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User experience is the focus of interaction design, and designing for errors is crucial for improving user experience. One method of designing for errors is to identify human errors and then initiate corrective actions on high‐risk errors to reduce their adverse effects. In this study, we proposed a hybrid approach for risk analysis of human error concerning user experience of interactive systems. In this approach, systematic human error reduction and prediction approach (SHERPA) is first adopted to identify human error concerning user experience. Subsequently, failure mode and effect analysis (FMEA) is used to analyze the risk factors of the error, including occurrence, severity, and detection. Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is then used to calculate the risk priority number to rank the errors. Finally, corrective actions for high‐risk errors are recommended. An in‐vehicle information system was used to demonstrate the proposed approach. The results indicated that the proposed approach can effectively analyze the risk of human error concerning user experience and be used as a universal reliability approach for improving user experience in interaction design.

User experience (UX), which encompasses all aspects of a user’s interaction with an interactive product, has been recognized as central to interaction design. This paper proposes a Taguchi‐based hybrid approach to realize the optimal UX design. In this approach, design analysis is first used to identify design patterns and UX characteristics. According to the results, a Taguchi experiment is conducted and the signal‐to‐noise ratios are computed. Subsequently, the preference weights for the UX characteristics are obtained by using analytical hierarchy process‐based group decision making. A multiperformance characteristic index is then defined based on the gray relational grade (GRG) obtained through gray relational analysis. On the basis of the GRG, the optimal design can be obtained. A mobile health application design was used to demonstrate the proposed approach. The results show that this approach can effectively enhance UX quality and be used as a universal design approach for optimizing UX.

In today’s competitive market, industrial product form design is moving towards being consumer centric. Affective responses relate to customers’ affective needs and are receiving increasing attention. To design a product form that can appeal to consumers, designers should consider multiple affective responses (MARs). This paper proposes a robust design approach that uses a fuzzy-based hybrid Taguchi method to derive the optimal product form design concerning MARs. First, design analysis is used to identify design variables and MARs. According to the results, a Taguchi experiment is designed in which fuzzy sets are used to measure the MARs; then, signal-to-noise (S/N) ratios are calculated. Subsequently, a fuzzy questionnaire with multiple answers is employed to acquire consumers’ preference weights for MARs, following which Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is adopted to transform the multiple S/N ratios into a multiperformance characteristic index (MPCI). On the basis of the MPCI, the effects of design variables are identified through analysis of variance and the response table and the response graph are obtained. Consequently, the optimal form design is achieved. A car profile design was used as an example to demonstrate the proposed approach. The results indicate that this approach can effectively improve consumers’ affective response qualities and can be used as a robust design approach to optimize product form design.

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