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Operations Management and Data Analytics Modelling
Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0.It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma.Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problemsThis book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.
R 7,566.17
Operations Management and Data Analytics Modelling
Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0.It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma.Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problemsThis book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.
R 2,786.15
Business Analytics for Supply Chains and Operations
All businesses face continuous pressure to improve efficiency, reduce costs, and enhance profitability. By adopting an analytical approach, managers and business owners can identify opportunities and solutions that may not be immediately apparent. This book demonstrates how such an approach can be applied systematically to address complex operational challenges.Business Analytics for Supply Chains and Operations introduces a range of key topics that are grouped into three areas: modelling, optimisation, and probability. The optimisation component includes methods such as linear and integer programming and network flows, which are used to address logistics problems (e.g. transportation) in supply chains and production strategies in operations. The probabilistic component covers queueing systems and inventory models, providing tools to analyse uncertainty in operational settings.The book aims to enable readers to increase the efficiency and productivity of business operations. This requires analysts to observe and define challenges concisely, precisely, and logically. Familiarity with both classical and state-of-the-art operational research techniques and tools is essential for approaching such challenges effectively. These tools allow analysts to devise solutions, algorithms, and methods that provide a competitive advantage. Finally, results must be communicated clearly to support management decision-making. This book guides the reader through this process using numerous examples and well-worked solutions.The book is designed for postgraduate and advanced undergraduate students on business degrees, as well as for practising managers seeking analytical tools for decision-making. It emphasises hands-on learning with three main computational tools: Excel (the primary tool, introduced in depth), the MathProg modelling language for optimisation, and SimPy (with Python and a brief introduction to Simio) for simulation experiments. Online support materials include PowerPoint slides, a test bank, computer lab sheets with solutions, and links to video tutorials.
R 8,572.00
Operations Management Analytics
Operations Management Analytics, 4th Edition, provides a clear and accessible introduction to this important area of study. Taking an international approach, and written in a concise style, this revised new edition has been updated throughout to ensure that all key areas of operations in both the manufacturing and service industries are accounted for.New to this edition, the reader will find coverage of Industry 4.0, supply chain disruption, Internet of Things (IoT), 3D printing, Big Data Analytics, AI and digitalisation. Environmental and sustainability issues are emphasised, as are globalisation and automation processes. Aimed in particular at students seeking an introduction to the subject, Operations Management Analytics provides the reader with a comprehensive resource upon which to base their learning. A number of new case studies are featured – these are drawn from the service industry, manufacturing and the public sector – and come from a range of international contexts. Each chapter is complemented by a strategy link section that relates the chapter topic to operations strategy and an analytics section that provides quantitative content and exercises. End-of-chapter questions and exercises encourage the reader to reflect on what they have learnt.Operations Management Analytics, 4th Edition, is the ideal textbook for undergraduate students seeking to quickly get to grips with this fascinating and lively subject.
R 3,810.00
Applied Big Data Analytics in Operations Management
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.
R 6,209.00
Supply Chain and Operations Analytics
This book presents the concepts, strategies and decision-making processes of supply chain and operations management through simple to advanced analytics. It provides the tools necessary to comprehend supply chain and operations management, quantitatively and analytically, through exercises and examples.Using accessible quantitative models, the volume provides a unified framework for supply chain analytics for products – right from sourcing to manufacturing to delivery and remanufacturing, which closes the supply chain. The book synthesizes a collection of models in all areas of the supply chain – such as sourcing, inventory, production planning and control, forecasting of demand, transportation, network planning and design, data aggregation and mining, and the return of products – in the context of both the formulation and solution of the problems in each area using suitable software and Excel Solver for ease of understanding. The use of simulation and stochastic and system design models are added attractions of the book.This book will be useful to students, researchers and faculty working in the field of supply chain management, operations management and industrial engineering, both at graduate and research levels. It will also be an invaluable companion to consultants and practitioners, working with models and modelling systems, helping them to make better supply chain decisions.
R 9,381.69
Creating Values with Operations and Analytics
This book showcases how the latest and most advanced types of analytical modeling and empirical analysis can help to create value in the global supply chain. Focusing on practical relevance, it shares valuable management insights and addresses key issues in operations management (OM), demonstrating how past research has led to various practices and impacts, while also exploring the aspirations of the latest research. It presents current research on various topics such as global supply chain design, service supply chains, product design, responsible supply chains, performance and incentives in operations, data analytics in health services, new business models in the digital age, and new digital technology advances such as blockchain. In addition, it presents practical case studies on the aforementioned topics.Beyond the value of its contents, the book is intended as a tribute to Professor Morris Cohen, who has been a major contributor to advancing the research frontier in operations management and a driving force in shaping the field.Given its scope, the book will appeal to a wide readership, from researchers and PhD students to practitioners and consultants.
R 4,657.39
Supply Chain and Operations Analytics
This book presents the concepts, strategies and decision-making processes of supply chain and operations management through simple to advanced analytics. It provides the tools necessary to comprehend supply chain and operations management, quantitatively and analytically, through exercises and examples.Using accessible quantitative models, the volume provides a unified framework for supply chain analytics for products – right from sourcing to manufacturing to delivery and remanufacturing, which closes the supply chain. The book synthesizes a collection of models in all areas of the supply chain – such as sourcing, inventory, production planning and control, forecasting of demand, transportation, network planning and design, data aggregation and mining, and the return of products – in the context of both the formulation and solution of the problems in each area using suitable software and Excel Solver for ease of understanding. The use of simulation and stochastic and system design models are added attractions of the book.This book will be useful to students, researchers and faculty working in the field of supply chain management, operations management and industrial engineering, both at graduate and research levels. It will also be an invaluable companion to consultants and practitioners, working with models and modelling systems, helping them to make better supply chain decisions.
R 2,547.05
Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics
Businesses are collecting massive amounts of data every day as a way to better understand their processes, competition, and the markets they serve. This data can be used to increase organizational productivity and performance; however, is essential that organizations collecting large data sets have the tools available to them to fully understand the data they are collecting.Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics takes a critical look at methods for enhancing an organization’s operations and day-to-day activities through the effective use of data. Focusing on a variety of applications of predictive analytics within organizations of all types, this critical publication is an essential resource for business managers, data scientists, graduate-level students, and researchers.
R 7,965.93
Production and Operations Management
This proceedings volume convenes selected, peer-reviewed contributions presented at the POMS 2021 – International Conference on Production and Operations Management, which was virtually held in Lima, Peru, December 2-4, 2021. This book presents results in the field of Operations Management of key relevance to practitioners, instructors, and students. Topics focus on Operations Management, Logistics and Supply Chain Management, and Industrial and Production Engineering and Management, where mathematics and its applications play a role. In this work, readers will find a colorful collection of real-world case studies, accompanied by operations research-based managerial models. They touch on myriad topics, ranging from Artificial Intelligence and Data Analytics in Operations, Defense, Tourism, and other emerging issues in Operations Management to Healthcare Operations Management and Humanitarian Operations and Crisis Management.The POMS Lima 2021 International Conference has been organized by the Latin America & Caribbean Chapter of the Production and Operations Management Society, the most renowned professional and academic organization representing the interests of production and operations management professionals and academicians around the world. Since 2018, POMS International Conferences have been organized by POMS-LA, the first venue being in Rio de Janeiro, Brazil. Venue 2021 event was hosted by the Pontifical Catholic University of Peru and Pacific University, two Peruvian Latin-American leading academic institutions from Peru.
R 8,059.00
Creating Values with Operations and Analytics
This book showcases how the latest and most advanced types of analytical modeling and empirical analysis can help to create value in the global supply chain. Focusing on practical relevance, it shares valuable management insights and addresses key issues in operations management (OM), demonstrating how past research has led to various practices and impacts, while also exploring the aspirations of the latest research. It presents current research on various topics such as global supply chain design, service supply chains, product design, responsible supply chains, performance and incentives in operations, data analytics in health services, new business models in the digital age, and new digital technology advances such as blockchain. In addition, it presents practical case studies on the aforementioned topics.Beyond the value of its contents, the book is intended as a tribute to Professor Morris Cohen, who has been a major contributor to advancing the research frontier in operations management and a driving force in shaping the field.Given its scope, the book will appeal to a wide readership, from researchers and PhD students to practitioners and consultants.
R 6,594.00
Modeling for Sustainable Management in Agriculture, Food and the Environment
Recent developments in computer science, data mining and big data analytics have resulted in new operational frameworks in agriculture, food and the environment, which in fact, share a strong link between them. A key challenge for researchers is to extract new data patterns and utilize them in decision making. Managers, policy makers, and practitioners have to be aware of these methodologies in order to establish efficient and effective working groups for the tasks to be resolved. The book reviews the complexity of the interrelationship between agriculture, food production and processing, and environmental issues. It also highlights the prospects of modeling in various cases of problem solving in these sectors, and reviews the new and future challenges. Consumer awareness in food production and processing practices is continually increasing and the necessity for advanced behavioural tools follows the same trend. Furthermore, the value chain management challenge is becoming one of the most crucial tasks due to the increased importance of new parameters like the origin of products, its environmental footprint and the enhancement of local production, etc. The book addresses these topics in a holistic approach, merging modeling with advanced marketing practices in a coherent and innovative manner, being an effective tool in a continuously demanding world.
R 2,821.00
Industrial Engineering and Operations Management
This proceedings volume convenes peer-reviewed, selected papers presented at the XXVIII International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM) that was held in Mexico City, Mexico, July 17-20, 2022, with a special focus on applications of industrial engineering and operations management for research and practice. Fields covered include operations, manufacturing, industrial and production engineering and management, emphasizing optimization models and data science applications to real-world problems.In this book, the reader will find works on topics as optimization models; stochastic optimization; digital transformation in the supply chain; data science applications in operations management; Industry 4.0: manufacturing planning & control; blockchain; intelligent transportation systems; sustainable and reverse logistics; big data and demand planning; predictive and prescriptive analytics; last-mile delivery optimization; stochastic inventory models; new trends in information technology for operation management; stochastic optimization; optimization models for omnichannel; safety in operation management; and more. This volume includes relevant information for academics, since most of the chapters focus on real-world case studies and systematic reviews, but also for professionals in the industrial sector as it presents solutions to complex industrial challenges. Previous 2018, 2019, 2020, and 2021 IJCIEOM proceedings can also be found in Springer's catalog.
R 9,158.00
Big Data Management And Analytics
With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.
R 3,843.43
Business Analytics for Managers
The intensified used of data based on analytical models to control digitalized operational business processes in an intelligent way is a game changer that continuously disrupts more and more markets. This book exemplifies this development and shows the latest tools and advances in this field Business Analytics for Managers offers real-world guidance for organizations looking to leverage their data into a competitive advantage. This new second edition covers the advances that have revolutionized the field since the first edition's release; big data and real-time digitalized decision making have become major components of any analytics strategy, and new technologies are allowing businesses to gain even more insight from the ever-increasing influx of data. New terms, theories, and technologies are explained and discussed in terms of practical benefit, and the emphasis on forward thinking over historical data describes how analytics can drive better business planning. Coverage includes data warehousing, big data, social media, security, cloud technologies, and future trends, with expert insight on the practical aspects of the current state of the field. Analytics helps businesses move forward. Extensive use of statistical and quantitative analysis alongside explanatory and predictive modeling facilitates fact-based decision making, and evolving technologies continue to streamline every step of the process. This book provides an essential update, and describes how today's tools make business analytics more valuable than ever. Learn how Hadoop can upgrade your data processing and storageDiscover the many uses for social media data in analysis and communicationGet up to speed on the latest in cloud technologies, data security, and morePrepare for emerging technologies and the future of business analytics Most businesses are caught in a massive, non-stop stream of data. It can become one of your most valuable assets, or a never-ending flood of missed opportunity. Technology moves fast, and keeping up with the cutting edge is crucial for wringing even more value from your data—Business Analytics for Managers brings you up to date, and shows you what analytics can do for you now.
R 1,186.00
Data Analytics
Good data analytics is the basis for effective decisions. Whoever has the data, has the ability to extract information promptly and effectively to make pertinent decisions. The premise of this handbook is to empower users and tool developers with the appropriate collection of formulas and techniques for data analytics and to serve as a quick reference to keep pertinent formulas within fingertip reach of readers. This handbook includes formulas that will appeal to mathematically inclined readers. It discusses how to use data analytics to improve decision-making and is ideal for those new to using data analytics to show how to expand their usage horizon. It provides quantitative techniques for modeling pandemics, such as COVID-19. It also adds to the suite of mathematical tools for emerging technical areas. This handbook is a handy reference for researchers, practitioners, educators, and students in areas such as industrial engineering, production engineering, project management, civil engineering, mechanical engineering, technology management, and business management worldwide.
R 11,133.27
Analytics, Operations, and Strategic Decision Making in the Public Sector
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.
R 6,247.58
Analytics, Operations, and Strategic Decision Making in the Public Sector
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.
R 8,359.24
Segmentation, Revenue Management and Pricing Analytics
The practices of revenue management and pricing analytics have transformed the transportation and hospitality industries, and are increasingly important in industries as diverse as retail, telecommunications, banking, health care and manufacturing. Segmentation, Revenue Management and Pricing Analytics guides students and professionals on how to identify and exploit revenue management and pricing opportunities in different business contexts. Bodea and Ferguson introduce concepts and quantitative methods for improving profit through capacity allocation and pricing. Whereas most marketing textbooks cover more traditional, qualitative methods for determining customer segments and prices, this book uses historical sales data with mathematical optimization to make those decisions. With hands-on practice and a fundamental understanding of some of the most common analytical models, readers will be able to make smarter business decisions and higher profits.This book will be a useful and enlightening read for MBA students in pricing and revenue management, marketing, and service operations.
R 3,553.00
Operational Research in the Era of Digital Transformation and Business Analytics
This proceedings volume presents new methods and applications in Operational Research and Management Science with a special focus on Business Analytics. Featuring selected contributions from the XIV Balkan Conference on Operational Research held in Thessaloniki, Greece in 2020 (BALCOR 2020), it addresses applications and methodological tools or techniques in various areas of Operational Research, such as agent-based modelling, big data and business analytics, data envelopment analysis, data mining, decision support systems, fuzzy systems, game theory, heuristics, metaheuristics and nature inspired optimization algorithms, linear and nonlinear programming, machine learning, multiple criteria decision analysis, network design and optimization, queuing theory, simulation and statistics.
R 10,268.84
Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry
This book covers aspects of data science and predictive analytics used in oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital well, value chain integration, crude basket forecasting and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies.Features:Provides understanding of basics of IT technologies applied in Oil and Gas sectorIncludes deep comparison between different artificial intelligence techniquesAnalyses different simulators in Oil and Gas sector as well as discussion of AI applicationsFocuses on in-depth experimental and applied topicsDetails different case studies for upstream and downstreamThis book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics and digital transformation process in oil and gas.
R 6,654.18
Modeling for Sustainable Management in Agriculture, Food and the Environment
Recent developments in computer science, data mining and big data analytics have resulted in new operational frameworks in agriculture, food and the environment, which in fact, share a strong link between them. A key challenge for researchers is to extract new data patterns and utilize them in decision making. Managers, policy makers, and practitioners have to be aware of these methodologies in order to establish efficient and effective working groups for the tasks to be resolved. The book reviews the complexity of the interrelationship between agriculture, food production and processing, and environmental issues. It also highlights the prospects of modeling in various cases of problem solving in these sectors, and reviews the new and future challenges. Consumer awareness in food production and processing practices is continually increasing and the necessity for advanced behavioural tools follows the same trend. Furthermore, the value chain management challenge is becoming one of the most crucial tasks due to the increased importance of new parameters like the origin of products, its environmental footprint and the enhancement of local production, etc. The book addresses these topics in a holistic approach, merging modeling with advanced marketing practices in a coherent and innovative manner, being an effective tool in a continuously demanding world.
R 9,836.56
Operations Management
Operations Management: An Integrated Approach provides an account of the systems, processes, people and technology that determine an organisation's strategy and success. With contributions from leading experts internationally, the text takes a comprehensive, comparative, and best-practice approach and applies this specifically to the Asia-Pacific region. Rigorous in scholarship yet eminently accessible in style, Operations Management is replete with pedagogical features - figures and tables, discussion exercises, 'Learnings from the Internet', and a diversity of long and short case studies from around the world. Students are taken on a seamless journey from the fundamentals of operations management, through to the multiple approaches, the various innovations, challenges and risks, and ultimately to models of sustainability and evaluative tools and techniques. The text effectively prepares future managers across every sector of the economy to lead, organise, plan and control a set of resources, in pursuit of identified goals. The book will be supported by an extensive companion website featuring PowerPoint slides for each chapter, sample answers, teaching notes and figures/images for presentations.
R 5,414.00
Harness Oil and Gas Big Data with Analytics
Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages: Data management, including storing massive quantities of data in a manner conducive to analysis and effectively retrieving, backing up, and purging dataQuantification of uncertainty, including a look at the statistical and data analytics methods for making predictions and determining the certainty of those predictionsRisk assessment, including predictive analysis of the likelihood that known risks are realized and how to properly deal with unknown risks Covering the major issues facing the oil and gas industry in the exploration and production stages, Harness Big Data with Analytics reveals how to model big data to realize efficiencies and business benefits.
R 2,443.00
Innovative Technology at the Interface of Finance and Operations
This book examines the challenges and opportunities arising from an assortment of technologies as they relate to Operations Management and Finance. It contains primers on operations, finance, and their interface. Innovative technologies and new business models enabled by those technologies are changing the practice and the theory of Operations Management and Finance, as well as their interface. These technologies and business models include Big Data and Analytics, Artificial Intelligence, Machine Learning, Blockchain, IoT, 3D printing, sharing platforms, crowdfunding, and crowdsourcing.The book will be an attractive choice for PhD-level courses and for self-study.
R 5,861.00
Operations Management
Operations Management (OM) is a multi-faceted blend of myriad academic andpractical disciplines – from engineering and economics via mathematics and marketing, to systems and psychology. To capture the state of the art, the bookreviews contemporary and classic scholarship in one of the oldest business and management disciplines. To offer the reader a thought-provoking point of entry into the selected sources, the book curates its content as an imaginary exhibit, eachchapter a thematic OM ‘gallery’ (process; planning and control; people; strategy and measurement; technology) introduced by a description of some extraordinary artefacts, paintings, sculptures and architecture.The content has been curated around three principles intended to benefit the casual reader and both new and established OM scholars. First, it incorporates works that build on, or help to distinguish, fundamental tenets from more transitory fads. Second, the text makes significant efforts to try and balance the gravitational pull of the factory, (even though this may not offer an accurate representation of the majority of the field) and third, to try to keep managerial rather than technical/ analytical concerns to the fore.This concise book provides a useful overview of current and classic OM research. Written by a leading authority, it is intended to be a valuable and engaging resource for both students and scholars of business.
R 1,430.13
Data Modelling and Analytics for the Internet of Medical Things
The emergence of the Internet of Medical Things (IoMT) is transforming the management of diseases, improving diseases diagnosis and treatment methods, and reducing healthcare costs and errors. This book covers all the essential aspects of IoMT in one place, providing readers with a comprehensive grasp of IoMT and related technologies.Data Modelling and Analytics for the Internet of Medical Things integrates the architectural, conceptual, and technological aspects of IoMT, discussing in detail the IoMT, connected smart medical devices, and their applications to improve health outcomes. It explores various methodologies and solutions for medical data analytics in healthcare systems using machine learning and deep learning approaches, as well as exploring how technologies such as blockchain and cloud computing can further enhance data analytics in the e-health domain. Prevalent IoMT case studies and applications are also discussed.The book suits scientists, design engineers, system integrators, and researchers in the field of IoMT. It will also be of interest to postgraduate students in computer science focusing on healthcare applications and as supplementary reading for IoMT courses.
R 9,324.22
Fundamental Aspects of Operational Risk and Insurance Analytics
A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive frameworkGuidelines for how operational risk can be inserted into a firm’s strategic decisionsA model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.
R 6,023.00
Handbook of Operations Research and Management Science in Higher Education
This handbook covers various areas of Higher Education (HE) in which operations research/management science (OR/MS) techniques are used. Key examples include: international comparisons, university rankings, and rating academic efficiency with Data Envelopment Analysis (DEA); formulating academic strategy with balanced scorecard; budgeting and planning with linear and quadratic models; student forecasting; E-learning evaluation; faculty evaluation with questionnaires and multivariate statistics; marketing for HE; analytic and educational simulation; academic information systems; technology transfer with systems analysis; and examination timetabling. Overviews, case studies and findings on advanced OR/MS applications in various functional areas of HE are included.
R 6,594.00
Data Analytics and Machine Learning for Integrated Corridor Management
In an era defined by rapid urbanization and ever-increasing mobility demands, effective transportation management is paramount. This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.From the fundamental principles of traffic signal dynamics to the cutting-edge applications of machine learning, each chapter of this comprehensive guide unveils essential aspects of modern transportation management systems. Chapter by chapter, readers are immersed in the complexities of traffic signal coordination, corridor management, data-driven decision-making, and the integration of advanced technologies. Closing with chapters on modeling measures of effectiveness and computational signal timing optimization, the guide equips readers with the knowledge and tools needed to navigate the complexities of modern transportation management systems. With insights into traffic data visualization and operational performance measures, this book empowers traffic engineers and administrators to design 21st-century signal policies that optimize mobility, enhance safety, and shape the future of urban transportation.
R 6,662.54
Data Analytics and Machine Learning for Integrated Corridor Management
In an era defined by rapid urbanization and ever-increasing mobility demands, effective transportation management is paramount. This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.From the fundamental principles of traffic signal dynamics to the cutting-edge applications of machine learning, each chapter of this comprehensive guide unveils essential aspects of modern transportation management systems. Chapter by chapter, readers are immersed in the complexities of traffic signal coordination, corridor management, data-driven decision-making, and the integration of advanced technologies. Closing with chapters on modeling measures of effectiveness and computational signal timing optimization, the guide equips readers with the knowledge and tools needed to navigate the complexities of modern transportation management systems.With insights into traffic data visualization and operational performance measures, this book empowers traffic engineers and administrators to design 21st-century signal policies that optimize mobility, enhance safety, and shape the future of urban transportation.
R 2,674.00
Logistics, Supply Chain and Financial Predictive Analytics
This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves.The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.
R 6,015.28
Operations Management
Operations Management (OM) is a multi-faceted blend of myriad academic andpractical disciplines – from engineering and economics via mathematics and marketing, to systems and psychology. To capture the state of the art, the bookreviews contemporary and classic scholarship in one of the oldest business and management disciplines. To offer the reader a thought-provoking point of entry into the selected sources, the book curates its content as an imaginary exhibit, eachchapter a thematic OM ‘gallery’ (process; planning and control; people; strategy and measurement; technology) introduced by a description of some extraordinary artefacts, paintings, sculptures and architecture.The content has been curated around three principles intended to benefit the casual reader and both new and established OM scholars. First, it incorporates works that build on, or help to distinguish, fundamental tenets from more transitory fads. Second, the text makes significant efforts to try and balance the gravitational pull of the factory, (even though this may not offer an accurate representation of the majority of the field) and third, to try to keep managerial rather than technical/ analytical concerns to the fore.This concise book provides a useful overview of current and classic OM research. Written by a leading authority, it is intended to be a valuable and engaging resource for both students and scholars of business.
R 3,602.36
Big Data Applications in Industry 4.0
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making
R 2,745.33
In-Memory Data Management
In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes.
R 3,510.23
Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks
This thesis deals with two important and very timely aspects of the future power system operation - assessment of demand flexibility and advanced demand side management (DSM) facilitating flexible and secure operation of the power network. It provides a clear and comprehensive literature review in these two areas and states precisely the original contributions of the research.The book first demonstrates the benefits of data mining for a reliable assessment of demand flexibility and its composition even with very limited observability of the end-users. It then illustrates the importance of accurate load modelling for efficient application of DSM and considers different criteria in designing DSM programme to achieve several objectives of the network performance simultaneously. Finally, it demonstrates the importance of considering realistic assumptions when planning and estimating the success of DSM programs.The findings presented here have both scientific and practical significance; they gained her BSc and MSc degrees in electrical engineering from the University of Belgrade in 2011 and 2012 respectively. She graduated with her PhD from the University of Manchester. She has presented at several conferences, and has won runner-up prizes in poster presentation at three. She has authored or co-authored more than 40 journal, conference and technical papers.provide a basis for further research, and can be used to guide future applications in industry.
R 3,761.63
Total Quality Management and Operational Excellence
The notion of 'Quality' in business performance has exploded since the publication of the first edition of this classic text in 1989. Today there is a plethora of performance improvement frameworks including lean–Six Sigma and the latest version of ISO 9001, offering an often confusing variety of ways to achieve business excellence.Quality guru John Oakland’s famous TQM model, in many ways a precursor to these frameworks, has evolved to become the ultimate holistic overview of performance improvement strategy. Incorporating the frameworks that succeeded it, the revised model redefines Quality by:Accelerating changeReducing costProtecting reputationThe popular, practical, jargon-free writing style, along with ten supporting case studies, effortlessly ties the model to its real-life applications, making it easy to understand how to apply what you’ve learned to your practices and achieve sustainable competitive advantage.Guiding readers through the language of TQM and OpEx and all their recent developments, including data analytics, this book sets out a clear way to manage change. This exciting update of a classic is all the busy student or professional will need to begin understanding how to manage Quality and achieve Operational Excellence.
R 1,150.00
Pandemic Risk Management in Operations and Finance
COVID-19 has spread around the world, causing tremendous structural change, and severely affecting global supply chains and financial operations. As such there is a need for analytic tools help deal with the impact of the pandemic on the world’s economies; these tools are not panaceas and certainly won’t cure the problems faced, but they offer a means to aid governments, firms, and individuals in coping with specific problems. This book provides an overview of the COVID-19 pandemic and evaluates its effect on financial and supply chain operations. It then discusses epidemic modeling, presenting sources of quantitative and text data, and describing how models are used to illustrate the pandemic impact on supply chains, macroeconomic performance on financial operations. It highlights the specific experiences of the banking system, which offers predictions of the impact on the Swedish banking sector. Further, it examines models related to pandemic planning, such as evaluation of financial contagion, debt risk analysis, and health system efficiency performance, and addresses specific models of pandemic parameters. The book demonstrates various tools using available data on the ongoing COVID-19 pandemic. While it includes some citations, it focuses on describing the methods and explaining how they work, rather than on theory. The data sets and software presented were all selected on the basis of their widespread availability to any reader with computer links.
R 3,074.94
Modelling, Computation and Optimization in Information Systems and Management Sciences
This proceedings set contains 85 selected full papers presentedat the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015, held on May 11–13, 2015 at Lorraine University, France. The present part II of the 2 volume set includes articles devoted to Data analysis and Data mining, Heuristic / Meta heuristic methods for operational research applications, Optimization applied to surveillance and threat detection, Maintenance and Scheduling, Post Crises banking and eco-finance modelling, Transportation, as well as Technologies and methods for multi-stakeholder decision analysis in public settings.
R 6,598.25
Data Analytics-Based Demand Profiling and Advanced Demand Side Management for Flexible Operation of Sustainable Power Networks
This thesis deals with two important and very timely aspects of the future power system operation - assessment of demand flexibility and advanced demand side management (DSM) facilitating flexible and secure operation of the power network. It provides a clear and comprehensive literature review in these two areas and states precisely the original contributions of the research.The book first demonstrates the benefits of data mining for a reliable assessment of demand flexibility and its composition even with very limited observability of the end-users. It then illustrates the importance of accurate load modelling for efficient application of DSM and considers different criteria in designing DSM programme to achieve several objectives of the network performance simultaneously. Finally, it demonstrates the importance of considering realistic assumptions when planning and estimating the success of DSM programs.The findings presented here have both scientific and practical significance; they gained her BSc and MSc degrees in electrical engineering from the University of Belgrade in 2011 and 2012 respectively. She graduated with her PhD from the University of Manchester. She has presented at several conferences, and has won runner-up prizes in poster presentation at three. She has authored or co-authored more than 40 journal, conference and technical papers.provide a basis for further research, and can be used to guide future applications in industry.
R 3,504.01
Big Data Analytics in the Insurance Market
Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. This book will be a 'must' for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance.The insurance industry is largely dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential. Yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy.This book an invaluable resource for any insurance professional from practitioners and policymakers working at insurance companies, to undergraduate and graduate students of economics management, and finance.Providing high quality academic research, ESFIRM provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale.
R 4,564.84
Total Quality Management and Operational Excellence
The notion of 'Quality' in business performance has exploded since the publication of the first edition of this classic text in 1989. Today there is a plethora of performance improvement frameworks including lean–Six Sigma and the latest version of ISO 9001, offering an often confusing variety of ways to achieve business excellence.Quality guru John Oakland’s famous TQM model, in many ways a precursor to these frameworks, has evolved to become the ultimate holistic overview of performance improvement strategy. Incorporating the frameworks that succeeded it, the revised model redefines Quality by:Accelerating changeReducing costProtecting reputationThe popular, practical, jargon-free writing style, along with ten supporting case studies, effortlessly ties the model to its real-life applications, making it easy to understand how to apply what you’ve learned to your practices and achieve sustainable competitive advantage.Guiding readers through the language of TQM and OpEx and all their recent developments, including data analytics, this book sets out a clear way to manage change. This exciting update of a classic is all the busy student or professional will need to begin understanding how to manage Quality and achieve Operational Excellence.
R 7,327.00
Logistics, Supply Chain and Financial Predictive Analytics
This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves.The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.
R 6,316.06
R 10,257.00
Model Management and Analytics for Large Scale Systems
Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.
R 4,414.00
R 2,136.00
