| Title |
Agent-based modelling and simulation for circular business model experimentation |
| ID_Doc |
25845 |
| Authors |
Lange, KPH; Korevaar, G; Oskam, IF; Nikolic, I; Herder, PM |
| Title |
Agent-based modelling and simulation for circular business model experimentation |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.rcradv.2021.200055 |
| Abstract |
The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation. |
| Author Keywords |
Circular economy; Business model experimentation; Agent-based modelling; Industrial symbiosis networks |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001107593900001 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.rcradv.2021.200055
|