<link rel="stylesheet" href="styles.cf390c6bfbe7555f.css">

學術出版;;Publications

Permanent URI for this communityhdl:11536/1

收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

Browse

Filters

2015 - 20183

Settings

🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Wang, Chih-HsuanSubject: search.filters.subject.Kansei engineering

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item type:Item,
    Combining rough set theory with fuzzy cognitive pairwise rating to construct a novel framework for developing multi-functional tablets
    (2018-01-01)
    Wang, Chih-Hsuan
    ;
    工業工程與管理學系
    ;
    Department of Industrial Engineering and Management
    To survive in a fiercely competitive market, global companies must effectively capture user requirements, perceptions, and preferences and efficiently convert them into attractive product design and development. Compared to functional or technical features, affective or ergonomic features can exert more influence on satisfying diverse consumers and accommodating a product to a wide range of usage. In practice, a quantitative approach to transform vague user perceptions of affective features into innovative products is necessary. In this study, a novel framework is proposed to help practitioners achieve the following goals. Initially, Kansei engineering (KE) is integrated with the theory of inventive problem solving (TRIZ) to accomplish systematic innovation. Secondly, to accomplish product planning, rough set theory (RST) is used to derive decision rules that can relate user perceptions to demographic variables (i.e. age, gender, and occupation). Finally, to accomplish product recommendation, fuzzy cognitive pairwise rating (FCPR) is applied to quantify user preference. In summary, the presented framework is effective to construct a product platform for developing innovative tablets and efficient to derive insightful decision rules for targeting the ad-hoc user groups.
  • Thumbnail Image
    Item type:Item,
    Integrating affective features with engineering features to seek the optimal product varieties with respect to the niche segments
    (2017-08-01)
    Wang, Chih-Hsuan
    ;
    Chin, Hsin-Tze
    ;
    工業工程與管理學系
    ;
    Department of Industrial Engineering and Management
    In recent years, the popularity of smart phones substantially leads to poor sales of the low-end digital cameras. One of the most astounding industry news is Kodak's bankruptcy in 2011 although Kodak was a pioneer in the field of digital still cameras. In reality, not only functional capability but also affective design can influence user purchase intentions on consumer electronics. In this paper, both affective features (AFs), and engineering features (EFs) are considered to achieve successful product planning. In particular, two critical issues are addressed: (1) market partitioning and (2) product differentiation. Initially, Kansei engineering is employed to capture user attitude toward AFs. Then, a classification tree is constructed to carry out effective market partitioning. Secondly, correspondence analysis is applied to capture user perceptions of EFs for identifying the core features that best characterize distinct market segments. Finally, VIKOR (VIseICriterijumska Optimizacija I Kompromisno Resenje) ranldng is conducted to prioritize various product portfolios to accomplish product differentiation. In summary, the presented framework can help industrial practitioners transform diverse customer requirements into attractive alternatives while keep controllable manufacturing costs. (C) 2016 Elsevier Ltd. All rights reserved.
  • Thumbnail Image
    Item type:Item,
    Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras
    (2015-04-18)
    Wang, Chih-Hsuan
    ;
    工業工程與管理學系
    ;
    Department of Industrial Engineering and Management
    Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).