Sustainable Transitions Narratives: An Analysis of the Literature through Topic Modelling

Stefani, Gianluca; Biggeri, Mario; Ferrone, Lucia

doi:10.3390/su14042085

Cited by 8 publications

(2 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The mostly empirical frameworks of transition studies, such as the MLP, may benefit from the theoretical integration of paradox theory because it helps to qualify the interaction of different transition pathways and tensions between regime elements (Gruchmann et al, 2021). Similar advances have recently been proposed in sustainability transition studies as captured by notion of transition narratives (Frantzeskaki et al, 2012;Stefani et al, 2022), which may seem conflicting but can be juxtaposed in practice to unlock complementarities between them (Luederitz et al, 2017).…”

Section: Theoretical Implications: Proposing a Paradox Perspective On...mentioning

confidence: 97%

Divergent Transition Pathways for Artificial Intelligence: A Longitudinal and Multi-Level Perspective Using Structural Topic Modeling

Dahlke,

Ebersberger

2023

Preprint

View full text Add to dashboard Cite

The potential of artificial intelligence (AI) to constitute a general-purpose technology with diverse algorithmic specifications makes it challenging to assess its overall impact on existing socio-economic regimes. Leveraging the multi-level perspective, we seek to depict the trajectory of micro-, meso-, and macro-level forces and their interactions to characterize AI transition pathways in industry. We treat business and information systems literature as a proxy capturing business practices that relate to factors influencing AI transitions on all three different levels. Based on 10,036 publications over 25 years, we map the topic landscape of AI-related research, longitudinal patterns of topics, and structural changes of topic networks. The results indicate a strong and myopic focus on technological capabilities and efficiency rationales. Topic network structures indicate that transition pathways may diverge between a symbiotic and stabilizing transformation process and a more radical pathway of regime substitution. Based on these findings, we argue that sociotechnical transition pathways may not only occur in sequence, but simultaneously and ambiguously. This highlights the need for a nuanced understanding of convergent and divergent transition pathways for emerging digital general-purpose technology that do not tend to settle on one dominant design. We propose to leverage paradox theory to reconcile these tensions. JEL: M000, O310, O320, 033

show abstract

Section: Theoretical Implications: Proposing a Paradox Perspective On...mentioning

confidence: 97%

Divergent Transition Pathways for Artificial Intelligence: A Longitudinal and Multi-Level Perspective Using Structural Topic Modeling

Dahlke,

Ebersberger

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…useful approach for the categorization and mass analysis of media articles [55,57], also in the context of sustainability narratives [63,[76][77][78][79].…”

Section: Plos Sustainability and Transformationmentioning

confidence: 99%

Media narratives on (Ecological) sustainability: A topic modeling analysis of entrepreneurship news in the MENA region

Hager,

Alzafari,

Rashid

2024

PLOS Sustain Transform

View full text Add to dashboard Cite

Amidst the increasing ecological pressures arising from industrial activity and consumerism, with particularly tangible impacts outside of the global north, the private sector is being held accountable to reduce its environmental footprint and transition to sustainable business models and processes. Nevertheless, perceptions of sustainability and its dimensions largely vary between cultures and contexts, while local media discourses both shape and reflect those concepts and narratives. This in turn shapes sustainability practices and the nature and impacts of emerging entrepreneurial business activity. Given the dearth of sustainability research in the Middle East & North Africa (MENA) and the region’s extreme vulnerability to climate change, pollution, draughts combined with political instability and institutional fragility, this paper provides an in-depth analysis of media narratives at the intersection of sustainability and entrepreneurship in the region. This was done by means of the machine learning method of topic modelling on two datasets of 486 and 217 news media articles extracted from a major regional English-language news outlet, followed by a manual content analysis of the extracted topics and articles. We find that the term sustainability is highly associated with economic prosperity and that ecology-related themes are often formulated in terms of financial gain, for instance transitioning out of oil & gas dependence. We find a surprising lack of focus on water scarcity and biodiversity, coupled with a welcomed focus on the energy transition, recycling, urban mobility, as well as social networking and minority integration. Our findings hence provide a nuanced contextual understanding of sustainability, which may support businesses and decision-makers alike in (re)defining priorities and reflecting upon the status quo and necessary next steps in the transition to more sustainable societies.

show abstract

The renewable energy role in the global energy Transformations

Hassan,

Viktor,

J. Al-Musawi

et al. 2024

Renewable Energy Focus

View full text Add to dashboard Cite

Sustainable Transitions Narratives: An Analysis of the Literature through Topic Modelling

Cited by 8 publications

References 71 publications

Divergent Transition Pathways for Artificial Intelligence: A Longitudinal and Multi-Level Perspective Using Structural Topic Modeling

Divergent Transition Pathways for Artificial Intelligence: A Longitudinal and Multi-Level Perspective Using Structural Topic Modeling

Media narratives on (Ecological) sustainability: A topic modeling analysis of entrepreneurship news in the MENA region

The renewable energy role in the global energy Transformations

Contact Info

Product

Resources

About