Generative mechanisms of IT-enabled transformation of a hospital laboratory: A critical realist evaluation

Abstract

Research efforts in the domain of IT-enabled Organizational Transformation (ITOT) have predominantly focused on identifying the determinants contributing to success in ITOT and the significance of their existing theories. However, the socio-technical dynamics driving the transformation process remain largely understudied. To understand and adequately investigate how the organization transformation process emerges and evolves over time, we need to examine how the social and technical components interact through human agents and under different contextual conditions to enable successful IT-enabled transformations. Considering these social and technical components and their interactions as constitutive of generative mechanisms — that is, the causal mechanisms posited by critical realism — we conducted an in-depth case study of a hospital laboratory’s IT-enabled transformation efforts. Through a critical realist lens, we provide a rich description of key generative mechanisms that contributed towards this laboratory’s successful transformation. Among them, our analysis identifies four noteworthy generative mechanisms which manifested over time to progress the transformation process: (1) inertia disruption; (2) cognitive frame alignment; (3) auto-validation; and (4) affordance actualization. At this laboratory, each and every generative mechanism identified demonstrates how interactions among social and technical components — mediated by the laboratory employees — lead to evolving structural configurations over time, facilitating overall transformation. Our goal is to offer a theoretical explanation by way of generative mechanisms to explain not only how but why the laboratory transformation vision emerged and evolved. Our research advances a causal understanding of the socio-technical process of IT-enabled organizational transformation and offers a rigorous example of applying critical realism and generative mechanisms perspective to study complex IT phenomena.