A Clustering Approach to Affective Response Dimension Selection for Product Design

In the product design field, it is important to pin point critical product form features (PFFs) that influence consumers' affective responses (CARs) of a product design. In this paper, an approach based on least squares support vector regression (LS-SVR) and automatic relevance determination (ARD) is proposed to streamline the task of product form feature selection (PFFS) according to the CAR data. The representation of PFFs is determined by morphological analysis and pairwise adjectives are used to express CARs. In order to gather the CAR data, an experiment of semantic differential (SD) evaluation on collected product samples was conducted. The LS-SVR prediction model can be constructed using the PFFs as input data and the evaluated SD scores as output value. The optimal parameters of the LS-SVR model are tuned by using Bayesian inference. Finally, an ARD selection process is used to analyze the relative relevance of PFFs to obtain feature ranking.

During the New Product Development (NPD) cycle, it is important to focus and integrate relevant information into the stages of product conceptualisation, design and development so that they can be used for product and process design effectively. In this paper, a Generic Product and Process Development System (GPDS), which integrates knowledge-based technologies of Rule-Based Expert System (RBES) and Case-Based Reasoning (CBR), is proposed to facilitate product and process development. Although RBES is adopted for sorting product design criteria, relevant past cases are retrieved by the CBR system during product and process design stages. In doing so, previous knowledge in terms of rules and past practices will be made use of during the product and process design stages, resulting in an enhancement of the efficiency of design and operations. By applying GPDS in Hasbro Fast East Limited, the new product design life cycle is greatly shortened with significant reduction in the total development cost.

Product evaluation is an essential aspect of the product design and development process to improve an existing product significantly. In many cases, consumers rely on their subjective and emotional judgement on their product perception. Kansei is a Japanese term that encompasses the concept of sensibility, impression, and emotion. This study aims at employing the Kansei Engineering framework as a subjective evaluation method to evaluate the subjective impression of a product design. The general stages of the Kansei Engineering framework were used as the subjective evaluation method, and the SD method was used to gather users’ perceptions of product images. The results of the study showed that Kansei Engineering Type 1 could be employed as a method in the subjective evaluation of a product. The implication of this finding is discussed.

Kansei Engineering (KE) is a user-oriented technology combing customer psychological feelings and engineering for designing and developing products. Conventionally, questionnaire surveys have been extensively applied for understanding customers’ affective demands, responses and evaluations. However, the questionnaire is usually time-consuming, labour-intensive and small in data size. Online customer reviews provide trustable, continuously updated and free customers’ responses. Existing studies generally focus on the polarity classification of the positivity and negativity of the review texts. This study proposes an opinion mining approach based on KE and machine learning to extract and measure users’ affective responses to products from online customer reviews. Five types of machine learning algorithms are applied, including Support Vector Machine (SVM), Support Vector Regression (SVR), Classification and Regression Tree (CART), Multi-Layer Perceptron (MLP) and Ridge Regression (RR). An experiment has been conducted to illustrate the proposed approach. The results show that SVM+SVR is the best performer. It achieved a recall, precision and score of more than 80% for the classification of the soft-hard attribute with the smallest mean square error. Based on the proposed method, designers and manufacturers can effectively know customers’ responses to products through inputting the review texts to facilitate the process of product design.

In product design fields where the demand for an efficient usability is critical to its final success, it is essential to integrate user requirements into the design process from the earliest design stages. Particularly in the medical context, it is essential to systematically control the design phases in order not to neglect the strict constraints related to engineering design quality, safety, and usability requirements for the end user. Hence, in this work, an integrated user-centered product design and process simulation method is proposed. This method is aimed at enriching the state of the art in integrated product design and process simulation in the early design stages, as well as providing a novel design example of a device thought for medical contexts. The case study consists in the design of an intercom, aimed at improving patient-doctor communication in the case of bedridden patients on with helmet for Continuous Positive Airway Pressure (CPAP) therapy during COVID-19 pandemic emergency. Patients undergoing helmet-assisted ventilation are often immersed in a highly noisy environment, unable to fully communicate their needs to the doctors. Intercom devices are addressed to the doctors for improving ease communication with the patient. The proposed user-centered design for manufacturing and assembly proved to be efficient in such a complex design context.KeywordsUser-centered designIntegrated product and process design methodProcess simulation

PurposeThis study research contributes in fulfilling the gap by carrying out a systematic literature review (SLR) of contemporary research studies in closed-loop supply chain (CLSC). To the best of the author’s knowledge, an SLR rooted in bibliometric analysis has not been carried focusing on advent developments in CLSC. SLR employs scientific methodologies to select papers from standard databases. The SLR using advanced bibliometric and network analysis enables unveiling the key features of the contemporary literature.Design/methodology/approachThe author has analyzed over 333 documents published from 2008 and onward. Using the contemporary tools from bibliometric analysis tools, the author presented an exploratory analysis. A network analysis is utilized to visualize literature and create clusters for the cocited research studies, keywords and publication sources. A detailed multivariate analysis of most influential works published based top 100 articles via a cocitation matrix is done. The multivariate analysis used k-means clustering in which optimal number of clusters are estimated. The analysis is further extended by using a factor analysis, which enables determining the most influential clusters in the k-means clustering analysis.FindingsThe SLR using a bibliometric and network analysis enables unveiling the key features of the contemporary literature in CLSC. The author examined published research for influential authors, sources, region, among other key aspects. Network analysis enabled visualizing the clusters of cocited research studies, cowords and publication sources. Cluster analysis of cocited research studies is further explored using k-means clustering. Factor analysis extends findings by identifying most contributing grouping of research areas within CLSC research. Each clustering technique disclosed a unique grouping structure.Originality/valueCLSC has received considerable attention, and its core areas start with focusing on reverse logistics concepts relating reuse, recycling, remanufacturing, among others. Contemporarily, the studies have enhanced reverse logistics core functionalities interfaced with the other interesting avenues related to CO2 emission reduction, greening and environmental protection, sustainability, product design and governmental policies. Earlier studies have presented a literature review of CLSC; however, these reviews are commonly conducted in the traditional manner where the authors select papers based on their area of expertise, interest and experience. As such these reviews fall short in utilizing the advanced tools from bibliometric analysis.

Based on the theory of user needs and the product development mode and framework of mobile Internet interactive innovation, a new “reality → virtual → reality” interactive innovation product development mode is constructed. It draws on the unique characteristics, systematic technical system, and comprehensive scientific and technological layout of the Metaverse. On this basis, a framework for product development and design based on interactive innovation from the Metaverse perspective is innovatively proposed. In the Metaverse scenario, interactive innovation knowledge can be easily and effectively transformed into design knowledge, and all groups of users truly participate in the whole process of product design. Moreover, the development of interactive innovative products in the Metaverse scenario can be combined with artificial intelligence (AI) technology to further automate the statistical analysis of user needs and preferences so as to meet the dynamic needs of users and accurately develop products that fit user needs and enterprise standards. In addition, users, designers, and enterprises can make joint decisions on product design solutions and development forms, and the Metaverse technology can also optimize the products with continuous iteration and obtain the optimal solutions. An automotive case study illustrates the feasibility and effectiveness of the model for product development innovation and enterprise digital transformation.

PurposeUnique product design is a highlight of sustainable branding. The purpose of this paper is to investigate whether product design affects customers’ psychological responses (i.e. cognitive and affective responses) to smartphones, and, in turn, affects their brand loyalty (i.e. attitudinal and behavioral brand loyalty), further advancing the knowledge of product design and brand management.Design/methodology/approachThis work used survey data from 456 Taiwanese with experience using smartphone. Structural equation modeling was employed to test the proposed model and hypotheses.FindingsThe results indicate that the product design significantly affects both cognitive response and affective response, which, in turn, significantly affect both attitudinal brand loyalty and behavioral brand loyalty. The findings also suggest that the moderating effect of product involvement on the relationship between product design and affective response is statistically significant, although it does not positively and significantly moderate the link between product design and cognitive response.Research limitations/implicationsThis study has two main limitations. First, this study was conducted in the context of smartphones, thus potentially constraining the generalization of the results to other industries. Second, the data in this study were obtained from a cross-sectional design.Practical implicationsThese findings can permit companies to generate more brand loyalty in their customers and guide their management of assets and marketing activities.Originality/valueThis paper presents new insights into the nature and importance of product design in brand value.

Driven by the demand for innovation, design is constantly evolving and is increasingly focused on integrating new technologies into design processes. Technological innovations have proven to be of fundamental importance, both in speeding up and improving production processes and managing and enriching the ideational process.We are now surrounded by software in which the participation of artificial intelligence is constant, but although it has become pervasive, we often do not even notice its presence. In the field of product design, several software exploiting artificial intelligence have been diffused to provide us with virtual products at the two-dimensional level. These software are capable of transforming the ideational stages of a project, as they generate original idea proposals in a matter of minutes. One of the most popular software is Midjourney, which is based on the key text-to-image concept, and can create images from prompts, and descriptive keywords provided by the designer. There are also interesting examples in this regard. Think of the work done by Filippo Nassetti, a British architect and designer, who came up with a series of sunglasses and eyeglasses by going through Midjourney, to obtain zoomorphic-inspired products that recall the textures of biological and mineral microstructures. The surreal collection of biomorphically shaped glasses is an example of the exploration of the creative potential of Midjourney software.Another interesting project is the one tackled by the Oio company for the Spawns spoon collection, in collaboration with Giosanpietro Jewelry. According to Simone Rebaudengo, director and co-founder together with Matteo Loglio of the Oio company, the products in the Spawns collection derive from an ongoing dialogue between different skills that has led to the collaboration between man and algorithm, resulting in an expansion of the handmade, merging the ancient world of craftsmanship with that of advanced technology, defining what they call 'craft intelligence.The paper aims to explore the relationships, potentials and limitations of integrating artificial intelligence into the design process through a design experience that tests the innovative potential of text-to-image software in product ideation and reflects on the redefinition of the designer's role in this rapidly and continuous changing scenario.The case study presented therefore experiments with a design process in which the ideation phase is supported by AI, particularly by text-to-image software, which allows textual descriptions to be translated into visual representations, generating highly detailed images and offering new creative possibilities. The work addressed outlines perspectives and critical issues, which deserve further investigation. On the one hand, one potential that is being outlined is the possibility of visualizing even complex ideas by entrusting the imaginative component to the software, having a multiplicity of alternatives and expanding the ideational range with novel solutions from which to make more informed design choices. Text-to-image software also simulates effective virtual prototyping, allowing a concept to be prefigured and visualized in a three-dimensional context before committing to physical production.On the other hand, text-to-image software has some significant limitations, for example in the poor correspondence of generated images with design intentions and the designer's need to acquire technical skills to effectively use text-to-image software, going on to delineate the possibility of a figure such as that of the prompt designer.Therefore, the presented project aims to contribute to the contemporary debate on the integration of AI into design processes with the collaboration of text-to-image software as another avenue for innovation in product design. The scenario sketched out defines an area in which the role of the designer and human creativities proves irreplaceable, leaving one to understand how more and more a process of understanding and collaboration with AI technologies is needed, and how the skills required of future designers are going to vary and expand.Nozaki, N., Konno, E., Sato, M., Sakairi, M., Shibuya, T., Kanazawa, Y., & Georgescu, S., 2017, Application of artificial intelligence technology in product design. Fujitsu Sci. Tech. J, 53(4), 43-51.F. Morace, Design più umano. Quello che l’intelligenza artificiale non potrà mai darci. Egea, 2018S. Quintarelli, Intelligenza artificiale: cos'è davvero, come funziona, che effetti avrà. Bollati Boringhieri, Torino, 2020G. E. Valori, Intelligenza artificiale tra mito e realtà. Motore di sviluppo o pericolo imminente? Rubbettino, 2021L. Keeheon, A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design. Sustainability 2021, 13(5), 2668; https://doi.org/10.3390/su13052668M. Mitchell, L'intelligenza artificiale: una guida per esseri umani pensanti. Einaudi, 2022

The study of Consumer Affective Factor (CAF) for Kansei engineering has been an important issue in the industrial design field in recent years. CAF is usually presented in the form of adjectives. Based on the Kansei Engineering (KE) concept, this study conducted Factor Analysis (FA) and Procuresses Analysis (PA) to select the CAF from digital camera product's shape. First, in the initial stage of the study, 120 samples of digital camera were col- lected from the fashion market place in Taiwan. In the meanwhile, we deleted more similar appearance digital camera samples to obtain 50 samples for experiment. Twenty pairs of ad- jectives describing the digital cameras were used for a Semantic Differential (SD) experiment. The results of the factor loaded from the FA, then we could obtain representative pairs of adjectives. PA was also used to decide adjective priorities according to the sorting rule. Final results showed that the PA was an effective method for the CAF selection.

The authors investigate the neglected problem of generalizing from multiattribute attitude models based on data for actual brands of real products to reach conclusions on affective responses toward artificial objects or hypothetical concepts, such as those that might be used to develop new product designs. They propose an approach involving four stages of analysis to examine the intervening role of multiattribute attitude models for real products in accounting for the effects of artificial design features on affective responses. The method decomposes the overall relationship of affect to artificial design features into (1) the mediating effects of a multiattribute attitude model based on real products, (2) other indirect effects, and (3) a residual direct effect. This general approach is illustrated and supported by an application to data on responses to male vocal recordings (real products) and alternative recording mixes (artificial objects). The results suggest the need to proceed with caution in using multiattribute attitude models based on real products to guide the design of artificial objects in laboratory tests oriented toward new product development.

Nowadays, Korean culture affects fashion cultural industry. Furthermore, art and fashion collaborate considerably more now than in the past. Korean fashion experts and fashion cultural industry have mainly focused on global tourists. Fashion cultural products that promote the image of Korea synthesize both traditional and contemporary traits of the Korean culture (Cho, 2007), which reflects cultural and economic values. Hallyu, which means ‘Korean Wave’, has been a popular trend of Korean cultural contents on the global market. The target market of the contemporary Korean fashion clothing has mostly targeted global tourists. However, traditional products dominate over a few contemporary products on the Korean cultural product market. This study focuses on the contemporary Korean fashion clothing that are designed and reinterpreted in our times. When these designs become available on the market, they can excite more interest both in the fashion industry and among the consumers. This will help highlight the importance and potential of the present-day Korean cultural products. The purpose of the study is to figure out effects of contemporary Korean fashion clothing attributes on consumer response and consumer behavior. Contemporary Korean fashion clothing attributes are divided to Korean culture, fashion/practicality, creativity/uniqueness and design/aesthetic traits. Consumer response is to see the affective and cognitive response. Also, consumer behavior is to see preference and purchase intention.In the study, the data was used to conduct exploratory factor analysis and reliability analysis with SPSS, 21.0 and Amos 18.0 was used to conduct confirmatory factor analysis and structural equation modeling for testing the hypotheses. The results revealed fashion/practicality, creativity/unique attributes had positive effect on affective response and creativity/unique, design/aesthetic attributes had positive effect on the cognitive response. In addition, affective and cognitive response had positive effect on preference but only affective response had positive effect on purchase intention. Lastly, preference had positive effect on the purchase intention.The implications of this study would stimulate the expansion and further development of the Korean contemporary design market. However, as a limitation of research, limited category of product was used so more various kinds of fashion category can be used for the future research.


 The purpose of this study is to test the Influence of Product Quality, Product Design and Celebrity Endorsement on the Purchase Decision of the Honda Vario Matic motorcycle in Yogyakarta. This research is a type of quantitative research conducted in the form of a survey of consumers who have purchased a Honda Vario 150c c automatic motorcyclein Yogyakarta. This study is to analyze the influence of variables The influence of product quality, product design and celebrity endorsement on consumer purchase decisions. To answer research questions and test the hypotheses proposed, multiple linear regression analysis tools are used. The population in this study was all consumers who had made a purchase or who were going to buy a Honda Vario motorcycle as many as 112 people with characteristics (age, gender, income of respondents, occupation ) as subjects of the study. The results showed that 1). Product Quality has a significant effect on the Purchase Decision on the Honda Vario Automatic Motorcycle in Yogyakarta City, 2). Product Design has a significant positive effect on the purchase decision on the Honda Vario Matic Motorcycle in Yogyakarta, 3). Celebrity Endorsement has a significant positive effect on the purchase decision on the Honda Vario Matic Motorcycle in Yogyakarta, 4) Product Quality, Product Design and Celebrity Endorsement influence the purchase decision on the Honda Vario automatic motorcycle in Yogyakarta.
 Keywords: Product Quality, Product Design, Celebrity Endorsment, Purchase Decision

Employing rough sets and association rule mining in KANSEI knowledge extraction

Product design plays a major role in drawing consumers’ attention to the product at the beginning of consumer-product interactions (Blijlevens et al. 2009; Crilly et al. 2004; Kreuzbauer and Malter 2005). Such interactions, however, do not occur in vacuum and external factor could also influence consumers’ perceptions of the product. While previous research suggests that environment congruence facilitates consumers’ positive evaluations of the product and thus the product’s environment must be aligned with the design elements embedded in the product (Berger and Fitzsimons 2008; Meyers-Levy and Tybout 1989; Wu et al. 2013), the generalizability of this idea is challenged in this study. More precisely, this work empirically investigates how product design cues, environment visual congruence, and their interaction may influence consumers’ aesthetic, affective, and behavioral responses.