Decision Making Optimization Models for Business Partnerships

Regular price €132.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
Category=KCH
Category=KJMV5
Category=KJT
Category=PBT
Data Envelopment Analysis
Decision-Making Optimization Models
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
mergers and acquisitions efficiency
operations research
parametric and nonparametric optimization
parametric econometrics
partnership optimization in business
performance benchmarking
resource allocation models
strategic alliances analysis
sustainability assessment

Product details

  • ISBN 9781032382487
  • Weight: 850g
  • Dimensions: 156 x 234mm
  • Publication Date: 12 Jun 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

Efficiency and productivity improvement are imperative for businesses to remain competitive in an increasingly dynamic marketplace. While business organizations have the potential to thrive independently, collaborating with others fosters a collective strength that can lead to greater innovation, expanded reach, and shared success.

Decision making optimization models for business partnerships are essential, as businesses seldom have all the resources they need, and thus, they require alliances and partnerships with others to enable them to meet their goals. Decision Making Optimization Models for Business Partnerships extends non-parametric data envelopment analysis (DEA) and parametric econometrics approaches to better understand how economic efficiency and market competitiveness are achieved for different types of partnerships and strategic alliances.

Features

  • Global contributions for a wide range of professionals and academics
  • Invaluable resources for businesses, analysts, and academics interested in DEA, optimization, and operations research more widely
  • Introduces readers to novel approaches, models, and decision making techniques on performance evaluation and business partnerships via the medium of parametric and nonparametric optimization.

Gholam R. Amin is Associate Professor of Management Science in the Faculty of Business at the University of New Brunswick, Saint John, Canada. He is an associate editor of the IMA Journal of Management Mathematics at Oxford University Press. Dr. Amin’s research interests include performance measurement, productivity and efficiency analysis through data envelopment analysis, optimization, and inverse optimization approaches. Dr. Amin has published in several leading international journals including Operations Research (FT-50), European Journal of Operational Research, Journal of Productivity Analysis, Annals of Operations Research, International Journal of Production Research, Journal of the Operational Research Society, Computers and Operations Research, Computers & Industrial Engineering, Applied Mathematical Modeling, International Journal of Approximate Reasoning, International Journal of Intelligent Systems, ABACUS, Soft Computing, International Journal of Performance Analysis in Sport, Health Economics, Policy and Law, European Journal of Sport Science, Journal of Intelligent Manufacturing, International Journal of Computer Mathematics, and IMA Journal of Management Mathematics among others.

Mustapha Ibn Boamah is Professor of Economics in the Faculty of Business at the University of New Brunswick, Saint John, Canada. Dr. Ibn Boamah’s research interests include open-economy macroeconomics, monetary economics, international finance, and the economics of financial institutions. He has published in various peer-reviewed journals including publications in the Review of Financial Economics, Atlantic Economic Journal, Strategic Change, Social Responsibility Journal, International Journal of Organizational Analysis, International Journal of Social Economics, Managerial and Decision Economics, Annals of Operations Research, and the European Journal of Operational Research.