Assessment of the creative potential of design problems via novelty and usefulness

新颖性 计算机科学 相似性(几何) 创造力 新知识检测 人工智能 光学(聚焦) 工程设计过程 优先次序 设计方法 任务(项目管理) 分类 机器学习 管理科学 研究设计
作者
Sanjay Singh,Amaresh Chakrabarti
出处
期刊:Design science [Cambridge University Press]
卷期号:11 被引量:1
标识
DOI:10.1017/dsj.2025.10043
摘要

Abstract Current design theories and models predominantly focus on evaluating innovation through design solutions, using measures of novelty and usefulness as indicators of creativity. In contrast, the assessment of creative potential of design problems has attracted far less attention. To systematically explore the creative potential of design problems, a comprehensive literature review is conducted, revealing significant gaps where existing methods have yet to be applied. To address these gaps, first, an extensive database of design problems has been constructed using data collected from design patents, surveys, and questionnaires. Three distinct quantitative methods have been developed: the first for assessing novelty using SAPPhIRE model of causality, the second for assessing usefulness using usefulness indicators, and the third for assessing creative potential. The novelty method quantifies the minimum distance between a current problem and the old problems in the database, using textual similarity at different levels of SAPPhIRE abstraction. Expert evaluation of the novelty method indicates substantial agreement with experts’ intuitive notion, in addition to higher effectiveness compared to existing methods. The first two methods have then been integrated into the third method for assessing the overall creative potential of a design problem. Statistical analyses confirmed the correlation of both novelty and usefulness with creative potential, supporting findings in the literature. To demonstrate the methods, detailed case studies have been presented, illustrating the application of the methods. This systematic approach provides a robust framework for objective assessment of creativity in design problems, facilitating better prioritization and decision-making in engineering design contexts.
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