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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 21 | Page No.: 3792-3803
DOI: 10.3923/jas.2009.3792.3803
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Modified IPA for Order-Winner Criteria Improvement: A MICMAC Approach

Hsiu-Yuan Hu, Shao-I, Chiu and Tieh-Min Yen

The goal of the study is to establish a new decision analysis methodology from a systematic perspective, in order to help business build market strategies and make improvements that win more orders. The Importance-Performance Analysis (IPA) model has been extensively applied to the consumer satisfaction analysis. However, the conventional IPA model implied some key assumptions, that the quality characteristics are mutually independent variables; thus, it failed to analyze how the types of quality characteristics affect the whole system from a systematic point of view. Under that assumption, if the quality characteristics do correlate, the conventional IPA model could not accurately analyze the importance and priority of improvement and may lead to a wrong decision. We propose a new decision analysis methodology, the M-IPA model. By using Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) to calculate the correlation (influences) between quality characteristics, the model finds the core driving factor to the order-winner criteria and uses it to modify the importance of quality characteristics in the IPA model. We use a case study on the air conditioning technology industry to illustrate the applications and benefits of the M-IPA model. In this study, we get the conclusion that the MICMAC model failed to discuss the decision model for the market strategy of order-winner criteria. Thus, by integrating the MICMAC and IPA models, we establish a new decision analysis methodology and find out the core improvement items in an order-winner criteria system.
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How to cite this article:

Hsiu-Yuan Hu, Shao-I, Chiu and Tieh-Min Yen, 2009. Modified IPA for Order-Winner Criteria Improvement: A MICMAC Approach. Journal of Applied Sciences, 9: 3792-3803.

DOI: 10.3923/jas.2009.3792.3803






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