User experience plays an indispensable role in intelligent product design. Building a system for user research, capturing firsthand information from users and turning insights into achievable product design solutions is the key to innovation. This article introduces service design into product design and studies the design cue construction method through intelligent product design case. First, the authors capture customer touchpoints in the process of user interaction with the product by observing the user behavior and perform the correlation analysis of the customer touchpoint to obtain the user’s complaints and dissatisfaction. Second, the authors use positive creation theory to transform requirements and turn the complaints collected in user research into achievable functional requirements. Third, the authors use the KANO model for sensitivity analysis of functional requirements and select high-sensitivity requirements for priority development. Finally, using the service design innovation methods to analyze the user experience and stakeholders, the design cue map can be exported, and a new service system was established to enhance the overall user experience.

Introduction: The telecommuting experience and job performance have been significantly impacted by the COVID-19 pandemic, and job performance stability of telecommuting employees has become a critical concern. Objective: A decision model for telecommuting experience service design was constructed based on a backpropagation (BP) neural network to provide a theoretical basis for enterprises to evaluate telework performance and the psychological health of employees. Methods: The analytic hierarchy process (AHP) was used to determine the core stakeholders. The grey relational analysis (GRA) method and the NASA Task Load Index (NASA-TLX) scale were used to measure the factors affecting employees’ telecommuting experience and job performance. A BP neural network relationship model of employees’ telecommuting experience was established to predict its impact on employees’ job performance. Results: Based on the model prediction results, a service system map was created, and the potential to enhance the telework performance of employees was evaluated. Discussion: It was concluded that the factors affecting the telecommuting experience were diverse, but emotions had the dominant influence. Significant positive correlations were found between emotional impact and temporal perception, execution difficulty, and communication barriers. Conclusion: The proposed decision model for telecommuting experience service design accurately predicted the impact of telecommuting efficiency, providing an effective approach for innovative remote management.

Customer perception is an important consideration factor in evaluating the quality of human-computer interaction services. Sustainable user experiences and marketing strategies can be created by analyzing customer perception. By understanding consumer satisfaction with product services in the customer perception area, appropriate product service failure prevention strategies can be formulated. A service failure evaluation model is proposed in this study, which considers the customer tolerance area to accurately evaluate consumers’ behavioral experiences from purchasing to using products. The concept of tolerance area is introduced, and a combination of the fuzzy Failure Mode and Effect Analysis (FMEA) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to construct a human-computer interaction service failure evaluation model. Potential service failure factors of smart speakers are accurately evaluated by this model, and these service failure factors are ranked within the tolerance area. The research identifies voice misinterpretation and signal connectivity issues as the primary risk factors impacting the quality of human-computer interaction for smart speakers. The application of this method not only enhances the evaluation of smart speaker human-computer interaction services quality but also aids in the precise identification and prioritization of critical failure modes. The proposed service failure prevention strategies can reduce consumer dissatisfaction and provide innovative references for smart product design and marketing. The findings bolster empirical evidence for service failure prevention strategies in smart products and pave the way for novel perspectives on enhancing the quality of human-computer interaction services.

Adapting to working from home caused physical and psychological difficulties, leading to work–family imbalance and lower employee performance during the COVID-19 pandemic. This study intends to identify the relationship between variables affecting telecommuting experience and improve employees’ perceived organizational support by constructing a balanced model of telecommuting experience. An online questionnaire survey was conducted with 142 employees from different organizations telecommuting during the epidemic in Xi’an. The NASA-TLX scale was used to quantitatively evaluate the cognitive load of employees working from home, and the Analytic Hierarchy Process method was applied to map negative experience factors with cognitive load to obtain the weight value of each factor. Finally, a balanced model of telecommuting experience was constructed through a system map. The results show that mental demand was the key factor affecting employees’ telecommuting experience. A good telecollaboration system could effectively manage work tasks and reduce the psychological load of employees. Frustration and temporal demand also significantly affected employees’ telecommuting experience, mainly due to work–family conflict. Adopting flexible work hours and organizing online sharing activities could reshape employees’ social relationships with their families and colleagues, effectively improving the telecommuting experience. The empirical study validated the effectiveness of the telecommuting experience balance model.