James J.H. Liou

Comments on “Multiple criteria decision making (MCDM) methods in economics: an overview”

Abstract This paper offers comments on a previously published paper, titled “Multiple criteria decision making (MCDM) methods in economics: an overview,” by Zavadskas and Turskis (2011). The papers authors made great efforts to summarize MCDM methods but may have failed to consider several important new concepts and trends in the MCDM field for solving actual problems. First, the traditional model assumes the criteria are independently and hierarchically structured; however, in reality, problems are often characterized by interdependent criteria and dimensions and may even exhibit feedback-like effects. Second, relatively good solutions from the existing alternatives are replaced by aspiration levels to fit todays competitive markets. Third, the emphasis in the field has shifted from ranking and selection when determining the most preferable approaches to performance improvement of existing methods. Fourth, information fusion techniques, including the fuzzy integral method, have been developed to aggreg...

Developing a hybrid multi-criteria model for selection of outsourcing providers

Outsourcing is a good strategy for firms that need to reduce operating costs and improve competitiveness, but it remains important for firms to scientifically select the appropriate outsourcing providers. Some efforts have been made regarding outsourcing problems, but these efforts incorrectly assumed that the criteria in the decision process are independent, which is not true in the real world. In this paper, we propose a new hybrid multiple criteria decision-making (MCDM) model, which addresses the dependent relationships among criteria with the aid of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to build a relations-structure among criteria. The Analytical Network Process (ANP) is used to determine the relative weights of each criterion with dependence and feedback. The VIKOR method (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning Multi-criteria Optimization and Compromise Solution) is then used to prioritize the alternatives. The proposed model can help practitioners improve their decision process, especially when criteria are numerous and inter-related. Throughout our study, we use data from a Taiwanese airline to demonstrate this method.

A Dominance-based Rough Set Approach to customer behavior in the airline market

Market segmentation is a crucial activity in the present business environment. Data mining is a useful tool for identifying customer behavior patterns in large amounts of data. This information can then be used to help with decision-making in areas such as the airline market. In this study, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining customer attitudes and loyalties, which can help managers develop strategies to acquire new customers and retain highly valued ones. A set of rules is derived from a large sample of international airline customers, and its predictive ability is evaluated. The results, as compared with those of multiple discriminate analyses, are very encouraging. They prove the usefulness of the proposed method in predicting the behavior of airline customers. This study demonstrates that the DRSA model helps to identify customers, determine their characteristics, and facilitate the development of a marketing strategy.

New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management

Greening the supply chain is an increasingly important concern for many business enterprises and a challenge for logistics management. Critical functions within green supply chain management are internal improvements and selection of green suppliers. This study proposes a novel, hybrid model that addresses dependent relationships between various criteria and the vague information coming from decision-makers. The Decision-making Trial and Evaluation Laboratory (DEMATEL) technique structures the relationships among criteria, thereby constructing an influential network relationship map (INRM). Meanwhile the DEMATEL-based, analytical network process (ANP) method aids in obtaining influential weights of the criteria. Decision-makers may hold diverse opinions and preferences due to incomplete information, differences in knowledge or simply conflicts that are inherent between various departments. This can make it difficult to judge the performance of alternatives. One remedy is to apply a modified COmplex PRoportional ASsessment of alternatives with Grey relations. Next, this is applied to improve each criterion for integration of the performance values obtained in closing the aspiration level from different expert opinions based on INRM. An empirical example using data from a Taiwanese electronics company is provided to demonstrate our proposed method. The results can provide firms with a knowledge-based understanding of the source of some problems, thus reducing the performance gaps and closing the aspiration levels. Finally, there is a discussion on certain managerial implications.

Using a multiple-GA method to solve the batch picking problem: considering travel distance and order due time

Warehousing involves all activities related to the movement of goods such as receiving, storage, order picking, accumulation, sorting and shipping within warehouses or distribution centres. Among these activities, order picking is the most costly process because its operations are labour-intensive and repetitive. In this paper, we propose a batch picking model that considers not only travel cost but also an earliness and tardiness penalty to fulfil the current complex and quick-response oriented environment. This model is solved using a multiple-GA method for generating optimal batch picking plans. The core of the multiple-GA method consists of the GA_BATCH and GA_TSP algorithms. The GA_BATCH algorithm finds the optimal batch picking plan by minimizing the sum of the travel cost and earliness and tardiness penalty. The GA_TSP algorithm searches for the most effective travel path for a batch by minimizing the travel distance. To exhibit the benefits of the proposed model a set of simulations and a sensitivity analysis are conducted using a number of datasets with different order characteristics and warehouse environments. The results from these experiments show that the proposed method outperforms benchmark models.

A fuzzy integral-based model for supplier evaluation and improvement

Decisions related to supplier improvement and selection are inherently multiple criteria decision making (MCDM) problems and are strategically important to companies. Although efforts have been made to discover systematic methods to select the proper supplier, these efforts have assumed that the criteria are independent, which is not actually the case. Some studies that have treated the criteria as interdependent use additive models to obtain aggregate performance. We propose a novel fuzzy integral-based model that addresses the interdependence among the various criteria and employs the non-additive gap-weighted analysis. The structure of the relationships among the criteria and the criteria weights are developed using Decision Making Trial and Evaluation Laboratory (DEMATEL) combined with a fundamental concept of an analytic network process (ANP) called DANP. The fuzzy integral is then used to aggregate the gaps using the weights obtained from the DANP. The proposed model addresses the shortcomings of prior models and provides a more reasonable representation of the real world. The method is demonstrated using supplier evaluation and improvement data from a Taiwanese company.

Integrating DANP and modified grey relation theory for the selection of an outsourcing provider

Highlights? This study proposes a novel hybrid model to select an outsourcing provider. ? We combine DANP and grey relation methods and fix some previous drawbacks. ? The model addresses dependent relationships between the various criteria. ? The model could apply to general service industries. Globalization has inevitably forced firms to pursue outsourcing as a strategy to reduce operating costs and improve their competitiveness in the global marketplace. However, a successful outsourcing activity depends on the selection of the appropriate provider. Unlike previous multiple criteria decision-making (MCDM) methods that assume the criteria are independent, we propose a novel hybrid model, combining a Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) method called DANP, which addresses the dependent relationships between the various criteria to better reflect the real-world situation. At the same time, instead of ranking the alternatives, we apply a modified grey relation method to select and improve the criterion-gaps to the aspiration levels. To demonstrate the usefulness and effectiveness of the proposed model, we use data from a Taiwanese company.

A hybrid ANP model in fuzzy environments for strategic alliance partner selection in the airline industry

Strategic airline alliances are an increasingly common strategy for enhancing airline competitiveness and satisfying customer needs, especially in an era characterized by blurring industry boundaries, fast-changing technologies, and global integration. Airlines have been very active in utilizing this form of strategic development. However, the selection of a suitable partner for a strategic alliance is not an easy decision, involving a host of complex considerations by different departments. Furthermore the decision-makers may hold diverse opinions and preferences arising due to incomplete information and knowledge or inherent conflict between various departments. In this study fuzzy preference programming and the analytic network process (ANP) are combined to form a model for the selection of partners for strategic alliances. The effects of uncertainty and disagreement between decision-makers as well as the interdependency and feedback that arise from the use of different criteria and alternatives are also addressed. This generic model can be easily extended to fulfill the specific needs of a variety of companies.

Using decision rules to achieve mass customization of airline services

This paper uses the Dominance-based Rough Set Approach (DRSA) to formulate airline service strategies by generating decision rules that model passenger preference for airline service quality. DRSA could help airlines eliminate some services associated with dispensable attributes without affecting passenger perception of service quality. DRSA could also help airlines achieve mass customization of airline services and generate additional revenues by active or passive targeting of quality services to passengers.

New concepts and trends of MCDM for tomorrow – in honor of Professor Gwo-Hshiung Tzeng on the occasion of his 70th birthday

Abstract This article introduces several new concepts and trends in multiple criteria decision making (MCDM) for solving actual problems, as proposed by Professor Gwo-Hshiung Tzeng. These new concepts are as follows: (1) interdependency in real-world problems; (2) replacing the relative good solution from the existing alternatives using aspiration levels; (3) shifting from ranking and selection to performance improvement; (4) information fusion/aggregation; and (5) changeable decision spaces. To honor Prof. Tzengs contribution in the MCDM field and to commemorate his 70th birthday, this article also highlights his research career in MCDM and some publication list in the past 10 years.