Multi-Attribute Decision Making
Ahmad Jafarnejad Chaghoshi; seyed mahdi rouhani poor; hannan Amoozad Mahdiraji; Mohammad Ehsanifar
Abstract
Purpose: product quality includes three variables: design, conformance and use. Measuring the quality of products with respect to all three quality variables is one of the important challenges of the country. Therefore, the present study was an attempt to figure out how quality factors are related to ...
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Purpose: product quality includes three variables: design, conformance and use. Measuring the quality of products with respect to all three quality variables is one of the important challenges of the country. Therefore, the present study was an attempt to figure out how quality factors are related to each other and to determine the relative weight of these factors and to provide a product quality measurement model using hesitant fuzzy linguistic terms.
Methodology: The present study falls into the category of applied studies in terms of objective and can be recognized as a quantitative study in terms of methodology. The population of the study incorporates academic experts and university-industry experts. Sample size (n=10) was determined using the purposeful and snowball sampling method. Due to the uncertainty of experts' in determining the mutual impact of product quality factors, the DEMATEL technique was combined with hesitant fuzzy logic, the resulting technique was then integrated with the network analysis process (DANP), and the final model was extracted. Thanks to this procedure, the present study can be deemed innovative.
Findings: The cause and effect relationships between the main factors of product quality were identified and extracted using DEMATEL technique. Then, taking into account the intensity of the mutual impact of quality factors on each other and using the DNAP technique, the product quality factors were ranked in three dimensions: design quality, conformance and use. According to the findings, management factors and resources (employees-infrastructure-environment) were identified as causal factors that affect other factors. On the other hand, the DANP output showed that "design quality" is the most important factor in product quality. so, with the relative weights of the factors, the product quality measurement model was obtained.
Originality/ value: Researchers and industrial managers at the national level will be able to identify the relationship between quality factors and use this model to measure product quality or the quality rate of goods according to relative weight of each factor.