Optimized Visualization of Building Fire Risks through Mobile Application

This dataset embodies the findings of a user-oriented study leveraging the Kano model, an innovative product development and customer satisfaction paradigm introduced by Noriaki Kano. The model categorizes product attributes into six types: Must-Be, Attractive, One-Dimensional, Indifferent, Questionable, and Reverse, thereby providing comprehensive insight into how these attributes affect user satisfaction and dissatisfaction.

The Kano model enables a dual assessment approach, evaluating attributes based on their 'functionality' (presence) and 'dysfunctionality' (absence). For example, a 'Must-be' attribute causes dissatisfaction when absent, but its presence doesn't necessarily enhance satisfaction. In contrast, an 'Attractive' attribute, when present, significantly bolsters satisfaction, but its absence doesn't result in dissatisfaction.

In this study, we harnessed the Kano method, which entails the use of a specific Kano questionnaire, to determine critical product features based on users' perceptions. Each feature was questioned in two contexts: functionality (where the requirement is fulfilled) and dysfunctionality (where the requirement is not fulfilled). User responses, graded on a five-point scale ranging from "This would make me very happy" to "This would bother me a lot," facilitated us in understanding their requirements.

We applied two techniques to interpret the data obtained from the Kano questionnaire: Discrete and Continuous evaluation.

Discrete Evaluation: This approach categorizes each product attribute into one of the Kano categories, as indicated by user responses. Features are then sorted by response frequency. Additionally, we utilized the Fong test - a statistical method extraneous to the Kano model, but effective in determining the statistical significance of the categorization. This test differentiates the most common from the second most common responses for feature classification.

Continuous Evaluation: This methodology delivers a more nuanced perspective, accounting for satisfaction and dissatisfaction factors for each product attribute. This allows us to precisely determine how the presence or absence of an important feature impacts user satisfaction, aiding in identifying major contributors to overall user satisfaction or dissatisfaction.

The file titled ‘Overview_Significant_Fire_Probability_Features_Kano_groups' elucidates the discrete evaluation procedure, highlighting the fire probability features with a significant influence on user satisfaction as determined by the Fong test. The ‘Kano_items_eng.png ' file displays the items from the Kano questionnaire used in this study. These items were randomly shown to participants in a functional or dysfunctional context. The user responses, varying from "This would make me very happy" (indicating a feature considered desirable) to "This would bother me a lot" (implying dissatisfaction in the absence of the feature), are instrumental in understanding user preferences and needs.