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Costa, E., Fontes, M. & Bento, N. (2023). Towards Sustainable Business Models: Exploring Transformative Pathways for Decarbonization. 7a Edição workshop Dinâmia´Cet: rumos da investigação num mundo em transformação .

J. E. Costa et al.,  "Towards Sustainable Business Models: Exploring Transformative Pathways for Decarbonization", in 7a Edição workshop Dinâmia´Cet: rumos da investigação num mundo em transformação , Lisboa, 2023

@misc{costa2023_1728213341882,
	author = "Costa, E. and Fontes, M. and Bento, N.",
	title = "Towards Sustainable Business Models: Exploring Transformative Pathways for Decarbonization",
	year = "2023",
	url = "https://www.dinamiacet.iscte-iul.pt/"
}

TY  - CPAPER
TI  - Towards Sustainable Business Models: Exploring Transformative Pathways for Decarbonization
T2  - 7a Edição workshop Dinâmia´Cet: rumos da investigação num mundo em transformação 
AU  - Costa, E.
AU  - Fontes, M.
AU  - Bento, N.
PY  - 2023
CY  - Lisboa
UR  - https://www.dinamiacet.iscte-iul.pt/
AB  - The modern industrial society's technological advancement and innovation have caused a significant increase in carbon emissions, resulting in concern about socio-environmental risks. To avoid compromising future generations, the development of sustainable and transformative business models has become increasingly relevant in achieving decarbonization. This study investigates how the transformation of business models can support the decarbonization process and sustainable transition pathways. The study utilizes a secondary data analysis to identify and describe the key-elements in emerging and transformative business models. It draws from relevant literature such as business models, transformation, and sustainability transition theory, and examines a set of start-ups to achieve its objectives. The objective was to identify and characterize key elements of emerging business models with transformative potential and capable of leading to a model of production and consumption of low-carbon goods and services and to support the sustainability transitions pathways. The study found that Business-to-Business-to-Consumer (B2B2C) models with the implementation of artificial intelligence and automatic learning resources indicate the best transforming conditions. These models allow for the shortening of the path from design to commercialization of goods and services, providing sustainable added value. The findings suggest that the use of artificial intelligence and automatic learning, which integrate and approximate production and consumption, are differential factors that enhance the transformation to more sustainable models and accelerate the transition to a low-carbon economy. The study fills a knowledge gap regarding the contributions of transforming business models to the transition to a low-carbon society, suggesting that the advancement of transformative and sustainable business models will become more granular and pervasive over time as artificial intelligence tools and the sustainable industry reach a more established state. The research reveals where policymakers can focus attention to support the transition to a more sustainable low-carbon economy through the development of innovative and transformative business models.
ER  -