A study on extraction of consumer affective factor for Kansei engineering

Consumers’ affective responses (CARs) to the appearance of a product will greatly influence their purchasing decisions. In the product design field, researchers often provide adjectives so that consumers can express their subjective feelings. However, there exists both similarity and vagueness among these adjectives, which make it difficult to choose suitable adjectives for semantic differential (SD) experiments. This study proposes an approach based on factor analysis (FA), hierarchical clustering analysis (HCA) and k-means clustering. First, an SD experiments is conducted to collect CARs evaluated data about a series of selected product samples. Second, FA is applied to the CARs data to extract the factor loadings of the adjectives. Finally, the clustering approach, which comprises HCA and k-means clustering, is used to group these adjectives according to the factor loading results obtained from the FA. A case study of mobile phone design is used to demonstrate the effectiveness of the proposed approach. Three representative pairwise adjectives: coarse-delicate, unoriginal-creative and discordant-harmonious were obtained from the experimental results conducted on the initial set of 22 pairwise adjectives. This proposed method is very helpful to product designers during new product development. keywords:Factor analysis、Hierarchical cluster analysis、K-means clustering、Kansei engineering、Product design.

Though the physical burdens by welding works and manual material handling works in the shipbuilding have been studied before, the grinding work will be one of the most severe work for the human body. In the grinding work, undesired sound, hand-arm vibration and reaction force from the tool are big, and the adequate countermeasures for the body work seem to be necessary, because the aging of the workers and embrittlement of the youth will become remarkable in near future. Therefore, in this paper, the human body analysis at grinding work has been carried out, using general-purpose human simulation software “Jack”; static strength prediction of human body, lumbar force analysis, and energy consumption analysis, same as previous reports.This time, “Kansei Engineering” technique has been introduced for the evaluation of the results by biomechanical analysis. SD (Semantic Differential) evaluation has been carried out concerning the body feeling of the grinding workers, and then multiple factor analysis, one of multivariate analysis, has been executed, according to the process of “Kansei Engineering”. The results have been compared with the analytical results by the digital human model, and it was concluded that both were well coincided especially for the lower human body.

The role of government health websites as a source of referrals and credible health information is very important, especially now that everything is digital. People use the internet and make health websites as the first step in finding health information, government policies related to health, and public health services. So it is very important to consider the user aspect in designing the appearance of an appropriate health website. This study utilizes the Kansei Engineering KEPack type 1 in analyzing various emotional factors related to the e-government website interface in the health sector. So that it can be found that the psychological emotional factors of users are important and become the main recommendations in the design of the website interface. We are focuses on user preferences for the e-government site interface of the Karawang District Health Office with the Kansei Engineering Type I approach. The Kansei Engineering study was conducted to analyze various emotional factors related to the user interface by comparing 5 specimens of e-Government sites in the health sector. A total of 20 kansei words were identified which were then processed using the multivariate statistical method Cronbach's Alpha (CA), Coefficient Correlation Analysis (CCA), Factor Analysis (FA). The result is that 4 kansei words have a high influence and successfully present a matrix of design element recommendations with 7 main elements and 45 sub-criteria for specific design elements.

Android-based devices have become devices for every student in communication activities and learning media, therefore the Introduction to Linguistics course requires learning media, so the alternative is to use an Android-based application. The purpose of this study was to analyze the emotional factor in designing the interface for Android-based Introductory Linguistics teaching materials with the Kansei Engineering approach; make recommendations for the interface design of Android-based Introduction to Linguistics teaching materials. The method used is Kansei Engineering Type I (KEPack). The application of Kansei Engineering in the design of the Android-based Learning Application interface produces interface design elements in designing Android-based Learning Applications consisting of 7 major parts, namely Page Body, Header, Top Menu, Left Menu, Main Menu, Right Menu and Footer. To detect users of research android-based learning applications using 18 Kansei Word Specimens consisting of 4 applications, participants were taken with the slovin approach which collected 190 students from 360 students, the process of analyzing the elements needed in designing the application interface design with the Kansei Engineering approach, using the Kansei Engineering method. multivariate calculations. The methods are Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) and Partial Least Square (PLS). Display design sourced from all participants, which will be used for public display, for Introductory Linguistics Learning, namely the concept of "Colorfull" emotion.

One of the most important contributors to foreign exchange is tourism, and one type of accommodation that can help the tourism industry is hotels. Currently, the website is one of the elements that helps visitors obtain information about the hotel and make reservations for available rooms. One technique for attracting hotel customers is to create an eye-catching website. The process of translating human emotions and feelings into a design–in this case, the design of a website interface–is known as Kansei Engineering. The main goal of this study is to select the most critical emotional factors for redesigning the website of the Ocean View Tulamben Bali Hotel. This study contributes to the knowledge in the field of website interface design based on emotional factors by applying the multivariate method and Kansei Engineering. The related users’ critical emotions were translated into Kansei words in this study. Seven Kansei words related to the website interface were used and six hotel websites were used as samples. The 33 respondents were employees of the Ocean View Tulamben Bali Hotel. Multivariate statistical analysis, including Cronbach’s alpha, coefficient correlation analysis, factor analysis, and partial least squares, were used to examine the respondents’ questionnaire responses. Recommendations for redesigning the hotel website interface were derived from the average of all questionnaires. The results showed that the Kansei word “futuristic” was the most important user emotion. Keywords: website; user interface; web design; emotional factor; Kansei Engineering https://doi.org/10.55463/issn.1674-2974.51.11.7

Employing rough sets and association rule mining in KANSEI knowledge extraction

Peppermint hard candy is increasing sold in the market. It causes a tight business competition and need some efforts for the product to survive and to win the competition. One effort that can be done is to design peppermint hard candy packaging. This paper describes the peppermint hard candy primary packaging design in accordance with the consumers’ needs. Kansei engineering (KE) was used in this study to translate consumer perceptions of the primary packaging design. Data is processed by using factor analysis and conjoint analysis. Based on the analysis, the design of peppermint hard candy packaging desired by the consumer was plastic, tubular, printed sticker label, flip-top accessory and transparent colors. The label design element has the highest importance value (30.524%) followed by material design elements (29.188%), shape (21.763%), accessories (11.300%) and color (7.226%).

PurposeBelief in Mazu has a crucial cultural status in Taiwan and the coastal area of Fujian, China. The design and manufacture of apparel and accessories to be placed on statues of the deity are also considered a sacred and critical part of the religion’s cultural and artistic inheritance. The crown hat of Mazu is one of the most essential elements of the deity’s apparel. The paper aims to discuss these issues.Design/methodology/approachThis study explored the styles of Mazu crown hats using Kansei engineering (KE). People generally use adjectives words to provide aesthetic evaluations. Fuzzy theory is suitable for processing linguistic problems that include vagueness, thereby providing a reasonable method of quantifying such aesthetic evaluations. Therefore, this study first established a fuzzy positioning model (FPM) of word evaluations for analysis. Factor analysis was used to obtain representative image adjectives that represented Mazu’s image. Fuzzy analysis methods were then employed to rank the various image adjectives through evaluation words and to determine the differences between adjectives. Finally, on the basis of image analysis results and expert suggestions, the crown hat was redesigned and its suitability verified.FindingsFour results were obtained. First, four image adjectives appropriate for representing Mazu’s image were identified, of which “noble and kind” is the most suitable. Second, fuzzy analysis was found to successfully rank style images. Third, the crown hat style and design characteristics suitable for Mazu were acquired. Fourth, the verification demonstrated that the redesign effectively enhanced the perceived image of the crown hat design.Originality/valueThis study employed KE to improve the design of a Mazu crown hat. The proposed FPM can aid the development of cultural and creative design.

In order to improve the attractiveness of social robot serving health interventions in public workspace, we propose a product design method with the combination of Style-generative adversarial network (StyleGAN) model and particle swarm optimisation-support vector regression (PSO-SVR). This paper aims to explore the modelling generation method of social robots for health intervention based on artificial intelligence generated content (AIGC) and a mapping model between the shape characteristics and users’ visual perception based on Kansei Engineering (KE). Firstly, to address the defects of typical KE over-reliance on existing samples, we introduce the StyleGAN model in AIGC to learn and train existing robots’ shape samples and generate new robots’ shape sample images. Secondly, the morphological deconstruction method is used to deconstruct the shape features of the new robot sample. Factor analysis (FA) is also used to reduce dimension and cluster emotional words and establish a Likert scale between the shape features of robots and users’ emotional vocabulary. Finally, particle swarm optimisation-support vector regression (PSO-SVR) is used to establish a mapping model between the shape features of social robots and the emotional images of users, thus obtaining the most attractive shape combination scheme. The research results showed that the StyleGAN model in AIGC can be used to assist industrial designers in creative expression and provide rich sample sources for KE; and the PSO-SVR of machine learning can be used to build a mapping model among users’ visual feelings, emotional images and shape features. In the end, we designed an attractive social robot for public health intervention.

Aims: The COVID-19 pandemic and consequent extreme restrictions imposed by governments across the world forced psychotherapists to abruptly change their working modality. The first aim of the current study was to assess psychotherapists’ self-perceptions (i.e., affective and cognitive perceptions about their self and their self in relation to clients) when providing telepsychotherapy during the first peak of the COVID-19 pandemic in Italy. The second aim was to explore the associations between psychotherapists’ self-perceptions, characteristics, and clinical practices.Method: An online survey was administered to 281 Italian licensed psychotherapists (Mage=45.15; SD=10.2; 83.6% female) between April 5 and May 10, 2020. The survey comprised ad-hoc questions that were designed to collect sociodemographic details and information related to working practices. Moreover, a semantic differential (SD) scale was developed to assess psychotherapists’ self-perceptions, and a factor analysis was performed from the SD items.Results: The SD scale showed an overall trend of positive psychotherapist self-perception during telepsychotherapy, despite reports of greater fatigue and directive and talkative behavior during sessions. Four SD factors accounted for 45% of the variance: “Affective Availability,” “Attitude Predisposition,” “Well-being,” and “Interventionism.” Scores on the first three factors were indicative of psychotherapists’ Positive vs. Negative self-perception. A comparison of the Positive and Negative attitudinal profiles using the chi-squared test with Yates’s correction and a Monte Carlo simulation found that psychotherapists with a Positive profile reported greater satisfaction with the telematic modality and were more likely to perceive that their clients were able to maintain privacy during sessions.Conclusion: The results suggest that Italian psychotherapists have been able to promptly adapt to the imposed telematic modality during the COVID-19 pandemic. However, they may have attempted to compensate for their physical distance from clients by intervening more during sessions. These findings may support psychotherapists who are currently practicing and inform future practitioners who are considering the use of telematic treatment as a routine component of psychotherapeutic care.

In recent years, a continuous and rapid evolution of the analysis’ processes, design, and industrial products’ production, take place. Additive technologies spreads, together with digital modeling systems’ diffusion and application, in the field of industrial design and into the market. The designers and entrepreneurs’ modus operandi is changing, according to the potentialities offered by the new digital tools (both knowingly and unconsciously). Factory and designers began to experiment, research and rethink products’ identity, linked to the potential offered by new materials, as well as new processes. Complex shapes control, printing process optimization, exasperation of customization factors, become substantial features to determine new consumer scenarios, and to radically rethink the product idea, starting from the user as a cultural and physical reference, with the main goal of determining competitive repositioning strategies of design-oriented businesses. The paper presents the results of a research based to the 3d design process applied to the fashion accessories’s sector, developed into the Department of Architecture, d’Annunzio University, Chieti-Pescara (Italy). The research has highlighted the benefits relating to the introduction of digital design tools and additive production processes in the filed of fashion. At the same time, the meanings of unique products (tailor made, specifically featured for user anthropometrics, flexible in different usability context, and ultimately highly customizable) for the user and investors.

Augmented reality (AR) is believed to be the next wave of online learning. New user experiences become possible to afford AR capabilities with the advent of powerful smartphones. Most studies related to the use of augmented reality in education focused on cognition with little consideration given to emotions which is important in learning. Therefore, this research aims to identify salient connections between emotions and design elements of augmented reality-based mobile learning material by applying Kansei Engineering (KE) approach. In this research, mobile augmented reality application related to the human heart was prepared to be used as a case study. Seven specimens of the mobile augmented reality application were evaluated with 55 emotions of Kansei Words (KW). 28 students from one of the public universities performed the evaluation experiment. The gathered data were then analyzed using Factor Analysis and Principal Component Analysis. The results revealed the important pillars of emotions or kansei semantic space emotions for augmented reality-based mobile learning materials. Based on Factor Analysis, it revealed four main pillars; professional-motivated, confused, wandering-thrilled and one additional pillar; trustable. Besides that, this research described design elements of augmented reality-based mobile learning material that might evoke specific emotions based on five identified pillars. Ultimately, this research is an attempt to guide the design with affective elements during preparation of augmented reality learning materials in the future.

The paper represents the research of a road landscape from hedonomic point of view, which is a necessary and important part of landscape sustainability. The proposed research method consists of preparative inquiry of the roadscape using Kansei engineering and SD (semantic differential) technique, and the main inquiry using multiple linear regression analysis. The application of the method to the landscape of Lithuanian highways let us identify the factors which influence the hedonomics of a road landscape.

The market share of small household appliances has grown tremendously in recent years. Varied innovation methods are applied in developing small household appliances, including Turkish Coffee Makers; however, Kansei Engineering has not yet been carried out in this field. This paper aims to conduct Kansei Engineering methodology on these machines to provide design inputs for industrial designers. The domain of the study is Turkish Coffee Makers with one pot and without a water tank, and the target is between 20–40 aged Turkish people. 382 participants attended the study, and 16 stimuli were utilised. The study methods are extracting Kansei words, selecting product properties, affinity diagram, SD Questionnaire, factor, descriptive, and PLS analyses. The results suggest that designers can generate Turkish Coffee Makers with Square with fillet as the top view, Trapezoid as the front view, C-shape cornered as the right view, and two colours as the main body colour; and design these products depending on the design factors of stylish, easy to use, joyful, trend follower, functional, desirable, youthful, dissimilar, and luxurious to succeed in the market. As a result, product designers might determine the product properties more efficiently via the findings of this study.

The objective of this research was to study the influencing factors related to the creativity and innovation skills of students in the field of industrial product design, and the population was defined as three hundred and nine students in the product design program at King Mongkut’s Institute of Technology Ladkrabang with the sample group comprising two hundred and seventy-five 1st–4th year students selected using stratified sampling. Additionally, structured interviews were used as the research tool (Cronbach’s alpha = 0.803), which was analyzed by Exploratory Factor Analysis and Confirmatory Factor Analysis. In this case, it was found from the EFA analysis that there were three components (KMO = 0.950): 1) the fundamental component of self-concept, 2) the consideration of the impact on others, and 3) the drive component that stimulates development, with the goodness of fit index as follows: χ^2 = 22.202, df = 26, relative χ^(2 )= .854, p-value = .678, RMSEA = .000, RMR = .010, GFI = .985, AGFI = .963, NFI = .994, TLI = 1.002, PGFI = .388, RFI = .987, AIC = 102.202. In this study, the composition from EFA was shown to be consistent with the CFA by having a structural equation model with a measurement model that fits well with the theoretical model of stimulating creativity and innovation. Moreover, it corresponds to the empirical data at a good level with the following values: χ^(2 )= 19.964, relative χ^(2 )= .768, p-value = .795, RMSEA = .000, GFI = .987, CFI = 1.000.
 
 Received: 9 February 2023 / Accepted: 20 April 2023 / Published: 5 May 2023