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

Juliana Zapata Riveros,Silvia Ulli-Beer,Matthias Speich,Mirjam West

doi:10.3390/su13137264

Juliana Zapata Riveros, Silvia Ulli-Beer + Show 2 more

Open Access

https://doi.org/10.3390/su13137264

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Journal: Sustainability	Publication Date: Jun 29, 2021
Citations: 5	License type: CC BY 4.0

Affiliation: ZHAW Zurich University of Applied Sciences

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.

Highlights

This paper addresses the research–practice gaps in business model innovation by presenting a combination of two established fields of methods (BMI and system dynamics (SD)) and complementing them with a prospective transition analysis to provide a holistic assessment of the scalability of a novel time-based business model at the energy–industry interface
Scenario than in the CP scenario, since, as mentioned before, the model assumes that the scenario than in the CP scenario, since, as mentioned before, the model assumes that the energy coming from own renewables has no cost
This paper presents a tailored methodical framework to assess the prospects of innovative business models under high uncertainty, applied to a case study in the energy sector

Summary

Introduction

Climate change mitigation requires a transition to a low-carbon society, i.e., significant reductions of greenhouse gas (GHG) emissions. The decarbonization of the energy sector is decisive to this end [1]. Thanks to several effective climate policies and technological progress, the share of power generation stemming from renewable sources (such as solar and wind) has largely increased in the previous years, and an accelerated uptake of related technologies is expected for the future [2]. Major technological changes in the industrial sectors are necessary to achieve a low-carbon transition [3]. There are several pathways to reduce GHG emissions in the industry, such as adopting highly energy-efficient technologies, implementing carbon capture and storage systems, and the electrification of production processes [4]. The strong penetration of renewables provides the necessary carbon-neutral energy sources for a clean industrial electrification

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