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Sailing toward sustainability is becoming the strategic focus of shipping firms. Drawing on organizational information processing theory (OIPT) and the theory of planned behavior (TPB), we investigated the impact of digital transformation (DT) on shipping firms’ sustainable management performance and the boundary conditions guiding this relationship.

The authors examined the hypotheses by employing hierarchical linear modeling on two-wave time-lagged data from 189 shipping firm employees in China.

The results suggest that a shipping firm’s DT is positively associated with its sustainable management performance and that the relationship is strengthened by having better cross-functional and customer coordination mechanisms. Furthermore, our three-way interaction analyses show that while injunctive norms in a shipping firm’s networks can strengthen the contingency roles of both cross-functional and customer coordination mechanisms, descriptive norms alone significantly influence customer coordination.

Drawing on organizational information processing and planned behavior theories, the present research provides new insights into leveraging DT for sailing toward sustainable success. Moreover, this study extends the current understandings of the boundary conditions of the relationship between DT and sustainable management performance by showing the two-way and three-way interaction effects of coordination mechanisms and subjective norms. The findings of the present research can be utilized as effective strategies for promoting sustainable management performance.

The purpose of this paper is to propose and demonstrate how Tourism2vec, an adaptation of a natural language processing technique Word2vec, can serve as a tool to investigate tourism spatio-temporal behavior and quantifying tourism dynamics.

Tourism2vec, the proposed destination-tourist embedding model that learns from tourist spatio-temporal behavior is introduced, assessed and applied. Mobile positioning data from international tourists visiting Tuscany are used to construct travel itineraries, which are subsequently analyzed by applying the proposed algorithm. Locations and tourist types are then clustered according to travel patterns.

Municipalities that are similar in terms of their scores of their neural embeddings tend to have a greater number of attractions than those geographically close. Moreover, clusters of municipalities obtained from the K-means algorithm do not entirely align with the provincial administrative segmentation.

Shared leadership has received significant empirical and theoretical attention in the project management literature. However, a dearth of studies reveals how shared leadership promotes project performance. Drawing on the theory of conservation of resources, this research proposes a serial mediation model that investigates the relationship between shared leadership and project performance through team failure learning and team resilience.

A field study was conducted that surveyed 79 project teams in various industries (comprising 380 project team members and 79 project managers) using a multisource, time-lagged survey design.

Our findings show that shared leadership has a positive impact on project performance. More importantly, team failure learning and team resilience play sequential mediating roles in the relationship between shared leadership and project performance.

This research offers new ways for project managers to manage project performance effectively. Project managers are encouraged to recognize the benefits of shared leadership. To do this, they should facilitate team failure learning and improve team resilience, which serves to boost project performance.

This research provides a novel perspective on how shared leadership influences project performance. To the best of our knowledge, we are among the first to explore the serial mediating effects of team failure learning and team resilience on the relationship between shared leadership and project performance.