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| big data analytics in supply chain management: Big Data Analytics in Supply Chain Management Iman Rahimi, Amir H. Gandomi, Simon James Fong, M. Ali Ülkü, 2020-12-20 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. |
| big data analytics in supply chain management: Big Data Driven Supply Chain Management Nada R. Sanders, 2014-05-07 Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance. |
| big data analytics in supply chain management: Big Data Analytics in Supply Chain Management Iman Rahimi, Amir H. Gandomi, Simon James Fong, M. Ali Ülkü, 2020-12-20 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. |
| big data analytics in supply chain management: Supply Chain Management in the Big Data Era Chan, Hing Kai, Subramanian, Nachiappan, Abdulrahman, Muhammad Dan-Asabe, 2016-11-04 Technological advancements in recent years have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Supply Chain Management in the Big Data Era is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes. Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations. |
| big data analytics in supply chain management: Research Anthology on Big Data Analytics, Architectures, and Applications Information Resources Management Association, 2022 Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians. |
| big data analytics in supply chain management: Supply Chain Analytics Peter W. Robertson, 2020-11-25 Supply Chain Analytics introduces the reader to data analytics and demonstrates the value of their effective use in supply chain management. By describing the key supply chain processes through worked examples, and the descriptive, predictive and prescriptive analytic methods that can be applied to bring about improvements to those processes, the book presents a more comprehensive learning experience for the reader than has been offered previously. Key topics are addressed, including optimisation, big data, data mining and cloud computing. The author identifies four core supply chain processes – strategy, design, execution and people – to which the analytic techniques explained can be applied to ensure continuous improvement. Pedagogy to aid learning is incorporated throughout, including an opening section for each chapter explaining the learnings designed for the chapter; worked examples illustrating how each analytic technique works, how it is applied and what to be careful of; tables, diagrams and equations to help ‘visualise’ the concepts and methods covered; chapter case studies; and end-of-chapter review questions and assignment tasks. Providing both management expertise and technical skills, which are essential to decision-makers in the supply chain, this textbook should be essential reading for advanced undergraduate and postgraduate students of supply chain analytics, supply chain leadership, and supply chain and operations management. Its practice-based and applied approach also makes it valuable for operating supply chain practitioners and those studying for professional qualifications. Online resources include chapter-by-chapter PowerPoint slides, tutorial exercises, written assignments and a test bank of exam questions. |
| big data analytics in supply chain management: Logistics, Supply Chain and Financial Predictive Analytics Kusum Deep, Madhu Jain, Said Salhi, 2018-08-06 This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves. The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction. |
| big data analytics in supply chain management: Big Data, Big Analytics Michael Minelli, Michele Chambers, Ambiga Dhiraj, 2013-01-22 Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more. |
| big data analytics in supply chain management: Integrating Blockchain Technology Into the Circular Economy Khan, Syed Abdul Rehman, 2022-03-11 In recent decades, the industrial revolution has increased economic growth despite its immersion in global environmental issues such as climate change. Researchers emphasize the adoption of circular economy practices in global supply chains and businesses for better socio-environmental sustainability without compromising economic growth. Integrating blockchain technology into business practices could promote the circular economy as well as global environmental sustainability. Integrating Blockchain Technology Into the Circular Economy discusses the technological advancements in circular economy practices, which provide better results for both economic growth and environmental sustainability. It provides relevant theoretical frameworks and the latest empirical research findings in the applications of blockchain technology. Covering topics such as big data analytics, financial market infrastructure, and sustainable performance, this book is an essential resource for managers, operations managers, executives, manufacturers, environmentalists, researchers, industry practitioners, students and educators of higher education, and academicians. |
| big data analytics in supply chain management: Enterprise Analytics Thomas H. Davenport, 2013 International Institute for Analytics--Dust jacket. |
| big data analytics in supply chain management: The Applied Business Analytics Casebook Matthew J. Drake, 2014 The first collection of cases on big data analytics for supply chain, operations research, and operations management, this reference puts readers in the position of the analytics professional and decision-maker. Perfect for students, practitioners, and certification candidates in SCM, OM, and OR, these short, focused, to-the-point case studies illustrate the entire decision-making process. They provide realistic opportunities to perform analyses, interpret output, and recommend an optimal course of action. Contributed by leading big data experts, the cases in The Applied Business Analytics Casebook covers: Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models |
| big data analytics in supply chain management: Integrated Business Information Systems Klaus-Dieter Gronwald, 2017-05-30 Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM), Business Intelligence (BI) and Big Data Analytics (BDA) are business related tasks and processes, which are supported by standardized software solutions. The book explains that this requires business oriented thinking and acting from IT specialists and data scientists. It is a good idea to let students experience this directly from the business perspective, for example as executives of a virtual company. The course simulates the stepwise integration of the linked business process chain ERP-SCM-CRM-BI-Big Data of four competing groups of companies. The course participants become board members with full P&L responsibility for business units of one of four beer brewery groups managing supply chains from production to retailer. |
| big data analytics in supply chain management: Encyclopedia of Organizational Knowledge, Administration, and Technology Khosrow-Pour D.B.A., Mehdi, 2020-09-29 For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication. |
| big data analytics in supply chain management: Operations Management and Data Analytics Modelling Lalit Kumar Awasthi, Sushendra Kumar Misra, Dilbagh Panchal, Mohit Tyagi, 2021-12-30 Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0. It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma. Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problems This book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science. |
| big data analytics in supply chain management: Big Data Bill Schmarzo, 2013-09-23 Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice. |
| big data analytics in supply chain management: The Palgrave Handbook of Methods for Media Policy Research Hilde Van den Bulck, Manuel Puppis, Karen Donders, Leo Van Audenhove, 2019-08-13 The Palgrave Handbook of Methods for Media Policy Research covers the craft that is and the methods used in media and communication policy research. It discusses the steps involved in conducting research, from deciding on a topic, to writing a report and everything in between and, furthermore, deals with a wide variety of qualitative and quantitative methods of data collection and analysis. The handbook invites researchers to rediscover trusted methods such as document analysis, elite interviews and comparisons, as well as to familiarize themselves with newer methods like experiments, big data and network analysis. For each method, the handbook provides a practical step-by-step guide and case studies that help readers in using that method in their own research. The methods discussed are useful for all areas of media and communication policy research, for research concerning the governance of both mass media and online platforms, and for policy issues around the globe. As such, the handbook is an invaluable guide to every researcher in this field. |
| big data analytics in supply chain management: Big Data Analytics Kiran Chaudhary, Mansaf Alam, 2022-01-19 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 algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The 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. |
| big data analytics in supply chain management: Big Data at Work Thomas Davenport, 2014-02-04 Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource. |
| big data analytics in supply chain management: Supply Chain Management Nada R. Sanders, 2017-10-19 Supply chain management, rapidly-advancing and growing ever more important in the global business climate, requires an intense understanding of both underlying principles and practical techniques. Including both a broad overview of supply chain management and real-world examples of SCM in companies ranging from small to large, this book provides students with both the foundational material required to understand the subject matter and practical tips that demonstrate how the latest techniques are being applied. Spanning functional boundaries, this well-regarded book is now in its second edition and has quickly become a standard course text at many universities. This newest edition continues to provide a balanced, integrative, and business-oriented viewpoint of the material, and deeply explores how SCM is intertwined with other organizational functions. New material has been added to address the importance of big data analytics in SCM, as well as other technological advances such as 3-D printing, cloud computing, machine learning, driverless vehicles, the Internet of Things, RFID, and others. |
| big data analytics in supply chain management: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| big data analytics in supply chain management: Encyclopedia of Business Analytics and Optimization Wang, John, 2014-02-28 As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal. |
| big data analytics in supply chain management: Big Data Analytics in Healthcare Anand J. Kulkarni, Patrick Siarry, Pramod Kumar Singh, Ajith Abraham, Mengjie Zhang, Albert Zomaya, Fazle Baki, 2019-10-01 This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms. |
| big data analytics in supply chain management: New Horizons for a Data-Driven Economy José María Cavanillas, Edward Curry, Wolfgang Wahlster, 2016-04-04 In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment. |
| big data analytics in supply chain management: Big Data For Dummies Judith S. Hurwitz, Alan Nugent, Fern Halper, Marcia Kaufman, 2013-04-02 Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization. |
| big data analytics in supply chain management: Web, Artificial Intelligence and Network Applications Leonard Barolli, Makoto Takizawa, Fatos Xhafa, Tomoya Enokido, 2019-03-14 The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications. |
| big data analytics in supply chain management: Analytics in Operations/Supply Chain Management Muthu Mathirajan, Chandrasekharan Rajendran, Sowmyanarayanan Sadagopan, Arunachalam Ravindran, Parasuram Balasubramanian, 2016-03-30 Efficient and effective operations/supply chain management is pivotal to an organisation's success in today's competitive global environment. This Symposium Proceedings focuses on the role of analytics in operations /supply chain management, particularly in the context of multi criteria decision making. It highlights emerging concepts and potential applications. |
| big data analytics in supply chain management: Software Engineering in IoT, Big Data, Cloud and Mobile Computing Haengkon Kim, Roger Lee, 2020-12-26 This edited book presents scientific results of the International Semi-Virtual Workshop on Software Engineering in IoT, Big data, Cloud and Mobile Computing (SE-ICBM 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science. |
| big data analytics in supply chain management: Evolutionary Computation in Scheduling Amir H. Gandomi, Ali Emrouznejad, Mo M. Jamshidi, Kalyanmoy Deb, Iman Rahimi, 2020-04-09 Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering. |
| big data analytics in supply chain management: Ten Years to Midnight Blair H. Sheppard, 2020-08-04 “Shows how humans have brought us to the brink and how humanity can find solutions. I urge people to read with humility and the daring to act.” —Harpal Singh, former Chair, Save the Children, India, and former Vice Chair, Save the Children International In conversations with people all over the world, from government officials and business leaders to taxi drivers and schoolteachers, Blair Sheppard, global leader for strategy and leadership at PwC, discovered they all had surprisingly similar concerns. In this prescient and pragmatic book, he and his team sum up these concerns in what they call the ADAPT framework: Asymmetry of wealth; Disruption wrought by the unexpected and often problematic consequences of technology; Age disparities--stresses caused by very young or very old populations in developed and emerging countries; Polarization as a symptom of the breakdown in global and national consensus; and loss of Trust in the institutions that underpin and stabilize society. These concerns are in turn precipitating four crises: a crisis of prosperity, a crisis of technology, a crisis of institutional legitimacy, and a crisis of leadership. Sheppard and his team analyze the complex roots of these crises--but they also offer solutions, albeit often seemingly counterintuitive ones. For example, in an era of globalization, we need to place a much greater emphasis on developing self-sustaining local economies. And as technology permeates our lives, we need computer scientists and engineers conversant with sociology and psychology and poets who can code. The authors argue persuasively that we have only a decade to make headway on these problems. But if we tackle them now, thoughtfully, imaginatively, creatively, and energetically, in ten years we could be looking at a dawn instead of darkness. |
| big data analytics in supply chain management: The Internet of Things Daniel Giusto, Antonio Iera, Giacomo Morabito, Luigi Atzori, 2010-03-10 This book constitutes the proceedings from the 20th Tyrrhenian Workshop on Digital Communications, held September 2009 in Pula, Sardinia, Italy and focused on the Internet of Things. |
| big data analytics in supply chain management: Supply Chain 4.0 Emel Aktas, Michael Bourlakis, Ioannis Minis, Vasileios Zeimpekis, 2021-02-03 Supply Chain 4.0 has introduced automation into logistics and supply chain processes, exploiting predictive analytics to better match supply with demand, optimizing operations and using the latest technologies for the last mile delivery such as drones and autonomous robots. Supply Chain 4.0 presents new methods, techniques, and information systems that support the coordination and optimization of logistics processes, reduction of operational costs as well as the emergence of entirely new services and business processes. This edited collection includes contributions from leading international researchers from academia and industry. It considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, Internet of Things, and decision support systems for transportation and logistics. It also highlights market requirements and includes case studies of cutting-edge applications from innovators in the logistics industry. |
| big data analytics in supply chain management: The Big Data-Driven Digital Economy: Artificial and Computational Intelligence Abdalmuttaleb M. A. Musleh Al-Sartawi, 2021-05-28 This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals. |
| big data analytics in supply chain management: Big Data Analytics Using Multiple Criteria Decision-Making Models Ramakrishnan Ramanathan, Muthu Mathirajan, A. Ravi Ravindran, 2017-07-12 Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data. |
| big data analytics in supply chain management: Artificial Intelligence for Knowledge Management Eunika Mercier-Laurent, M. Özgür Kayalica, Mieczyslaw Lech Owoc, 2021-07-03 This book features a selection of extended papers presented at the 8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, held in Yokohama, Japan, in January 2021, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2020.* The 14 revised and extended papers presented together with an invited talk were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and discuss methodological, technical and organizational aspects of artificial intelligence used for knowledge management. *The workshop was held virtually. |
| big data analytics in supply chain management: Proceedings of the Seventh International Forum on Decision Sciences Xiang Li, Xiaofeng Xu, 2020-11-21 These proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics, supply chain management, and decision sciences. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium “The Seventh International Forum on Decision Sciences”, which took place in Windsor, Canada. |
| big data analytics in supply chain management: Big Data Optimization: Recent Developments and Challenges Ali Emrouznejad, 2016-05-26 The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book. |
| big data analytics in supply chain management: Analytics in a Big Data World Bart Baesens, 2014-04-15 The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities. |
| big data analytics in supply chain management: Sales Engagement Manny Medina, Max Altschuler, Mark Kosoglow, 2019-03-12 Engage in sales—the modern way Sales Engagement is how you engage and interact with your potential buyer to create connection, grab attention, and generate enough interest to create a buying opportunity. Sales Engagement details the modern way to build the top of the funnel and generate qualified leads for B2B companies. This book explores why a Sales Engagement strategy is so important, and walks you through the modern sales process to ensure you’re effectively connecting with customers every step of the way. • Find common factors holding your sales back—and reverse them through channel optimization • Humanize sales with personas and relevant information at every turn • Understand why A/B testing is so incredibly critical to success, and how to do it right • Take your sales process to the next level with a rock solid, modern Sales Engagement strategy This book is essential reading for anyone interested in up-leveling their game and doing more than they ever thought possible. |
| big data analytics in supply chain management: Impacts and Challenges of Cloud Business Intelligence Aljawarneh, Shadi, Malhotra, Manisha, 2020-12-18 Cloud computing provides an easier alternative for starting an IT-based business organization that requires much less of an initial investment. Cloud computing offers a significant edge of traditional computing with big data being continuously transferred to the cloud. For extraction of relevant data, cloud business intelligence must be utilized. Cloud-based tools, such as customer relationship management (CRM), Salesforce, and Dropbox are increasingly being integrated by enterprises looking to increase their agility and efficiency. Impacts and Challenges of Cloud Business Intelligence is a cutting-edge scholarly resource that provides comprehensive research on business intelligence in cloud computing and explores its applications in conjunction with other tools. Highlighting a wide range of topics including swarm intelligence, algorithms, and cloud analytics, this book is essential for entrepreneurs, IT professionals, managers, business professionals, practitioners, researchers, academicians, and students. |
| big data analytics in supply chain management: Big Data Analytics David Loshin, 2013-08-23 Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. - Guides the reader in assessing the opportunities and value proposition - Overview of big data hardware and software architectures - Presents a variety of technologies and how they fit into the big data ecosystem |
BIG | Bjarke Ingels Group
BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, …
Bjarke Ingels Group - BIG
Since BIG inception in 2006, David Zahle has been responsible for delivering imaginative and pioneering designs for buildings such as Copenhill, a waste-to energy plant with a ski slope on …
Athletics Las Vegas Ballpark | BIG | Bjarke Ingels Group
The project builds on a longstanding collaboration between BIG and the Athletics dating back to a different ballpark design in Oakland, California in 2018. The new ballpark’s roof is accentuated …
Jinji Lake Pavilion | BIG | Bjarke Ingels Group
Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, Architecture, Planning and Products. A plethora of in-house perspectives allows us to see …
Gowanus 175 Third Street | BIG | Bjarke Ingels Group
Catalyzed by the major Gowanus rezoning in 2021 – one of the most significant rezonings in New York City in recent years – 175 Third Street builds on years of BIG’s prior study and design …
Sankt Lukas Hospice and Lukashuset | BIG | Bjarke Ingels Group
A small step for each of us becomes a BIG LEAP for all of us. BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the …
Google Bay View | BIG | Bjarke Ingels Group
Leon Rost — Partner, BIG The campus includes 17.3 acres of high-value natural areas – including wet meadows, woodlands, and marsh – that contribute to Google’s broader efforts to …
Gelephu International Airport | BIG | Bjarke Ingels Group
As Bhutan’s second international airport, the project is a collaboration with aviation engineering firm NACO and an integral part of the Gelephu Mindfulness City (GMC) masterplan designed …
Opera and Ballet Theatre of Kosovo | BIG | Bjarke Ingels Group
BIG proposes a simple and prag matic arrangement of the performance venues draped in a soft, undulating exterior skin of photovoltaic tiles. The theatre ’s form is reminiscent of the free …
Freedom Plaza | BIG | Bjarke Ingels Group
Freedom Plaza will extend BIG’s contribution to New York City’s waterfront, alongside adjacent coastal projects that include the East Side Coastal Resiliency project, the Battery Park City …
BIG | Bjarke Ingels Group
BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, …
Bjarke Ingels Group - BIG
Since BIG inception in 2006, David Zahle has been responsible for delivering imaginative and pioneering designs for buildings such as Copenhill, a waste-to energy plant with a ski slope on …
Athletics Las Vegas Ballpark | BIG | Bjarke Ingels Group
The project builds on a longstanding collaboration between BIG and the Athletics dating back to a different ballpark design in Oakland, California in 2018. The new ballpark’s roof is accentuated …
Jinji Lake Pavilion | BIG | Bjarke Ingels Group
Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, Architecture, Planning and Products. A plethora of in-house perspectives allows us to see …
Gowanus 175 Third Street | BIG | Bjarke Ingels Group
Catalyzed by the major Gowanus rezoning in 2021 – one of the most significant rezonings in New York City in recent years – 175 Third Street builds on years of BIG’s prior study and design …
Sankt Lukas Hospice and Lukashuset | BIG | Bjarke Ingels Group
A small step for each of us becomes a BIG LEAP for all of us. BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the …
Google Bay View | BIG | Bjarke Ingels Group
Leon Rost — Partner, BIG The campus includes 17.3 acres of high-value natural areas – including wet meadows, woodlands, and marsh – that contribute to Google’s broader efforts to …
Gelephu International Airport | BIG | Bjarke Ingels Group
As Bhutan’s second international airport, the project is a collaboration with aviation engineering firm NACO and an integral part of the Gelephu Mindfulness City (GMC) masterplan designed …
Opera and Ballet Theatre of Kosovo | BIG | Bjarke Ingels Group
BIG proposes a simple and prag matic arrangement of the performance venues draped in a soft, undulating exterior skin of photovoltaic tiles. The theatre ’s form is reminiscent of the free …
Freedom Plaza | BIG | Bjarke Ingels Group
Freedom Plaza will extend BIG’s contribution to New York City’s waterfront, alongside adjacent coastal projects that include the East Side Coastal Resiliency project, the Battery Park City …
