| Title |
Business model development concept for SMEs in the era of twin transition |
| ID_Doc |
9646 |
| Authors |
Gallina, V; Steinwender, A; Zudor, E; Preuveneers, D; Schlund, S |
| Title |
Business model development concept for SMEs in the era of twin transition |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.procs.2024.01.052 |
| Abstract |
The urgent need to act against climate change is emphasized in many initiatives, such as the Sustainable Development Goals, the European Green Deal, and the Circular Economy Action Plan. The role of the industrial sector is crucial. Companies, however, have to operate in a very complex environment driven by digitization and are supposed to be more sustainable. This paper explores how companies can implement the ecological transformation, with a focus on the role of digital technologies and data in enabling the twin transition. This paper proposes an approach to support SMEs in the twin transition through a combination of digital and sustainable business model development. The concept includes an interdisciplinary methodology that combines qualitative and quantitative approaches, focusing on the latter. The suggested method collection includes adaptations of the business model canvas, value proposition analysis, data-driven decision-making, and the integration of environmental and economic considerations using the system of environmental-economic accounting. In particular, approaches to define the quantification of economic as well as ecological value will be key levers for sustainable implementation. By leveraging these approaches, SMEs can navigate the challenges of digital transformation and sustainability and contribute to a more sustainable future. (c) 2024 The Authors. Published by Elsevier B.V. |
| Author Keywords |
quantitative approach; value creation; business model; digitization; sustainability |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001196800600052 |
| WoS Category |
Computer Science, Theory & Methods; Engineering, Industrial; Engineering, Manufacturing |
| Research Area |
Computer Science; Engineering |
| PDF |
https://doi.org/10.1016/j.procs.2024.01.052
|