Data Envelopment Analysis With Stata
Download Data Envelopment Analysis With Stata PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Envelopment Analysis With Stata book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Data Envelopment Analysis Using Stata
This book presents the concept and practical implementation of assessing the managerial ability of a Decision-Making Unit (DMU) through Data Envelopment Analysis (DEA). Managerial ability data is derived from publicly available accounting information, and the DEA methodology is performed utilizing Stata software. Those with research interests in accounting, auditing, and finance can utilize DEA to assess managerial ability through the practical examples presented in this book. This book comprises seven chapters: (1) Introduction to Managerial Ability, (2) Literature Review on Managerial Ability, (3) Data Envelopment Analysis (DEA) as a Performance Evaluation Tool, (4) DEA Application Using Stata, (5) DEA Application for Assessing Managerial Ability Scores, (6) Research on the Association between Managerial Ability and Audit Quality, and (7) Conclusion. The book “Data Envelopment Analysis Using Stata: A Practical Approach on How Managerial Ability Affects Audit Partners’ Quality in Research” highlights research example employing real-world data from entities listed on the Indonesia Stock Exchange to demonstrate the application of managerial ability through DEA with Stata and its association with audit partner quality, contributing to the overall audit quality in the financial statements of listed firms. This book aims to provide readers with comprehensive insights and references concerning the concept of managerial ability and its application across various disciplines.
Data Envelopment Analysis
This handbook represents a milestone in the progression of Data Envelopment Analysis (DEA). Written by experts who are often major contributors to DEA theory, it includes a collection of chapters that represent the current state-of-the-art in DEA research. Topics include distance functions and their value duals, cross-efficiency measures in DEA, integer DEA, weight restrictions and production trade-offs, facet analysis in DEA, scale elasticity, benchmarking and context-dependent DEA, fuzzy DEA, non-homogenous units, partial input-output relations, super efficiency, treatment of undesirable measures, translation invariance, stochastic nonparametric envelopment of data, and global frontier index. Focusing only on new models/approaches of DEA, the book includes contributions from Juan Aparicio, Mette Asmild, Yao Chen, Wade D. Cook, Juan Du, Rolf Färe, Julie Harrison, Raha Imanirad, Andrew Johnson, Chiang Kao, Abolfazl Keshvari, Timo Kuosmanen, Sungmook Lim, Wenbin Liu, Dimitri Margaritis, Reza Kazemi Matin, Ole B. Olesen, Jesus T. Pastor, Niels Chr. Petersen, Victor V. Podinovski, Paul Rouse, Antti Saastamoinen, Biresh K. Sahoo, Kaoru Tone, and Zhongbao Zhou.
Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency
In today's highly competitive and rapidly evolving global landscape, the quest for efficiency has become a crucial factor in determining the success of organizations across various industries. Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency is a comprehensive guide that delves into the powerful mathematical tool of DEA, is designed to assess the relative efficiency of decision-making units (DMUs), and provides valuable insights for performance improvement. This book presents a systematic overview of DEA models and techniques, from fundamental concepts to advanced methods, showcasing their practical applications through real-world examples and case studies. Catering to a broad audience, this book is designed for students, researchers, consultants, decision-makers, and enthusiasts in the field of efficiency analysis and performance measurement. Consultants and practitioners will gain practical insights for applying DEA in various contexts, and decision-makers will be equipped to make informed decisions for maximizing efficiency. Additionally, individuals with a general interest in data analysis and performance measurement will find this book accessible and informative. This book covers a wide range of topics, including mathematical foundations of DEA, DEA models and variations, DEA efficiency and productivity measures, DEA applications in various industries such as healthcare, finance, supply chain management, environmental management, education management, and public sector management.