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In this paper, the authors propose the user evaluation support methods for IGA (Interactive Genetic Algorithm)-based 3D room layout generation. Although IGA is useful for applying the user preferences to the solution, IGA-based systems force users to evaluate a lot of individuals, causing the fatigue of operators. Therefore, we adopted the following methods in order to cope with the problem:

(a) Prediction of user preferences with a conjoint analysis.

(b) Individuals clustering with a self-organizing map.

To make a 3D scene such as a furniture layout, the IGA-based 3D room layout system is very helpful because it requires easy 3D graphics and manipulation only. The authors have been developing a web-based system that optimizes 3D room layouts based on user preferences. Finally, we tested the usefulness of our system with the demonstration, and had positive outcomes.

An innovative process that assists users in non-quantitative problem solving is presented. The process, called Ramic, employs the idea of psychological projection in an innovative way to help users focus, express and think through problems. Its applicability ranges from assisting with simple non-analytic decision-making to developing and assessing strategies.

In the virtual realm, harnessing the power of psychological projection for problem solving has been attempted in the form of a process called Sand Tray. Attempts at virtualization have garnered little traction potentially due to encumbrance of the interface. Ramic, in contrast, is innately set up for digital use through a relatively simple interface.

A key question this paper explores is how to quantitatively measure the value of Ramic in relation to the well-established process of Sand Tray. Even though these processes operate on qualitative problems, a preference analysis tool called conjoint analysis is used to build an experiment and derive specific user utilities for each process.

To perform the study, both processes required testing in the physical domain. A 32-person study is presented and indicates the Ramic projective process to have a 23% higher user utility than Sand Tray in the area of problem solving. As such, it presents an opportunity to explore a new way in which individuals can approach non-analytical problem solving and how computers can assist them in the task.

Product packaging has a great influence on customers’ decision-making and shapes purchase intentions. The graphic message is the crucial component of this impact. Digital presentations of goods are ubiquitous, therefore understanding how graphical features influence customer decisions is of enormous theoretical and practical importance. Despite the interest, the role of specific factors and their combinations is still unclear, especially if medium-involvement products are concerned. Since only a few studies have considered this context, this research examines how eight variants of a digital presentation of cordless kettle packaging influence purchase willingness, which was derived from pairwise comparisons using eigenvectors. The experimental conditions differed in three factors: the existence of a product graphical context, a brief or extended product description, and white or black packaging background color. Results of analyses of variance and conjoint analyses revealed a significant role of all examined effects, with the background color being the least influential. The best-rated designs included graphical context and extended textual information. There were also some meaningful gender-related differences revealed by conjoint analyses. The black background color was much more important for females than males. The outcomes broaden our knowledge on people’s perception of packaging design graphical factors, and their impact on purchase decisions.

Under what circumstance do entrepreneurs decide to discover entrepreneurial opportunities to start new businesses? Informational economics suggests when entrepreneurs possess prior specific knowledge, they decide to discover opportunities. This paper contributes to informational economics perspective by taking resource dependence theory into consideration. Utilizing a conjoint experiment and a multilevel analysis of 66 student entrepreneurs, we found that students’ prior specific knowledge significantly influences students’ decision to discover opportunities. Further, we found that power imbalance moderates the relationship between prior specific knowledge and students’ decisions to discover opportunities. Our paper has theoretical implications and practical implications for entrepreneurs, educators and policy makers.

The paper summarizes the results of a fundamental research project to understand the perception of high-end products by consumers. The first part consisted of a series of in-depth qualitative interviews with over 75 global leaders of luxury and premium companies, star designers and thought leaders. The analysis of the collected data identified five dimensions of high-end offerings, with each dimension having a unique set of four factors. The second part included a massive quantitative (based on Rule Developing Experimentation) survey conducted in the US, UK, Italy and China with about 1800 qualified middle- to upper-class respondents participating in a total of 20 distinct conjoint-based surveys to discover the driving forces behind their perceptions of high-end products. This paper considers in depth one of the five dimensions — leadership and innovation. The analysis of the quantitative part includes mind-set segmentation and demographic subgroups. The research addresses one aspect of today's big question: "How can global brands migrate from being cost-driven commodities to higher margins and profits?" The answer is in the high-end.

The proposed consumer-driven innovation approach allows for the creation of individual communications with heterogeneous customers. It utilizes Rule Developing Experimentation (a modified conjoint analysis-based approach) to create a database of messages specific to the product and to segment consumers based on the patterns of individual utilities assigned to the different test elements. The paper introduces a new approach to identify a small subset of classification messages that allows for an actionable and parsimonious classification of any new population into pattern-based segments to achieve better targeting.

The approach is demonstrated by a case study of identifying segment membership for better messages targeting prospective customers of a KIA car dealership.