This book discusses the effective use of modern ICT solutions for business needs, including the efficient use of IT resources, decision support systems, business intelligence, data mining and advanced data processing algorithms, as well as the processing of large datasets (inter alia social networking such as Twitter and Facebook, etc.). The ability to generate, record and process qualitative and quantitative data, including in the area of big data, the Internet of Things (IoT) and cloud computing offers a real prospect of significant improvements for business, as well as the operation of a company within Industry 4.0. The book presents new ideas, approaches, solutions and algorithms in the area of knowledge representation, management and processing, quantitative and qualitative data processing (including sentiment analysis), problems of simulation performance, and the use of advanced signal processing to increase the speed of computation. The solutions presented are also aimed at the effective use of business process modeling and notation (BPMN), business process semantization and investment project portfolio selection. It is a valuable resource for researchers, data analysts, entrepreneurs and IT professionals alike, and the research findings presented make it possible to reduce costs, increase the accuracy of investment, optimize resources and streamline operations and marketing.

Value-creation in Middle Market Private Equity by John A. Lanier holistically examines the ecosystem relationships between middle market private equity firms and their portfolio companies. Small business is the job creating engine in the US economy, and consequently is a prime target market for private equity investment. Indeed, private equity backs over six of each 100 private sector jobs. Both the small businesses in which private equity firms invest, and the private equity firms making the investments, face inter- and intra-company fiduciary leadership challenges while implementing formulated strategy. The architecture of each private equity firm-portfolio company relationship must be uniquely crafted to capitalize on the projected return on investment that is memorialized in the investment thesis. Given the leveraged capital structure of portfolio companies, the cost of a misstep is problematic. Individual private equity professionals are typically members of multiple investment teams for the firm. Not only may each investment team have its own unique leadership style, but its diverse members have to assimilate styles for each team in which they participate relative to a specific portfolio company. Acquisitions and their subsequent integrations add exponential complexity for both private equity investment and portfolio company leadership teams; indeed, cultural integration ranks among the most chronic acquisition obstacles. Accordingly, the stakeholders of private equity transactions do well to embrace leadership best practices in applying value-creation toolbox best practices. The perspectives of both the private equity investment team and the portfolio company leadership team are within the scope of these chapters.

Supply Chain Management, Enterprise Resources Planning (ERP), and Advanced Planning Systems (APS) are important concepts in order to organize and optimize the flow of materials, information and financial funds. This book, already in its fifth edition, gives a broad and up-to-date overview of the concepts underlying APS. Special emphasis is given to modeling supply chains and implementing APS successfully in industry. Understanding is enhanced by several case studies covering APS from various software vendors. The fifth edition contains updated material, rewritten chapters and an additional case study.

Dynamic complexity results from hidden, un known factors-or more precisely, interactions between factors-that can unexpectedly im pact the perfor mance of systems. When the influences of dynamic complexity are not meas ured and understood, new never-seen-before behaviors can come as unwelcomed surprises, which disrupt the performance of systems. Left alone, processes that were once prized for their effi ciency unexpectedly begin to degrade-costs increase, while volumes and quality decline. Evidence of problems may come too late for effective resolution as technology advance ments induce rapid change and compress the time available to react to that change. The results of dynamic complexity are always negative and unmanaged dynamic complexity can bring business or global systems to the point of sudden chaos. The 2009 H1N1 pandemic, 2008 Credit Crunch and 2011 Fukushima Daiichi nuclear disaster are global examples of the dangers of undiagnosed dynamic complexity. With increasing frequency executive leaders today are discovering that their business and IT system performance levels are not meeting expectations. In most cases these performance deficiencies are caused by dynamic complexity, which lies hidden like a cancer until the symptoms reveal themselves-often when it is too late to avoid negative impacts on business outcomes. This book examines the growing business problem of dynamic complexity and presents a path to a practical solution. To achieve better predictability, organizations must be able to expose new, dangerous patterns of behavior in time to take corrective actions and know which actions will yield the optimal results. The book authors promote new methods of risk management that use data collection, analytics, machine learning and automation processes to help organizations more accurately predict the future and take strategic actions to improve performance outcomes. The presented means of achieving this goal are based upon the authors' practical experiences, backed by scientific principles, and results achieved through consulting engagements with over 350 global organizations.

This book acts as a valuable quick-access resource on the challenges and opportunities that the digital age presents to organizational leadership. Balanced, comprehensive, and thought-provoking, the book will be useful to professionals and practitioners. The book broadly follows a macro, meso, and micro approach to argumentation and is best read from beginning to end. The book synopsizes the historical context of technological revolutions and reflects on first-order results from enhanced use of information and communication technology in organizations; considers second-level impacts from information and communication technology on economy, society, work, and the very act of organizing; maps out core concepts of agility and principles that leaders should honor to exploit agility in newfound workforce ecosystems; showcases emerging leadership behaviors and mindsets; and specifies the good practice needed to plan and lead digital strategies. The book invites reference to the author's popular Knowledge Solutions: Tools, Methods, and Approaches to Drive Organizational Performance (2017) and the more recent Leading Solutions: Essays in Business Psychology (2021), which it both rests on and extends.

Information Technology (IT) - the field that links computer and communications equipment and software - is transforming the way modern business is done. Examples of factors leading these changes are: rapidly decreasing costs of computer hardware, government de-regulation, accelerating global competitiveness, an increasing management awareness, and the knowledge of how to employ Information Technology successfully. These have all led to the increase of IT's effects on existing markets, and, in the process, are creating entirely new markets. This book explores a variety of advances in IT by a group of researchers who are at the cutting edge of this research. Moreover, the book examines these innovative developments in terms of the Information Technology field and its effect on modern business. It is becoming increasingly apparent that IT is critical to success in today's competitive marketplace. As a result, this book examines a host of emerging effects at work in these developments and seeks to make sense out of these counter-acting, sometimes multiplicative, effects which can become obstacles for managers who wish to develop competitive applications of IT. These effects and the development of IT are grouped into four general categories in the book: Future Markets, Inter-Organizational Systems, Focused Applications, and Future Strategies.

In H2H Marketing the authors focus on redefining the role of marketing by reorienting the mindset of decision-makers and integrating the concepts of Design Thinking, Service-Dominant Logic and Digitalization. It's not just technological advances that have made it necessary to revisit the way everybody thinks about marketing; customers and marketers as human decision-makers are changing, too. Therefore, having the right mindset, the right management approach and highly dynamic implementation processes is key to creating innovative and meaningful value propositions for all stakeholders. This book is essential reading for the following groups: Executives who want to bring new meaning to their lives and organizations Managers who need inspirations and evidence for their daily work in order to handle the change management needed in response to the driving forces of technology, society and ecology Professors, trainers and coaches who want to apply the latest marketing principles Students and trainees who want to prepare for the future Customers of any kind who need to distinguish between leading companies Employees of suppliers and partners who want to help their firms stand out. The authors review the status quo of marketing and outline its evolution to the new H2H Marketing. In turn, they demonstrate the new marketing paradigm with the H2H Marketing Model, which incorporates Design Thinking, Service-Dominant Logic and the latest innovations in Digitalization. With the new H2H Mindset, Trust and Brand Management and the evolution of the operative Marketing Mix to the updated, dynamic and iterative H2H Process, they offer a way for marketing to find meaning in a troubled world.

This book covers important issues related to managing supply chain risks from various perspectives. Supply chains today are vulnerable to disruptions with a significant impact on firms' business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. This book presents a set of models, frameworks, strategies, and analyses that are essential for managing supply chain risks. As a comprehensive collection of the latest research and most recent cutting-edge developments on supply chain risk and its management, the book is structured into three main parts: 1) Supply Chain Risk Management; 2) Supply Chain Vulnerability and Disruptions Management; and 3) Toward a Resilient Supply Chain. Leading academic researchers as well as practitioners have contributed chapters, combining theoretical findings and research results with a practical and contemporary view on how companies can manage the supply chain risks and disruptions, as well as how to create a resilient supply chain. This book can serve as an essential source for students and scholars who are interested in pursuing research or teaching courses in the rapidly growing area of supply chain risk management. It can also provide an interesting and informative read for managers and practitioners who need to deepen their knowledge of effective supply chain risk management.

This write-in workbook is an invaluable resource to help students improve their Maths and English skills and help prepare for Level 1 and Level 2 Functional Skills exams. The real-life questions are all written with a business administration context to help students find essential Maths and English theory understandable, engaging and achievable. Written by Carole Vella, lecturer with a wealth of experience in the Retail and Business Administration industry, this workbook is an effective resource to support Maths and English learning in the classroom, at work and for personal study at home.

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 provides an understanding of innovation models and why they are important in the business context, and considers sources of innovation and how to apply business frameworks using real-world examples of innovation-led businesses. After providing a solid background to the key concepts related to innovation models, the book looks at why innovation takes place and where the sources of innovation lie, from corporate research to crowd-sourced and government-funded initiatives. Innovation models across manufacturing, services and government are explored, as well as measuring innovation, and the impact of design thinking and lean enterprise principles on innovation and sustainability-driven imperatives. Offering a truly comprehensive and global approach, Business Innovation should be core or recommended reading for advanced undergraduate, postgraduate, MBA and Executive Education students studying Innovation Management, Strategic Management and Entrepreneurship.

With this textbook, Vaisman and Zimanyi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details "Implementation and Deployment," including physical design, ETL and data warehouse design methodologies. Part III covers "Advanced Topics" and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQL database systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. "I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition." From the foreword by Panos Vassiliadis, University of Ioannina, Greece.

This book includes high-quality research papers presented at 20th International Conference on Informatics in Economy (IE 2021), which is held in Bucharest, Romania during May 2021. The book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data-mining and machine learning, quantitative economics.

This supplement text bridges the gap between the fundamentals of how businesses operate (processes) and the tools that business people use to accomplish their tasks (systems). The authors have developed this text for an introductory MIS or general business course to establish a fundamental understanding of business processes. Business students, regardless of their functional discipline, will be able to apply the real-world concepts discussed in this text immediately upon entering the workforce.

As more and more businesses adopt enterprise systems globally, it becomes increasingly important for business schools to offer a process-based curriculum to better reflect the realities of modern business. Given the integration of business operations and enterprise systems, Magal and Word have designed this text to reflect, in a "practical and accessible" format, how real-world business processes are managed and executed.

Inspired by the podcast Dear Multi-Hyphenate, this book explores how to be a multi-hypenate - an artist with multiple proficiencies - in the entertainment industry. Answers questions about individual mission-driven entrepreneurship in the Theatre industry. Each chapter features an interview with a notable theatre artist.

This book helps marketing decision makers in allocating their budget to diverse communication channels and different business units in an ROI-optimal way, and to adapt it in an agile manner. The optimal allocation of resources in marketing is not very complex in theory, but in practice a variety of questions arise, for example: How do you find the optimal mix, even across brands and product lines, and how do you adjust it dynamically? What is the right balance between image and performance marketing? How do you tackle strategic data management and other organizational challenges? The authors guide the reader through the entire process from data collection to marketing mix modeling and campaign tracking to tool selection. The book strikes the right balance between theoretical sophistication and necessary pragmatism, with numerous concrete recommendations for decision makers.

The three volumes of Interest Rate Modeling present a comprehensive and up-to-date treatment of techniques and models used in the pricing and risk management of fixed income securities. Written by two leading practitioners and seasoned industry veterans, this unique series combines finance theory, numerical methods, and approximation techniques to provide the reader with an integrated approach to the process of designing and implementing industrial-strength models for fixed income security valuation and hedging. Aiming to bridge the gap between advanced theoretical models and real-life trading applications, the pragmatic, yet rigorous, approach taken in this book will appeal to students, academics, and professionals working in quantitative finance. Volume I provides the theoretical and computational foundations for the series, emphasizing the construction of efficient grid- and simulation-based methods for contingent claims pricing. The second part of Volume I is dedicated to local-stochastic volatility modeling and to the construction of vanilla models for individual swap and Libor rates. Although the focus is eventually turned toward fixed income securities, much of the material in this volume applies to generic financial markets and will be of interest to anybody working in the general area of asset pricing.

People have a hard time communicating, and also have a hard time finding business knowledge in the environment. With the sophistication of search technologies like Google, business people expect to be able to get their questions answered about the business just like you can do an internet search. The truth is, knowledge management is primitive today, and it is due to the fact that we have poor business metadata management.
This book is about all the groundwork necessary for IT to really support the business properly. By providing not just data, but the context behind the data. For the IT professional, it will be tactically practical--very "how to" and a detailed approach to implementing best practices supporting knowledge management. And for the the IT or other manager who needs a guide for creating and justifying projects, it will help provide a strategic map.

* First book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management.
* Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, and filled with war stories, examples, and cases from current projects.
* Very practical, includes a complete metadata acquisition methodology and project plan to guide readers every step of the way.
* Includes sample unstructured metadata for use in self-testing and developing skills.

The main objective is to provide quick and essential knowledge for the subject with the help of summary and solved questions /case studies without going into detailed discussion. This book will be much helpful for the students as a supplementary text/workbook; and to the non-computer professionals, who deal with the systems analysis and design as part of their business. Such problem solving approach will be able to provide practical knowledge of the subject and similar learning output, without going into lengthy discussions. Though the book is conceived as supplementary text/workbook; the topics are selected and arranged in such a way that it can provide complete and sufficient knowledge of the subject.

Artificial intelligence - and social responsibility. Two topics that are at the top of the business agenda. This book discusses in theory and practice how both topics influence each other. In addition to impulses from the current often controversial scientific discussion, it presents case studies from companies dealing with the specific challenges of artificial intelligence. Particular emphasis is placed on the opportunities that artificial intelligence (AI) offers for companies from different industries. The book shows how dealing with the tension between AI and challenges caused by new corporate social responsibility creates strategic opportunities and also innovation opportunities. It highlights the active involvement of stakeholders in the design process, which is meant to build trust among customers and the public and thus contributes to the innovation and acceptance of artificial intelligence. The book is aimed at researchers and practitioners in the fields of corporate social responsibility as well as artificial intelligence and digitalization. The chapter "Exploring AI with purpose" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book establishes constructivist, interpretivist, and linguistic approaches based on conventions about the nature of qualitative and text data, the author's influence on text interpretation, and the validity checks used to justify text interpretations. Vast quantities of text and qualitative data in organizations often go unexplored. Text analytics outlined in this book allow readers to understand the process of converting unstructured text data into meaningful data for analysis in order to measure employee opinions, feedback, and reviews through sentiment analysis to support fact-based decision making. The methods involve using NVivo and RapidMiner software to perform lexical analysis, categorization, clustering, pattern recognition, tagging, annotation, memo creation, information extraction, association analysis, and visualization. The methodological approach in the book uses innovation theory as a sensitizing concept to lay the foundation for the analysis of research data, suggesting approaches for empirical exploration of organizational learning, knowledge management, and innovation practices amongst geographically dispersed individuals and team members. Based on data obtained from a private educational organization that has offices dispersed across Asia through focus group discussions and interviews on these topics, the author highlights the need for integrating organizational learning, knowledge management, and innovation to improve organizational performance, exploring perspectives on collective relationships and networks, organizational characteristics and structures, and tacit and overt values which influence such innovation initiatives. In the process, the author puts forward a new theory which is built on three themes: relationship and networks, knowledge sharing mechanisms, and the role of social cognitive schema that facilitate emergent learning, knowledge management, and innovation.

Software systems that used to be relatively autonomous entities such as e.g. accounting systems, order-entry systems etc. are now interlinked in large networks comprising extensive information infrastructures. What earlier used to be stand-alone proprietary systems are now for the most part replaced by more or less standardized interdependent systems that form large networks of production and use. Organizations have to make decisions about what office suite to purchase? The easiest option is to continuously upgrade the existing office suite to the latest version, but the battle between WordPerfect and Microsoft Word demonstrated that the choice is not obvious. What instant messenger network to join for global communication? Preferably the one most colleagues and friends use; AOL Instant Messenger, Microsoft Messenger, and ICQ represent three satisfactory, but disjunctive alternatives. Similarly organizations abandon their portfolio of homegrown IT systems and replace them with a single Enterprise Resource Planning (ERP) system. Several ERP alternatives exist on the market, but which is the right one for you? The argumentation and rationale behind these considerations are obviously related to the technological and social networks we are embedded in, but it is not always easy to specify how.
Networked Information Technologies: Diffusion and Adoption offers contributions from academics and practitioners who study networked information systems from a diffusion and adoption point of view. Themes related to the conceptualisation of diffusion and adoption of networked information systems are discussed along with studies of the diffusion of networked information systems in public sector institutions and private businesses.
This volume contains the edited proceedings of the IFIP Conference on The Diffusion and Adoption of Networked Information Technologies, which was sponsored by the International Federation for Information Processing (IFIP) Working Group 8.6 and held in Copenhagen, Denmark in October 2003.

Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students' anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep ("organic") understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/

This book is a review of the analytical methods required in most of the quantitative courses taught at MBA programs. Students with no technical background, or who have not studied mathematics since college or even earlier, may easily feel overwhelmed by the mathematical formalism that is typical of economics and finance courses. These students will benefit from a concise and focused review of the analytical tools that will become a necessary skill in their MBA classes. The objective of this book is to present the essential quantitative concepts and methods in a self-contained, non-technical, and intuitive way.