A hybrid dynamic MADM model for problem-improvement in economics and business

Abstract

A typical multiple attribute decision making (MADM) model is a scientific analytical model for evaluating and improving a set of alternatives based on multiple criteria. However, this study identified some important new concepts and limitations/defects of traditional MADM for solving the real-world problems. First, the traditional MADM model assumes that criteria considered are independent and hierarchical in structure; however, the real-world problems often involve interdependent criteria, and thus interdependent models are required. Second, relatively good solutions from existing alternatives are replaced by the aspiration levels. Third, the trend has shifted from how to “rank” or “select” the most preferable alternatives, to how to “improve” their performances. Fourth, information fusion/aggregation, such as fuzzy integrals, basically, a non-additive/super-additive model, has been developed for performance aggregation. Therefore, to overcome the defects of the conventional MADM method and solve complex and dynamic real world problems, a Hybrid Dynamic Multiple Criteria Decision Making (HDMADM) method is needed. Finally, this study presented real cases to demonstrate the effectiveness of the HDMADM method for overcoming the defects of the conventional MADM method.

Keywords:

• MCDM (Multiple Criteria Decision Making)
• MADM (Multiple Attribute Decision Making)
• MODM (Multiple Objective Decision Making)
• DEMATEL (Decision Making Trial and Evaluation Laboratory)
• DANP (DEMATEL-based ANP)
• Fuzzy integral
• INRM (Influential Network Relationship Map)
• VIKOR
• aspiration level

JEL Classification:

• C00
• C02
• C18
• C54
• C61
• D70
• D78
• O20

Additional information

Notes on contributors

Kua-Hsin Peng

Kua-Hsin PENG received her PhD degree from the Department of Management Science of National Chiao Tung University, Taiwan in 2011. Currently, she is an Assistant Professor in the Department of Leisure and Recreation Management at Kainan University. She has published in numerous journals, including Tourism Management, Current Issues in Tourism, Journal of the Operational Research Society, Quality & Quantity, Expert Systems with Applications, Journal of Grey System, etc. Her research interest is applying hybrid MCDM method to solve some problems in tourism and leisure management, accreditation performance, etc.

Gwo-Hshiung Tzeng

Gwo-Hshiung TZENG. In 1967, he received the Bachelor's degree in Business Management from the Tatung Institute of Technology (now Tatung University), Taiwan; in 1971, he received the Master's degree in Urban Planning from Chung Hsing University (Now Taipei University), Taiwan; and in 1977, he received the PhD degree course in management science from Osaka University, Osaka, Japan. He was an Associate Professor at Chiao Tung University, Taiwan (1977–1981), a Research Associate at Argonne National Laboratory (July 1981–January 1982), a Visiting Professor in the Department of Civil Engineering at the University of Maryland, College Park (August 1989–August 1990), a Visiting Professor in the Department of Engineering and Economic System, Energy Modeling Forum at Stanford University (August 1997–August 1998), a Professor at Chaio Tung University (1981–2003), and a Chair Professor at Chiao Tung University. His current research interests include statistics, multivariate analysis, network, routing and scheduling, multiple criteria decision making, fuzzy theory, hierarchical structure analysis for applying to technology management, energy, environment, transportation systems, transportation investment, logistics, location, urban planning, tourism, technology management, electronic commerce, global supply chain, etc.