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Drawing on conservation of resources theory, this study aims to develop a resource-based model depicting a decreased level of psychological resourcefulness – relational energy, as a novel explanatory mechanism that accounts for the harm of abusive supervision, and we further investigate the role of leader humor as a boundary condition.

We applied multilevel path analysis to test our hypotheses with three-time-point survey data collected from 226 supervisor-employee dyads in a telecommunication company in China across six months.

Our results show that abusive supervision is negatively related to employee relational energy, leading to a subsequent decline in employee job performance. The predictions of the depleting effects get alleviated by leader humor.

This study foregrounds the importance of employee relationship management in the workplace and reveals that some abusive supervisors may manage to sustain employee performance and relational energy by using humor in their interactions, which necessitates immediate intervention.

These findings offer novel insights into the deleterious impact of abusive supervision by demonstrating the critical role of relational energy in dyadic interactions. We also reveal the potential dark side of leader humor in the context of abuse in the workplace.

The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.