2020
DOI: 10.1186/s40294-020-00074-6
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A modular multi-agent framework for innovation diffusion in changing business environments: conceptualization, formalization and implementation

Abstract: Understanding how innovations are accepted in a dynamic and complex market environment is a crucial factor for competitive advantage. To understand the relevant factors for this diffusion and to predict success, empirically grounded agent-based models have become increasingly popular in recent years. Despite the popularity of these innovation diffusion models, no common framework that integrates their diversity exists. This article presents a flexible, modular and extensible common description and implementati… Show more

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Cited by 12 publications
(6 citation statements)
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References 32 publications
(90 reference statements)
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“…The present analysis has been performed as an intermediate step for the parametrization of an agent-based model (cf. [42][43][44]) that aims to simulate residential PV adoption decisions in specific spatial-temporal contexts. Future research could build on these findings to further clarify the role of peers in the adoption process, which could in turn improve policymakers' ability to harness peer effects to support individual decision-making.…”
Section: Discussionmentioning
confidence: 99%
“…The present analysis has been performed as an intermediate step for the parametrization of an agent-based model (cf. [42][43][44]) that aims to simulate residential PV adoption decisions in specific spatial-temporal contexts. Future research could build on these findings to further clarify the role of peers in the adoption process, which could in turn improve policymakers' ability to harness peer effects to support individual decision-making.…”
Section: Discussionmentioning
confidence: 99%
“…Applying different approaches such as in-depth interviews, focus groups, and also representative surveys with decision-makers could be relevant to move this research forward. Finally, the findings should also be incorporated into energy system models for managing and predicting low carbon technology adoptions (e.g., agent-based models of technology adoption [105]).…”
Section: Future Workmentioning
confidence: 99%
“…The goal is an operationalization of hypotheses with, e.g., representative quantitative surveys. In our future research, we are aiming to carry out exactly such quantitative analyses for a sub-area, namely energy system models for predicting PV adoptions on the basis of empirically grounded agent-based modelling [101,102].…”
Section: Discussionmentioning
confidence: 99%