A Hybrid Fuzzy Analytic Network Process Approach to the New Product Development Selection Problem

New product development selection is a complex decision-making process. To uphold their competence in competitive business environments, enterprises are required to continuously introduce novel products into markets. This paper presents a fuzzy analytic network process (FANP) for solving the product development selection problem. The fuzzy set theory is adopted to represent ambiguities and vagueness involved in each expert's judgment. In the proposed model, the fuzzy Kano method and fuzzy DEMATEL are employed to filter criteria and establish interactions among the criteria, whereas the SAM is applied to aggregate experts' opinions. Unlike the commonly used top-down relation-structuring approach, the proposed FANP first identifies the interdependence among the criteria and then the identified relationships are mapped to the clusters. This approach is more realistic, since the inner and outer relationships between criteria are simultaneously considered to establish the relationships among clusters. The proposed model is illustrated through a real life example, with a comparative analysis using modified TOPSIS and gray relation analysis in the synthesizing phase. The concluded results were approved by the case company. The proposed methodology not only is useful in the case study, but also can be generally applied in other similar decision situations

Supplier and Producer Profit Sharing Models Based on Inspection Sampling Policy

International audience(Civ. 1re, 27 juin 2018, n° 17-15.039, inédit

A Multicriteria Selection Model for Developing New Color Calibration Device

Color Calibration Device is a key component for the performance of Medical Display Monitor (MDM). MDMs have been extensively used in hospitals in the past decades. The technological requirements of MDMs are higher than those of general purpose display monitors, but the gross profit margins of MDMS are larger as well. The purpose of this research is to build a hybrid multiple criteria decision making (MCDM) model useful in developing new color calibration device for the MDM industry. The proposed MCDM model uses fuzzy Kano method to filter the performance criteria, and then apply the analytic network process (ANP) in selecting the best alternative among three new products. In this study, gray relation analysis (GRA) is used to build a relations-structure for ANP criteria. The paper also presents a case study on model implementation in a LCD high-tech company. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.479

A Hybrid Fuzzy Analytic Network Process Approach to the New Product Development Selection Problem

New product development selection is a complex decision-making process. To uphold their competence in competitive business environments, enterprises are required to continuously introduce novel products into markets. This paper presents a fuzzy analytic network process (FANP) for solving the product development selection problem. The fuzzy set theory is adopted to represent ambiguities and vagueness involved in each expert’s judgment. In the proposed model, the fuzzy Kano method and fuzzy DEMATEL are employed to filter criteria and establish interactions among the criteria, whereas the SAM is applied to aggregate experts’ opinions. Unlike the commonly used top-down relation-structuring approach, the proposed FANP first identifies the interdependence among the criteria and then the identified relationships are mapped to the clusters. This approach is more realistic, since the inner and outer relationships between criteria are simultaneously considered to establish the relationships among clusters. The proposed model is illustrated through a real life example, with a comparative analysis using modified TOPSIS and gray relation analysis in the synthesizing phase. The concluded results were approved by the case company. The proposed methodology not only is useful in the case study, but also can be generally applied in other similar decision situations