This paper investigates commuter transportation choices in Linköping, Sweden, to inform the design of sustainable and user-friendly solutions. The study uses interviews, observations, and travel diaries to understand factors influencing mode selection, revealing a prevalence of car usage and significant challenges with public transport. Based on this analysis, three commuter personas were developed. Student groups then used these personas to generate design solutions aimed at lowering barriers to public transport adoption and incentivizing its use.  

Kansei Engineering is a methodology seeking to grasp customers’ feelings and subjective affective opinion of products as well as turning their affective needs into suitable product concepts. The procedure is rather complex and requires a fair amount of interdisciplinary expertise and experience in order to achieve reliable results. The high threshold to learn those techniques is preventing many practitioners from applying it. There are, however, software packages that have supported product designers to perform Kansei Engineering evaluations without being experts in the field of statistical mathematics. This paper will give a short overview on Kansei procedure, and the methods attached to it, and shows present and future areas of application for computerized tools in Kansei Engineering.

The KEER 2018 is the 7th event in a Conference Series held under the auspices of theJapan Society of Kansei Engineering (JSKE), theTaiwan Institute of Kansei (TIK), and theEuropean Kansei Group (EKG).Malaysia Association of Kansei Engineering (MAKE) is the local organizer of this conference, strongly supported by Research Interest Group of Kansei / Affective Engineering (RIG KAE), Universiti Teknologi MARA (UiTM), UiTM Sarawak, Sarawak Convention Bureau (SCB), Malaysia Convention & Exhibition Bureau (MyCEB), Ministry of Higher Education (MoHE), and Kolej Univeristi Poly-Tech MARA. KEER 2018 will be held in Kuching Sarawak, Malaysia. KEER 2018 conference theme is “Go Green with Emotion” reflecting the growing spectrum in green design and technology through Kansei and Emotion approach towards sustainable economy, society, lifestyle and nature.​

Emotion is the new fashion! KEER 2018 provides a platform for everyone to gather, share, and learn how Kansei is related to emotion, and how Kansei Engineering is used to engineer emotion, what more, in the land of Orang Utan and Rafflessia. KEER  2018 is inviting authors from multidisciplinary fields to submit high quality and unpublished papers. Submissions are focused on human experience with topics related, but not limited, to Kansei and Emotion. KEER 2018 also provides a platform for researchers, innovators, academicians, practitioners, and other interested parties from diverse culture, background, and expertise, to gather,learn, and share different viewpoints in a warm, rich and open-minded context.Join us in our keynote session, parallel session, workshop, poster session, video festival, and exhibition.

Socioeconomic and demographic data of participants are often collected when performing a Kansei Engineering study for stratification purposes. This paper offers an alternative stratification procedure, directly based on the emotional response that participants give to prototypes. This approach can deliver groups that are more meaningful for the Kansei Engineering study. Socioeconomic and demographic data (among other kinds of data) can then be used to characterize the obtained emotional groups.

The Scandinavian confectionery market is dominated by three major manufacturers, of whom two are affiliates of international conglomerates and one is a domestic producer. The aim of this study was to map the affective impression of chocolate bars’ exterior and interior and give suggestions for a coherent design. Kansei Engineering was used for this. Products were rated on AVI scales with relevant Kansei words, resulting in affective profile graphs. These data were processed treated using Factor Analysis. Four factors were retrieved: Attraction, Life-Style, Familiarity and Snack. Multiple Regression Analysis and Rough Set Analysis were applied to map relationships between physical attributes and affective values. Attributes with significant affective impact are size, shape, color: and brand (packaging) and Surface roughness, Separation and top- and side-angles (shape). The data were used for successful product development and a product series with coherent attributes was developed. One product is used to illustrate the process. Kansei Engineering proved to be suitable for this task although the results may be biased since the evaluation is based on visual impression only.

Kansei or Affective Engineering is a relatively new research field in the West.Linköping University in Sweden has been pioneering research and applicationwithin Kansei Engineering since 1999. Several companies have cooperated indifferent Kansei studies, for example Toyota/BT, Volvo, Saab, Scania. In some of theearly studies, there were difficulties to apply the methodology. Reasons for thisincluded shortage of competence within affective design in European organizations,but also the fact that incitements for improvement of product design seemed to belacking. One of the problems applying the methodology was that Europeanparticipants in the studies did not accept to make a vast number of ratings duringlong time periods. Japanese researchers used 5-point semantic differentialquestionnaires and up to 300 rating-scales per participant and product. In order toovercome this problem, a modification of the rating scales was developed. Hence,data reduction methods such as factor analysis, affinity diagram and Pareto chartswere tested and validated in order to reduce the number of Kansei words andproduct samples used, without compromising the validity of the result. Thisapproach eventually resulted in the development of a universal Kansei EngineeringSoftware (KESo) which reduces the time needed for each Kansei Engineering study.Another objective for our research has been to develop and validate methods forincomplete data collection, i.e. a prioritization of product attributes. Another resultfrom the cooperation with industrial companies is that the companies stronglyemphasised that product development studies need to be less time and resourceconsuming.Keywords:

Evaluations of products based on visual stimuli are at the same time both subjective and important. The aim of this study was to examine the relationship between the visual properties of wood flooring and peoples reactions to computer visualization of interior wood products. The research strategy involved showing digital pictures of the same room, but with different wood floorings. The impressions of potential consumers were measured by means of rating scales for each descriptive word. This was done using the method of Kansei engineering, in which statistical connections between properties and semantics (descriptions) were analyzed. The research presented here contributes to theory and practice in two important ways. First and most important, the study shows that the chosen method is suitable for measuring peoples preferences on visualizations of interior wood. Second, the results indicate that certain properties are important for a floor to be judged as "good-looking" and others for a floor to be deemed "modern" or "vivid."