A fuzzy Kano model proposal for sustainable product design: Mobile application feature analysis

IF 6.6 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Applied Soft Computing Pub Date : 2025-03-01 Epub Date: 2025-02-04 DOI:10.1016/j.asoc.2025.112824
Necip Fazıl Karakurt , Selcuk Cebi
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Abstract

Companies aim to maximize profits by effectively designing mobile applications to promote their services in a competitive market. However, identifying the design features that significantly impact mobile applications is challenging due to their subjective nature. Traditional Kano approaches face limitations, such as information loss caused by considering only the most frequent values. To address these limitations, this study proposes a novel fuzzy Kano approach to better manage the subjectivity in human judgments and the uncertainty in user preferences. This approach uncovers hidden preference levels, accounts for uncertainties, resolves dual classification issues, compares membership degrees, and emphasizes subtle details that may otherwise be overlooked. The fuzzy Kano approach was applied to survey data from 100 participants, covering 33 mobile application features. By classifying these features, the fuzzy Kano model examined their influence on user satisfaction and quality perception. The results demonstrated the feasibility and effectiveness of the proposed method, identifying key features—such as Product Details, Order Management and Returns, and Product Opinions and Reviews—that, if absent, could lead to customer dissatisfaction. Additionally, the findings revealed significant differences between the fuzzy and traditional Kano models and highlighted variations in mobile application characteristics across different demographic groups, providing valuable insights for mobile application design.
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可持续产品设计的模糊Kano模型建议:移动应用程序特征分析
公司的目标是通过有效地设计移动应用程序,在竞争激烈的市场中推广他们的服务,从而实现利润最大化。然而,由于其主观性,确定对移动应用产生重大影响的设计功能是具有挑战性的。传统的Kano方法面临局限性,例如只考虑最频繁的值而导致的信息丢失。为了解决这些限制,本研究提出了一种新的模糊Kano方法,以更好地管理人类判断中的主观性和用户偏好的不确定性。这种方法揭示了隐藏的偏好级别,解释了不确定性,解决了双重分类问题,比较了成员度,并强调了可能被忽视的微妙细节。模糊卡诺方法应用于100名参与者的调查数据,涵盖33个移动应用程序功能。通过对这些特征进行分类,模糊Kano模型检验了它们对用户满意度和质量感知的影响。结果证明了所提出方法的可行性和有效性,确定了关键特征,如产品详细信息、订单管理和退货、产品意见和评论,如果没有这些特征,可能会导致客户不满。此外,研究结果揭示了模糊和传统Kano模型之间的显著差异,并强调了不同人口群体中移动应用特征的变化,为移动应用设计提供了有价值的见解。
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来源期刊
Applied Soft Computing
Applied Soft Computing 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
6.90%
发文量
874
审稿时长
10.9 months
期刊介绍: Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.
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