Автор: Cachon, Gerard Terwiesch, Christian Название: Operations management ISBN: 1260547612 ISBN-13(EAN): 9781260547610 Издательство: McGraw-Hill Рейтинг: Цена: 9779.00 р. Наличие на складе: Поставка под заказ.
Описание: Cachon Operations Management 2e is designed for undergraduate students taking an introductory course in Operations Management. This text will share many of the strengths of Matching Supply with Demand: An Introduction to Operations Management. Operations Management by Cachon comprehensively spans the relevant domain of topics, is accessible to a typical undergraduate student (i.e., limited real world business experience), incorporates the latest research and knowledge, and provides thorough pedagogical support for instructors along with innovative learning support for students.
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Описание: Features statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting–edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data–driven healthcare analytics in an effort to provide more personalized and efficient healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance care quality and operational efficiency. Organized into two main sections, Part One features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part Two focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: Contributions from well–known international experts who shed light on new approaches in this growing area Discussions on contemporary methods and techniques to address the handling of rich and large–scale healthcare data as well as the overall optimization of healthcare system operations Numerous real–world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry Plentiful applications that showcase the various analytical methods and tools that can be applied to successful predictive modeling The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate–level courses typically offered within operations research, industrial engineering, business, and public health departments. Hui Yang, PhD, is Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University. His research interests include sensor–based modeling and analysis of complex systems for process monitoring/control; system diagnostics/prognostics; quality improvement; and performance optimization with special focus on nonlinear stochastic dynamics and the resulting chaotic, recurrence, self–organizing behaviors. Eva K. Lee, PhD, is Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, Director of the Center for Operations Research in Medicine and HealthCare, and Distinguished Scholar in Health System, Health Systems Institute at both Emory University School of Medicine and Georgia Institute of Technology. Her research interests include health risk prediction; early disease prediction and diagnosis; optimal treatment strategies and drug delivery; healthcare outcome analysis and treatment prediction; public health and medical preparedness; large–scale healthcare/medical decision analysis and quality improvement; clinical translational science; and business intelligence and organization transformation.
Автор: Bendoly Elliot Название: Visual Analytics for Management ISBN: 1138190721 ISBN-13(EAN): 9781138190726 Издательство: Taylor&Francis Рейтинг: Цена: 9645.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides students with an in-depth understanding of the concepts, frameworks and processes used to analyze and present visual data for better decision-making. Expert contributors provide guidance in translating complex concepts from large data sets and how this translation drives management practice.
Описание: This handbook focuses on Data Envelopment Analysis (DEA) applications in operations analytics which are fundamental tools and techniques for improving operation functions and attaining long-term competitiveness. In fact, the handbook demonstrates that DEA can be viewed as Data Envelopment Analytics.Chapters include a review of cross-efficiency evaluation; a case study on measuring the environmental performance of OECS countries; how to select a set of performance metrics in DEA with an application to American banks; a relational network model to take the operations of individual periods into account in measuring efficiencies; how the efficient frontier methods DEA and stochastic frontier analysis (SFA) can be used synergistically; and how to integrate DEA and multidimensional scaling.In other chapters, authors construct a dynamic three-stage network DEA model; a bootstrapping based methodology to evaluate returns to scale and convexity assumptions in DEA; hybridizing DEA and cooperative games; using DEA to represent the production technology and directional distance functions to measure band performance; an input-specific Luenberger energy and environmental productivity indicator; and the issue of reference set by differentiating between the uniquely found reference set and the unary and maximal types of the reference set.Finally, additional chapters evaluate and compare the technological advancement observed in different hybrid electric vehicles (HEV) market segments over the past 15 years; radial measurement of efficiency for the production process possessing multi-components under different production technologies; issues around the use of accounting information in DEA; how to use DEA environmental assessment to establish corporate sustainability; a summary of research efforts on DEA environmental assessment applied to energy in the last 30 years; and an overview of DEA and how it can be utilized alone and with other techniques to investigate corporate environmental sustainability questions.
Название: Applied big data analytics in operations management / ISBN: 1522508864 ISBN-13(EAN): 9781522508861 Издательство: Turpin Рейтинг: Цена: 23654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management.Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.
Автор: Rahul Saxena; Anand Srinivasan Название: Business Analytics ISBN: 1489986723 ISBN-13(EAN): 9781489986726 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a practitioner`s guide to the extensive and comprehensive use of data, data analysis, explanatory and predictive models and methods, and management based on facts, in support of business decisions and actions. Includes real-world case studies.
Автор: Rahul Saxena; Anand Srinivasan Название: Business Analytics ISBN: 1461460794 ISBN-13(EAN): 9781461460794 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a practitioner`s guide to the extensive and comprehensive use of data, data analysis, explanatory and predictive models and methods, and management based on facts, in support of business decisions and actions. Includes real-world case studies.
Автор: Tavana Название: Recent Developments in Data Science and Business Analytics ISBN: 3319727443 ISBN-13(EAN): 9783319727448 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part I Marketing and Supply Chain Analytics: Chapter1: Research on Differential Pricing and Coordination Mechanism of Second-Class Supply Chain of New Products and Remanufactured Products.- Chapter2: A study on Cooperation Strategies of Dual Channel Supply Chain Based on Service Level.- Chapter3: The Quality Management of Food Supply Chain in Perspective of Food Safety.- Chapter4: Strategic Customer Behavior with Risk Preference for a Supply Chain Management Based on Double Channel.- Chapter5: Competition and Coordination in Single-supplier Multiple-retailer Supply Chain.- Chapter6: Research on the Construction of Enterprise Brand Competitiveness Evaluation System Based on the Integration of SWOT and AHP Model.- Chapter7: Reflections on the Training Mode of E-commerce Professionals with improved Practical Exercises and Innovative Ability.- Chapter8: Research on Evaluating Marketing Ability of Traditional Chinese Medicine Enterprises in Gansu Province.- Part II: Logistics and Operations Analytics: Chapter9: The Impact of the Relationship between Operational Cost and Oil Prices on Economic Assessment in Oil and Gas Industry.- Chapter10: The Construction of University Students' Entrepreneurship Competency Model in Application-Oriented Universities.- Chapter11: Improving Airport Security Screening System in Terms of Efficiency and Fairness Via Network Model.- Chapter12: Study on the Choice of Strategic Emerging Industries in Gansu Province Based on Multi-level Grey Model.- Chapter13: The Study of "Big Quality" Satisfaction Evaluation.- Chapter14: Research on Evaluation Index System of Enterprise Brand Competitiveness - Taking Liquor Industry as an Example.- Chapter15: Simulation of Stochastic Volatility Variance Swap.- Chapter16: Empirical Research of the Contribution Rate of University Science and Technology to the Regional Economic Development.- Chapter17: Research on Incentive Strategy of Logistics Outsourcing about Manufacturing Enterprises.- Chapter18: Research on External Quality Inspection Technology of Tropical Fruits Based on Computer Vision.- Chapter19: Wholesale Price Contract and Quantity Discount Contract under Competition with Various Games.- Chapter20: Evaluation of Science and Technology Service Industry in Shandong Province.- Part III: Financial Analytics: Chapter21: CEO's Background Characteristics, Financing Preference and Firm Performance-----Empirical Evidence from China's A-share Listed Companies.- Chapter22: Security Risk Management Approach for Improving Information Security Return of Investment.- Chapter23: Comparative Analysis on Investment and Financing Models of Urban Rail Transportation.- Chapter24: Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution.- Chapter25: Research on Liquidity Preferences of Mutual Fund.- Chapter26: Relationship of the Financial Agglomeration and Fiscal Expenditure Scale of Yangtze River Delta.- Chapter27: Applying Data Processing Method for Relationship Discovery in the Stock Market.- Chapter28: A Study on Assets Categorizations and Optimal Allocation via an Improved Algorithm.- Chapter29: Forecasting Stock Price Index Volatility with LSTM Deep Neural Network.- Chapter30: Improvement of Hedging Effect Based on the Average Hedging Ratio.- Chapter31: Finding the Lenders of Bad Credit Score Based on the Classification Method.- Part IV: Chapter32: Research Status and Prospect of Data Extraction and Cleaning Technology in Large Environment.- Chapter33: Research on Intelligent Sales Platform of Automobile Industry Based on Large Data Mining.- Chapter34: A Local Neighborhood Constraint Method for SIFT Features Matching.- Chapter35: A Wine Consumption Prediction Model Based on L-DAGLSSVM.- Chapter36: Fuzzy Control and Network System Design for Time Series Prediction Model.- Chapter37: Research on Data Storage Based on Cloud Platform.- Chapter38: An Automatic Multi-Objective Clustering based on Hierarchical Method
Автор: Cox Jr. Название: Causal Analytics for Applied Risk Analysis ISBN: 3319782401 ISBN-13(EAN): 9783319782409 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.
The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
Автор: Hammer Название: Management Approach for Resource-Productive Operations ISBN: 3658229381 ISBN-13(EAN): 9783658229382 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Markus Hammer investigates a time-based and analytics-supported operations management approach. He explores five perspectives: 1) the needs of industry, in particular manufacturing in process industries, 2) the impact of digitization, with focus on Big Data and analytics, 3) the management of operations through time-based performance metrics, 4) how operations improvement methods and advanced process control help achieve resource-productive operations and 5) learning from practice based on two empirical case studies. The author conceives, explains, and tests an implementation methodology. The final case study proves that the developed implementation methodology works in practice.
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.
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