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Terceira-G51 Sustainable Development Goals

Tracks
Ordinary/Refereed
Friday, August 30, 2024
9:00 - 10:30
S06

Details

Chair: Paolo Bottero


Speaker

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Dr. Livia Madureira
Associate Professor
UTAD (University of Tras-os-Montes e Alto Douro)

Pathways to Sustainable Growth: Unveiling a Sustainable Competitiveness Index for Firms and Industries

Author(s) - Presenters are indicated with (p)

Livia Madureira (p), Zeeshan Fareed, Rui Silva, Carla Marques

Discussant for this paper

Paolo Bottero

Abstract

As the world changes quickly in the global market, it is important for a company or industry to evaluate and improve their sustainable competitiveness. In this paper, we introduce the concept of the Sustainable Competitiveness Index (SCI) for firms and industries, as an evaluation tool capable of accommodating multiple dimensions including economic performance, environmental sustainability, social equity, and governance dimensions. Such index is necessary for strategic decision-making method and in general for sound development practice. To calculate SCI: Overall SCI is reflective of multi-dimensional components, where each indicator within each dimension is normalized, weighted, and summed. As an example, economic indicators are factors like how innovative the company is, and how well financial performance works, while environmental indicators are its carbon footprint and resource efficiency. Social indicators cover employee well-being and community engagement, and governance indicators evaluate transparency and ethical practices. By normalizing and assigning appropriate weights to each indicator, we generate a composite score that reflects the overall sustainable competitiveness of the firm or industry. Implementing our SCI offers significant benefits and policy implications. For businesses, it provides a clear framework to benchmark performance, identify areas for improvement, and implement strategies that align with sustainable development goals. It also enhances transparency and accountability, attracting investors and building consumer trust. For policymakers, our SCI serves as a valuable tool to monitor industry trends, promote best practices, and design policies that incentivize sustainable growth. Ultimately, our SCI supports a balanced approach to competitiveness, ensuring that economic success does not come at the expense of environmental health or social well-being.

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Mr Paolo Bottero
Ph.D. Student
Gran Sasso Science Institute

A place-based policy framework for SDGs: exploring opportunities in the geography of complex knowledge

Author(s) - Presenters are indicated with (p)

Paolo Bottero (p)

Discussant for this paper

Alessandro Lorenzo Palma

Abstract

With the 2030 Agenda, the United Nations determined that creativity, know-how, technology, and financial resources from all of society are necessary to achieve Sustainable Development Goals in every context. This research investigates how a place-based approach can foster SDG-related know-how production, drawing on the knowledge complexity framework. Due to the considerable amount of EU-led and government-funded programs to support research in the post-pandemic phase, the study is focused on Italy at the NUTS-3 level. To do so, a new dataset at the provincial level has been developed by georeferencing the affiliations of all the papers published in Italy from 2008 to 2022 on the Web of Science. Given the path-dependency of knowledge creation, this research investigates comparative advantages in SDG-related research while also exploring the untapped potential of territories. Furthermore, the knowledge space computation allows for the mapping of clusters of provinces. These are critical in the public funding allocation mechanisms. The analysis shows that medium-sized provinces have significant potential for SDG-related research, highlighting the importance of quality over quantity. Considering that knowledge (especially the most complex) is particularly sticky to places, this study provides further evidence for fostering more SDG-informed place-based policies for knowledge creation.
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