Abstract

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target can be the achievement of the minimum overall cost for a given satisfaction level. Kano’s quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a non-linear relationship to satisfaction, rather power-function should be used. For the customers’ subjective evaluation these relationships are not deterministic and are uncertain. Also the cost function are uncertain, where the loss aversion of decision makers should be considered as well. This paper proposes a method for fuzzy extension of Kano’s model and presents numerical examples.

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