Heuristics In Analytics

Author : Carlos Andre Reis Pinheiro,Fiona McNeill
Publisher : John Wiley & Sons
Page : 256 pages
File Size : 44,8 Mb
Release : 2014-01-31
Category : Business & Economics
ISBN : 9781118416747

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Heuristics in Analytics by Carlos Andre Reis Pinheiro,Fiona McNeill Pdf

Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more. Robust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. Heuristics in Analytics describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to: Realize just how random the world is, and how unplanned events can affect analysis Integrate heuristic and analytical approaches to modeling and problem solving Discover how graph analysis is applied in real-world scenarios around the globe Apply analytical knowledge to customer behavior, insolvency prevention, fraud detection, and more Understand how text analytics can be applied to increase the business knowledge Every single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, Heuristics in Analytics contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.

Author : Carlos Andre Reis Pinheiro,Fiona McNeill
Publisher : John Wiley & Sons
Page : 256 pages
File Size : 47,6 Mb
Release : 2014-03-03
Category : Business & Economics
ISBN : 9781118347607

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Heuristics in Analytics by Carlos Andre Reis Pinheiro,Fiona McNeill Pdf

Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more. Robust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. Heuristics in Analytics describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to: Realize just how random the world is, and how unplanned events can affect analysis Integrate heuristic and analytical approaches to modeling and problem solving Discover how graph analysis is applied in real-world scenarios around the globe Apply analytical knowledge to customer behavior, insolvency prevention, fraud detection, and more Understand how text analytics can be applied to increase the business knowledge Every single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, Heuristics in Analytics contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.

Author : Jürgen Deters
Publisher : Walter de Gruyter GmbH & Co KG
Page : 606 pages
File Size : 48,7 Mb
Release : 2022-11-07
Category : Business & Economics
ISBN : 9783110980967

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Analytics and Intuition in the Process of Selecting Talent by Jürgen Deters Pdf

Human decisions, especially in management and personnel selection, are based on making judgments about people analytically and intuitively. Yet in business and scientific contexts, judgments are expected to be based on a rational analysis rather than intuitions or emotions. Intuition is often seen as something mystical that should not be trusted and thus eliminated from human decision-making. Our empirical and theoretical research shows that this is impossible when people are dealing with people. Instead, intuitions and emotions have significant power in the decision-making process. Neuroscience even shows that humans are incapable of switching off their emotions or intuitions when making decisions. Therefore, intuition and emotions as evolutionary achievements of human beings should be looked at more closely to use the wisdom they offer. This book provides an insight into the current state of research on rational-analytical procedures in personnel selection and complements this with research on intuitions and emotions in personnel diagnostics. By integrating scientifically verifiable rational-analytical decision-making procedures with the inner experiential knowledge of people, this book bridges two complementary ways of recognizing and making good decisions. It demonstrates how intuitions are developed and used in different fields of practice and cultures and how scientific research results from rational-analytical and intuitive-emotional selection procedures are successfully integrated by practitioners.

Author : Steven Orla Kimbrough,Hoong Chuin Lau
Publisher : CRC Press
Page : 308 pages
File Size : 47,9 Mb
Release : 2018-09-03
Category : Business & Economics
ISBN : 9781315362595

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Business Analytics for Decision Making by Steven Orla Kimbrough,Hoong Chuin Lau Pdf

Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.

Author : Simone Gressel,David J. Pauleen,Nazim Taskin
Publisher : SAGE
Page : 354 pages
File Size : 49,5 Mb
Release : 2020-10-12
Category : Business & Economics
ISBN : 9781529738285

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Management Decision-Making, Big Data and Analytics by Simone Gressel,David J. Pauleen,Nazim Taskin Pdf

Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

Author : Abraham Duarte,Manuel Laguna,Rafael Marti
Publisher : Springer
Page : 136 pages
File Size : 46,8 Mb
Release : 2017-11-24
Category : Business & Economics
ISBN : 9783319681191

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Metaheuristics for Business Analytics by Abraham Duarte,Manuel Laguna,Rafael Marti Pdf

This essential metaheuristics tutorial provides descriptions and practical applications in the area of business analytics. It addresses key problems in predictive and prescriptive analysis, while also illustrating how problems that arise in business analytics can be modelled and how metaheuristics can be used to find high-quality solutions. Readers will be introduced to decision-making problems for which metaheuristics offer the most effective solution technique. The book not only shows business problem modelling on a spreadsheet but also how to design and create a Visual Basic for Applications code. Extra Material can be downloaded at http://extras.springer.com/978-3-319-68117-7.

Author : Pascal Alphonse
Publisher : Springer Nature
Page : 344 pages
File Size : 54,5 Mb
Release : 2024-06-05
Category : Electronic
ISBN : 9783031290503

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Essays on Financial Analytics by Pascal Alphonse Pdf

Author : Pablo Moscato,Natalie Jane de Vries
Publisher : Springer
Page : 1005 pages
File Size : 45,6 Mb
Release : 2019-05-30
Category : Computers
ISBN : 9783030062224

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Business and Consumer Analytics: New Ideas by Pablo Moscato,Natalie Jane de Vries Pdf

This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.

Author : David A. Bader
Publisher : CRC Press
Page : 681 pages
File Size : 55,6 Mb
Release : 2022-07-20
Category : Business & Economics
ISBN : 9781000538694

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Massive Graph Analytics by David A. Bader Pdf

"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.

Author : Zheng Xiang,Daniel R. Fesenmaier
Publisher : Springer
Page : 307 pages
File Size : 47,6 Mb
Release : 2016-10-12
Category : Business & Economics
ISBN : 9783319442631

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Analytics in Smart Tourism Design by Zheng Xiang,Daniel R. Fesenmaier Pdf

This book presents cutting edge research on the development of analytics in travel and tourism. It introduces new conceptual frameworks and measurement tools, as well as applications and case studies for destination marketing and management. It is divided into five parts: Part one on travel demand analytics focuses on conceptualizing and implementing travel demand modeling using big data. It illustrates new ways to identify, generate and utilize large quantities of data in tourism demand forecasting and modeling. Part two focuses on analytics in travel and everyday life, presenting recent developments in wearable computers and physiological measurement devices, and the implications for our understanding of on-the-go travelers and tourism design. Part three embraces tourism geoanalytics, correlating social media and geo-based data with tourism statistics. Part four discusses web-based and social media analytics and presents the latest developments in utilizing user-generated content on the Internet to understand a number of managerial problems. The final part is a collection of case studies using web-based and social media analytics, with examples from the Sochi Olympics on Twitter, leveraging online reviews in the hotel industry, and evaluating destination communications and market intelligence with online hotel reviews. The chapters in this section collectively describe a range of different approaches to understanding market dynamics in tourism and hospitality.

Author : Cyrus F. Nourani
Publisher : CRC Press
Page : 294 pages
File Size : 43,6 Mb
Release : 2019-06-26
Category : Computers
ISBN : 9780429878718

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Computing Predictive Analytics, Business Intelligence, and Economics by Cyrus F. Nourani Pdf

This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume.

Author : Masaaki Kurosu
Publisher : Springer
Page : 617 pages
File Size : 54,9 Mb
Release : 2018-07-10
Category : Computers
ISBN : 9783319912387

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Human-Computer Interaction. Theories, Methods, and Human Issues by Masaaki Kurosu Pdf

The 3 volume-set LNCS 10901, 10902 + 10903 constitutes the refereed proceedings of the 20th International Conference on Human-Computer Interaction, HCI 2018, which took place in Las Vegas, Nevada, in July 2018. The total of 1171 papers and 160 posters included in the 30 HCII 2018 proceedings volumes was carefully reviewed and selected from 4346 submissions. HCI 2018 includes a total of 145 papers; they were organized in topical sections named: Part I: HCI theories, methods and tools; perception and psychological issues in HCI; emotion and attention recognition; security, privacy and ethics in HCI. Part II: HCI in medicine; HCI for health and wellbeing; HCI in cultural heritage; HCI in complex environments; mobile and wearable HCI. Part III: input techniques and devices; speech-based interfaces and chatbots; gesture, motion and eye-tracking based interaction; games and gamification.

Author : Guillermo Gallego,Huseyin Topaloglu
Publisher : Springer
Page : 336 pages
File Size : 52,7 Mb
Release : 2019-08-14
Category : Business & Economics
ISBN : 9781493996063

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Revenue Management and Pricing Analytics by Guillermo Gallego,Huseyin Topaloglu Pdf

“There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available.” Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. “The book by Gallego and Topaloglu provides a fresh, up-to-date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in-depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it." Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. “This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field.” Robert L. Phillips, Director of Pricing Research at Amazon “At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference.” Richard Ratliff, Research Scientist at Sabre “This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers.” Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK.

Author : Jeff Hendrickson
Publisher : Packt Publishing Ltd
Page : 281 pages
File Size : 49,8 Mb
Release : 2023-08-18
Category : Computers
ISBN : 9781804613818

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Unleashing the Power of UX Analytics by Jeff Hendrickson Pdf

Optimize UX analytics for your design workflow and discover effective techniques and strategies to craft unforgettable, impactful user experiences Purchase of the print or Kindle book includes a free PDF eBook Key Features Enhance your understanding of qualitative and quantitative analysis for successful UX projects Apply design thinking and use surveys, interviews, and UX analytics tools for better product design Overcome bottlenecks and challenges at each stage of the user experience Book DescriptionUX analytics is a field that recognizes the significance of understanding human behavior and emotions in designing user experiences. It goes beyond mere metrics and embraces a people-centric approach. With the help of this comprehensive guide, you’ll acquire essential skills, knowledge, and techniques to establish a top-notch UX analytics practice. Unleashing the Power of UX Analytics will equip you with the strategies and tactics necessary to effectively collect, analyze, and interpret data, empowering you to make informed decisions that enhance the overall user experience. It emphasizes the importance of empathy in comprehending user needs and desires, enabling you to create meaningful and impactful design solutions. As you advance, this book walks you through the entire UX analytics process, from setting goals and defining key performance indicators (KPIs) to implementing various research methods and tools. You'll gain insights into user interview best practices, usability testing, and techniques for gathering qualitative and quantitative data. Armed with the knowledge of data analysis and interpretation, you'll be able to uncover patterns, trends, and user preferences to make data-driven decisions.What you will learn Understand the significance of analytics in successful UX projects Apply design thinking as a problem-solving tool in a UX practice Explore taxonomies, dashboards, KPIs, and data visualizations to understand data enterprise in depth Discover key considerations to determine which UX analytics tools are best for your projects Craft a North Star statement and understand how it guides your work Design and deliver the best research findings collateral Get to grips with heuristics and performing the effective evaluations Who this book is forThis book is for product managers, UX researchers, designers, and anyone involved in UX and business development, both in management roles and as individual contributors. If you are looking to master the methodologies, principles, and best practices for driving product design decisions through UX analytics, this book is absolutely the right pick for you. While a basic understanding of user experience principles is beneficial, it is not a prerequisite, as everything you need to know will be explained.

Author : C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publisher : Springer Nature
Page : 412 pages
File Size : 53,9 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9789811500947

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Big Data Analytics: Systems, Algorithms, Applications by C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston Pdf

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.