Understanding Digital Transformations of Construction Firms: An Institutional Work Perspective
S. Sreelakshmi & Ashwin Mahalingam
Abstract
Digital technologies, such as building information modeling (BIM), have been gaining traction in the construction industry. Various researchers have worked on identifying the critical factors in aiding or preventing technology adoption. However, technology adoption is often accompanied by, and in turn, drives organizational change. Since organizations tend to follow taken-for-granted practices, we consider an institutional theory approach combined with a practice perspective to analyze the microdynamics linked to technology adoption and consequent organizational change. Using an institutional work perspective to study the adoption of BIM, we try to understand how adoption and change are achieved by identifying the different purposive actions that firms undertake. The study uses a longitudinal qualitative case study approach to understand the journey of BIM implementation in one of India’s largest construction firms. Two subdivisions of this firm, that pioneered BIM adoption, were considered as cases. Through open-ended interviews with 50 respondents, we arrived at a historical account of the evolution of the BIM journey. Using a grounded theory approach, we identified three forms of institutional work- juxtaposing and routinizing, embedding coordination, and capacity building that triggered organizational change and technology adoption. This paper advances the literature on technology adoption in construction by identifying forms of institutional work and the microdynamics surrounding digital transformation in construction firms. This study also provides a suite of mechanisms for technology strategists in construction firms to promote BIM 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.