Abstract
Product evaluation practices spread throughout from initial creative stages to final products before communicating them to the market. They emphasize on assessing design alternatives against specified criteria, which can help promote design process, ensure design quality, and diminish design risk before making a decision. However, how to identify and improve the reliability of product evaluation opinions toward design alternatives has an important role in adding additional insurance and reducing uncertainty to successful product design. Aiming at this issue, this study employs a consensus model by integrating network analysis and analytic hierarchy process (AHP) method. The consensus model is constructed to measure the consistency of evaluators’ preferences and determine the rounds of evaluation. Complex network theory is integrated into the product evaluation process for network analysis of evaluators’ opinions, which can help determine evaluators’ weights in each evaluation round dynamically by changing the network topology. To obtain the weight of product evaluation indices, the AHP method is applied to avoid subjectivity given by evaluators. The process of the proposed method is presented, and the details are illustrated using a product evaluation example. The case study demonstrates that the proposed method is promising for improving the consensus level of evaluators’ opinions, reducing the influence of subjectivity, and finally improving the quality of design decision‐making.
Highlights
As the international market globalizing at high speed, enterprises have been facing a fierce competition and are propelled to concentrate on product innovation to maintain a competitive advantage
When dealing with consensus issues in product evaluation process, it often involves limited sets of design solutions, evaluators, and indices. As evaluators give their judgment about design alternatives against specified criteria, it is essential to determine the weight of each evaluator and criteria. e two factors will determine the consensus and the final decision outcomes, which should be calculated objectively rather than subjective assignment
Aiming to improve the opinion consistency among product design evaluators, ensure design quality, and reduce the risk of failure in product development, a consensus model is constructed by integrating network analysis and analytic hierarchy process (AHP) method. e network analysis method is introduced from the perspective of opinion dynamics [25], which applies complex network theory to treat each evaluator in the product evaluation process as a node and provides cohesion analysis according to the judgment given by evaluators about product alternatives. e interrelationship among nodes will change with the network evolving, which indicates that evaluators’ opinions will become aggregated to consistency or split
Summary
As the international market globalizing at high speed, enterprises have been facing a fierce competition and are propelled to concentrate on product innovation to maintain a competitive advantage. An effective path for product evaluation that can help promote the success of final design concept is to form a design decision-making group to collect their opinions, which usually contains consumers, industrial designers, engineering designers, and marketers. When dealing with consensus issues in product evaluation process, it often involves limited sets of design solutions, evaluators, and indices As evaluators give their judgment about design alternatives against specified criteria, it is essential to determine the weight of each evaluator and criteria. Aiming to improve the opinion consistency among product design evaluators, ensure design quality, and reduce the risk of failure in product development, a consensus model is constructed by integrating network analysis and analytic hierarchy process (AHP) method. Rough multistage network analysis, evaluators’ opinions can be aggregated considering their importance, can reduce the influence of subjectivity, and can improve the quality of design decision-making.
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