A Group Decision-Making Approach Based on DST and AHP for New Product Selection under Epistemic Uncertainty

Selecting the most appropriate new product(s) is regarded as a critical decision which greatly influences the development of manufacturing enterprises. In order to improve the accuracy of selection, more experts are required to be invited to predict key indicators for new products selection. Due to limited knowledge, experts use fuzzy numbers more confidently than using numerical values in the prediction. Therefore, new product selection is a multiattribute group decision-making process under epistemic uncertainty. The purpose of this paper is to introduce a new hybrid decision-making approach based on Analytic Hierarchy Process (AHP) and Dempster-Shafer Theory (DST) to evaluate and select a new product. AHP and DST are used in weight determination to improve the accuracy and objectivity. In addition, this paper proposes that DST is a proper mathematical framework to deal with the epistemic uncertainty on the indicators of new product scheme selection. In particular, the initial assessments from experts are disassembled and then combined into the evidence information. By setting confidence degree, reliability function and likelihood function are used to evaluate and rank new products. A case study in a home appliance manufacturer is provided to illustrate the proposed hybrid approach and demonstrate its applicability.