A systematic approach for coupling user satisfaction with product design

A fundamental assumption in this paper is that user satisfaction depends on product design. The approach consists of 5 steps: (1) define user satisfaction, (2) decompose product design elements, (3) conduct experiments, (4) develop relationship models, and (5) analyse critical design features. In order to demonstrate the practicability of this approach, relationship models were developed based on experimental data using a total of 60 subjects (30 American and 30 Korean subjects). In addition, critical design features and their common properties were identified for audio/visual consumer products. Similarities and differences between American and Korean consumers were discussed. The resulting relationship models can be used to predict user satisfaction and provide significant remedies for design change.     

A feature-based approach towards an integrated product model including conceptual design information

Due to the highly complex and informal data that has to be managed in the conceptual design this early design phase still lacks of suitable computer support. Furthermore, existing approaches towards a computer aided conceptual design are insufficiently integrated with the downstream applications of the product development process. The paper therefore introduces an approach towards a feature-based integrated product model that incorporates a feature-based representation scheme for capturing product semantics handled in the conceptual design phase and links early design with part and assembly modelling.     

Incorporating user satisfaction into the look-and-feel of mobile phone design

The look-and-feel of the mobile phone was investigated using a consumer survey. Seventy-eight participants evaluated the design of 50 different mobile telephones on the perceived scale of image/impression characteristics, including: luxuriousness, simplicity, attractiveness, colourfulness, texture, delicacy, harmoniousness, salience, rigidity, and overall satisfaction. Stepwise multiple linear regression analysis were used to evaluate results. The results showed that the image and impression characteristics of the products were closely related to the human-product interface specifications as well as overall shape of the product. Design variables such as texture, use of surface curvature, surface treatment, operating sound, and control response ratio were perceived as important by customers. This study also suggested a series of statistical processes for selecting and screening the critical design variables closely related to the customer's impression of a product. The product evaluation and analysis methods could be generalized to other consumer products.     

Single users' affective responses models for product form design

This paper presents a neural network based approach to modeling consumers' affective responses for product form design. A theoretical framework for a single user's perception is developed. On the basis of this theoretical framework, a mathematical model which enables single users' responses to different products to be predicted was developed. The results obtained show that the mathematical models developed achieved highly accurate predictions.For the purpose of obtaining a global model various individual mathematical models were created, which were based on the opinions of users representing different groups of opinion. The results suggest that, under some conditions, the combined use of various models of individual users can perform as well as a single model generated on the basis of mean market responses.     

The Design with Intent Method: A design tool for influencing user behaviour

Using product and system design to influence user behaviour offers potential for improving performance and reducing user error, yet little guidance is available at the concept generation stage for design teams briefed with influencing user behaviour. This article presents the Design with Intent Method, an innovation tool for designers working in this area, illustrated via application to an everyday human-technology interaction problem: reducing the likelihood of a customer leaving his or her card in an automatic teller machine. The example application results in a range of feasible design concepts which are comparable to existing developments in ATM design, demonstrating that the method has potential for development and application as part of a user-centred design process.     

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.     

Characterising user capabilities to support inclusive design evaluation

Designers require knowledge and data about users to effectively evaluate product accessibility during the early stages of design. This paper addresses this problem by setting out the sensory, cognitive and motor dimensions of user capability that are important for product interaction. The relationship between user capability and product demand is used as the underlying conceptual model for product design evaluations and for estimating the number of people potentially excluded from using a given product.     

A systematic knowledge-based method for design of transformable product

A transformable product can perform different functions or change functionality by changing its physical structure. It is formed by integration of different components whose states can be transformed each other. However, there is a lack of systematic methods to guide design of the transformable product. In order to improve the design efficiency of transformable products, a large number of products are studied in this research to build a case base of transformation parameters and transformation principles for the design knowledge. A systematic design process is proposed to apply the design knowledge. The transformation design problem is first mapped from the problem domain to the knowledge domain expressed by transformation parameters. A general solution is then obtained in the knowledge domain. A multi-classification support vector machine is used to train a model of the transformation recommendation based on transformation parameters. Finally, the general solution is mapped into the problem domain for the specific solution using the analogy design. The effectiveness of the method is verified in the design of a self-propelled boom sprayer.     

A systematic data-mining-based methodology for product family design and product configuration

Product family design and product configuration based on data mining technology is identified as an intelligent and automated means to improve the efficiency of product development. However, few of previous literatures have proposed systematic product family design method based on data mining technology. To make up for this deficiency, this research put forward a systematic data-mining-based method for product family design and product configuration. First, the customer requirement information and product engineering information in the historical order are formatted into structural data. Second, principal component analysis is performed on historical orders to extract the customers' differentiated needs. Third, association rule algorithm is introduced to mine the rules between differentiated needs and module instances in the historical orders, thus obtained the configuration knowledge between customer needs and product engineer. Forth, the mined rules are used to construct association rule-based classifier (CBA) that is employed to sort out the best product configuration schemes as popular product variants. Fifth, sequence alignment technique is employed to identify modules for popular product variants, so that the module instances are divided into optional, common and special module, respectively, thereby the product platform is generated based on common modules. Finally, according to new customer needs, the CBA classifier is used to recommend the best configuration schemes, and then popular product variants are configured based on the product platform. The feasibility of the proposed method is demonstrated by the product family design example of desktop computer hosts.     

An approach to user knowledge acquisition in product design

As the world increasingly moves towards a knowledge-based economy, user requirements become an important factor for enterprises to drive product collaborative design evolution. To map user requirements to the product model, user requirements are generally extracted into knowledge that can be used for design decisions. However, because users are interest-driven participants and not professional design engineers, the effect of user knowledge acquisition is not ideal. There are significant challenges for rapid knowledge acquisition with dynamic user requirements. This paper presents an approach to user knowledge acquisition in the product design process, which obtains the tangible requirements of users under the premise that users are adequate for participation. In this approach, the typical information flow is divided into four stages: submission, interaction, knowledge discovery, and model evolution. In the submission stage, natural language processing technology is used to transform text form solutions into data, so that computer technology can be applied to manage large-scale user requirements. In the interaction stage, users are helped to improve their solutions by the iterative recommendation process. In the knowledge discovery stage, after less concerned partial solutions are removed and vacant items are predicted to be supplemented, the final collection of user design information is obtained. Finally, based on rough set theory, design knowledge can be extracted to support the decision of the product model. The washing machine design project is used as a case study to explain the implementation of the proposed approach.     

Does network quality matter? A field study of mobile user satisfaction

Mobile quality of experience and user satisfaction are growing research topics. However, the relationship between a user’s satisfaction with network quality and the networks real performance in the field remains unexplored.This paper is the first to study both network and non-network predictors of user satisfaction in the wild. We report findings from a large sample (2224 users over 12 months) combining both questionnaires and network measurements. We found that minimum download goodput and device type predict satisfaction with network availability. Whereas for network speed, only download factors predicted satisfaction. We observe that users integrate over many measurements and exhibit a known peak-end effect in their ratings. These results can inform modeling efforts in quality of experience and user satisfaction.     

A methodology to redesign heterogeneous product portfolios as homogeneous product families

This paper presents a methodology to redesign heterogeneous product portfolios as homogeneous product families. A heterogeneous portfolio is one that has no common components, or shares a minimum number of components. The methodology proposed to homogenize the portfolio begins by analyzing the current product offerings to determine customer needs and functions. Then, a granulation process is initiated to remove redundancies, and identify physical function carriers to deliver the required functions. Next, function carriers are grouped on the basis of their functional commonalities into groups for parallel development. The applicability and the use of the methodology are illustrated through the redesign of an existing heterogeneous ‘office furniture’ product portfolio.     

The measurement of user satisfaction with question answering systems

Question Answering Systems (QAS) are receiving increasing attention from IS researchers, particularly those in the information retrieval and natural language processing communities. Evaluation of an IS's success and user satisfaction are important issues, especially for emerging online service systems using the Internet. Although many QAS have been implemented, little work has been done on the development of an evaluation model for them. Our purpose was to develop a validated instrument to measure user satisfaction with QAS (USQAS). The proposed validated instrument was intended as a reference for the design of QAS from a user's perspective.     

The conceptualization and measurement of m-commerce user satisfaction

Many of the instruments for measuring user-perceived system quality and user information satisfaction were developed in the context of mainframe, PC and wire-based technologies of a bygone era. With the proliferation of wireless technologies, users are increasingly interfacing and interacting with mobile commerce (m-commerce) systems. It is therefore important to develop new instruments and scales, which are directly targeted for these new interfaces and applications. User satisfaction is commonly acknowledged as one of the useful proxy measures of system success. This study addresses the concern for an effective m-commerce system design by means of the conceptualization and measurement of an m-commerce user satisfaction (MCUS) construct. In this article, we introduce and define this construct of MCUS, provide empirical validation of the construct and its underlying dimensionality, develop a standardized instrument with desirable psychometric properties for measuring MCUS, and explore the measure’s theoretical and practical application. This empirically validated instrument will be useful to researchers in developing and testing m-commerce systems theories, as well as to organizations in designing better-accepted m-commerce systems.     

Investigating factors affecting social presence and user satisfaction with Mobile Instant Messaging

The purpose of this study is to examine the factors that influence social presence and user satisfaction with Mobile Instant Messaging (mIM). The proposed research model integrates channel expansion, social influence, social presence and media richness theories, to explain how user experience, social influence, and medium richness influence social presence and user satisfaction with mIM. A total of 239 students from a state university in the US participated in this study. Data was collected via a web-based survey. The results suggest that user experience, social influence, and perceived richness are important drivers for social presence and user satisfaction in mIM. The implications of the study findings are discussed in the paper.     

A methodology for evolutionary product design

this paper describes a function-based approach for conceptual design support in the context of evolutionary product development. The main objective is to improve a designers productivity by the effective reuse of existing design information in design alternative identification, evaluation, and modification. An integrated evolutionary design methodology, EPD, is presented. The proposed methodology divides the whole process into three inter-related phases: information recovery, information management, and information reuse. The detailed steps in each phase are elaborated, and various techniques are employed to improve information reuse efficiency. A case study on commercial electrostatic air cleaner was used to illustrate the whole process of product evolutionary design. The proposed methodology will have a positive impact on the future development of the conceptual design support system.     

A systematic approach for product families formation in Reconfigurable Manufacturing Systems

The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.