基于意图认知的复杂电气产品外观设计策略

受功能结构等多重约束和功能导向设计理念影响,复杂电气产品外观设计更关注 工程技术的合理性和功能表达的完整性,易忽略用户对产品的认知体验需求。针对这一问题, 分析该类产品外观设计意图产生模式和用户意图认知模式,总结意图认知中存在的 3 个问题： 用户认知创新与失真导致意图超出与缺漏、设计师与用户的认知差异导致语义鸿沟、用户单纯 化认知导致理解障碍。针对性提出复杂电气产品的 3 项外观设计策略：基于质量功能配置法 (QFD)的用户认知前置、构建延续性与差异性并存的外观设计特征库、以用户认知和工程约束 共性特征为引导的族群收敛,以在技术约束基础上实现用户对设计意图信息的获取和情感的满 足,进而提升该类产品外观设计的市场竞争力。     

Predicting user preferences of environment design: a perceptual mechanism of user interface customisation

It is a well-known fact that users vary in their preferences and needs. Therefore, it is very crucial to provide the customisation or personalisation for users in certain usage conditions that are more associated with their preferences. With the current limitation in adopting perceptual processing into user interface personalisation, we introduced the possibility of inferring interface design preferences from the user’s eye-movement behaviour. We firstly captured the user’s preferences of graphic design elements using an eye-tracker. Then we diagnosed these preferences towards the region of interests to build a prediction model for interface customisation. The prediction models from eye-movement behaviour showed a high potential for predicting users’ preferences of interface design based on the paralleled relation between their fixation and saccadic movement. This mechanism provides a novel way of user interface design customisation and opens the door for new research in the areas of human–computer interaction and decision-making.     

基于犹豫模糊语言术语集和粒子群优化算法的产品造型设计感性评价方法

产品造型感性评价反映了用户的意象感知,具有模糊性与不确定性,用户常难以准确描述其感 性偏好而表现出犹豫。针对该问题,引入犹豫模糊语言术语集(HFLTSs)描述用户感性评价,基于其数学算子构 建犹豫模糊语言共识模型以测度用户认知一致性程度,借助粒子群优化算法(PSO)实现非共识条件下用户评价 矩阵的优化与共识达成,通过逼近理想解排序法对产品造型方案进行优劣排序,提出了基于 HFLTSs 和 PSO 的 产品造型设计感性评价流程。以汽车充电桩造型方案感性评价为例,验证了 HFLTSs 有助于解决用户感性认知 的不确定问题,结合 PSO 能够提高犹豫模糊语言评价的一致性,从而提升产品造型感性评价质量。     

A method for product form design of integrating interactive genetic algorithm with the interval hesitation time and user satisfaction

Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the risk of their products being rejected by the market. Due to the ambiguity of user cognition, it is difficult to accurately obtain the user's preference for individual productions. To respond to the challenge, we propose an engineering scientific research method of interactive genetic algorithm with the interval arithmetic based on hesitation and fuzzy kano model(FKM) to explore the emotional needs of users for product forms and drive product modeling evolution design. Through expert interviews, the morphological characteristics and perceptual images factors of the products attracting users are investigated. In order to identify the user's satisfaction relationship with the perceptual images, we use FKM to analyze the product image style that meets the user's kansei needs accurately and selects 5 factors which is attractive attributes. Meanwhile, we attempt to transform this 5 factors into evaluation carrier to guide the evolution direction of product styling in HIIF-IGA, and then optimized four electric bikes with scores over 8.8 so that it could realize user demand-driven product evolution design. To handle users' ambiguity, the FAHP method is used to quantify the user's emotional imagery criterion and create a product evolution design system platform, which can automatically generate product styling design scheme in line with user preferences. This experimental results show that the proposed method can help enterprises effectively improve customer satisfaction and reduce the cost and time of product development.     

基于魅力因素的微型电动车造型设计

面向城市通勤出行的微型电动车日渐得到广泛关注。不同于燃油汽车的技术与结 构布局,微型电动车在概念造型设计时其创意自由度较高,然而创新型产品是否能够满足用户 偏好是设计师需要重点关注的问题。基于能够有针对性地解决用户与产品之间吸引力问题魅力 工学研究方法,通过评价构造法和数量化I 类对微型电动车样本进行用户偏好分析,寻求能够 有效满足用户偏好的形态魅力因素,植入设计方案中。该方法对提升创新型产品的形态吸引力 提供了一定参考,也对用户感性层面的研究提供了研究案例。     

Cultural Cognitive Style and Web Design: Beyond a Behavioral Inquiry into Computer-Mediated Communication

Numerous studies have identified links among culture, user preferences, and Web site usability. Most of these studies were reports of findings from a behavioral perspective in explaining how cultural factors affect processes of Web-related content design and use. Based on the research of Vygotsky and Nisbett, the authors propose a broader model, referred to as "cultural cognition theory," by which Web design, like other types of information production, is seen as being shaped by cultural cognitive processes that impact the designers' cognitive style. This study explores issues related to Web designers' cultural cognitive styles and their impact on user responses. The results of an online experiment that exposed American ¹ and Chinese users to sites created by both Chinese and American designers indicate that users perform information-seeking tasks faster when using Web content created by designers from their own cultures.     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

A two-phased SEM-neural network approach for consumer preference analysis

A fundamental task in the design of consumer products is consumer preference analysis. The primary focus of this task is establishing a mapping relationship between product parameters/attributes and consumer preferences. The key to connect the consumer space and the design space are user perceptions of the product. Among the many existing methods, the Structural Equation Model (SEM) is one of the most used methods because it explains the causal relationship between the input and the output variables explicitly. However, the relationship obtained from the conventional SEM is linear, which is usually not the case in practice. Fortunately, the Artificial Neural Network (ANN) provides a new perspective for building nonlinear models because of its nonlinear nature. Therefore, a two-phased SEM-NN approach for consumer preference analysis is introduced for identifying and mapping how product attributes affecting the fulfillment of user perceptions and ultimately their preferences. In this model, the consumer preference analysis is conducted in two phases: influence path construction, and path coefficient revision. The proposed method can reserve the original SEM topology that reflects the causal relationship between variables while using the training algorithm of ANN to obtain more accurate path coefficients. This model could help the designers to identify and map how product attributes affecting the consumer preferences, and to better understand the factors that affect user perceptions and the inner relationships between them. To demonstrate effectiveness of the model, a case study of smartphone is presented. It is shown that the SEM-NN model can make full use of the causal analysis of SEM and the nonlinear nature of ANN and ultimately provides more reliable results of consumer preference analysis.     

Characterizing online health and wellness information consumption: A study

To seek answers to health queries, we often find ourselves on a quest to assimilate information from varied online sources. This information search and fusion from different sources elicits user preferences, which can be driven by demographics, context, and socio-economic factors. To that end, we study these factors as part of health-information seeking behavior of users on a large health and wellness-based knowledge sharing online platform. We begin by identifying the topical interests of users from different content consumption sources. Using these topical preferences, we explore information consumption and health-seeking behavior across three contextual dimensions: user-based demographic attributes, time-related features, and community-based socioeconomic factors. We then study how these context signals can be used to explain specific user health topic preferences. Our findings suggest that linking demographic features to user profiles is more effective in explaining health preferences than other features. Our work demonstrates the value of using contextual factors to characterize and understand the content consumption of users seeking health and wellness information online.     

The impact of cognitive machines on complex decisions and organizational change

Humans and organizations have limitations of computational capacity and information management. Such constraints are synonymous with bounded rationality. Therefore, in order to extend the human and organizational boundaries to more advanced models of cognition, this research proposes concepts of cognitive machines in organizations. From a micro point of view, what makes this research distinct is that, beyond people, it includes in the list of participants of the organization the cognitive machines. From a macro point of view, this paper relies on the premise that cognitive machines can improve the cognitive abilities of the organization. From such perspectives, it presents rationale and principles of a class of cognitive machines with capabilities to carry out complex cognitive tasks in organizations. It also introduces analyses of the cognitive machines in organizations through theories of bounded rationality, economic decision-making, and conflict resolution. The analyses indicate that these machines can solve or reduce intra-individual and group dysfunctional conflicts which arise from decision-making processes in the organization, and thus they can improve the degree of organizational cognition. From all these backgrounds, this research outlines implications of cognitive machines for organizations.     

Evaluating recommender systems from the user’s perspective: survey of the state of the art

A recommender system is a Web technology that proactively suggests items of interest to users based on their objective behavior or explicitly stated preferences. Evaluations of recommender systems (RS) have traditionally focused on the performance of algorithms. However, many researchers have recently started investigating system effectiveness and evaluation criteria from users?? perspectives. In this paper, we survey the state of the art of user experience research in RS by examining how researchers have evaluated design methods that augment RS??s ability to help users find the information or product that they truly prefer, interact with ease with the system, and form trust with RS through system transparency, control and privacy preserving mechanisms finally, we examine how these system design features influence users?? adoption of the technology. We summarize existing work concerning three crucial interaction activities between the user and the system: the initial preference elicitation process, the preference refinement process, and the presentation of the system??s recommendation results. Additionally, we will also cover recent evaluation frameworks that measure a recommender system??s overall perceptive qualities and how these qualities influence users?? behavioral intentions. The key results are summarized in a set of design guidelines that can provide useful suggestions to scholars and practitioners concerning the design and development of effective recommender systems. The survey also lays groundwork for researchers to pursue future topics that have not been covered by existing methods.     

Perceptual foundations in the design of visual displays

This paper discusses how perception affects the relationship between screen design and memory and cognition. The effects of visual grouping, location of material, distinctiveness of elements and arrangement in layouts, and motion are discussed and analyzed. The perceptual and cognitive principles explored can be applied to the design of any visual display. This information provides designers with a perceptual framework for maximizing learning conditions.     

A Visual Information Processing Model to Characterize Interactive Visualization Environments

Interactive visualizations have the potential to greatly enhance our ability to analyze data. Although the user is central to the use of such environments, perceptual and cognitive processes are not well understood within the context of interactive visualization. Although cognitive psychology has provided a greater understanding of visual perception and cognition, a theoretical framework that links this knowledge with the interactive visualization process is needed. This article aims to fill this gap by introducing a visual information processing model that facilitates the understanding of how users interact with interactive visualization environments.     

Decision theoretic modeling of affective and cognitive needs for product experience engineering: key issues and a conceptual framework

User experience (UX) design plays a critical role in product experience engineering. To create a theoretical foundation of UX design, it is imperative to develop mathematical and computational models for elicitation, quantification, evaluation and reasoning of affective–cognitive needs that are inherent in the fulfillment of user experience. This paper explores the key research issues for understanding how human users’ subjective experience and affective prediction impact their choice behavior under uncertainty. A conceptual framework is envisioned by extending prospect theory in the field of behavioral economics to the modeling of user experience choice behavior, in which inference of affective influence is enacted through the shape parameters of prospect value functions.     

多意象驱动下的产品造型个性化定制系统研究

构建了一种基于多意象驱动下的产品个性化定制系统,增加用户对个性化定制的体验度,从而实现智能的产品个性化定制设计。通过对当下三种产品个性化定制模式的比较研究和分析,提出了个性化定制系统的构架模型和系统流程。然后通过用户参与模式、感性意象挖掘、关联方法建立多意象驱动机制,并结合感性工学的相关研究方法、BP神经网络以及多目标粒子群算法构建了面向产品意象造型的智能设计模型,实现了多意象驱动下的产品造型个性化定制。最后以人形卡通文具的个性化定制进行了实例验证。结果表明多意象驱动的产品造型个性化定制系统更加丰富了消费者对产品造型意象风格的体验,满足了消费者日益迫切的个性化设计需求,符合智能时代对产品设计开发的需要。     

Disentangling utilitarian and hedonic consumption behavior in online shopping: An expectation disconfirmation perspective

Increasingly, researchers have come to acknowledge that consumption activities entail both utilitarian and hedonic components. Whereas utilitarian consumption accentuates the achievement of predetermined outcomes typical of cognitive consumer behavior, its hedonic counterpart relates to affective consumer behavior in dealing with the emotive and multisensory aspects of the shopping experience. Consequently, while utilitarian consumption activities appeal to the rationality of customers in inducing their intellectual buy-in of the shopping experience, customers’ corresponding emotional buy-in can only be attained through the presence of hedonic consumption activities. The same can be said for online shopping. Because the online shopping environment is characterized by the existence of an IT-enabled web interface that acts as the focal point of contact between customers and vendors, its design should embed utilitarian and hedonic elements to create a holistic shopping experience. Building on Expectation Disconfirmation Theory (EDT), this study advances a research model that not only delineates between customers’ utilitarian and hedonic expectations for online shopping but also highlights how these expectations can be best served through functional and esthetic performance, respectively. Furthermore, we introduce online shopping experience (i.e., transactional frequency) as a moderator affecting not only how customers form utilitarian and hedonic expectations but also how they evaluate the functional and esthetic performances of e-commerce sites. The model is then empirically validated via an online survey questionnaire administered on a sample of 303 respondents. Theoretical contributions and pragmatic implications to be gleaned from our research model and its subsequent empirical validation are discussed.     

产品外形设计中客户感性认知模型及应用

为了更好地利用客户的感性认知支持产品外形设计活动,提出一种产品外形设计中客户感性认知与产品外形特征关联模型.在分析产品外形设计中所涉及的客户感性认知特点的基础上,建立产品外形特征要素与客户感性认知要素的关联模式;以认知行为为标准,利用特征匹配实现了客户感性认知的识别与相似性分析;提出了基于模糊认知图的客户感性认知与产品外形特征关联模型,利用蚁群聚类算法确定模糊认知图的结构及邻接矩阵,从而获取客户感性认知以指导产品的外形设计.最后通过实例验证了该模型的有效性和实用性.     

The impact of aging on access to technology

The number of people over the age of 65 is increasing worldwide with the fastest growing subgroup those aged 80+ years. Computer and information technologies hold promise in terms of increasing the quality of life for older people. However, successful use of technology by older adults is predicated on systems that are designed to accommodate the needs and preferences of this user group. This paper discusses the implications of age-related changes in cognition for system design. Generally, the existing literature shows that, although older adults are willing to use technology, many report usability problems with existing systems and these problems may in part be due to the cognitive and perceptual demands placed on the user. These findings are discussed in terms of guidelines for system design.     

A user-centric evaluation of context-aware recommendations for a mobile news service

Traditional recommender systems provide personal suggestions based on the user’s preferences, without taking into account any additional contextual information, such as time or device type. The added value of contextual information for the recommendation process is highly dependent on the application domain, the type of contextual information, and variations in users’ usage behavior in different contextual situations. This paper investigates whether users utilize a mobile news service in different contextual situations and whether the context has an influence on their consumption behavior. Furthermore, the importance of context for the recommendation process is investigated by comparing the user satisfaction with recommendations based on an explicit static profile, content-based recommendations using the actual user behavior but ignoring the context, and context-aware content-based recommendations incorporating user behavior as well as context. Considering the recommendations based on the static profile as a reference condition, the results indicate a significant improvement for recommendations that are based on the actual user behavior. This improvement is due to the discrepancy between explicitly stated preferences (initial profile) and the actual consumption behavior of the user. The context-aware content-based recommendations did not significantly outperform the content-based recommendations in our user study. Context-aware content-based recommendations may induce a higher user satisfaction after a longer period of service operation, enabling the recommender to overcome the cold-start problem and distinguish user preferences in various contextual situations.     

一种QoS感知的Web服务群体评价方法

传统QoS感知的Web服务选择方法需要用户给出精确权重以表达其对QoS属性的偏好。为解决用户无明确偏好情况下的服务选择问题,提出了一种QoS感知的Web服务群体评价方法。对Web服务群体评价的需求进行了详细的分析,以有明确QoS偏好的用户对服务的历史选择结果为基础,利用群决策的Condorcet和Borda函数集结这些结果得到服务的群体评价,从而使得无明确QoS偏好用户可以参考该评价结果进行服务选择。理论分析和仿真实验验证了该服务群体评价方法的合理性和有效性。