Applications of Management Science
1st Edition
Published on 11. September 2020
256 pages
978-1-83867-000-9 (ISBN)
Description
Applications of Management Science presents current studies in the application of management science to the solution of significant managerial decision-making problems. It significantly aids in the dissemination of the solution of managerial decision-making problems with management science methodologies.
With a focus on the application of management science methodologies data envelopment analysis and multi-criteria decision making, this volume is split into three sections:
1. Applications of optimization;
2. Data envelopment analysis and applications;
3. Data envelopment analysis.
To those involved in the applications of multi-criteria decision making, data envelopment analysis and decision making, in a realistic managerial problem solving environment through the use of state of the art management science modelling, this is a must-read.
With a focus on the application of management science methodologies data envelopment analysis and multi-criteria decision making, this volume is split into three sections:
1. Applications of optimization;
2. Data envelopment analysis and applications;
3. Data envelopment analysis.
To those involved in the applications of multi-criteria decision making, data envelopment analysis and decision making, in a realistic managerial problem solving environment through the use of state of the art management science modelling, this is a must-read.
More details
Series
Language
English
Place of publication
Bingley
United Kingdom
Target group
Professional and scholarly
File size
9,10 MB
ISBN-13
978-1-83867-000-9 (9781838670009)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Dr. Kenneth D. Lawrence is a Professor of Management Science and Business Analytics at the Tuchman School of Management at the New Jersey Institute of Technology. His research centers on forecasting, multi-criteria decision making, data development analysis and data mining.
Dr. Dinesh R. Pai is an Associate Professor of Supply Chain Management in the School of Business Administration, Penn State Harrisburg. His research interests are in the areas of supply chain management business analytics, and performance evaluation.
Dr. Dinesh R. Pai is an Associate Professor of Supply Chain Management in the School of Business Administration, Penn State Harrisburg. His research interests are in the areas of supply chain management business analytics, and performance evaluation.
Content
Chapter 1. Multi-objective Newsvendor Models with CVAR for Flowers Industry; Bartosz SawikChapter 2. Selected Multiple Criteria Supply Chain Optimization Problems; Bartosz Sawik
Chapter 3. Evaluating Consumer Loans Using Machine Learning Techniques; D. K. Malhotra, Kunal Malhotra and Rashmi Malhotra
Chapter 4. Use of Maximal Covering Location Problem to Design Closed Loop Supply Chain Network under Product Substitution; Murtadha Aldoukhi and Surrendra Gupta
Chapter 5. Territorial Branding as an Instrument for Competitiveness of Rural Development; Karachyna Nataliia, Vakar Tetiana, Moroz Yevheniia, Semtsov Volodymyr and Vitiuk Anna
Chapter 6. Developing Composite Indices for Assessing Vulnerability to Floods Due to Climate Change: Applying the Ordered Rated Effectiveness (ORE) Modeling Method; Ronald Klimberg and Samuel Ratick
Chapter 7. A Comparative Analysis of Public and Private Universities in the United States Using Data Envelopment Analysis Models; Rashmi Malhotra, D. K. Malholtra and Robert Nydick
Chapter 8. Productivity in the U.S. Consumer Drug Store Business; Kenneth D. Lawrence, Sheila M. Lawrence, Stephan P. Kudbya and Dinesh R. Pai
Chapter 9. Decision Making and Productivity Measurement; Dariush Khezrimotlagh
Chapter 10. How to Deal with the Number of Decision Making Units and Number of Variables in Multiple Input-Output Production Functions; Dariush Khezrimotlagh
Chapter 11. Evaluating Effective Performance Using Ordered Weighted Averaging (OWA) and Data Envelopment Analysis (DEA) Optimization; Ronald Klimberg and Samuel Ratick
Chapter 3. Evaluating Consumer Loans Using Machine Learning Techniques; D. K. Malhotra, Kunal Malhotra and Rashmi Malhotra
Chapter 4. Use of Maximal Covering Location Problem to Design Closed Loop Supply Chain Network under Product Substitution; Murtadha Aldoukhi and Surrendra Gupta
Chapter 5. Territorial Branding as an Instrument for Competitiveness of Rural Development; Karachyna Nataliia, Vakar Tetiana, Moroz Yevheniia, Semtsov Volodymyr and Vitiuk Anna
Chapter 6. Developing Composite Indices for Assessing Vulnerability to Floods Due to Climate Change: Applying the Ordered Rated Effectiveness (ORE) Modeling Method; Ronald Klimberg and Samuel Ratick
Chapter 7. A Comparative Analysis of Public and Private Universities in the United States Using Data Envelopment Analysis Models; Rashmi Malhotra, D. K. Malholtra and Robert Nydick
Chapter 8. Productivity in the U.S. Consumer Drug Store Business; Kenneth D. Lawrence, Sheila M. Lawrence, Stephan P. Kudbya and Dinesh R. Pai
Chapter 9. Decision Making and Productivity Measurement; Dariush Khezrimotlagh
Chapter 10. How to Deal with the Number of Decision Making Units and Number of Variables in Multiple Input-Output Production Functions; Dariush Khezrimotlagh
Chapter 11. Evaluating Effective Performance Using Ordered Weighted Averaging (OWA) and Data Envelopment Analysis (DEA) Optimization; Ronald Klimberg and Samuel Ratick
