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.
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.
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