10.2: Adoption of Innovations in Work Networks

Project: Research project

Project Details

Description

Adoption of innovations, whether new ideas, technologies, or products, is crucially important in knowledge societies. Studies of adoption of innovations have generally focused on products with little societal impact and, even if large-scale and real-world based, on heterogeneous populations. These limitations have so far hindered the development and testing of a mechanistic understanding of the adoption process. Prior experimental and computational research by the principal investigators strongly suggest that a new mechanisms inspired by opinion models is better able to reproduce adoption than contagion-like models. Specifically, a study of the adoption by critical care physicians of a medical innovation that complements current protocols for the diagnosis of life-threatening bacterial infections suggests that the adoption proposed involves a bi-directional flow of influence instead of the uni-directional (from adopter to non-adopter) flow considered in contagion models.
Our proposed research aims to craft a deeper understanding of the mechanisms driving adoption in environments where innovations have clear societal impact. For a “low-burden” innovation – that is, an innovation that does not involve the replacement of a practice or product – we found relatively high-levels of willingness of the agents to adopt the innovation. We will now investigate how the spread of the innovation will differ in the case of an innovation with a high-burden for adoption (Aim 1). Additionally, we will also investigate how the insights uncovered on the mechanisms driving adoption can be used to design interventions that foster more widespread and faster adoption. Because optimizing design of interventions will be particularly important for high-burden innovations, we will use our research findings to build a web-based application that uses network data and individual characteristic as inputs in order to predict the effect of different types of interventions on outcomes (Aim 2).
Our research will thus provide a fundamental advance in our understanding of the adoption of innovations within networks of highly-trained individuals such as physicians, teachers, researchers, lawyers, and military officers. Additionally, our research will provide the tools for managers to optimize the design of interventions aiming at the faster and more robust adoption of important work-related innovations.
StatusFinished
Effective start/end date6/1/145/31/18

Funding

  • Army Research Office (W911NF-14-1-0259-P00004)

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