Practitioners deconstructing and reconstructing practices when responding to the implementation of BIM

Abstract

When managers are implementing change, practitioners are sometimes seen as the receivers of the change. However, practitioners often need to actively create the changes to daily practices because managers might not be familiar with the practices. Building information modelling (BIM), an important driver of organizational change, requires change not only by bringing new technology into use but also to the practices of collaboration between different professions. In their daily work, practitioners can create new practices through reflective learning. We have a limited understanding of how practitioners are actively involved in a change through reflective learning when implementing BIM. To address this limitation, we conducted a qualitative case study. Our primary data consist of interviews, which were analysed with insights from philosophy. We identified two methods of reflective learning from the data: deconstruction and reconstruction. Deconstruction occurs when the new requirements for the practices are based on different ideas of work, which asks practitioners to change their old ideas before creating new practices. Reconstruction does not necessarily require changes to the basic ideas of work but changes are seen more as improvements. Our research contributes to construction management literature by linking the reflective learning of practitioners to the change caused by BIM.

Keywords:

• Building information modelling
• change
• learning
• practitioner
• reflect.

Acknowledgement

We gratefully acknowledge the individuals in the construction project who enabled us to collect the data. The study was conducted as part of RYM PRE Model Nova and CoCoNet research projects. RYM PRE Model Nova belonged to the Built Environment Process Re-engineering research programme, coordinated by the RYM Ltd. in Finland. The Finnish Funding Agency for Innovation (for RYM PRE Model Nova project) with partner companies and the Academy of Finland (for CoCoNet project) financially supported the research, which is gratefully acknowledged.

Additional information

Funding

This work was supported by the Tekes – the Finnish Funding Agency for Innovation [1954/31/2010]; The Academy of Finland [264079].