Moving towards a data-driven approach to self-leadership: exploring the combination of app-based reflection diaries and data-based ideation techniques
Christian Hoßbach et al.
What the paper says
Responding to the rapidly changing nature of work in organisations, self-leadership becomes an increasingly relevant competence. Although a lot of approaches for fostering self-leadership exist, they fall short of actualising technological potential for enabling people to derive self-leadership strategies based on systematic data collection. We present a data-driven approach to self-leadership that combines app-based reflection diaries with data-based ideation techniques and develop a prototypical intervention design to test its effectiveness. A randomised controlled field intervention with 61 students at a German university who needed to cope with the frequently changing study conditions during the COVID-19 pandemic provided initial support for its positive effects on self-leadership, creative self-efficacy, and resilience. An exploratory analysis of the daily reflection data provided further insights into potential mechanisms involved in this process. We discuss these findings to lay out an agenda for future research exploring data-driven approaches to self-leadership and their practical applications.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.47 × 0.4 = 0.19 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.