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The purpose of this paper is to advance our understanding of the roles that service employees’ responses to high job demands play in service innovation, by examining the effects that service employees’ motivational orientation in self-regulation (regulatory focus) and their emotional labour strategy have on their creativity.

By integrating regulatory focus theory and emotion regulation theory, the authors developed a theoretical model to propose the links between promotion and prevention regulatory foci, different emotional labour strategies and frontline employee creativity. The research hypotheses were tested using hierarchical linear model based on data collected from 304 frontline employees and 72 supervisors in 51 restaurants.

The results showed that promotion focus was positively related to frontline employee creativity while prevention focus was negatively related to it. In addition, both emotional labour strategies (deep acting and surface acting) mediated the effect of promotion focus on frontline employee creativity. Surface acting mediated the effect of prevention focus on frontline employee creativity.

This is the first research conducted to explain, from a self-regulatory perspective, the influence that is exerted on service employees’ service innovation by their responses to high job demands. The findings identify the effects that service employees’ promotion focus or prevention focus in self-regulation have on their creativity, and the data unravel the role of emotional labour strategy as the mediating mechanism that explains the influence of regulatory focus on service employee creativity. On the basis of the findings, managerial directions are offered with regard to managing service employees’ regulatory focus and emotional labour, with a view to enhancing the creativity and innovation within a service organisation.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.