When Two Worlds Collide: Understanding Group Dynamics During the Adoption of Big Data Analytics
Angela Graf et al.
What the paper says
The adoption of digital technologies transforms not only technical infrastructures but also social interaction and, in particular, collaboration within organizations. This study explores group dynamics during digital technology adoption, using a Big Data Analytics (BDA) adoption project as its empirical setting. While prior research has emphasized the role of BDA in organizational change, it has largely overlooked the group level, where BDA’s potential unfolds through interdisciplinary and cross-functional collaboration between business experts and data science experts. Based on an interpretative case study conducted at an international manufacturing and retail company, we examine how cross-functional teams composed of business experts and data science experts interact throughout a BDA project. Drawing on social identity theory and Bourdieu’s theory of practice, we not only identify observable group practices but also unpack the underlying dispositions and power relations that drive these dynamics. We identify a set of recurring group practices that emerge both between the two subgroups and within the team as a whole. While the subgroups maintain symbolic distance through mutual stereotyping, gatekeeping, and avoidance of responsibility, external organizational pressures trigger temporary alignment in the form of joint practices aimed at deflecting criticism. Our data further reveal that these practices are shaped by underlying group habitus and symbolic power positioning. The study contributes to a more nuanced understanding of group dynamics in digital innovation contexts by demonstrating how latent dispositions and symbolic power asymmetries shape collaboration in cross-functional teams. It also illustrates how in-group cohesion and out-group demarcation can both impede and stabilize project trajectories. Finally, the findings offer practical insights for organizations seeking to strengthen interdisciplinary and cross-functional collaboration during digital technology adoption.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| 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.