Individual products and models on the market must be specifically differentiated from the rest to meet user demand. In terms of consumer purchasing behaviour, consumers increasingly base their decisions on subjective terms or the impression that the product leaves on them, both in terms of functionality, usability, safety, and price adequacy, and regarding the emotions and feelings that it triggers in them. This demand has lead both Asia and Europe to implement new methodologies to develop new products, such as “emotional design” or Kansei engineering. This paper presents a systematic literature review (SLR) on the most relevant methodologies based on Kansei engineering and their relevant results in the specific discipline of product design, addressing these five questions: (RQ1) How many studies on KE and emotional design are there in the Scopus and Web of Science (WoS) databases from 1995 to February 2021? (RQ2) Which research topics and types of KE are addressed? (RQ3) Who is leading the research on KE and emotional design? (RQ4) What are the benefits and drawbacks of using and applying the methodology? (RQ5) What are the limitations of the current research? We analysed 87 studies focusing on the Kansei methodology used for product design and device technologies (e.g., shape design, actuators, sensors, structure) and aesthetic aspects (e.g., Kansei words selection, the quantification of measured emotions of results, and detected shortcomings), and provided the database with all the collected information. One identified and highlighted sector in the results is the electronic–technological-device sector. Results confirm that this type of methodology has a majority and direct application in these sectors, and they are widely represented in the automotive and electronics industries. Lastly, this SLR provides researchers with a guide for comparative emotional-design work, and facilitates future designers who want to implement emotional design in their work by selecting the specific type according to the results of the SLR.

Specific disciplines in engineering, such as manufacturing processes, require students in their academic stage to pay special attention, given the possible changes that may affect the acquisition of competencies. In an environment of uncertainty, such as a global pandemic, teaching must adapt without losing the effective delivery of content to students. The health and safety measures applied during the first months of the pandemic led to a different type of teaching to that which had customarily been applied, such as synchronous and asynchronous methodologies defined by the university’s governing bodies, where face-to-face and online methodologies coexisted in the same academic year. All of this avoided interrupting the academic year. This paper studies the results achieved in this uncertain environment, extends them and compares them with the following year, where only the face-to-face methodology was applied to the students enrolled in Manufacturing Processes 2 at the Centro Universitario de Mérida within the Bachelor’s Degree in Design Engineering and New Product Development (Grado en Ingeniería en Diseño y Desarrollo de Nuevos Productos -GIDIDP-). An analysis of variance (ANOVA) was applied to the data obtained to locate the significant differences between the samples taken in the first year with online and face-to-face teaching methodologies and those taken in the second year with an exclusively face-to-face methodology. When comparing the results, maintaining face-to-face teaching proved essential, as it contributes towards achieving better marks or maintaining the level. However, online methodologies also help as an additional tool to acquire other knowledge and specific skills in these technical engineering subjects, specifically those dealing with the manufacturing processes addressed in this study.

The entertainment industry undergoes constant changes, and video games, along with the ways people enjoy them, evolve dynamically. In this context, there arises a need to innovate in areas such as user–game interaction and the design of conventional controllers to keep up with these transformations. This study has found that the design requirements of the external geometry of video game controllers significantly impact users’ purchasing decisions, who often rely on their sensations and emotions. The primary aim of this research has been to demonstrate that it is possible to develop a specific methodology to establish design guidelines that evaluate geometry and ergonomic aspects, considering users’ emotional needs. To achieve this goal, the Kansei methodology has been employed, an engineering discipline that focuses on product design based on emotional interaction and user sensations when using them. Through advanced statistical techniques such as principal component analysis and linear regression, the set of observations has been reduced and a robust predictive model has been developed. Following this methodological approach, surveys and field studies have been conducted, thus differentiating the project from a conventional engineering approach in various stages. Special attention has been paid to the tactile part of the controller, especially its casing. After thorough analysis, the redesigned casing, incorporating improvements derived from statistical analyses, has been compared to existing market models. The results obtained show a significant improvement compared to existing market models, particularly highlighting enhancements in functional characteristics and ergonomic design, enabling comfortable use for individuals with different hand sizes and preventing the grip surface from being slippery. In summary, this work supports the effectiveness of the Kansei methodology as an approach to adapting product design to users’ perceptions and emotional needs.

The accelerated development of smart devices and the increased demand for technological services have given rise to new services with great potential for development in the market. Applications for museums are no exception, and more and more institutions are including such solutions in the cultural industry. However, there is still much to be developed, given the difficulties that people with disabilities have in accessing them. In this work were studied the characteristics that the future application (App) of the Helga de Alvear Museum in Cáceres should have so that it can be used satisfactorily by the maximum number of visitors, regardless of their sensory, intellectual, or motor capacity. Kansei Engineering has identified the emotions and sensations that favour the interaction of users with the application and which have been converted into functionalities and design requirements in order to present a graphic proposal and structure for the App. The appearance and functioning of this App are presented visually, supported by an initial theoretical and research part that has helped to identify the rest of the specific objectives. Some specifications to take into account are functional, non-functional, programming, sequence diagrams, and basic interface requirements. This application has two generic and five specific itineraries to solve the disabilities mentioned in this paper, making it accessible to the different groups. The importance of obtaining an equivalence between the essential requirements of the standard and the basic design specifications that should regulate the work process resides not only in having a direct equivalence but also in obtaining guidelines for other designers who want to face extensive regulation and need help to interpret it and be able to make decisions straightforwardly.

Kansei Engineering enables users’ emotional perceptions to be incorporated into the design process; however, its integration with sustainability and cost criteria remains limited, particularly in the field of museum exhibition design. The aim of this research is to evaluate a design-support framework that integrates Kansei Engineering, statistical analysis, and supervised machine learning to jointly analyze perceived desirability, perceived sustainability, and perceived economic efficiency during the early stages of museum display-case design and alternative selection. As a case study, four museum display case configurations were developed, differentiated primarily by their materials and construction solutions, and evaluated by 150 participants using twelve Kansei semantic pairs. Different algorithms were compared for predicting desirability, with Random Forest achieving the best performance under participant-level validation (RMSE = 0.711; MAE = 0.546; MAPE = 11.81%; $R^2=0.763$), and reliability emerging as the main predictor. Desirability showed an overall positive association with perceived sustainability ($\rho =0.291$) and a negative association with perceived economic efficiency ($\rho =-0.524$); however, both relationships were conditioned by the alternative evaluated. When used in isolation, desirability showed limited predictive ability for perceived sustainability ($R^2=0.095$; $RMSE=1.240$) and perceived economic efficiency ($R^2=0.249$; $RMSE=1.198$). When the different design alternatives were incorporated into the models, predictive performance increased to approximately $R^2=0.75$ and $R^2=0.66$, respectively. The results indicate that desirability, perceived sustainability, and perceived economic efficiency should be addressed jointly as a multicriteria problem. The proposed model therefore provides a tool for comparing configurations and guiding the generation and selection of alternatives toward solutions that balance emotional acceptance, sustainability, and economic considerations from the early stages of the design process.