Towards a kansei-based user modeling methodology for eco-design

We propose here to highlight the benefits of building a framework linking Kansei Design (KD), User Centered Design (UCD) and Eco-design, as the correlation between these fields is barely explored in research at the current time. Therefore, we believe Kansei Design could serve the goal of achieving more sustainable products by setting up an accurate understanding of the user in terms of ecological awareness, and consequently enhancing performance in the Eco-design process. In the same way, we will consider the means-end chain approach inspired from marketing research, as it is useful for identifying ecological values, mapping associated functions and defining suitable design solutions. Information gathered will serve as entry data for conducting scenario-based design, and supporting the development of an Eco-friendly User Centered Design methodology (EcoUCD).ANR-ECOUS

Mining quality determinants of product-service systems from user-generated contents

The concurrent availability of an ever-increasing volume of User-Generated Content (UGC) and text mining techniques has enabled methods to conduct both qualitative and quantitative research that was unimaginable a few years ago. These investigations have proved to generate interesting insights with potential implications in manufacturing and engineering design. This paper introduces a novel practical methodology to address the following research issue: how to infer the quality determinants of a Product-Service System (PSS) from UGCs? Analyzing a sample of UGCs by means of a topic modelling method, the idea of this study is to produce and examine the set of determinants relevant to the perception of the quality of a specific PSS. The application of the proposed approach is exemplified on a specific use-oriented PSS: car-sharing

Application of Natural Language Processing to Determine User Satisfaction in Public Services

Research on customer satisfaction has increased substantially in recent years. However, the relative importance and relationships between different determinants of satisfaction remains uncertain. Moreover, quantitative studies to date tend to test for significance of pre-determined factors thought to have an influence with no scalable means to identify other causes of user satisfaction. The gaps in knowledge make it difficult to use available knowledge on user preference for public service improvement. Meanwhile, digital technology development has enabled new methods to collect user feedback, for example through online forums where users can comment freely on their experience. New tools are needed to analyze large volumes of such feedback. Use of topic models is proposed as a feasible solution to aggregate open-ended user opinions that can be easily deployed in the public sector. Generated insights can contribute to a more inclusive decision-making process in public service provision. This novel methodological approach is applied to a case of service reviews of publicly-funded primary care practices in England. Findings from the analysis of 145,000 reviews covering almost 7,700 primary care centers indicate that the quality of interactions with staff and bureaucratic exigencies are the key issues driving user satisfaction across England