Innovation diffusion among heterogeneous agents: Exploring complexity with agent-based modelling (ABM)

Nazmun N. Ratna, Anne Dray, Pascal Perez, R. Quentin Grafton, Tom Kompas

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    Abstract

    In this chapter we apply agent-based modelling (ABM) to capture the complexity of the diffusion process depicted in Medical Innovation, the classic study on diffusion of a new drug tetracycline byColeman, Katz, and Menzel (1966). Based on our previous model with homogenous social agents, Gammanym (Ratna et al., 2007), in this chapter we further our analysis with heterogeneous social agents who vary in terms of their degree of predisposition to knowledge. We also explore the impact of stage-dependent degrees of external influence from the change agent, pharmaceutical company in this case. Cumulative diffusion curves suggest that the pharmaceutical company plays a much weaker role in accelerating the speed of diffusion when a diffusion dynamics is explored with complex agents, defined as heterogeneous agents under stage-dependent degrees of external influence. Although our exploration with groups of doctors with different combination of social and professional integration signifies the importance of interpersonal ties, our analysis also reveals that degree of adoption threshold or individual predisposition to knowledge is crucial for adoption decisions. Overall, our approach brings in fresh insights to the burgeoning policy literature exploring complexity, by providing necessary framework for research translation to policy and practice.

    Original languageEnglish
    Title of host publicationApplications of Complex Adaptive Systems
    PublisherIGI Global
    Pages113-141
    Number of pages29
    ISBN (Print)9781599049625
    DOIs
    Publication statusPublished - 2008

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