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On Vehicle Evaluation and Design Using Data Envelopment Analysis with Hierarchical Concepts

Part of: Design Management

Published online by Cambridge University Press:  26 July 2019

Victor Parque ,
Kazuhiro Honobe ,
Satoshi Miura  and
Tomoyuki Miyashita

Abstract

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In recent years, product complexity in terms of function and structure has been driven by technological development in complementary components. Designing unbiased product evaluation metrics being to grasp the complex relationships of product features, and able to capitalize on market needs has become a challenge in industrial practice.

In this paper, we propose a hybrid framework in which evaluation models are generated by integrating Interpretive Structural Modeling (ISM), Hierarchical Clustering and Data Envelopment Analysis (DEA). Whereas ISM constructs hierarchical digraphs (skeletons), Hierarchical Clustering reduces dimensionality of pairwise comparisons (correlations) of design variables, and suggests possible evaluation configurations, and DEA computes weights to provide optimal evaluation metrics. Our computational experiments using more than twenty thousand vehicles from 1982 to 2013 confirmed the feasibility and usefulness of DEA with hierarchical concepts to generate the optimal vehicle evaluation metric, and to suggest configurations for vehicle design layouts.

Keywords

Design informaticsNew product developmentConceptual design
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 1225 - 1234
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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