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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Costa, E., Fontes, M. & Bento, N. (2023). Transformative Business Models for decarbonization: Insights from prize-winning start-ups at the Web Summit . Sustainability. 15 (18)
Exportar Referência (IEEE) 
J. E. Costa et al.,  "Transformative Business Models for decarbonization: Insights from prize-winning start-ups at the Web Summit ", in Sustainability, vol. 15, no. 18, 2023
Exportar BibTeX 
@article{costa2023_1730773559940,
	author = "Costa, E. and Fontes, M. and Bento, N.",
	title = "Transformative Business Models for decarbonization: Insights from prize-winning start-ups at the Web Summit ",
	journal = "Sustainability",
	year = "2023",
	volume = "15",
	number = "18",
	doi = "10.3390/su151814007",
	url = "https://www.mdpi.com/journal/sustainability"
}
Exportar RIS 
TY  - JOUR
TI  - Transformative Business Models for decarbonization: Insights from prize-winning start-ups at the Web Summit 
T2  - Sustainability
VL  - 15
IS  - 18
AU  - Costa, E.
AU  - Fontes, M.
AU  - Bento, N.
PY  - 2023
SN  - 2071-1050
DO  - 10.3390/su151814007
UR  - https://www.mdpi.com/journal/sustainability
AB  - The increasing social pressure for decarbonization has placed businesses under considerable scrutiny to actively reduce carbon emissions. A critical step towards achieving this objective is to shift conventional production and consumption systems to more sustainable alternatives. Thus, there is an emergent need to understand the patterns and drivers of the transformative business models (BMs) that underpin that shift. This study adopts a mixed-methods approach that integrates different literature streams—including Sustainability Transitions Theory (STT), Strategic Niche Management (SNM), and the Business Models approach—and stakeholders’ interviews to investigate the key elements of business models that lead towards sustainable practices. This research examines the organizational arrangements of European start-ups operating between 2014 and 2020. The transformation towards decarbonized production and consumption is characterized by an efficient combination of business strategies that incorporate advanced technologies (ATs), such as artificial intelligence (AI), machine learning (ML) and its algorithms, along with sustainable elements, resulting in transformative business models. By exploring the driving elements behind the transition to low-carbon approaches, this study fills a significant gap in the existing literature on business models. The findings from this research also hold relevance for policymakers to promote decarbonization.
ER  -