Comparative Study of AHP and ANP on Multi-Automotive Suppliers with Multi-Criteria
Agility in supply chain management for automotive industries is important in order to supply the customer requirements at right time and making the supply chain capable to compete with internal and external competitors. This study finds what the most agile automotive factory in supply chain is. Two...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/6084/ http://umpir.ump.edu.my/id/eprint/6084/1/IMECS_2014.pdf |
| Summary: | Agility in supply chain management for automotive industries is important in order to supply the customer requirements at right time and making the supply chain capable to compete with internal and external competitors. This study finds what the most agile automotive factory in supply chain is. Two approaches, namely, Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP) are applied to propose a framework for recognizing the most agile automotive factory in supply chain. In AHP, the criteria are considered independently but in ANP interdependencies between criteria are also considered. Five criteria, which are involved in this study, are: response to changes, flexibility, competency, economical optimization, and speed. The related sub-criteria are identified by industrial experts and Delphi method. Two models are elaborated using two AHP and ANP approaches considering four suppliers: A, B, C, D factories. Pairwise comparison matrixes are designed in questionnaires for determining the importance degree between criteria and sub-criteria based on Saaty scale (1-9). The validity of questionnaires is also confirmed by industrial experts using Cronbach’s alpha. Questionnaire asks from industrial engineers and production managers to express their opinions through pairwise comparison matrixes about criteria and sub-criteria. The geometrical mean is used to summarize the evaluations. The results of models are valid because the overall inconsistency of models are lower than 0.1 in all matrixes. Finally, regarding to the obtained ultimate weights, the suppliers are ranked. It is identified that factory A with ultimate weight of 50.4% in AHP and weight of 54.2% in ANP models has been selected as the most agile supplier. On the other hand, factory D with 7.2% in AHP and 7.1% in ANP has been recognized as the least agile supplier. |
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