Modeling Firm Search and Innovation Trajectory Using Swarm Intelligence
We developed a swarm intelligence-based model to study firm search across innovation topics. Firm search modeling has primarily been “firm-centric,” emphasizing the firm’s own prior performance. Fields interested in firm search behavior—strategic management, organization science, and economics—lack...
| Հիմնական հեղինակներ: | , , |
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| Ձևաչափ: | Հոդված |
| Լեզու: | English |
| Հրապարակվել է: |
MDPI AG
2023-01-01
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| Շարք: | Algorithms |
| Խորագրեր: | |
| Առցանց հասանելիություն: | https://www.mdpi.com/1999-4893/16/2/72 |
| Ամփոփում: | We developed a swarm intelligence-based model to study firm search across innovation topics. Firm search modeling has primarily been “firm-centric,” emphasizing the firm’s own prior performance. Fields interested in firm search behavior—strategic management, organization science, and economics—lack a suitable simulation model to incorporate a more robust set of influences, such as the influence of competitors. We developed a swarm intelligence-based simulation model to fill this gap. To demonstrate how to fit the model to real world data, we applied latent Dirichlet allocation to patent abstracts to derive a topic search space and then provide equations to calibrate the model’s parameters. We are the first to develop a swarm intelligence-based application to study firm search and innovation. The model and data methodology can be extended to address a number of questions related to firm search and competitive dynamics. |
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| ISSN: | 1999-4893 |