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Research on the weak demand signal identification model of innovative product based on domain ontology construction

计算机科学 本体论 新颖性 鉴定(生物学) 模棱两可 数据挖掘 产品(数学) 领域(数学分析) 质量(理念) 信号(编程语言) 人工智能 数学 数学分析 哲学 植物 几何学 神学 认识论 生物 程序设计语言
作者
Dongyuan Zhao,Zhongjun Tang,Fengxia Sun
出处
期刊:Kybernetes [Emerald (MCB UP)]
被引量:1
标识
DOI:10.1108/k-05-2023-0850
摘要

Purpose This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty. Design/methodology/approach To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research. Findings Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity. Originality/value This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

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