Paper Type
Complete
Paper Number
1616
Description
Vehicle data can enable novel, data-driven services that will potentially lead to an increase in comfort, efficiency, and security. However, it is highly uncertain if and to what extent a data-driven automotive service ecosystem is viable and will emerge in the future. Furthermore, it is a challenge to analyze central aspects of this ecosystem such as the adoption rate of data-driven services. The service adoption rate depends on various factors such as attitude towards the technology, available service offerings, news and media coverage, regulations, and peer pressure or imitation rate. To deal with this complexity and to enable a simulation-based analysis of the complex relationships between these factors, System Dynamics (SD)-based modeling is a promising approach. We present a simplified SD-model of the data-driven automotive service ecosystem and simulate two extreme cases of future scenarios. Our findings are relevant for both decision-makers to answer strategic questions and scientists to better understand ecosystem behavior.
Recommended Citation
Lindow, Friedrich; Kaiser, Christian; Fellmann, Michael; and Stocker, Alexander, "A System Dynamics Model-Based Simulation of the Data-Driven Automotive Service Ecosystem" (2021). AMCIS 2021 Proceedings. 15.
https://aisel.aisnet.org/amcis2021/adopt_diffusion/adopt_diffusion/15
A System Dynamics Model-Based Simulation of the Data-Driven Automotive Service Ecosystem
Vehicle data can enable novel, data-driven services that will potentially lead to an increase in comfort, efficiency, and security. However, it is highly uncertain if and to what extent a data-driven automotive service ecosystem is viable and will emerge in the future. Furthermore, it is a challenge to analyze central aspects of this ecosystem such as the adoption rate of data-driven services. The service adoption rate depends on various factors such as attitude towards the technology, available service offerings, news and media coverage, regulations, and peer pressure or imitation rate. To deal with this complexity and to enable a simulation-based analysis of the complex relationships between these factors, System Dynamics (SD)-based modeling is a promising approach. We present a simplified SD-model of the data-driven automotive service ecosystem and simulate two extreme cases of future scenarios. Our findings are relevant for both decision-makers to answer strategic questions and scientists to better understand ecosystem behavior.
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