Search results for "Operations Management and Data Analytics Modelling"
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Predictive Analytics in Human Resource Management
This volume is a step-by-step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organisational impact, to aid in strategising and better decision-making.The book:Presents key concepts and expands on the need and role of HR analytics in business management.Utilises popular analytical tools like artificial neural networks (ANNs) and K-nearest neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening.Discusses real-world corporate examples and employee data collected first-hand by the authors.Includes individual chapter exercises and case studies for students and teachers.Comprehensive and accessible, this guide will be useful for students, teachers, and researchers of data analytics, Big Data, human resource management, statistics, and economics. It will also be of interest to readers interested in learning more about statistics or programming.
R 2,949.06
Data Analytics Initiatives
The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex?Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure.In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.
R 2,454.00
Big Data and Blockchain for Service Operations Management
This book aims to provide the necessary background to work with big data blockchain by introducing some novel applications in service operations for both academics and interested practitioners, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book intends to cover theory, research, development, and applications of big data and blockchain, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management, and life sciences, to help service operations management.
R 6,594.00
Big Data Management and Analytics
As more companies go digital and conduct their business online, this book provides practical examples of how they can better manage their data and use it to generate maximum value. It offers an integrated approach by treating data as an asset and discusses how to preserve and protect it just like any other corporate asset.Big Data Management and Analytics: Concepts, Tools, and Applications illustrates effective strategies for managing, governing, and analyzing big data to gain a competitive edge for companies utilizing big data and analytics. It offers a comprehensive guide on methods, tools, and concepts to efficiently manage and analyze big data in order to make informed decisions. Additionally, this book explores the significance of artificial intelligence and machine learning in leveraging big data and how they can be optimized in a well-structured environment. This book also emphasizes treating big data as a valuable asset and outlines strategies for preserving and safeguarding it like any other corporate asset. The inclusion of case studies ensures that the methodologies and concepts presented can be easily implemented in day-to-day operations.Given the current significance of big data in the business world, this book equips readers with the necessary skills to effectively manage this valuable asset. It is tailored for practitioners, students, and professionals working in data mining, big data, and machine learning across various industries, including manufacturing.
R 6,654.18
Aligning Business Strategies and Analytics
This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap.Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry.
R 4,320.93
Operations Research in Space and Air
Operations Research in Space and Air is a selection of papers reflecting the experience and expertise of international OR consulting companies and academic groups. The global market and competition play a crucial part in the decision making processes within the Space and Air industries and this book gives practical examples of how advanced applications can be used by Space and Air industry management. The material within the book provides both the basic background for the novice modeler and a useful reference for experienced modelers. Students, researchers and OR practitioners will appreciate the details of the modeling techniques, the processes that have been implemented and the computational results that demonstrate the benefits in applying OR in the Space and Airline industries. Advances in PC and Workstations technology, in optimiza tion engines and in modeling techniques now enable solving problems, never before attained by Operations Research. In recent years the Ital ian OR Society (AfRO, www. airo. org) has organized annual forums for researchers and practitioners to meet together to present and dis cuss the various scientific and technical OR achievements. The OR in Space 8 Air session of AfR02001 and AfR02002 Conferences, together with optimization tools' applications, presented recent results achieved by Alenia Spazio S. p. A. (Turin), Alitalia, Milan Polytechnic and Turin Polytechinc. With additional contributions from academia and indus try they have enabled us to capture, in print, today's 'state-of-the-art' optimization and data mining solutions.
R 8,183.20
Sport Facility Operations Management
Now in a fully revised and updated fourth edition, Sport Facility Operations Management goes beyond the basic theories of sport facility management to examine the practical realities connecting facilities, people, and technology.An essential textbook for any sport facilities course, it introduces the fundamentals of facility management and presents cutting-edge, evidence-based perspectives that show the reader how to become a more effective practitioner and deliver better results for their organization. Every chapter includes in-depth case studies to illustrate best practice, as well as ‘Technology Now,’ ‘Facility Focus,’ and ‘In the Field’ features to highlight key points. This new edition includes expanded coverage of important themes in contemporary sport facilities operations management, including cybersecurity, the use of AI, data analytics, sustainability, and the politics of event bidding and facility financing, as well as a brand-new chapter on how to build and develop a career in sport facilities management.This book is an invaluable course text for sport management educators and students, especially those studying facility management. It is also useful reading for industry professionals working in sport facility management, from grassroots and community complexes to global mega stadiums and arenas.Ancillary materials accompanying this book include PowerPoint presentations for each chapter; multiple-choice and essay questions; online appendices with diagrams, schematics, manuals, and forms; a glossary; and a sample master syllabus.
R 7,042.97
Pharmaceutical Operations Management
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.This book brings together a winning team of international operations experts to set the framework for building a world-class manufacturing organization. Pharmaceutical Operations Management focuses on key concepts such as: Policy Execution, Risk Management, Supply chain modeling, Advance process control and Six Sigma for the pharmaceutical industry: critical techniques which will offset cost, increase efficiency and turn any manufacture into financial winner.
R 5,282.79
Production and Operations Management Systems
Since the beginning of mankind on Earth, if the "busyness" process was successful, then some form of benefit sustained it. The fundamentals are obvious: get the right inputs (materials, labor, money, and ideas); transform them into highly demanded, quality outputs; and make it available in time to the end consumer. Illustrating how operations relate to the rest of the organization, Production and Operations Management Systems provides an understanding of the production and operations management (P/OM) functions as well as the processes of goods and service producers. The modular character of the text permits many different journeys through the materials. If you like to start with supply chain management (Chapter 9) and then move on to inventory management (Chapter 5) and then quality management (Chapter 8), you can do so in that order. However, if your focus is product line stability and quick response time to competition, you may prefer to begin with project management (Chapter 7) to reflect the continuous project mode required for fast redesign rapid response. Slides, lectures, Excel worksheets, and solutions to short and extended problem sets are available on the Downloads / Updates tabs.The project management component of P/OM is no longer an auxiliary aspect of the field. The entire system has to be viewed and understood. The book helps students develop a sense of managerial competence in making decisions in the design, planning, operation, and control of manufacturing, production, and operations systems through examples and case studies. The text uses analytical techniques when necessary to develop critical thinking and to sharpen decision-making skills. It makes production and operations management (P/OM) interesting, even exciting, to those who are embarking on a career that involves business of any kind.
R 11,172.92
Financial Data Analytics
This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization.This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach. Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.
R 5,804.91
Absolute Essentials of Operations Management
This short textbook consolidates all the key aspects of operations management into a concise and easily accessible reference tool.Comprising the management of creating goods and delivering services to customers, operations management plays an essential role in the success of any organization. This book discusses the main areas of operations management, such as the design of the operations system, including product, process and job design. It also covers the management of operations, including lean operations and supply chain management.Breaking the subject down into its key components, this book provides a core introduction for undergraduate students studying operations management as part of business and management degrees.
R 3,601.46
Basics of Operations Management
Through a collection of curated readings, Basics of Operations Management introduces students to fundamental concepts within the discipline. The text is intended to be used in conjunction with active learning activities and practical mathematical appli¬cations in the live or virtual classroom to enhance learning and comprehension.The book is organized into eight learning modules that build upon each other to provide students with a foundational understanding of operations management. Each module begins with an introduction and learning objectives, ends with discussion or practice questions and, if applicable, links to sample classroom activities that have proven effective in helping students understand and apply the operational concepts. Opening modules introduce students to operations management and the supply chain, address capacity and demand management, and discuss facility location and layout. Additional modules cover quality management, statistical process control, lean six-sigma, inventory management, and resource management. Designed to help students better understand how manufacturing and service operations function, Basics of Operations Management is ideal for courses in operations management and supply chain management.
R 3,114.65
Operations Management in the Era of Fast Fashion
This book reports the latest business practices, operations models, technologies and circular supply chain structure of the fast fashion companies and provides many important managerial insights on the sustainable operations management in the fast fashion era. Sustainability is a timely topic in both the academia and the business world. In the fast fashion era, there are considerable criticisms about its environmental pollution generated in the manufacturing and post-consumption processes. Over the past decades, many fast fashion companies, such as H&M, Zara, and Uniqlo, have implemented different sustainable programs to mitigate the negative impacts to the environment. Nowadays, the industry is moving one step further by addressing zero landfill through 3Rs principle (i.e., reducing, reusing and recycling), and pursuit of the circular supply chains. This book aims to reveal the exploratory, qualitative empirical and quantitative analytical studies on how to achieve the goal of being environmentally sustainable in the fast fashion era.
R 6,155.90
Essential Guide to Operations Management
The revised and updated second edition of the popular and practical guide to contemporary operations management – now featuring a new chapter on managing sustainable supply networks.The Essential Guide to Operations Management explores fundamental operations management principles and shows how they are applied in real-life situations in both the services and manufacturing sectors. It adapts a strategic stance by providing a framework for effective decision-making: determining operations strategies; designing processes, products and work organisations; managing change through effective project management and technology transfer; exploring contemporary approaches to operations planning and control; and then managing quality and improvement strategies. As such, it addresses the needs of practising managers, postgraduate MBA and MSc students and final-year undergraduates in advanced operations management elective courses.The Essential Guide to Operations Management: Concepts and Case Notes, Second Edition, is supported by updated case studies throughout and online support materials for lecturers.
R 2,125.00
Mathematical Modeling for Big Data Analytics
Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques.This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.
R 5,297.00
Data Analytics and Business Intelligence
Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making.BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others.BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.
R 3,152.47
R 245.00
Advancing Big Data Analytics for Healthcare Service Delivery
In recent years, there has been steady increase in the interest shown in both big data analytics and the use of information technology (IT) solutions to improve healthcare services. Despite the growing interest, there are limited materials, to addressing the needs and challenges posed by the activities and processes including the use of big data. From IT solutions’ perspectives, this book aims to advance the deployment and use of big data analytics to increase patients’ big data usefulness and improve healthcare service delivery.The book provides significant insights and useful guide on how to access and manage big data, in improving healthcare service delivery. The book contributes a fresh perspective, which primarily comes from the complementary use of analytics approach with actor-network theory (ANT), and other techniques, in advancing healthcare service delivery. Accessing and managing healthcare big data have always been a challenging exercise. Due to the sensitivity of the health sector, the focus on patients’ big data is from either technical or social perspective. Thus, the book employs sociotechnical theories, ANT and structuration theory (ST) as lenses to examine and explain the factors that enable and constrain the use of patients’ big data for health services. By doing so, the book brings a different dimension and advance health service delivery.Providing a timely and important contribution to this critical area, this book is a valuable, international resource for academics, postgraduate students and researchers in the areas of IT, big data analytics, data management and health informatics.
R 7,567.05
Data Analytics for Smart Infrastructure
This book presents, for the first time, data analytics for smart infrastructures. The authors draw on over a decade’s experience working with industry and demonstrating the capabilities of data analytics for infrastructure and asset management. The volume gives data-driven solutions to cover critical capabilities for infrastructure and asset management across three domains: 1) situation awareness 2) predictive analytics and 3) decision support. The reader will gain from various data analytic techniques including anomaly detection, performance evaluation, failure prediction, trend analysis, asset prioritization, smart sensing and real-time/online systems. These data analytic techniques are vital to solving problems in infrastructure and asset management. The reader will benefit from case studies drawn from critical infrastructures such as water management, structural health monitoring and rail networks. This groundbreaking work will be essential reading for those studying and practicing analytics in the context of smart infrastructure.
R 2,943.45
Big Data Analytics
Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including:Big data analytics and algorithmMarket basket analysisAnticipating consumer purchase behaviorVariation in shopping patternsBig data analytics for market intelligenceThe third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.
R 2,046.14
Strategic Operations Management
Strategic Operations Management, 4th Edition, shows how vital it is to have world-class operations management in any organisation. In the past, where organisations tended to be more hierarchical than today, the words, "strategy" and "operations" were almost mutually exclusive. In today's highly competitive environment, though, strategic operations capabilities must be in place for organisations to provide goods and services that meet and exceed customer requirements. Key issues such as cost, speed, quality, flexibility and constant innovation are all part of strategic operations. However, achieving such capabilities does not come by chance - instead a range of factors need to be put in place. This new edition pays equal attention to manufacturing and service sectors. It includes numerous references to, and discusses, major changes taking place in the business world, including 3-D printing; virtual organisations; Cloud – Big Data and the Internet of Things; Servitization, global markets, ongoing innovation and managing within complex supply networks. Cases are included from a range of settings across the globe.Students taking MBA, MSc and MBM classes on operations management, advanced operations management, and strategic operations management will find this textbook fulfills all their requirements whilst advanced undergraduate classes in these areas will also find the book an essential read.
R 3,297.00
Essential Guide to Operations Management
The revised and updated second edition of the popular and practical guide to contemporary operations management – now featuring a new chapter on managing sustainable supply networks.The Essential Guide to Operations Management explores fundamental operations management principles and shows how they are applied in real-life situations in both the services and manufacturing sectors. It adapts a strategic stance by providing a framework for effective decision-making: determining operations strategies; designing processes, products and work organisations; managing change through effective project management and technology transfer; exploring contemporary approaches to operations planning and control; and then managing quality and improvement strategies. As such, it addresses the needs of practising managers, postgraduate MBA and MSc students and final-year undergraduates in advanced operations management elective courses.The Essential Guide to Operations Management: Concepts and Case Notes, Second Edition, is supported by updated case studies throughout and online support materials for lecturers.
R 8,107.20
Art of Data Science
Although change is constant in business and analytics, some fundamental principles and lessons learned are truly timeless, extending and surviving beyond the rapid ongoing evolution of tools, techniques, and technologies. Through a series of articles published over the course of his 30+ year career in analytics and technology, Doug Gray shares the most important lessons he has learned – with colleagues and students as well – that have helped to ensure success on his journey as a practitioner, leader, and educator.The reader witnesses the Analytical Sciences profession through the mind’s eye of a practitioner who has operated at the forefront of analytically inclined organizations, such as American Airlines and Walmart, delivering solutions that generate hundreds of millions of dollars annually in business value, and an educator teaching students and conducting research at a leading university. Through real‑world project case studies, first‑hand stories, and practical examples, we learn the foundational truth underlying successful analytics applications. From bridging theory and practice, to playing a role as a consultant in digital transformation, to understanding how analytics can be economically transformational, identifying required soft skills like leadership skills, and understanding the reasons why data science projects often fail, the reader can better visualize and understand the nuanced, multidimensional nature of Analytical Sciences best practices, projects, and initiatives.The readers will gain a broad perspective on where and how to find success with Analytical Sciences, including the ability to ensure that we apply the right tool, at the right time and right place, and sometimes in different industries.Finally, through the author’s own career synopsis on becoming a practitioner and leader, and his distilled insights, the reader is offered a view into the future that analytics holds, along with some invaluable career advice regarding where to focus, how to make good choices, and how to measure success individually and organizationally.
R 2,945.95
Manage Your Own Learning Analytics
This book sheds light on the practice of learning analytics, illuminating how others approach their data analysis. At the beginning of the book, a ‘prescriptive learning analytics planning model’ gives straightforward instructions for people to follow. This book is organized into ten chapters, falling into four topical sections: Managing Learning Analytics (overview, instructional systems design (ISD), instructional design, and planning data analysis); Cognitive Performance Measurement Practices (classical test theory (CTT), Rasch measurement theory (RMT), Item response theory(IRT), Rasch Modeling Tools (research design, setting methodology); and Case Studies (corporate training settings, healthcare industry, and educational courseware design). This book is an important reference for: educational research community and instructional systems designers; corporate training developers; postgraduate course developers; and doctoral students.
R 5,425.86
Predictive Analytics for the Modern Enterprise
The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics in the cloud. Author Nooruddin Abbas Ali, principal solutions architect at MongoDB, brings you up to speed through industry use cases and end-to-end hands-on examples. This book helps business technology leaders: Implement and operationalize predictive analytics in your organization Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow
R 1,505.00
AI-Centric Modeling and Analytics
This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, ML-aided models, IoT-driven applications, and cybersecurity techniques in the era of the Industrial Revolution 4.0.AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. The book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with discussing AI-centric robotics process automation systems that are useful in many government and private industries.This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students across various fields.
R 9,967.58
Management and Visualisation
As organisations of all sizes become increasingly digitalised, a core management challenge remains unresolved. The ability to successfully and sustainably connect the stated vision of an organisation with its strategic plans and, in turn, with the reported reality of day-to-day operations, is largely an elusive ambition, despite the many stated advantages provided by contemporary technologies. In this book, the case is made for visual management as a method of communications, planning, learning and reporting that connects the organisation in a single, meaningful and seamless way. Throughout this book, visual management is theorised around the position that all forms of management documentation are an artefact of human construction and of the organisation itself that reflect learned patterns of activity. The book places visual management as a more intuitive and seamless method of coordinating, learning and communicating across an organisation than more traditional formats of presenting management documents. Consciously assembling the artefacts of an organisation in order to manage it introduces a layer of criticality that encourages reflection and consistency that is often absent from current management practice. The benefits that a visual approach brings to organisational management are an increasing necessity, as machine learning, robotics and process automation remove traditional roles from organisations and necessitate new views on how individuals now fit into a data-informed business. The book contributes to the academic debate regarding resource-based and knowledge-based views of the organisation by advocating a different, more holistic viewpoint and will thus appeal to academics and researchers in this area. It would also benefit students across business disciplines, whilst the practical models and tools offered will benefit directors and managers looking to implement their own visual organisational language.
R 3,297.00
Process Modeling and Management for Healthcare
From the Foreword:"[This book] provides a comprehensive overview of the fundamental concepts in healthcare process management as well as some advanced topics in the cutting-edge research of the closely related areas. This book is ideal for graduate students and practitioners who want to build the foundations and develop novel contributions in healthcare process modeling and management."--Christopher Yang, Drexel UniversityProcess modeling and process management are traversal disciplines which have earned more and more relevance over the last two decades. Several research areas are involved within these disciplines, including database systems, database management, information systems, ERP, operations research, formal languages, and logic. Process Modeling and Management for Healthcare provides the reader with an in-depth analysis of what process modeling and process management techniques can do in healthcare, the major challenges faced, and those challenges remaining to be faced. The book features contributions from leading authors in the field.The book is structured into two parts. Part one covers fundamentals and basic concepts in healthcare. It explores the architecture of a process management environment, the flexibility of a process model, and the compliance of a process model. It also features a real application domain of patients suffering from age-related macular degeneration.Part two of the book includes advanced topics from the leading frontiers of scientific research on process management and healthcare. This section of the book covers software metrics to measure features of the process model as a software artifact. It includes process analysis to discover the formal properties of the process model prior to deploying it in real application domains. Abnormal situations and exceptions, as well as temporal clinical guidelines, are also presented in depth Pro.
R 2,725.19
R 19,396.05
New Trends and Applications in Internet of Things (IoT) and Big Data Analytics
This book focuses on the use of The Internet of Things (IoT) and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. IoT and big data emerged from the early 2000s data boom, driven forward by many of the early internet and technology companies. The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. There are a variety of IoT-based applications being used in different sectors and have succeeded in providing huge benefits to the users. The generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends to adopt the data analytics to strengthen solutions. The success of IoT depends upon the influential association of big data analytics. New technologies like search engines, mobile devices, and industrial machines provided as much data as companies could handle—and the scale continues to grow. In a study conducted by IDC, the market intelligence firm estimated that the global production of data would grow 10x between 2015 and 2020. So, the proposed book covers up all the aspects in the field discuss above.
R 8,643.04
AI-Based Data Analytics
This book covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviourAI-Based Data Analytics: Applications for Business Management has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.
R 2,711.00
Foundations of Predictive Analytics
Drawing on the authors’ two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish–Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as well as popular nonlinear modeling approaches, including additive models, trees, support vector machine, fuzzy systems, clustering, naïve Bayes, and neural nets. The authors go on to cover methodologies used in time series and forecasting, such as ARIMA, GARCH, and survival analysis. They also present a range of optimization techniques and explore several special topics, such as Dempster–Shafer theory.An in-depth collection of the most important fundamental material on predictive analytics, this self-contained book provides the necessary information for understanding various techniques for exploratory data analysis and modeling. It explains the algorithmic details behind each technique (including underlying assumptions and mathematical formulations) and shows how to prepare and encode data, select variables, use model goodness measures, normalize odds, and perform reject inference.Web ResourceThe book’s website at www.DataMinerXL.com offers the DataMinerXL software for building predictive models. The site also includes more examples and information on modeling.
R 3,716.06
Data Analytics and Management in Data Intensive Domains
This book constitutes the refereed proceedings of the 20th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2018, held in Moscow, Russia, in October 2018.The 9 revised full papers presented together with three invited papers were carefully reviewed and selected from 54 submissions. The papers are organized in the following topical sections: FAIR data infrastructures, interoperability and reuse; knowledge representation; data models; data analysis in astronomy; text search and processing; distributed computing; information extraction from text.
R 1,545.07
Big Data Analytics in Supply Chain Management
In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations.From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.
R 2,825.95
R 1,629.00
Operations Management and Systems Engineering
This book comprises select proceedings of the International Conference on Production and Industrial Engineering (CPIE) 2018. The book focuses on the latest developments in the domain of operations management and systems engineering, and presents analytical models, case studies, and simulation approaches relevant to a wide variety of systems engineering problems. Topics such as decision sciences, human factors and ergonomics, transport and supply chain management, manufacturing design, operations research, waste management, modeling and simulation, reliability and maintenance, and sustainability in operations and manufacturing are discussed in this book. The contents of this book will be useful to academics, researchers and practitioners working in the field of systems engineering and operations management.
R 6,841.19
R 19,459.89
Operations Management
`This reader is an outstanding piece of work. It captures the essence of operations management by providing an interesting and sometimes provoking set of readings. It also provides an excellent review of the topic. Its approach to operations management is both topical and comprehensive. The editors have done an outstanding job of including many of the significant recent developments in the area, particularly in the technology and operations strategy areas′ - Nigel Slack, Professor of Operations Strategy, Warwick UniversityHow have consumer demands, environmental and ethical concerns, the advancement of technology and the globalization of business changed and redefined operations management? This Reader explains new and emerging areas and re-evaluates some important mainstream issues. Leading specialists contribute their experiences and thoughts on four key areas. They are: - Strategy - makes the case for regarding operations as a strategic asset in their own right - Methodology - examines the myriad of approaches taken towards process improvement- Technology - asks why problems associated with the implementation of technology continue to dog organisations - Human Issues - repositions human input to the top of the operational agenda
R 3,737.00
Contemporary Leadership in Sport Organizations
Contemporary Leadership in Sport Organizations, Third Edition, equips sport management students and practitioners with the leadership skills needed to succeed in today's complex, fast-changing sport industry.This third edition integrates contemporary leadership theory with the realities shaping modern sport organizations. Across all sections of the text, updated research and new sport industry examples--including name, image, and likeness (NIL) changes; the transfer portal; enterprise risk analysis; decision science; data analytics; and artificial intelligence--demonstrate how leaders must operate in data-rich, highly dynamic environments.Updates in the third edition include the following: Key Takeaways at the end of each chapter provide actionable insights that can be applied in real-world situations.Questions for Discussion promote engagement and assess understanding of key chapter concepts.The full-color design enhances photos and illustrations, improving clarity and visual appeal.Interactive branching scenarios in the web resource guide students through choices to identify optimal solutions to various situations.At its core, the text positions leadership as a distinct discipline rather than simply a subset of sport management. As such, it serves as an applied, next-step leadership resource for programs seeking stronger alignment with real-world complexity, strategic decision making, and contemporary sport issues--shifting the focus from leadership development to leadership in action.To reinforce this applied approach, the online web resource included with the text contains case studies, interactive scenarios, and leadership style self-assessments to emphasize critical thinking, practical application, and decision making across youth, collegiate, professional, and global sport settings.In addition, traditional leadership models are expanded and updated to reflect today's demands, with enhanced coverage of adaptive, agile, distributed, and emotionally intelligent leadership. This evolution is further supported by increased attention to organizational culture, ethics, diversity, and international perspectives, ensuring a comprehensive and forward-looking view of leadership in sport.Today's sport organization leaders are expected not only to deliver results but also to build trust, strengthen organizational culture, and demonstrate authenticity and accountability to stakeholders. Contemporary Leadership in Sport Organizations prepares future leaders to meet this challenge.Note: A URL to access the online materials is included in this print book.
R 4,054.00
Optimizing Decision-Making in Engineering
This comprehensive book explores the evolving landscape of decision-making processes for engineering and IT professionals in increasingly heterogeneous technological environments. It addresses critical gaps in current educational materials by examining how technological advancements, situational awareness challenges, human-machine intelligence integration, and virtual uncertainties impact modern decision-making frameworks. The book provides a complete journey map of decision-making that connects theoretical foundations with practical applications, offering readers a structured approach to navigate complex adaptive systems in our data-driven society.Optimizing Decision-Making in Engineering: A Journey Mapping Perspective includes an in-depth exploration of cognitive and emotional engagements in decision-making, an analysis of how advanced design functionalities influence cognitive biases and heuristics, and an examination of decision-making under virtual conditions where physical touch is absent. It presents analytical tools such as decision trees, Bayesian networks, and multi-criteria decision-making models (AHP, TOPSIS), while incorporating emerging technologies like artificial intelligence, virtual/augmented reality, IoT, and big data analytics. Real-world scenarios, use cases, and strategic frameworks like the Cynefin framework and Roger’s model provide a practical context for theoretical concepts.Designed for technology professionals, including CTOs, IT project managers, systems architects, UX directors, and engineering team leads, this resource equips product managers, business analysts, solution architects, and digital transformation consultants with enhanced decision-making capabilities for complex environments. This comprehensive guide delivers particular value for specialized roles such as AI ethics officers, human factors engineers, and digital experience strategists, providing frameworks applicable across autonomous systems, healthcare technology, immersive experiences, retail analytics, and advanced manufacturing operations.
R 5,165.00
R 2,139.63
Data Analytics for Engineering and Construction Project Risk Management
This book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes.The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts’ judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory.The book is organized in three parts and fourteen chapters. In Part I the authors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution.
R 3,264.91
Applied Data Analysis for Urban Planning and Management
This book showcases the different ways in which contemporary forms of data analysis are being used in urban planning and management. It highlights the emerging possibilities that city-regional governance, technology and data have for better planning and urban management - and discusses how you can apply them to your research.Including perspectives from across the globe, it’s packed with examples of good practice and helps to demystify the process of using big and open data.Learn about different kinds of emergent data sources and how they are processed, visualised and presented.Understand how spatial analysis and GIS are used in city planning.See examples of how contemporary data analytics methods are being applied in a variety of contexts, such as ‘smart’ city management and megacities.Aimed at upper undergraduate and postgraduate students studying spatial analysis and planning, this timely text is the perfect companion to enable you to apply data analytics approaches in your research.
R 4,678.12
Managing Operations
Looking at the operations of an organization, this book examines the different types of organization in both the public and private sectors. It then considers the internal relationships between operations, marketing, personnel and other functions within organizations. The specific aspects of operations are covered in detail: Work practices. Planning. Resourcing. Legislation. Customer relations.
R 1,207.00
Big Data Analytics
Successfully navigating the data-driven economy presupposes a certain understanding of the technologies and methods to gain insights from Big Data. This book aims to help data science practitioners to successfully manage the transition to Big Data. Building on familiar content from applied econometrics and business analytics, this book introduces the reader to the basic concepts of Big Data Analytics. The focus of the book is on how to productively apply econometric and machine learning techniques with large, complex data sets, as well as on all the steps involved before analysing the data (data storage, data import, data preparation). The book combines conceptual and theoretical material with the practical application of the concepts using R and SQL. The reader will thus acquire the skills to analyse large data sets, both locally and in the cloud. Various code examples and tutorials, focused on empirical economic and business research, illustrate practical techniques to handle and analyse Big Data. Key Features: - Includes many code examples in R and SQL, with R/SQL scripts freely provided online. - Extensive use of real datasets from empirical economic research and business analytics, with data files freely provided online. - Leads students and practitioners to think critically about where the bottlenecks are in practical data analysis tasks with large data sets, and how to address them. The book is a valuable resource for data science practitioners, graduate students and researchers who aim to gain insights from big data in the context of research questions in business, economics, and the social sciences.
R 8,572.00
R 669.39
