A hybrid consumer‐oriented model for product affective design: An aspect of visual ergonomics

Crucial issues for product designers include how to capture consumers’ attention, evoke their pleasurable preferences, and affect their purchase decisions. In this article, we focus on consumers’ affective preferences in relation to visual ergonomics to propose a new hybrid consumer‐oriented model using gray relational analysis (GRA), gray prediction (GP), and the technique for order preference by similarity to ideal solution (TOPSIS). The GRA is used to identify the most influential elements of the product form to help product designers focus their attention more on these elements without compromising the predictive performance. The GP is used in conjunction with the GRA to obtain a better structure for the hybrid consumer‐oriented model, and TOPSIS is performed to determine the optimal alternatives for best matching consumers’ affective preferences. These experimental results show that the new hybrid consumer‐oriented model incorporated with the CAD/CAM system can facilitate the product affective design process.     

Application of Evolutionary Neural Networks on Optimization Design of Mobile Phone Based on User's Emotional Needs

Taking users’ emotional needs into consideration, this research aims to propose a new method to present product design features exactly and completely. On the basis of genetic algorithm integrated with back‐propagation (BP) neural networks, taking the mobile phone as research object, an optimization design algorithm was finally designed. First, the continuous and discrete design variables that describe mobile phones were screened with methods of dimensions, coordinate label, and morphological analysis. Forty three‐dimensional (3D) mobile phone models were designed by using 3D design software PROE. Accordingly, 12 representative mobile phones were selected through multidimensional scaling analysis and cluster analysis. Fourteen pairwise Kansei image words were obtained by collecting, screening, surveys, and statistical analysis method. Second, a BP neural networks model between design variables and user preference along with Kansei image words was established and verified with questionnaire survey data. Finally, the optimization design model for mobile phones was established considering design requirements and users’ emotional needs. A genetic algorithm integrated with BP neural networks was used to optimize mobile phone design. The results show that the optimization scheme is superior to others, and this paper will provide design suggestion for mobile phone designers.     

产品形态多意象蛛网灰靶决策模型

针对概念设计中多意象设计方案决策困难的现象,提出了一种产品形态多意象蛛网灰靶决策方法。首先,运用感性工学相关方法获取设计主体的认知数据,结合熵权法及博弈论思想构建基于设计主体认知数据的综合评价模型,并根据各意象的设计主体综合评价数据确定各意象的权重关系;其次,通过人工选择的方式从产品形态进化系统中选择多个进化方案,运用蛛网图表征各进化方案的意象关系,构建多意象蛛网灰靶决策模型,计算决策系数,对其进行比较排序,得到符合设计主体认知的相对最优方案;最后,应用灰色关联分析法验证该决策模型的可行性。结果表明,该模型能够帮助设计师在设计决策阶段快速、准确地确定符合多设计主体认知的多意象方案,为产品方案的多意象决策提供了新的理论和方法。     

Identifying mobile phone design features critical to user satisfaction

A variety of mobile phones are available to consumers. They differ from each other in many design features including shape, color, size, and material. This study attempts to identify some of the design features of a mobile phone critical to user satisfaction. Empirical models linking design features to satisfaction levels were developed and used to identify critical design features. Design properties common to “desirable” and “undesirable” phones were then extracted by comparing the values of the critical design features. The approach used in this study may help the product designers identify critical design features with their desirable properties in a systematic manner. © 2004 Wiley Periodicals, Inc. Hum Factors Man 14: 15–29, 2004.     

The underlying factors dominating categorical perception of product form of mobile phones

The purpose of this study was to explore the mechanisms that dominate the users' mental models for product form classification. A think aloud hierarchical grouping test and a semantic differential experiment were conducted to analyze the way subjects classified the real product samples of mobile phones. From the database of similarity and image test as well as the morphological analysis of product form, cluster analyses were used to analyze the procedure of product form classification and the effects of total images and local form features on product form classification. The result of cluster analyses indicated that local features were the dominant mechanisms that the study subjects used for the classification of a large number of similar products. Moreover, results of the think aloud task demonstrated that in the process of product form classification, subjects would first employ local features and later total images step by step in the hierarchical grouping task. The mental models the participants employed in processing product form classification confirmed the cognitive models preliminarily proposed by other scholars. An overlapping phenomenon could be found in the classification based on image perceptions and similarity data. At early stages, product form classification was mainly dominated by local features, and at later stages, total images would gradually take over the dominance position. These two processing models interacted with each other during the classification procedure. The classification based upon the real product samples in clustering schedule and distribution can help explore the effects of varying form factors on people's visual perceptions. Designers can subtly take the dominant form features under control so as to work out new products that stand out among competitors.

Relevance to industry

The exploration of the mental model the users apply in product form classification can help clarify the roles total images and local features play in specific visual perceptions, which can further offer hints to designers in new product design and development. The creative manipulation of specific images and form features will add emergent attraction to new product form. This not only reduces the risk in new product design and development but also helps guarantee that the new product draws user's attention in the market.     

基于灰色层次分析法的老年人APP 用户体验评价研究

为了提高老年人APP 的用户体验水平,提出一种基于灰色层次分析法(AHP)的老 年人APP 用户体验评价模型。首先,构建用户体验的评价体系;接着,通过AHP 计算评价指 标的权重;最后,采用灰色关联分析法(GRA)将用户体验的评价指标整合为灰色关联度,从而 根据灰色关联度选择最优方案。以移动医疗APP 作为案例,结果表明基于灰色AHP 的APP 用 户体验评价模型可以有效地评价老年人APP 的用户体验水平,为设计决策提供依据。     

Development of a web-based survey system for evaluating affective satisfaction

The concept of affective satisfaction is used to measure subjective feelings or impressions toward a product and to provide designers with knowledge about how well users are affectively satisfied. Numerous studies of affective satisfaction toward mobile devices have been conducted in laboratory environments. However, evaluating affective satisfaction whenever a new product is designed can be expensive. Therefore, this study proposes a method to develop a web-based survey system for evaluating affective satisfaction. A case study evaluating the affective satisfaction of thirty mobile phones was conducted by more than three hundred participants. The multiple linear regression technique was applied to build the relationship models between affective satisfaction and design features of the mobile phones. The proposed method can be used for a guideline to evaluate the affective satisfaction over the internet. Moreover, designers can use this method in product families other than mobile phones.

Relevance to industry

The results of this study can be used to evaluate affective satisfaction of consumer electronic products efficiently. Moreover, designers can get feedback on their prototypes of products through analyzing the evaluation results.     

The use of the Taguchi method with grey relational analysis and a neural network to optimize a novel GMA welding process

The objective of this paper is to present an integrated approach using the Taguchi method (TM), grey relational analysis (GRA) and a neural network (NN) to optimize the weld bead geometry in a novel gas metal arc (GMA) welding process. The TM is first used to construct a database for the NN. The GRA is adopted to solve the problem of multiple performance characteristics in a GMA welding process using activating flux. The grey relational grade obtained from the GRA is used as the output of the back-propagation (BP) NN. Then, a NN with the Levenberg-Marquardt BP (LMBP) algorithm is used to provide the nonlinear relationship between welding parameters and grey relational grade of each weldment. The optimal parameters of the novel GMA welding process were determined by simulating parameters using a well-trained BPNN model. Experimental results illustrate the proposed approach.     

灰关联分析在产品感性设计中的应用研究

本文以青年男性眼镜为例进行灰关联分析在产品感性设计中的应用研究实验,通过灰关联分析模型分析设计元素与消费者感性评价数据之间的关系,提取对于时尚男性眼镜设计最具影响力的三个设计元素。通过实验表明,灰关联分析模型可以帮助设计师在进行感性设计时更加快速和准确地把握产品的设计要点,提高产品设计的时效性。     

基于色彩案例和灰度关联分析的产品配色设计方法

为有效辅助工业设计师进行产品配色设计,提出基于色彩案例和灰度关联分析的 产品配色设计方法。从目标意象出发,通过分析并筛选产品配色样本,研究色彩合并、取舍和 色彩案例表示方法,基于对目标产品赋色区域划分实现色彩案例向目标产品配色映射,引入灰 度关联分析方法评价映射后的色彩方案与案例色彩的关联性。以剪式升降机的配色设计为例, 验证了该方法能够有效实现案例色彩向目标产品配色转换,生成用户满意方案。     

Prototypes in pervasive computing

In product design, prototypes - approximations of a product along some dimensions - are the essential medium for information, interaction, integration, and collaboration. Information appliances such as mobile phones, digital cameras, and music players are a growing area of ubiquitous computing. Designers currently create two separate sets of prototypes: "looks-like" prototypes that show only the device's form (the atoms) and "works-like" prototypes that use a computer display to demonstrate the interaction (the bits). Because of the required skill and time investment, designers don't build comprehensive prototypes that join form and function until late in development.     

多目标驱动的产品形态基因网络模型研究

为解决产品设计过程中用户需求的主观性、模糊性问题,进一步提高产品意象传 达的准确度,提出一种多目标驱动的产品形态基因网络模型(M-FGN)构建方法。以品牌形象、 用户偏好、社会情境为驱动目标,构建多目标驱动空间;分析产品形态基因节点与边的设计, 以产品形态基因为节点,以节点之间的相关性为边,构建 M-FGN 网络;对网络进行拓扑分析, 析出隐性设计知识辅助设计师进行产品形态设计。以某国有企业 AGV 小车形态设计为例,通 过分析 AGV 小车侧面形态 M-FGN 网络,将析出知识提供给设计师进行针对性形态方案设计, 对子代方案进行对比评价,验证了 M-FGN 网络模型的有效性。     

Product design enhancement using apparent usability and affective quality

In this study, apparent usability and affective quality were integrated in a design framework called the Usability Perception and Emotion Enhancement Model (UPEEM). The UPEEM was validated using structural equation modeling (SEM). The methodology consists of four phases namely product selection, attribute identification, design alternative generation, and design alternative evaluation. The first stage involved the selection of a product that highly involves the consumer. In the attribute identification stage, design elements of the product were identified. The possible values of these elements were also determined for use in the experimentation process. Design of experiments was used to identify how the attributes will be varied in the design alternative stage and which of the attributes significantly contribute to affective quality, apparent usability, and desirability in the design evaluation stage. Results suggest that product attributes related to form are relevant in eliciting intense affect and perception of usability in mobile phones especially those directly related to functionality and aesthetics. This study considered only four product attributes among so many due to the constraints of the research design employed. Attributes related to aesthetic perception of a product enhance apparent usability such as those related to dimensional ratios.     

Classification model for product form design using fuzzy support vector machines

Consumer preferences regarding product design are often affected by a large variety of form features. Traditionally, the quality of product form design depended heavily on designers’ intuitions and did not always prove to be successful in the marketplace. In this study, to help product designers develop appealing products in a more effective manner, an approach based on fuzzy support vector machines (fuzzy SVM) is proposed. This constructs a classification model of product form design based on consumer preferences. The one-versus-one (OVO) method is adopted to handle a multiclass problem by breaking it into various two-class problems. Product samples were collected and their form features were systematically examined. To formulate a classification problem, each product sample was assigned a class label and a fuzzy membership that corresponded to this label. The OVO fuzzy SVM model was constructed using collected product samples. The optimal training parameter set for the model was determined by a two-step cross-validation. A case study of mobile phone design is given to demonstrate the effectiveness of the proposed methodology. The performance of fuzzy SVM is also compared with SVM. The results of the experiment show that fuzzy SVM performed better than SVM.     

D-Checklist:一种老年人手机设计方法

老年人的数量和比例不断增加,设计适合老年人使用的手机以提高老年人的生活质量、改善老年人的生活状态具有重要的社会意义和经济意义。通过对使用上下文,即老年人用户的特点、老年人使用手机的特点及现有手机制造和软件设计技术的分析,找出影响老年人手机可用性的六个核心要素,针对每个要素提出相对应的设计要点,并以此为基础提出一种新的老年人手机设计方法:D-Checklist法。通过评估说明此方法可以有效提高所开发的老年人手机的可用性。     

支持进化的计算机辅助设计环境

介绍一个支持进化的计算机辅助设计环境。多Agent系统的结构为设计人员在该环境下的协作及资源共享提供了支撑框架，基于树结构的遗传算法为拓宽设计人员的思维空间提供了一种工具。文中用一个手机设计实例描述了该环境中进化设计的过程。该实例用基于数学表达式二叉树的遗传算法及数学软件工具MATLAB生成形状草图，用基于特征的设计产品树产生可选的部件组合。由于进化过程由设计人员引导，因此可以较快地实现令人满意的结果。     

Is grey relational analysis superior to the conventional techniques in predicting financial crisis?

This study proposes a new approach for analyzing the credit risks of banking industry based on the modeling of grey relational analysis (GRA). In order to construct a financial crisis warning system for banking industry, a GRA approach is developed and applied to the real data set with 111 samples. The results of the current model are compared to those of traditional ones, logistic regression and back-propagation neural network. The results illustrate that in the prediction of financially crisis as well as financially sound banks, the proposed GRA model demonstrates better prediction accuracy than the conventional ones. The results also imply that the financial data set one year before the crisis leads to the best accuracy. It is helpful for the establishment of early warning models of financial crisis for banks. The current results show that the proposed GRA provides a novel approach in handling financial crisis warning tasks.     

Pico-ing into the future of mobile projection and contexts

Ten years ago, we were on the verge of having cameras built into our mobile phones, but knew very little about what to expect or how they would be used. Now we are faced with the same unknowns with mobile projector phones. This research seeks to explore how people will want to use such technology, how they will feel when using it, and what social effects we can expect to see. This paper describes our two-phase field investigation that uses a combination of methods to investigate how, when, and why mobile projections may be used. The first study used an experience sampling method to investigate responses to a range of different media types, and, for example, the choice of surfaces used in each case. The second study asked users to create video diary entries showing when, where, and why they would have wanted to project information. Together these studies provide complementary insights into the future use of mobile projector phones. Our results cover detailed responses to a range of media types from the first study, while the second identified which of the known mobile information needs were commonly recorded by participants. Both studies provide insights that may help shape the hardware, software, and interaction design of mobile projector phones as they become increasingly available.     

Application of neural network in QFD matrix

The major challenge for contemporary enterprises is to make products fulfill customers’ expectations. Conceptual design is the foundation of the development process, as it starts from the customer needs identification and decides about the whole product life cycle. Quality function deployment (QFD) helps to extract product characteristics from customer demands. Optimization of the product development process requires different product variant information at the early stage of product development. At the early designing stage, designers lack sufficient product information and have difficulty in determining it. The idea of the paper is to provide measurable engineering information for the quality function deployment method. For this purpose, a chosen artificial intelligence method was used. In the experiment, artificial neural network (NN) was applied. The results of analyses show that the intelligent estimation methods are useful and effective. The methods of estimation consist of four stages: goal setting, data acquisition, configuration of NN architecture, fulfilling of the QFD matrix. Finally, to illustrate the procedure of the chosen engineering characteristic estimation, a toothed gear box example was used.     

Beyond usability: the OoBE dynamics of mobile data services markets

With processors imbedded in appliances, cars, books, and other retail products, modern society has entered the world of pervasive computing. Yet few consumers are able to set up new digital devices and integrate them into everyday life. From this perspective, the data-enabled mobile phone leads the way. In many markets, mobile phones have a product life cycle of 12 months or less. Some subscribers are able to put their new phones to immediate and full use. For others, the learning curve is so steep that they move on to a replacement without having learned to exploit the functionality available in the first one. This work applies earlier findings by IMARC researchers in segmenting mobile data services (MDS) markets, interprets recent survey data, and synthesizes a model to guide design of the Out-of-the-Box Experience (OoBE) for mobile data subscribers. This integrative model can be applied across cultures to help service developers, facilitators and operators design, distribute and communicate new MDS to fulfill the demand side requirements of potential adopters, and to guide packaging design to improve user experiences during the early stages of use.