Simulating Innovation Systems and STI Policy: An Agent-Based Perspective

Walter Ruiz, Danilo Spinola, Maria Luisa Villalba

    Research output: Working paper

    Abstract

    This paper develops an Agent-Based Model (ABM) to study the impact of Science, Technology, and Innovation (STI) policies on innovation systems. The model, which we call the Adaptive Innovation System Model (AdaptISM), simulates the technological innovation capabilities required for knowledge and technology generation, diffusion, and utilisation, integrating decision rules that capture the emergent behaviours of agents interacting with innovation opportunities. The model is empirically validated using data from the coffee and avocado agricultural production chains (APCs) in Antioquia, Colombia, which are two sectors of regional economic and local importance. The validation process allows the evaluation of individual and combined STI policy modes, identifying which policy strategies most effectively enhance innovation performance and economic outcomes. By enabling the exploration of ?what-if? scenarios, the ABM provides a tool to assess STI policy contributions systematically and offers practical insights into resource allocation in local innovation systems. This approach addresses a critical challenge in innovation policy design: understanding how STI policies influence system performance. The findings highlight the utility of combining policy approaches to improve innovation and economic growth, offering a replicable framework for policymakers and researchers seeking to optimise the performance of innovation systems.
    Original languageEnglish
    PublisherCentre for Accountancy Finance and Economics (CAFE), Birmingham City Business School, Birmingham City University
    Volume32
    Publication statusPublished (VoR) - 20 Jan 2025

    Keywords

    • STI policy
    • innovation systems
    • agricultural production chains
    • Agent-based modelling

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