Advanced Mathematical Methods For Economic Efficiency Analysis
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Advanced Mathematical Methods for Economic Efficiency Analysis
Economic efficiency analysis has received considerable worldwide attention in the last few decades, with Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) establishing themselves as the two dominant approaches in the literature. This book, by combining cutting-edge theoretical research on DEA and SFA with attractive real-world applications, offers a valuable asset for professors, students, researchers, and professionals working in all branches of economic efficiency analysis, as well as those concerned with the corresponding economic policies. The book is divided into three parts, the first of which is devoted to basic concepts, making the content self-contained. The second is devoted to DEA, and the third to SFA. The topics covered in Part 2 range from stochastic DEA to multidirectional dynamic inefficiency analysis, including directional distance functions, the elimination and choice translating algorithm, benefit-of-the-doubt composite indicators, and internal benchmarking for efficiency evaluations. Part 3 also includes exciting and cutting-edge theoretical research on e.g. robustness, nonparametric stochastic frontier models, hierarchical panel data models, and estimation methods like corrected ordinary least squares and maximum entropy.
Decision Mathematics, Statistical Learning and Data Mining
Author: Wan Fairos Wan Yaacob
language: en
Publisher: Springer Nature
Release Date: 2024-10-26
This book is a collection of selected research papers presented at the Mathematics, Statistics and Computing Technology (ICMSCT2023), held at the UST Angelicum College, Philippines, from 20th to 21st September 2023. This biennial event is a result from collaborations of university partners in Malaysia, Thailand, Indonesia and Philippines. Increasing investment in digital technologies is a challenge faced by most countries after the crisis caused by COVID-19 and the demand of technological revolution 4.0. Indirectly, regardless of their level of development, they take into account the importance of redesigning strategies for resilient and sustainable regional economic development, increasing regional resilience and minimizing recovery costs as a basis for development. In such situation, this book gather discussion, viewpoints and findings on the recent works of mathematical and computing technology applications in order to propose solutions to overcome adversity of digital resilience. This book covers a wide range of topics on applied mathematics, which includes decision mathematics and also applied statistics covering statistical learning with applications. In addition, the book also highlight the latest application of statistical mining and data visualization, particularly on data mining, machine learning and data visualization. Editors believe this book will interest and influence researchers on the recent techniques, methodologies and applications to ensure digital resilience and support future research.
Environmental Modeling for Sustainable Regional Development: System Approaches and Advanced Methods
Understanding the advancement of sustainable development is critical to managing human activities to avoid the overexploitation of resources and pollution of the environment beyond tolerable levels. Sustainable development involves not only preservation and care of the environment, but also recognition of the complex relations between economic, social and living systems. Environmental Modeling for Sustainable Regional Development: System Approaches and Advanced Methods presents processing methods and their applications, which are practical for decision making and task management at the regional level as well as for scientific studies in sustainable development assessment. This book serves as a reference guide for post-graduate students in the field of management as well as a critical guide for managers, government officials, and information professionals.