Search results for "Operations Management and Data Analytics Modelling"
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Chemotherapy Appointment Scheduling
This book discusses how analytics can handle uncertainty and fairness issues in scheduling chemotherapy treatments. Specifically, the authors explore the complexities of chemotherapy scheduling, showing how analytics can be used to create fairer and more efficient chemotherapy schedules. By addressing uncertainty in infusion times and balancing the needs of both patient and staff, the book offers novel insights, practical models, and actionable solutions for healthcare professionals aiming to improve patient care in chemotherapy clinics. Readers will gain a deep understanding of the unique challenges in scheduling chemotherapy treatments, with a focus on handling uncertainty in treatment durations, coordinating clinic resources, and ensuring fairness among patients. This book uses real data from chemotherapy clinics to develop models and generate solutions representing fair and efficient schedules. Alongside methodological knowledge, readers will acquire managerial insights that can directly enhance the scheduling processes in real-world oncology settings.
R 2,623.35
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 9,315.40
Development Methodologies for Big Data Analytics Systems
This book presents research in big data analytics (BDA) for business of all sizes. The authors analyze problems presented in the application of BDA in some businesses through the study of development methodologies based on the three approaches - 1) plan-driven, 2) agile and 3) hybrid lightweight. The authors first describe BDA systems and how they emerged with the convergence of Statistics, Computer Science, and Business Intelligent Analytics with the practical aim to provide concepts, models, methods and tools required for exploiting the wide variety, volume, and velocity of available business internal and external data - i.e. Big Data - and provide decision-making value to decision-makers. The book presents high-quality conceptual and empirical research-oriented chapters on plan-driven, agile, and hybrid lightweight development methodologies and relevant supporting topics for BDA systems suitable to be used for large-, medium-, and small-sized business organizations.
R 6,594.00
Salesforce Data Architecture and Management
Learn everything you need to become a successful data architect on the Salesforce platformKey FeaturesAdopt best practices relating to data governance and learn how to implement themLearn how to work with data in Salesforce while maintaining scalability and security of an instanceGain insights into managing large data volumes in SalesforceBook DescriptionAs Salesforce orgs mature over time, data management and integrations are becoming more challenging than ever. Salesforce Data Architecture and Management follows a hands-on approach to managing data and tracking the performance of your Salesforce org.You'll start by understanding the role and skills required to become a successful data architect. The book focuses on data modeling concepts, how to apply them in Salesforce, and how they relate to objects and fields in Salesforce. You'll learn the intricacies of managing data in Salesforce, starting from understanding why Salesforce has chosen to optimize for read rather than write operations. After developing a solid foundation, you'll explore examples and best practices for managing your data. You'll understand how to manage your master data and discover what the Golden Record is and why it is important for organizations. Next, you'll learn how to align your MDM and CRM strategy with a discussion on Salesforce's Customer 360 and its key components. You'll also cover data governance, its multiple facets, and how GDPR compliance can be achieved with Salesforce. Finally, you'll discover Large Data Volumes (LDVs) and best practices for migrating data using APIs.By the end of this book, you'll be well-versed with data management, data backup, storage, and archiving in Salesforce.What you will learnUnderstand the Salesforce data architectureExplore various data backup and archival strategiesUnderstand how the Salesforce platform is designed and how it is different from other relational databasesUncover tools that can help in data management that minimize data trust issues in your Salesforce orgFocus on the Salesforce Customer 360 platform, its key components, and how it can help organizations in connecting with customersDiscover how Salesforce can be used for GDPR complianceMeasure and monitor the performance of your Salesforce orgWho this book is forThis book is for aspiring architects, Salesforce admins, and developers. You will also find the book useful if you're preparing for the Salesforce Data Architecture and Management exam. A basic understanding of Salesforce is assumed.
R 1,433.00
Operations Management
Operations Management befasst sich mit dem Prozess der Auftragserfüllung bei Sach- und Dienstleistungen. Kundenaufträge sollen schnell, pünktlich, in der geforderten Qualität und zu angemessenen Kosten realisiert werden. Nur wer die Erwartungen seiner Kunden richtig versteht, kann die eigenen Prozesse und Strukturen erfolgreich gestalten. Zusätzlich zu berücksichtigen sind die verfügbaren Methoden der Termin- und Kapazitätsplanung.Das Lehrbuch erläutert methodisch und didaktisch, welche unterschiedlichen Möglichkeiten bestehen, die Auftragserfüllung auf den Kunden auszurichten. Dabei werden Sach- und Dienstleistungen gemeinsam behandelt, gibt es doch immer weniger Waren, die nicht in Verbindung mit begleitenden Dienstleistungen wie zum Beispiel Finanzierung, Service oder Ersatzteilversorgung verkauft werden. Die 4. Auflage wurde überarbeitet und berücksichtigt auch aktuelle Entwicklungen im Qualitätsmanagement (Neuerungen der DIN EN ISO 9001:2015) und der Digitalisierung (Industrie 4.0).
R 1,731.48
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 theauthors 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 3,891.76
People Analytics
How can you turn HR data into insights that boost business performance? People Analytics by Cole Napper is a practical guide for HR managers, business partners and mid-career professionals who want to use data, analytics and AI to deliver measurable value across the organization. Written by a leading voice in the field, the book explains how to integrate people analytics into daily decision-making, from building robust HR data infrastructure to applying ethical, AI-driven insights. Drawing on real-world examples from Toyota, PepsiCo, Lightcast, Booster and FedEx, it provides a clear roadmap for building capability and confidence in data-led HR. You'll learn how to: - Design a people analytics function that supports strategic business goals - Build high-quality HR data systems for accurate, reliable insights - Apply AI and generative AI to enhance analysis and forecasting - Use analytics ethically to improve talent decisions and workforce planning With practical models, step-by-step guidance and proven real-world examples, People Analytics equips mid-career professionals to turn HR data into a competitive advantage, helping you make smarter decisions and demonstrate the strategic value of your role. Themes include: people analytics, HR data strategy, AI in HR, ethical analytics, data-driven decision-making
R 4,892.18
IoT, Machine Learning and Data Analytics for Smart Healthcare
Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system.This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues.This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students
R 6,659.39
Computational Intelligence for Business Analytics and Decision Systems
This book offers a complete and forward-looking discussion of how artificial intelligence and advanced analytics are changing modern business decision-making. This book combines foundational theory with leading-edge application in computational intelligence to offer a structured approach to intelligent, data-driven enterprise systems.This book brings together contributions from leading thinkers in the field and covers foundational methodologies including machine learning, deep learning, neural networks, fuzzy logic, soft computing, evolutionary and genetic algorithms, and hybrid intelligent systems. It also explores other important areas including predictive and prescriptive analytics, optimization algorithms, big data analytics, and data mining techniques to support intelligent business systems.This book also explores how these methodologies are applied in financial analytics, risk management, portfolio optimization, customer analytics, market segmentation, demand forecasting, supply chain analytics, and operations optimization. It also places special emphasis on explainable artificial intelligence, intelligent decision support systems, and enterprise performance analytics to ensure that advanced computational models are transparent, reliable, and strategically aligned to enterprise goals.This book is intended for researchers, postgraduate students, data scientists, financial analysts, operations managers, digital transformation leaders, and other professionals who are interested in computational intelligence and its application in intelligent business systems. It offers a structured approach to intelligent enterprise systems, which can increase competitiveness, improve forecasting, optimize enterprise resources, and support digital transformation in a sustainable manner.With its blend of rigorous analytical techniques and practical business insights, this book is an essential reference to how intelligent algorithms and decision systems are changing the future of business analytics.
R 9,158.00
R 5,379.00
Data Analytics
This book constitutes the refereed conference proceedings of the 31st British International Conference on Databases, BICOD 2017 - formerly known as BNCOD (British National Conference on Databases) - held in London, UK, in July 2017.The 17 revised full papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics such as data cleansing, data integration, data wrangling, data mining and knowledge discovery, graph data and knowledge graphs, intelligent data analysis, approximate and flexible querying, data provenance and ontology-based data access. They are organized in the following topical sections: data wrangling and data integration; data analysis and data mining; graph data querying and analysis; multidimensional data and data quality; and distributed and multimedia data management.
R 2,155.68
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018.The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
R 4,351.13
Data Science and Productivity Analytics
This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of ‘productivity analysis/data envelopment analysis’ and ‘data science/big data’. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others.Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data.Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.
R 6,228.00
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018.The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
R 4,743.35
Essentials of Operations Management
Covering the most critical topics and strategies in the field, Essentials of Operations Management provides business students with the most up-to-date coverage of modern topics not always found in other texts, such as human resources in operations, facility location, "green" operations, and the balanced scorecard approach to operations. Author Scott Young draws on his many years of teaching experience at both the undergraduate and MBA level to provide the essential content necessary for success in operations—in an affordable text. Key Features Includes a complete chapter (Chapter 4) on managing the operations workforce—an important topic for the well-rounded operations manager Applies "The Balanced Scorecard" approach to operations in Chapter 5, introducing students to a performance measure that balances customer, internal processes and learning and growth measures against traditional financial measures Covers sustainable operations in Chapter 7, including discussions of "green" operations and why they are important for any new operations manager Includes end-of-chapter projects and exercises that help students apply concepts to real-life situations Provides students with ample review opportunities through additional end-of-chapter features such as review questions, key terms, and summary points Instructor Resources on CD include PowerPoint® slides, chapter overviews, lecture outlines, review questions, and additional cases. Essentials of Operations Management is appropriate for undergraduate or MBA students taking Operations Management, Production and Operations Management, or Operations Strategy courses in schools of business.
R 5,886.33
Defining Enterprise Data and Analytics Strategy
This is the first of its kind book that describes key elements of enterprise data and analytics strategy, and prescribes a pragmatic approach to define the strategy for large enterprises. The book is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of the inherent complexity of such initiatives. Some of the questions that enterprises struggle with are: How to define enterprise data and analytics strategy? What are the key elements that should be considered while doing so? Why one-size-fits-all approach does not work for all enterprises? How to align data and analytics initiative with the business strategy of the CEO? How to establish a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies? How to define the right data and analytics organization model? Why data and analytics organization and processes need to be different from other functions? How to manage organizational change to ensure success of data and analytics initiative? How to define a business value measurement framework and calculate ROI from data and analytics initiative? What are the key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise? This book will help executives, chief digital/analytics officers, data and analytics professionals, and consultants, in answering the above questions. It will help them in addressing various dilemmas that they face every day and making their enterprises data-driven.
R 2,381.00
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 5,631.86
Modelling and Simulation in Management
This book is a comprehensive introduction of the reader into the simulation and modelling techniques and their application in the management of organisations. The book is rooted in the thorough understanding of systems theory applied to organisations and focuses on how this theory can apply to econometric models used in the management of organisations. The econometric models in this book employ linear and dynamic programming, graph theory, queuing theory, game theory, etc. and are presented and analysed in various fields of application, such as investment management, stock management, strategic decision making, management of production costs and the lifecycle costs of quality and non-quality products, production quality Management, etc.
R 6,601.89
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 7,002.23
Management Education and Automation
Due to automation, nearly half of the jobs will vanish over the next two decades in the US. However, the problem is not confined to any particular country. Management educators in higher education are faced with two fundamental questions: (a) how we prepare our students for new required technology competencies when conducting international business and (b) how we work with new technologies to prepare our students. While the next generation of employees requires competencies in working with artificial intelligence relying on data analytics, the emergence of artificial intelligence and new technologies in augmenting teaching is changing the nature of higher education across the globe. Management Education and Automation explores international management education in light of exponential development of artificial intelligence, big data, demographic shifts, expansion of robotic utilization in many economic sectors, aging populations and negative population growth in developed economies, multipolar international political systems, migration patterns, and fundamental shifts in individual and social interactions via digital media. It shows the latest state of knowledge on the topic and will be of interest to researchers, academics, policymakers, and students in the fields of international business and management, globalization, management education, and management of technology and innovation.
R 2,545.25
Handbook of Stochastic Models and Analysis of Manufacturing System Operations
This handbook surveys important stochastic problems and models in manufacturing system operations and their stochastic analysis. Using analytical models to design and control manufacturing systems and their operations entail critical stochastic performance analysis as well as integrated optimization models of these systems. Topics deal with the areas of facilities planning, transportation, and material handling systems, logistics and supply chain management, and integrated productivity and quality models covering:• Stochastic modeling and analysis of manufacturing systems• Design, analysis, and optimization of manufacturing systems• Facilities planning, transportation, and material handling systems analysis• Production planning, scheduling systems, management, and control• Analytical approaches to logistics and supply chain management• Integrated productivity and quality models, and their analysis • Literature surveys of issues relevant in manufacturing systems• Case studies of manufacturing system operations and analysisToday’s manufacturing system operations are becoming increasingly complex. Advanced knowledge of best practices for treating these problems is not always well known. The purpose of the book is to create a foundation for the development of stochastic models and their analysis in manufacturing system operations. Given the handbook nature of the volume, introducing basic principles, concepts, and algorithms for treating these problems and their solutions is the main intent of this handbook. Readers unfamiliar with these research areas will be able to find a research foundation for studying these problems and systems.
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R 3,289.84
Data and Analytics Strategy for Business
Struggling to convert your data, analytics and AI strategy into business value? Data and Analytics Strategy for Business by Simon Asplen-Taylor is an essential guide for CDOs, CAIOs, CIOs and CTOs seeking to deliver measurable results from data investments. Focused on aligning data, analytics and AI with strategic goals, this book helps leaders move from initial implementation to transformation. Fully updated with the latest AI developments, it provides practical tools and real-world insights to accelerate implementation, drive adoption and optimize performance across the organization. You'll learn how to: - Align data, analytics and AI to strategic business outcomes - Build trust through data quality, governance and transparency - Integrate AI and ML Secure executive and organizational buy-in for long-term success - Learn from real-world examples including Tesco and Facebook With guidance grounded in real results, Data and Analytics Strategy for Business helps senior leaders lead smarter, execute faster and unlock enterprise-wide impact. Themes include: data strategy, AI adoption, analytics leadership, digital transformation, data governance, performance optimization
R 4,894.54
Analytical Decision Making and Data Envelopment Analysis
This book explores the intersection of data envelopment analysis (DEA) and various analytical decision-making methodologies. Featuring contributions from experts in the field from across the world, each chapter delves into different aspects of DEA and its applications in real-world scenarios. The book covers a wide range of topics, including integrating DEA with machine learning techniques, performance evaluation in diverse sectors like banking and civil engineering, and using DEA in managerial decision-making. It also examines data mining during the Covid-19 pandemic and the application of blockchain and IoT in supply chain management. The book offers a deep dive into the evolution of nonparametric frontier methods and the development of new optimization algorithms, addressing the complexities of modern analytical decision-making tools.A few chapters delve into futuristic topics like fuzzy sets and their extensions in decision-making and exploring e-learning platforms for education. This book is an invaluable resource for researchers, practitioners and students interested in the latest DEA advancements and practical applications in various fields. Its multidisciplinary approach makes it a useful addition to the libraries of those seeking to understand the complexities and potentials of modern analytical decision-making tools.
R 8,807.67
Palgrave Handbook of Supply Chain and Disruptive Technologies
Disruptive technologies are revolutionising the supply chain landscape, driving innovation, and unlocking unprecedented value to achieve radical growth and operational excellence. This comprehensive handbook delves into the cutting-edge research and dynamic debates surrounding the development of digital capabilities. It explores how emerging technologies such as blockchain, big data analytics, cloud computing, artificial intelligence, drones, autonomous vehicles, 5G, and more are reshaping the industry. By harnessing these technologies, organisations can fully capitalise on their transformative potential, paving the way for a future of enhanced efficiency, agility, and competitive advantage. International experts contributing to this book provide in-depth examinations of emerging design practices, the integration of user experience and incremental customisation, and the technological interventions bridging build-to-model and conventional manufacturing. They also explore innovative practices in interactive design for product use and assess capabilities through the dynamic interaction between individuals and organisational structures. This comprehensive exploration offers invaluable insights into the future of supply chain digitalisation, making it an essential resource for achieving operational excellence and radical growth. This handbook will be of immense interest to a diverse audience, including academics and students in Business and Management, Logistics and Supply Chain Management, Operations Management, Technology Management, and Information Management. Additionally, it will captivate stakeholders, managers, and practitioners in these fields. By offering cutting-edge insights and practical guidance, this volume serves as an indispensable resource for anyone seeking to navigate and excel in the rapidly evolving landscape of supply chain digitalization.
R 8,059.00
Essential Guide to Operations Management
This book is a novel treatment of Operations Management. It takes a fresh insight to this increasingly important topic, exploring fundamental principles equally applicable to service and manufacturing situations. The book adapts a strategic stance by providing a framework for effective decision making and is aimed at practising managers who need to design working processes, manage change and make decisions within a strategic framework. The framework and supporting case vignettes allow the practitioner to grasp essential concepts quickly in a range of different operational contexts. "Bamford and Forrester have done an excellent job in creating a concise, salient, and appealing approach - they have captured the essential elements of designing processes, products and work organizations; exploring approaches to operations planning and control; managing change through effective project management and technology transfer; and then managing quality and improvement strategies".—Professor Rob Handfield, Professor of Supply Chain Management, North Carolina State University, USA "This is an excellent concise text that introduces students to all of the key areas - it's an invaluable aid for students in understanding all of the major aspects of operations and their importance to the success of businesses".—Professor Steve Brown, Professor of Management, University of Exeter Business School, University of Exeter, UK "For today's or tomorrow's business leaders this text has well structured invaluable content ready for immediate adoption. Follow the guide, put it into practice, and the rewards will follow".—Mr Vernon Barker, Managing Director, First TransPennine Express, First Group Plc, UK "This book combines technical theory 'book smarts' with real life experience 'street smarts' in a flowing read".—Mr Stephen Oliver, Vice President Marketing & Sales, Vicor Corporation, Boston, USA
R 1,922.00
R 4,132.00
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 2,424.96
Predictive Safety Analytics
Nearly all our safety data collection and reporting systems are backwardlooking: incident reports; dashboards; compliance monitoring systems; and so on. This book shows how we can use safety data in a forward-looking, predictive sense.Predictive Safety Analytics: Reducing Risk through Modeling and Machine Learning contains real use cases where organizations have reduced incidents by employing predictive analytics to foresee and mitigate future risks. It discusses how Predictive Safety Analytics is an opportunity to break through the plateau problem where safety rate improvements have stagnated in many organizations. The book presents how the use of data, coupled with advanced analytical techniques, including machine learning, has become a proven and successful innovation. Emphasis is placed on how the book can “meet you where you are” by illuminating a path to get there, starting with simple data the organization likely already has. Highlights of the book are the real examples and case studies that will assist in generating thoughts and ideas for what might work for individual readers and how they can adapt the information to their particular situations.This book is written for professionals and researchers in system reliability, risk and safety assessment, quality control, operational managers in selected industries, data scientists, and ML engineers. Students taking courses in these areas will also find this book of interest to them.
R 1,381.12
HBR Guide to Data Analytics Basics for Managers (HBR Guide Series)
Don't let a fear of numbers hold you back.Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.You'll learn how to:Identify the metrics you need to measureRun experiments and A/B testsAsk the right questions of your data expertsUnderstand statistical terms and conceptsCreate effective charts and visualizationsAvoid common mistakes
R 1,003.00
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 6,156.79
Practical Supply Chain and Logistics Analytics
Practical Supply Chain and Logistics Analytics provides essential analytical techniques for managing distribution, transportation, inventory, manufacturing, network design, customer logistics and procurement across the supply chain.This book delivers practical decision-analysis methodologies that supply chain professionals can immediately implement in their daily operations. Readers will gain a working knowledge of fundamental logistics analytical methods that offer critical quantitative perspectives for better decision-making. The text presents a comprehensive range of techniques with step-by-step guidance, real-world examples, and actionable insights that bridge theory and practice. Each chapter builds analytical competency through accessible explanations and implementable frameworks, enabling professionals to address specific logistics management challenges efficiently while developing their quantitative skill set for long-term career advancement.University lecturers will find it complements traditional supply chain textbooks and can also serve as the primary text for a first supply chain analytics class, while logistics professionals at all levels can use it as a reference guide for developing analyses to address specific management decisions.
R 10,139.56
Network Science Models for Data Analytics Automation
This book explains network science and its applications in data analytics for critical infrastructures, engineered systems, and knowledge acquisition. Each chapter describes step-by-step processes of how network science enables and automates data analytics through examples. The book not only dissects modeling techniques and analytical results but also explores the intrinsic development of these models and analyses. This unique approach bridges the gap between theory and practice and channels’ managerial and problem-solving skills.Engineers, researchers, and managers would benefit from the extensive theoretical background and practical examples discussed in this book. Advanced undergraduate students and graduate students in mathematics, statistics, engineering, business, public health, and social science may use this book as a one-semester textbook or a reference book. Readers who are more interested in applications may skip Chapter 1 and peruse through the rest of the book with ease.
R 3,972.40
Airline Operations and Management
Airline Operations and Management: A Management Textbook presents a survey of the airline industry, with a strong managerial perspective. It integrates and applies the fundamentals of several management disciplines, particularly operations, marketing, economics and finance, to develop a comprehensive overview. It also provides readers with a solid historical background, and offers a global perspective of the industry, with examples drawn from airlines around the world. Updates for the second edition include:Fresh data and examplesA range of international case studies exploring real-life applicationsNew or increased coverage of key topics such as the COVID-19 pandemic, state aid, and new business modelsNew chapters on fleet management and labor relations and HRMLecture slides for instructorsThis textbook is for advanced undergraduate and graduate students of airline management, but it should also be useful to entry and junior-level airline managers and professionals seeking to expand their knowledge of the industry beyond their functional area.
R 2,582.29
Big Data Analytics and Intelligent Applications for Smart and Secure Healthcare Services
The book provides a comprehensive discussion for utilizing computational models such as artificial neural networks, agent-based models, and decision field theory, for reliability engineering. It further presents optimization solutions for smart and secure healthcare services. The text showcases how to predict the failure and repair rates of healthcare subsystems using computational intelligence.This book:Explores how data-driven methodologies and advanced computational intelligence are revolutionizing the healthcare industry, promoting efficiency, accessibility, and sustainabilityHighlights the pivotal role that big data analytics plays in harnessing vast amounts of patient records, clinical information, and real-time medical data to provide timely insights for healthcare professionals and policymakersDiscusses the integration of artificial intelligence and machine learning techniques in healthcare, with a focus on revolutionizing disease detection, treatment planning, and resource allocationLays the foundation for developing sustainable healthcare systems that are adaptable to long-term challenges, such as population growth, emerging diseases, and resource constraintsCovers computational intelligence techniques, like fuzzy logic, neural networks, and evolutionary computations, emphasizing their role in solving complex, data-driven healthcare problemsIncludes topics like data management, visualization, protection, and complex adaptive systems, as well as hybrid computational intelligence techniques for synergistic problem-solving strategiesThis volume will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and mathematics.
R 7,576.15
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 6,544.95
R 1,069.00
Introduction to Operations Management
Introduction to Operations Management: A Supply Chain Process Approach details how firms buy, make, deliver, and return goods and services around the globe, providing students with a solid foundation of operations management concepts and techniques. The text offers a set of activities that guide the effectiveness of organizations and prepare operations managers and other employees to ensure their firms are competitive. The book is organized from a strategic to a tactical perspective, beginning with foundational concepts and ending with broader discussions of managing supply chains. Dedicated chapters address corporate strategy, services design, inventory management, aggregate planning, forecasting, lean systems, quality management, purchasing, logistics, and more. Numerous real-world examples, cases, and engaging exercises allow students to place themselves in the shoes of working operations management professionals. For the third edition, each chapter has been revised and updated to reflect the latest information. The largest updates address the COVID-19 pandemic and supply chain disruption. This edition also features new end-of-chapter problems and questions and four new contributed case studies. Written for today's students and the exciting, ever-evolving marketplace, the third edition of Introduction to Operations Management is the text to bring operations management into the post-pandemic era.
R 5,066.00
Handbook of Business Analytics
Business analytics are widely used in healthcare, manufacturing, and other industries that need to monitor or carefully analyze its users. Every day, over 2.5 quintillion data bytes are collected, for which it is essential to use business analytics. Many new software solutions and platforms have been relied upon to ingest and process large data sets.The book provides insights into business analytics as a key analytical technique to evaluate risk, project future commercial trends, and determine when upgradation is needed. It will help analysts and researchers in discovering trends and patterns in the data, which uses past information as a source and a variety of analytical algorithms for forecasting future events with a high level of accuracy, is the fundamental aim of business analytics. The chapters are written by academicians, industry experts, and researchers, each focusing on a different facet of business analytics. The book is meant for managers, executives, and entrepreneurs, who want to use data to improve consumer insights, strategic planning, and operational efficiency. With its theoretical foundations and real-world analytics applications, the book is also a great resource for academicians, scholars, and students studying business administration, data science, and information systems.
R 7,303.32
Big Data Management and Analytics
This book constitutes 5 revised tutorial lectures of the 9th European Business Intelligence and Big Data Summer School, eBISS 2019, held in Berlin, Germany, during June 30 – July 5, 2019. The tutorials were given by renowned experts and covered advanced aspects of business intelligence and big data. This summer school, presented by leading researchers in the field, represented an opportunity for postgraduate students to equip themselves with the theoretical and practical skills necessary for developing challenging business intelligence applications.
R 2,147.00
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 4,444.00
Developments in Data Extraction, Management, and Analysis
Developments in Data Extraction, Management, and Analysis is an essential collection of research on the area of data mining and analytics. Presenting the most recent perspectives on data mining subjects and current issues, this book is useful for practitioners and academics alike.
R 7,582.51
Data Analytics Made Easy
Learn how to gain insights from your data as well as machine learning and become a presentation pro who can create interactive dashboardsKey FeaturesEnhance your presentation skills by implementing engaging data storytelling and visualization techniquesLearn the basics of machine learning and easily apply machine learning models to your dataImprove productivity by automating your data processesBook DescriptionData Analytics Made Easy is an accessible beginner’s guide for anyone working with data. The book interweaves four key elements:Data visualizations and storytelling – Tired of people not listening to you and ignoring your results? Don’t worry; chapters 7 and 8 show you how to enhance your presentations and engage with your managers and co-workers. Learn to create focused content with a well-structured story behind it to captivate your audience.Automating your data workflows – Improve your productivity by automating your data analysis. This book introduces you to the open-source platform, KNIME Analytics Platform. You’ll see how to use this no-code and free-to-use software to create a KNIME workflow of your data processes just by clicking and dragging components. Machine learning – Data Analytics Made Easy describes popular machine learning approaches in a simplified and visual way before implementing these machine learning models using KNIME. You’ll not only be able to understand data scientists’ machine learning models; you’ll be able to challenge them and build your own.Creating interactive dashboards – Follow the book’s simple methodology to create professional-looking dashboards using Microsoft Power BI, giving users the capability to slice and dice data and drill down into the results.What you will learnUnderstand the potential of data and its impact on your businessImport, clean, transform, combine data feeds, and automate your processesInfluence business decisions by learning to create engaging presentationsBuild real-world models to improve profitability, create customer segmentation, automate and improve data reporting, and moreCreate professional-looking and business-centric visuals and dashboardsOpen the lid on the black box of AI and learn about and implement supervised and unsupervised machine learning modelsWho this book is forThis book is for beginners who work with data and those who need to know how to interpret their business/customer data. The book also covers the high-level concepts of data workflows, machine learning, data storytelling, and visualizations, which are useful for managers.No previous math, statistics, or computer science knowledge is required.
R 1,140.00
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 9,937.15
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 2,752.22
