Описание: Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications.
Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes:
The role of analytics in delivering effective messages on the web
Understanding the web by understanding its hidden structures
Being recognized on the web - and watching your own competitors
Visualizing networks and understanding communities within them
Measuring sentiment and making recommendations
Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics
Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.
Автор: Antoniou, Constantinos Название: Mobility Patterns, Big Data and Transport Analytics ISBN: 0128129700 ISBN-13(EAN): 9780128129708 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Поставка под заказ.
Описание:
Transportation modelers and analysts face new opportunities and challenges in the study of mobility patterns and transportation systems, thanks to the advent of paradigm-shifting big data. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications provides a guide to this new analytical framework related to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling.
Transportation systems analysis relies upon assumptions related to social, collective, personal, or disaggregate organization of desires expressed by the mobility of people or goods. Recent advances in information technology - such as available data from open sources, participation in media platforms, and sensor technologies - have created an environment of great change, and the potential for transportation structural reorganization. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications features prominent international expert overview on these new analytical frameworks, applications, and concepts in mobility analysis and transportation systems.
The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.
Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics
Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends
Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field
Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach
Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data
Автор: Murugan Anandarajan Название: Aligning business strategies and analytics. ISBN: 3319932985 ISBN-13(EAN): 9783319932989 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines issues related to the alignment of business strategies and analytics. Chapter 4 focuses on a case study of ARI, a leading fleet management company, and explores the application of advanced analytics to various facets of the industry and the company`s experience in aligning analytics with its business strategy.
Автор: Florica Tomos, Naresh Kumar, Nick Clifton, Denis H Название: Women Entrepreneurs and Strategic Decision Making in the Global Economy ISBN: 1522574794 ISBN-13(EAN): 9781522574798 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: There has been an increase in women entrepreneurs participating in the growth of local, regional, national, and global economies. While these women showcase crucial skills for strategic leadership and strategy that can advance companies, they face cultural, educational, social, and political barriers that impede their development and participation within the global economy.Women Entrepreneurs and Strategic Decision Making in the Global Economy is a pivotal reference source that provides vital research on understanding the value of women entrepreneurs and the strategies they can use on the economy and examines gender impact on strategic management and entrepreneurship. While highlighting topics such as emotional intelligence, global economy, and strategic leadership, this book is ideally designed for managers, entrepreneurs, policymakers, academicians, and students.
Автор: Murugan Anandarajan; Chelsey Hill; Thomas Nolan Название: Practical Text Analytics ISBN: 3319956620 ISBN-13(EAN): 9783319956626 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces text analytics as a valuable method for deriving insights from text data. Unlike other text analytics publications, Practical Text Analytics: Maximizing the Value of Text Data makes technical concepts accessible to those without extensive experience in the field. Using text analytics, organizations can derive insights from content such as emails, documents, and social media. Practical Text Analytics is divided into five parts. The first part introduces text analytics, discusses the relationship with content analysis, and provides a general overview of text mining methodology. In the second part, the authors discuss the practice of text analytics, including data preparation and the overall planning process. The third part covers text analytics techniques such as cluster analysis, topic models, and machine learning. In the fourth part of the book, readers learn about techniques used to communicate insights from text analysis, including data storytelling. The final part of Practical Text Analytics offers examples of the application of software programs for text analytics, enabling readers to mine their own text data to uncover information.
Chapter 1: Introduction to Risk and Uncertainty. This chapter provides: a) general discussion on the types of uncertainties in projects including the examples; we cover theoretical, frequentist, belief-based epistemic, as well as agnostic viewpoints on the uncertainty; we show these viewpoints in context of typical project uncertainties and contrast them against representations of uncertainty in other engineering disciplines; b) summary on the role of knowledge and assumptions in characterizing the uncertainty; we link the discussion on uncertainty to knowledge about the underlying phenomena, the embedded assumptions, and their validity over the course of the project; c) overview on the approaches that relate the risk to the underlying uncertainty; we discuss approaches to the risk-uncertainty relationship in different disciplines, and finally d) discussion on the organizational attitude and viewpoints toward the risk and uncertainty; we cover topics such as value of u
ncertainty (is it always bad?), organizational responsibility towards risk (who should be taking risk, when, and how much?), and the contrast between the decision-theoretic vs. managerial viewpoint on the uncertainty showing the differences that govern the choice of analysis and the methods.
Chapter 2.Project Risk Management Framework. This chapter provides: a) overview of the project systems, their complexity, life-cycle and risk-based decision-making; we define project as a complex system, and its life-cycle in the context of phase-gate process where decisions are evaluated under different objectives and criteria; we emphasize the points where the uncertainty is introduced and when it is reflected in project outcomes; we particularly stress the design and construction/installation i.e. execution phases of a project as this is the key focus of this text; b) outline of the high-level guidelines in conducting risk assessment and management (such as
ISO and PMI approach), the use of "risk language" and common terms in communicating risk (such as SRA glossary of terms), and more detailed description of each step; we particularly emphasize risk identification and assessment as they are the key focus of this text; c) formal definition of risk in projects distinguishing between variability of operations, event driven risk factors, and the combination of the two; also, we discuss risks in context of low probability - high impact and low impact - high probability; we emphasize the role of assumptions and knowledge in formally developing risk statement; and finally d) classifications methods for project risks as they relate to project objectives, their inception and resolution period, relationship to project structure i.e. internal-external, technical-no technical, and other key project parameters. The chapter includes homework examples.
Chapter 3: Project Data. This chapter provides a comprehensive summary on the type and sources of project data, and the methods for data acquisition. The key underpinning of this text is that risk analysis should be driven by data in a mathematically rigorous way; so where can one find such data? This chapter covers project data as they relate to planning and execution phase of the project; more specifically, we discuss data in terms of: a) project phase and system of interest; we contrast available data during planning and estimation vs. data during monitoring and control phase of the project, as well as whether data relates to internal project system (logistics, operations, etc.) or environmental systems (weather, market trends, etc), we define data collection objectives for each of the phase and the system type; b) observed vs. judgement/simulated data, or in other words, whether data is generated by the system and recorded by the participants, or assessed by individuals using their experience, judgements, models, or just gut f
Автор: P K Kapur; Ompal Singh Название: Strategic System Assurance and Business Analytics ISBN: 9811536465 ISBN-13(EAN): 9789811536465 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues.
Описание: This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems.
Описание: Prologue: Mail-order companies without catalogues, orchestras without conductors, self-determined footballers and five colours.- Creative Destruction - the Digital Revolution and its Consequences.- A brief history of the management ideas of the 20th century.- Cracks in the world view of classical management.- A Brief History of Successful Lateral Organizations.- Lateral Management in the 21st Century.- Epilogue.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492008 ISBN-13(EAN): 9781526492005 Издательство: Sage Publications Рейтинг: Цена: 7285.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Автор: Gerald William Evans, William E. Biles, Ki-Hwan G. Bae Название: Analytics, Operations, and Strategic Decision Making in the Public Sector ISBN: 152257591X ISBN-13(EAN): 9781522575917 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 31324.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Analytics for the public sector involves the application of operations research and statistical techniques to solve various problems existing outside of the private sector. The use of analytics for the public sector results in more efficient and effective services for the clients and users of these systems.Analytics, Operations, and Strategic Decision Making in the Public Sector is an essential reference source that discusses analytics applications in various public sector organizations, and addresses the difficulties associated with the design and operation of these systems including multiple conflicting objectives, uncertainties and resulting risk, ill-structured nature, combinatorial design aspects, and scale. Featuring research on topics such as analytical modeling techniques, data mining, and statistical analysis, this book is ideally designed for academicians, educators, researchers, students, and public sector professionals including those in local, state, and federal governments; criminal justice systems; healthcare; energy and natural resources; waste management; emergency response; and the military.
Описание: This book outlines the benefits and limitations of simulation, what is involved in setting up a simulation capability in an organization, the steps involved in developing a simulation model and how to ensure that model results are implemented. In addition, detailed example applications are provided to show where the tool is useful and what it can offer the decision maker. In Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics , Andrew Greasley provides an in-depth discussion of Business process simulation and how it can enable business analytics How business process simulation can provide speed, cost, dependability, quality, and flexibility metrics Industrial case studies including improving service delivery while ensuring an efficient use of staff in public sector organizations such as the police service, testing the capacity of planned production facilities in manufacturing, and ensuring on-time delivery in logistics systems State-of-the-art developments in business process simulation regarding the generation of simulation analytics using process mining and modeling people’s behavior Managers and decision makers will learn how simulation provides a faster, cheaper and less risky way of observing the future performance of a real-world system. The book will also benefit personnel already involved in simulation development by providing a business perspective on managing the process of simulation, ensuring simulation results are implemented, and that performance is improved.
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