Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-23533
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Combining business model innovation and model-based analysis to tackle the deep uncertainty of societal transitions : a case study on industrial electrification and power grid management
Authors: Zapata Riveros, Juliana Victoria
Speich, Matthias
West, Mirjam
Ulli-Beer, Silvia
et. al: No
DOI: 10.3390/su13137264
10.21256/zhaw-23533
Published in: Sustainability
Volume(Issue): 13
Issue: 13
Issue Date: 29-Jun-2021
Publisher / Ed. Institution: MDPI
ISSN: 2071-1050
Language: English
Subjects: Prosumer concepts; Technology change; Business strategies; System dynamics; Decentralization; Photovoltaic; Deep uncertainty; Low-carbon transitions
Subject (DDC): 333.79: Energy
Abstract: Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics, and exploratory model analysis to identify new business opportunities in a context of sociotechnical transition and assess their prospects through simulation experiments. This combination of methods is applied to the case of a potential business model for Distribution System Operators aiming at ensuring the stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendations for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.
URI: https://digitalcollection.zhaw.ch/handle/11475/23533
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Engineering
Organisational Unit: Institute of Sustainable Development (INE)
Appears in collections:Publikationen School of Engineering



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