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Author: Jairo R. Montoya-Torres Publisher: Springer Nature ISBN: 303128870X Category : Business & Economics Languages : en Pages : 234
Book Description
This book gathers a selection of peer-reviewed research papers presented at the joint IV ASOCIO/XIX IISE Region 16 Conference held in Chia and Bogota, Colombia. The conference was organized by the Universidad de La Sabana’s Research Group on Logistics Systems, in partnership with Chapters #782 (Universidad de La Sabana), #712 (Universidad Sergio Arboleda) and #988 (Universidad de Los Andes) of the Institute of Industrial and Systems Engineers (IISE). The main emphasis of the book is on modelling and solving business-related problems in operations research, and on applying descriptive, predictive and prescriptive analytics and the management sciences to actual decision-making in organizations. Both theoretical developments and algorithm implementation are presented. A special focus is given to business problems arising in emerging economies, particularly in Latin America and the Caribbean. This book is addressed to academics, practitioners, postgraduate students and researchers in operations research, analytics and industrial engineering, as well as to undergraduate students for educational purposes. In particular, the book will appeal to the academic and research community in Latin America and the Caribbean, as it presents projects developed and implemented there. Higher education engineering programs will benefit from the findings and insights shared in the fields of industrial engineering, operations research and analytics, applied mathematics, and computer science and engineering.
Author: Jairo R. Montoya-Torres Publisher: Springer Nature ISBN: 303128870X Category : Business & Economics Languages : en Pages : 234
Book Description
This book gathers a selection of peer-reviewed research papers presented at the joint IV ASOCIO/XIX IISE Region 16 Conference held in Chia and Bogota, Colombia. The conference was organized by the Universidad de La Sabana’s Research Group on Logistics Systems, in partnership with Chapters #782 (Universidad de La Sabana), #712 (Universidad Sergio Arboleda) and #988 (Universidad de Los Andes) of the Institute of Industrial and Systems Engineers (IISE). The main emphasis of the book is on modelling and solving business-related problems in operations research, and on applying descriptive, predictive and prescriptive analytics and the management sciences to actual decision-making in organizations. Both theoretical developments and algorithm implementation are presented. A special focus is given to business problems arising in emerging economies, particularly in Latin America and the Caribbean. This book is addressed to academics, practitioners, postgraduate students and researchers in operations research, analytics and industrial engineering, as well as to undergraduate students for educational purposes. In particular, the book will appeal to the academic and research community in Latin America and the Caribbean, as it presents projects developed and implemented there. Higher education engineering programs will benefit from the findings and insights shared in the fields of industrial engineering, operations research and analytics, applied mathematics, and computer science and engineering.
Author: Eduardo Rodriguez Publisher: CRC Press ISBN: 1351673165 Category : Business & Economics Languages : en Pages : 349
Book Description
This book focuses on understanding the analytics knowledge management process and its comprehensive application to various socioeconomic sectors. Using cases from Latin America and other emerging economies, it examines analytics knowledge applications where a solution has been achieved. Written for business students and professionals as well as researchers, the book is filled with practical insight into applying concepts and implementing processes and solutions. The eleven case studies presented in the book incorporate the whole analytics process and are useful reference examples for applying the analytics process for SME organizations in both developing and developed economies. The cases also identify multiple tacit factors to deal with during the implementation of analytics knowledge management processes. These factors, which include data cleaning, data gathering, and interpretation of results, are not always easily identified by analytics practitioners. This book promotes the understanding of analytics methods and techniques. It guides readers through numerous techniques and methods available to analytics practitioners by explaining the strengths and weaknesses of these methods and techniques.
Author: Eduardo Rodriguez Publisher: CRC Press ISBN: 1351673173 Category : Business & Economics Languages : en Pages : 272
Book Description
This book focuses on understanding the analytics knowledge management process and its comprehensive application to various socioeconomic sectors. Using cases from Latin America and other emerging economies, it examines analytics knowledge applications where a solution has been achieved. Written for business students and professionals as well as researchers, the book is filled with practical insight into applying concepts and implementing processes and solutions. The eleven case studies presented in the book incorporate the whole analytics process and are useful reference examples for applying the analytics process for SME organizations in both developing and developed economies. The cases also identify multiple tacit factors to deal with during the implementation of analytics knowledge management processes. These factors, which include data cleaning, data gathering, and interpretation of results, are not always easily identified by analytics practitioners. This book promotes the understanding of analytics methods and techniques. It guides readers through numerous techniques and methods available to analytics practitioners by explaining the strengths and weaknesses of these methods and techniques.
Author: Amanda L. Golbeck Publisher: Springer Nature ISBN: 3030600602 Category : Business & Economics Languages : en Pages : 432
Book Description
This edited collection brings together voices of the strongest thought leaders on diversity, equity and inclusion in the field of statistics and data science, with the goal of encouraging and steering the profession into the regular practice of inclusive and humanistic leadership. It provides futuristic ideas for promoting opportunities for equitable leadership, as well as tested approaches that have already been found to make a difference. It speaks to the challenges and opportunities of leading successful research collaborations and making strong connections within research teams. Curated with a vision that leadership takes a myriad of forms, and that diversity has many dimensions, this volume examines the nuances of leadership within a workplace environment and promotes storytelling and other competencies as critical elements of effective leadership. It makes the case for inclusive and humanistic leadership in statistics and data science, where there often remains a dearth of women and members of certain racial communities among the employees. Titled and non-titled leaders will benefit from the planning, evaluation, and structural tools offered within to contribute inclusive excellence in workplace climate, environment, and culture.
Author: Decision Sciences Institute Publisher: FT Press ISBN: 0134073053 Category : Business & Economics Languages : en Pages : 454
Book Description
Today, business success depends on making great decisions – and making them fast. Leading organizations apply sophisticated business analytics tools and technologies to evaluate vast amounts of data, glean new insights, and increase both the speed and quality of decision making. In The Best Thinking and Practices in Business Analytics from the Decision Sciences Institute, DSI has compiled award-winning and award-nominated contributions from its most recent conferences: papers that illuminate exceptionally high-value applications and research on analytics for decision-making. These papers have appeared in no other DSI collection. Explore them here, and you’ll discover powerful new opportunities for competitive advantage through analytics. For all business, academic, and organizational professionals concerned with the science of more effective decision-making; and for undergraduate students, graduate students, and certification candidates in all related fields.
Author: Luiz Paulo Favero Publisher: Academic Press ISBN: 0323859232 Category : Computers Languages : en Pages : 662
Book Description
Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. Presents a comprehensive and practical overview of machine learning, data mining and AI techniques for a broad multidisciplinary audience Serves readers who are interested in statistics, analytics and modeling, and those who wish to deepen their knowledge in programming through the use of R Teaches readers how to apply machine learning techniques to a wide range of data and subject areas Presents data in a graphically appealing way, promoting greater information transparency and interactive learning
Author: Joseph A. Cazier Publisher: John Wiley & Sons ISBN: 1119800994 Category : Computers Languages : en Pages : 327
Book Description
A step-by-step guide for business leaders who need to manage successful big data projects Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data takes you through the entire process of guiding an analytics initiative from inception to execution. You’ll learn which aspects of the project to pay attention to, the right questions to ask, and how to keep the project team focused on its mission to produce relevant and valuable project. As an executive, you can’t control every aspect of the process. But if you focus on high-impact factors that you can control, you can ensure an effective outcome. This book describes those factors and offers practical insight on how to get them right. Drawn from best-practice research in the field of analytics, the Manageable Tasks described in this book are specific to the goal of implementing big data tools at an enterprise level. A dream team of analytics and business experts have contributed their knowledge to show you how to choose the right business problem to address, put together the right team, gather the right data, select the right tools, and execute your strategic plan to produce an actionable result. Become an analytics-savvy executive with this valuable book. Ensure the success of analytics initiatives, maximize ROI, and draw value from big data Learn to define success and failure in analytics and big data projects Set your organization up for analytics success by identifying problems that have big data solutions Bring together the people, the tools, and the strategies that are right for the job By learning to pay attention to critical tasks in every analytics project, non-technical executives and strategic planners can guide their organizations to measurable results.
Author: Vincent Charles Publisher: Springer Nature ISBN: 3030433846 Category : Business & Economics Languages : en Pages : 441
Book Description
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.
Author: Jairo R. Montoya-Torres
Author: Jairo R. Montoya-Torres
Author: 
Author: Eduardo Rodriguez
Author: M. Gulnara Baldoquín
Author: Eduardo Rodriguez
Author: Amanda L. Golbeck
Author: Decision Sciences Institute
Author: Luiz Paulo Favero
Author: Joseph A. Cazier
Author: Vincent Charles