to a diverse audience, including students, researchers, academics, policymakers, industry professionals, and technology enthusiasts. It provides a valuable resource for those seeking a comprehensive understanding ofthe opportunities and challenges arising from the integration of digital transformation and AI in society.

The book shows application potentials of artificial intelligence in various industries and presents application scenarios on how a practical implementation can take place. The starting point is the description of legal aspects, which includes a European regulation for artificial intelligence and addresses the question of the permissibility of automated decisions. The description of various application potentials, mostly industry-related, and the presentation of some application scenarios form the focus of the topic volume. The book is based on the question of how artificial intelligence can be used in entrepreneurial practice. It offers important information that is just as relevant for practitioners as for students and teachers. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

The technological boom has provided consumers with endless choices, removing the hindrance of time and place. Understanding the dynamic and competitive business environment, marketers know they need to reinforce indestructible customer experience with the support of algorithmic configurations to minimize human intrusion. World Wide Web (WWW) and online marketing have changed the way of conducting business; with artificial intelligence (AI), business houses can furnish a customized experience to fulfil the perceived expectation of the customer.Artificial intelligence bridges the gap between business and prospective clients, provides enormous amounts of information, prompts grievance redressal system, and further complements the client's preference. The opportunities online marketing offers with the blend of artificial intelligence tools like chatbots, recommenders, virtual assistance, and interactive voice recognition create improved brand awareness, better customer relationshipmarketing, and personalized product modification.Explainable AI provides the subsequent arena of human–machine collaboration, which will complement and support marketers and people so that they can make better, faster, and more accurate decisions. According to PwC's report on Explainable AI(XAI), AI will have $15.7 trillion of opportunity by 2030. However, as AI tools become more advanced, more computations are done in a “black box” that humans can hardly comprehend. But the rise of AI in business for actionable insights also poses the following questions: How can marketers know and trust the reasoning behind why an AI system is making recommendations for action? What are the root causes and steering factors? Thus, transparency, trust, and a good understanding of expected business outcomes are increasingly demanded.

This book provides operational guidance on how to bring process mining to the next level, with process intelligence enabling companies to improve process efficiency and realize value. Written by practitioners, it combines the editor's 10-year experience in this field gained at Celonis and Siemens, with 12 best practice use cases from international companies representing multiple industries and domains. Part I sets the stage describing the evolution from process mining to process intelligence. The chapters guide the reader step by step, from getting started to driving adoption at scale. Success factors critical for digital transformations and a detailed path to value realization are presented. Best practices on operating models and Centers of Excellence (CoEs) are shared as accelerators for successful digital transformations. Part II presents 12 use cases written by transformation- and CoE leaders who have achieved significant impact and value with process intelligence in their respective organization. All use cases have been written independent from any particular software, with a focus on evangelizing the topic and showcasing how companies like ABB, BMW, Bosch, Merck, PepsiCo, Saint Gobin, Siemens, and others leverage the capability to drive value. Part III provides an outlook on the future of process intelligence from an academic and an operational perspective, with a special focus on the disruptive impact of GenAI with future scenarios, challenges and recommendations. The book is written by practitioners for practitioners. Readers may have responsibilities as senior executives, transformation leaders, process managers and experts, consultants, change evangelists, etc. The book provides operational, hands-on tips on how to accelerate process transformation in organizations by detailing best practices as well as possible pitfalls.

This book constitutes the thoroughly refereed proceedings of the CAiSE Forum 2024 which was held in Limassol, Cyprus, in June 2024, as part of the 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024. The CAiSE Forum is a place within the CAiSE conference for presenting and discussing new ideas and tools related to information systems engineering. Intended to serve as an interactive platform, the Forum aims at the presentation of emerging new topics and controversial positions, as well as demonstration of innovative systems, tools and applications. This year a special emphasis was given on Information Systems in the Age of Artificial Intelligence. The Forum received 31 submissions; 8 submissions were invited from the CAISE main research track. Out of the 23 regular submissions, 11 papers have been accepted. The 18 papers included in these proceedings include 10 vision papers and 8 tool demonstration papers.

This book examines aspects of financial and investment processes, as well as the application of information technology mechanisms to business and industrial management, using the experience of the Ukrainian economy as an example. An effective tool for supporting business data processing is combining modern information technologies and the latest achievements in economic theory. The variety of industrial sectors studied supports the continuous acquisition and use of efficient business analysis in organizations. In addition, the book elaborates on multidisciplinary concepts, examples, and practices that can be useful for researching the evolution of developments in the field. Also, in this book, there is a description of analysis methods for making decisions in business, finance, and innovation management.

This book (Volume 1) includes peer reviewed articles from the 5th International Conference on Data Science, Machine Learning and Applications, 2023, held at the G Narayanamma Institute of Technology and Sciences, Hyderabad on 15-16th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

This book presents the latest breakthroughs and cutting-edge advancements within this rapidly evolving field. By providing computational finance and business analytics, organizations can secure a competitive advantage in today's data-driven and cutting-edge business landscape. This book explores the most recent innovations and significant developments in both the domains of computational finance and business analytics, offering a thorough overview of the current landscape. It encompasses various dimensions including: Business Analytics Financial Analytics HR & Marketing Analytics By integrating the latest theoretical insights with practical applications, this book equips researchers, practitioners, and students with the knowledge and tools necessary to explore and progress in the ever-changing realm of computational finance and business analytics. As the present organizations confront the challenges and adapt the opportunities presented by the data revolution, this book serves as an essential guide, illuminating the transformative frontiers where computational finance and business analytics are redefining the realm of possibilities.

The two-volume set LNCS 15271 and 15272 constitutes the proceedings of the 4th Energy Informatics Academy Conference, EI.A 2024, held in Kuta, Bali, Indonesia, during October 23–25, 2024. The 40 full papers and 8 short papers included in these proceedings were carefully reviewed and selected from 64 submissions. They are categorized under the topical sections as follows: Part I: IoT Edge Computing, and Software Innovations in Energy, Big Data Analytics and Cybersecurity in Energy, Digital Twin Technology and Energy Simulations, Energy data and consumer behaviors, and Digitalization of District Heating and Cooling Systems. Part II: Smart Buildings and Energy Communities, Energy Pricing, Trading, and Market Dynamics, Demand Flexibility and Energy Conservation Strategies, Optimization of Energy Systems and Renewable Integration and Energy System Resilience and Reliability.

This book presents selected proceedings of the International Conference on Business Analytics in Practice (ICBAP2024), which was held on January 8–11, 2024, at the University of Sharjah, UAE. The book presents advanced modeling and examples to explore the practical applications of business analytics across various industries and domains. In addition, it dives deep into the world of data-driven decision-making, showcasing real-world case studies and best practices to illustrate how organizations can harness the power of analytics to optimize their decision-making processes. From descriptive analytics to predictive modeling and prescriptive analytics, readers will gain valuable insights into the different techniques and methodologies employed in business analytics.

This book stands out by exploring the significance of data in various aspects of business, including operations, decision-making, and application development, in a comprehensive and accessible manner. It delves into advanced topics such as data management, analytics, knowledge discovery, artificial intelligence, data-centric business models, emerging technologies, and ethical implications, providing a unique perspective. The book is appropriate for academics, professionals, and researchers with intermediate to advanced data management skills. Data plays a crucial role in today's rapidly evolving digital environment, serving as the foundation for businesses and the key element in driving innovation across diverse industries. This book delves into the latest advancements in data management, their impact on modern corporate settings, and advanced information and knowledge management concepts. The chapters in this book discuss various topics, including incorporating data-driven methods into business models, the difficulties and advantages of emerging technology, and the ethical aspects of making decisions based on data.

This book contains the refereed proceedings of two long-running events held along with the CAiSE conference relating to the areas of enterprise, business-process and information systems modeling: - the 25th International Conference on Business Process Modeling, Development and Support, BPMDS 2024, and - the 29th International Conference on Exploring Modeling Methods for Systems Analysis and Development, EMMSAD 2024. The conferences were taking place in Limassor, Cyprus, during June 3–4, 2024. For BPMDS 8 full papers and 3 short papers were carefully reviewed and selected for publication from a total of 25 submissions; for EMMSAD 11 full papers and 5 short papers were accepted from a total of 32 submissions after thorough reviews. The BPMDS papers deal with a broad range of theoretical and applications-based research in business process modeling, development and support. EMMSAD focusses on modeling methods for systems analysis and development.

As leaders plan to make significant investments to harness the power of foundational models such as ChatGPT, they need to understand the changes in organizational behaviors required for the successful implementation of such systems. The size, complexity and nature of this new wave of technologies requires a refresh in roles and responsibilities in conventional IT organizations. This book reveals practical and no-nonsense guidance on how to leverage generative AI to transform your business processes and organizational structures to achieve breakthroughs in efficiency, effectiveness and competitive advantage. Written in a lively, engaging, and often humorous style, this work provides practical insights and timely survival skills for leaders with anonymous but real-world experiences and case studies. If you're looking to understand how large language foundation models such as ChatGPT are reshaping managerial roles and organizational structures, and how they can leverage this knowledge to survive and thrive in this brave new world then Organizing for Generative AI and the Productivity Revolution is the book for you. What You Will Learn Review the key changes in current state roles and responsibilities that are required to successfully deploy generative AI systems Examine the organizational reporting structures and associated incentives that form a strong generative AI system Understand the financial, regulatory, and operational risks created by organizational behavioral issues that arise when organizations build and deploy large language models Compare the strategic differences in emerging versus traditional organizational behaviors, incentives, roles and responsibilities Who This Book Is For Executives and team leaders at enterprises large and small.

This book brings together a diverse range of findings on current and emerging business concerns when the authors were developing a series of 12 working Analytic Research Consortium (ARC) White Papers. It presents several, differently configured scenarios, drawing on cyber as an example; the use and further optimization of estimative/probabilistic language; communicating analytical insights and other findings concerning ‘(un)certainty'to decision-maker end-users; and mitigating risk. It also evaluates in detail today's rapidly evolving Gen-AI systems and technologies, e.g. those underlying OpenAI's ChatGPT and Google's Bard/Gemini. This includes their respective value concerning scenario development and other business-relevant methods, tools and techniques, e.g. ‘Red Teaming'. The topics discussed are assessed using the multi-methodologies of, firstly, ‘Intelligence Engineering'(IE) and, secondly, ‘Strategic Options Analysis'(SOA). The latter half of the book introduces an alternative scenario planning process, including use of new computer-software and AI tools. In addition to Gen-AI, we identify that the emerging discipline of Causal AI may work better for foresight and scenario activities. The book is a valuable read for a diverse readership from the public and private sectors, spanning government, the military, law enforcement, education, industry, commerce, retail, and enterprises of all sizes. Also, students at business schools and high-level decision-makers, including politicians, military commanders, and C-Suite leaders in various fields, will benefit from it.

This book includes peer reviewed articles from the 5th International Conference on Data Science, Machine Learning and Applications, 2023, held at the G Narayanamma Institute of Technology and Sciences, Hyderabad on 15-16th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

This book explores the profound impact of data on company operations, decision-making, and application development. The book delves into sophisticated information and knowledge management principles, including data governance, analytics, knowledge discovery, and artificial intelligence. The subject encompasses data-centric business models, emerging technology, and ethical considerations. Each chapter is authored by an expert in the area who offers important insights into the influence of data on the advancement of business and application development. The material herein is appropriate for a diverse audience, encompassing academics, practitioners, business professionals, and researchers. The editors sincerely appreciate the writers for their significant contributions, which have been crucial in developing an essential resource for studying and advancing data-centric businesses and applications.

This book examines aspects of financial and investment processes, as well as the application of information technology mechanisms to business and industrial management, using the experience of the Ukrainian economy as an example. An effective tool for supporting business data processing is combining modern information technologies and the latest achievements in economic theory. The variety of industrial sectors studied supports the continuous acquisition and use of efficient business analysis in organizations. In addition, the book elaborates on multidisciplinary concepts, examples, and practices that can be useful for researching the evolution of developments in the field. Also, in this book, there is a description of analysis methods for making decisions in business, finance, and innovation management.

Enterprise Interoperability X presents contributions ranging from academic research and case studies, to industrial and administrative experiences with interoperability. These contributions help organizations to analyse and improve their products and processes in the face of the high degree of uncertainty in the current commercial environment, and to predict their performance. To this end, the contributors exploit digital twin technology that integrates tools from the Internet of Things, artificial intelligence and software analytics. Enterprise interoperability necessarily arises from the processes required to make associated digital twins work together. The book forms the proceedings of the I-ESA'22 Conference, which was organised by the Universidad Politécnica de Valencia, on behalf of INTERVAL and the European Virtual Laboratory for Enterprise Interoperability (INTEROP-VLab), and was held in Valencia, Spain in March 2022. Many of the papers in this eleventh volume ofthe Proceedings of the I-ESA Conferences include examples and illustrations to help deepen readers'understanding and generate new ideas. Offering a detailed guide to the state of the art in systems interoperability, the book will be of great value to all engineers and computer scientists working in manufacturing and other process industries, and to software engineers and electronic and manufacturing engineers working in academic settings.

This book compiles artificial intelligence (AI) applications in new communication technologies such as the cognitive radio networks, internet of things (IoT), internet of drones (IoD), internet of vehicles (IoV), and autonomous underwater vehicles (AUV), which are expected to increase the amount of data traffic. Recognizing that AI is revolutionizing industries with its applications and helping us solve complex problems with ease, the book tackles a variety of industries and sectors such as agriculture, logistics, infrastructure, manufacturing, education, disaster management, transport, surveillance, and more. Contributions included in the book are useful for students, engineers (disciplines like telecommunication, mechanical and computer science, etc.), teachers, people studying and working for strategic, tactical and operational management. It is also useful for data scientists and anyone else who wants to have an insight into the impact of artificial intelligence on various industries. Due to its focus on healthcare and agriculture, the horizon of the book is enhanced to include healthcare industry personnels and agriculture sector. Additionally, it provides guidance for government personnel who are working towards system upgradation for managing dynamic traffic demands.

This book constitutes the refereed proceedings of the 8th International Conference on Business Intelligence, CBI 2023, which held in Istanbul, Turkey, during July 19–21, 2023.The 15 full papers included in this book were carefully reviewed and selected from 50 submissions. They were organized in topical sections as follows: artificial intelligence and business intelligence; and optimization and decision support.

Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected. Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book is appropriate for C-level executives engagedin the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science.

This book includes selected papers presented at World Conference on Information Systems for Business Management (ISBM 2022), held in Bangkok, Thailand, during September 2–3, 2022. It covers up-to-date cutting-edge research on data science, information systems, infrastructure and computational systems, engineering systems, business information systems, and smart secure systems.

This book gathers selected high-impact articles from the 3rd International Conference on Data Science, Machine Learning & Applications 2021. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.

Recent Advancements of Computational Finance and Business Analytics provide a comprehensive overview of the cutting-edge advancements in this dynamic field. By embracing computational finance and business analytics, organizations can gain a competitive edge in an increasingly data-driven and complex business environment.This book has explored the latest developments and breakthroughs in this rapidly evolving domain, providing a comprehensive overview of the current state of computational finance and business analytics. It covers the following dimensions of this domains:Business AnalyticsFinancial AnalyticsHuman Resource AnalyticsMarketing Analytics

This book is a revised version of the PhD dissertation written by the author at the Free University of Bozen-Bolzano in Italy. It presents a new approach to safety verification of a particular class of infinite-state systems, called Data-Aware Processes (DAPs). To do so, the developed technical machinery requires to devise novel results for uniform interpolation and its combination in the context of automated reasoning. These results are then applied to the analysis of concrete business processes enriched with real data. In 2022, the PhD dissertation won the “BPM Dissertation Award”, granted to outstanding PhD theses in the field of Business Process Management.

This book features a collection of high-quality research papers presented at the International Conference on Tourism, Technology and Systems (ICOTTS 2022), held at University of Chile, Santiago de Chile, Chile, from 3 to 5 November 2022. The book is divided into two volumes, and it covers the areas of technology in tourism and the tourist experience, generations and technology in tourism, digital marketing applied to tourism and travel, mobile technologies applied to sustainable tourism, information technologies in tourism, digital transformation of tourism business, e-tourism and tourism 2.0, big data and management for travel and tourism, geotagging and tourist mobility, smart destinations, robotics in tourism, and information systems and technologies.

This book constitutes the proceedings of the Third International Workshop on Model-Driven Organizational and Business Agility, MOBA 2023, which took place in Zaragoza, Spain, in June 2023. MOBA was launched with the purpose of fetching scientific rigor into the agile practice within an entire enterprise, especially focusing on the role of models and modeling. The 9 papers presented in this volume were carefully reviewed and selected from 18 submissions. They cover topics like business intelligence, agile business rules, agile software development, adaptive domain-specific interfaces, or reconfigurable software architectures.

This book constitutes revised selected papers from the 18th International Conference on Web Information Systems and Technologies, WEBIST 2022, which took place in Valletta, Malta, in October 2022. The 13 full revised papers presented in this book were carefully reviewed and selected from a total of 62 submissions. The selected papers contribute to the understanding of relevant current research trends in Web information systems and technologies, including deep learning, knowledge representation and reasoning, recommender systems, internet of things, Web intelligence and big data.

This book constitutes the refereed post-conference proceedings of the 24th International Conference on Enterprise Information Systems, ICEIS 2022, This conference was held virtually due to the COVID-19 crisis, during April 25-27, 2022.The 20 full papers included in this book were carefully reviewed and selected from 197 submissions. They were organized in topical sections as follows: Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; Information Systems Analysis and Specification; Human-Computer Interaction; and Enterprise Architecture.

Digitalisierung und Künstliche Intelligenz ermöglichen Unternehmen disruptive Erweiterungen ihrer Geschäftsmodelle. Wer rechtzeitig digitale KI-Geschäftsmodelle einführt, wird seinen Erfolg nachhaltig sichern können. Aber wie und wo können solche Modelle Anwendung finden? Diese Publikation gibt Antworten, wo KI-Geschäftsmodelle greifen können, und wie diese von der ersten Idee bis zur produktiven Anwendung realisiert werden können.

This book constitutes the proceedings of the 15th PLAIS EuroSymposium on Digital Transformation, PLAIS EuroSymposium 2023, which took place in Sopot, Poland, in September 2023. The primary objective of the PLAIS EuroSymposium 2023 was to foster discussions on general issues pertaining to digital transformation and related topics. The papers selected this year are related to the use of machine learning, internet of things and social media. The 7 full papers included in this volume were carefully reviewed and selected from a total of 22 submissions.

Dieses Buch stellt ausgewählte Beispiele der Digitalisierung im Zeitalter des digitalen Wandels vor. Es gliedert sich in die zwei Abschnitte'Digitale Innovation', in dem neue Technologien vorgestellt werden, die neue Geschäftsmöglichkeiten anregen und ermöglichen, und'Digitale Transformation', in dem Geschäfts- und Managementkonzepte vorgestellt werden, die spezifische technologische Lösungen für ihre praktische Umsetzung nutzen. Das Buch kombiniert neue Erkenntnisse aus Forschung, Lehre und Management, einschließlich digitaler Business-Transformation, E-Business, Wissensdarstellung, Mensch-Computer-Interaktion und Geschäftsoptimierung, und zeigt eine Bandbreite von Forschungsthemen sowie deren anwendungsorientierte Umsetzung in die Praxis auf. Es richtet sich an Akademiker und Akademikerinnen, die Inspiration suchen, sowie an Führungskräfte, die das Potenzial der neuesten Trends nutzen wollen, um die Gesellschaft und Unternehmen auf die nächste Stufe zu heben.

Chatbots sind eine vielversprechende Form der Kommunikation – jedoch schaffen es bisher nur wenige echten Mehrwert zu bieten. In diesem Praxisleitfaden lernen Sie Schritt für Schritt den gesamten Prozess der Chatbot-Entwicklung kennen: Von der Definition des Use Case über die Persönlichkeit des Chatbots und die Modellierung des Dialogablaufs bis hin zu Pilotbetrieb und Roll-Out. Sie erfahren für jeden Schritt, welche Strategien sich bewährt haben und was bei der Umsetzung besonders zu beachten ist. Einen Schwerpunkt bildet das Conversation Design, denn es ist entscheidend für eine gelungene User Experience, für Akzeptanz und langfristigen Erfolg des Chatbots. Anhand zahlreicher Fallbeispiele aus der Praxis und mit klar formulierten Handlungsempfehlungen zeigen die Autorinnen ganz konkret, wie erfolgreiche Chatbots gelingen.Der Inhalt• Bedarfsanalyse, Use Case und User Stories• Planung der Chatbot-Entwicklung• Chatbot-Persönlichkeit und Conversational Experience• Conversation Design, Proof-of-Concept und Prototyping• Dialogablauf und Copywriting • Implementierung, Finetuning und Roll-Out• Evaluation und Continuous Improvement

This book features a collection of high-quality research papers presented at the International Conference on Tourism, Technology and Systems (ICOTTS 2022), held at University of Chile, Santiago de Chile, Chile, from 3 to 5 November 2022. The book is divided into two volumes, and it covers the areas of technology in tourism and the tourist experience, generations and technology in tourism, digital marketing applied to tourism and travel, mobile technologies applied to sustainable tourism, information technologies in tourism, digital transformation of tourism business, e-tourism and tourism 2.0, big data and management for travel and tourism, geotagging and tourist mobility, smart destinations, robotics in tourism, and information systems and technologies.

Ihr Unternehmen hat sich für KI entschieden. Glückwunsch, was nun? Dieses praktische Buch bietet einen ganzheitlichen Plan für die Implementierung von KI aus der Perspektive der IT und des IT-Betriebs im Unternehmen. Sie erfahren etwas über die Fähigkeiten, das Potenzial, die Grenzen und die Herausforderungen von KI. In diesem Buch erfahren Sie, welche Rolle KI im Kontext etablierter Bereiche wie Design Thinking und DevOps, Governance und Change Management, Blockchain und Quantum Computing spielt, und diskutieren die Konvergenz von KI in diesen Schlüsselbereichen des Unternehmens.Deploying AI in the Enterprise bietet Anleitungen und Methoden zur effektiven Bereitstellung und Operationalisierung nachhaltiger KI-Lösungen. Sie lernen die Herausforderungen bei der Implementierung kennen, wie z. B. Probleme bei der KI-Operationalisierung und Hindernisse bei der Umsetzung von Erkenntnissen in umsetzbare Prognosen. Sie werden auch lernen, wie Sie die Schlüsselkomponenten der KI-Informationsarchitektur erkennen und welche Rolle sie für eine erfolgreiche und nachhaltige KI-Implementierung spielt. Und Sie werden verstehen, wie Sie KI effektiv einsetzen können, um die Nutzung von Kerninformationen in Master Data Management (MDM)-Lösungen zu verbessern.Was Sie lernen werdenVerstehen der wichtigsten KI-Konzepte, einschließlich maschinelles Lernen und Deep LearningBefolgen von Best Practices und Methoden zur erfolgreichen Bereitstellung und Operationalisierung von KI-LösungenErkennen der kritischen Komponenten der KI-Informationsarchitektur und der Bedeutung eines PlansIntegration von KI in bestehende Initiativen innerhalb einer OrganisationErkennen der aktuellen Grenzen von KI und wie sich dies auf Ihr Unternehmen auswirken könnteBewusstsein für wichtige und aktuelle KI-Forschung schaffenIhre Denkweise anpassen, um KI von einem ganzheitlichen Standpunkt aus zu betrachtenMachen Sie sich mit den Möglichkeiten von KI in verschiedenen Branchen vertraut.Für wen ist dieses Buch gedacht?IT-Profis, Datenwissenschaftler und Architekten, die sich mit den Herausforderungen bei der Implementierung und dem Betrieb von KI auseinandersetzen müssen und einen umfassenden Überblick darüber benötigen, wie sich KI auf andere geschäftskritische Bereiche auswirkt. Es ist keine Einführung, sondern richtet sich an Leser, die nach Beispielen für die Nutzung von Daten suchen, um daraus verwertbare Erkenntnisse und Vorhersagen abzuleiten, und die die aktuellen Risiken und Grenzen von KI verstehen und berücksichtigen müssen und wissen wollen, was dies in einem branchenrelevanten Kontext bedeutet.

This book includes peer reviewed articles from the 4th International Conference on Data Science, Machine Learning and Applications, 2022, held at the Hyderabad Institute of Technology & Management on 26-27th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

Smart Buildings sind intelligente, nachhaltige sowie mit ihrem ökologischen, ökonomischen und technologischen Umfeld vernetzte Gebäude, die ein Höchstmaß an Nutzerkomfort bieten und einen positiven Beitrag zum Umwelt- insbesondere auch Klimaschutz und damit für die Zukunft der Menschheit leisten. Ziel dieses essentials ist es, Projektentwicklern, Architekten, Fachplanern, Managern sowie Aufsichts- und Beiräten einen prägnanten Überblick über den Beitrag von Smart Buildings zur nachhaltigen Entwicklung zu ermöglichen.

Während die Technologie im Zeitalter des maschinellen Lernens rasant voranschreitet, mangelt es an klaren Absichten und der Formulierung akzeptabler ethischer Standards. Dieses Buch fasst das komplexe Thema der'guten'Technologie bereichsübergreifend zusammen und wechselt zwischen Theorie und Praxis. Die Autoren gehen auf die sich ständig ausweitende Diskussion über Künstliche Intelligenz (KI) und Ethik ein und geben eine Orientierung. Dabei werden insbesondere pragmatische und aktuelle Fragestellungen berücksichtigt, wie z.B. die Kollateralwirkungen der COVID19-Pandemie. Ein aktueller Überblick über die Digitalisierung - an sich schon ein sehr weites Feld - wird ebenso vorgestellt wie eine Analyse der Ansätze von KI aus ethischer Perspektive. Darüber hinaus werden konkrete Ansätze zur Berücksichtigung angemessener ethischer Prinzipien in KI-basierten Lösungen angeboten. Das Buch richtet sich sowohl an Wissenschaftler aus geistes- und wirtschaftswissenschaftlichen oder technischen Disziplinen als auch an Praktiker, die eine Einführung in das Thema und eine Orientierung mit konkreten Fragen und Hilfestellungen suchen.