Summary of background data: The concept of sustainability has been spread like one of the most cited and interesting trend topics giving a lot of definitions and good practices to perceive it. In this context, the perception of sustainability for the population and the companies is one of the aspects less frequently faced. In this work, this issue has been analysed using results from a survey in which a sample of 2,000 respondents answered to the perception of sustainability for Italian companies. Objectives: The main aim of the work is to detect to measure the sustainability concept level of understanding and the perception of the role played by the companies in this field. This objective was achieved asking the population how much they are informed about sustainability, SDGs and how much they are available to pay to choose a sustainable company respect to one not sustainable. Methods: Segments of respondents have been achieved using decision trees. The decisional rule used to obtain the nodes was the CHAID (Chi-squared Automatic Interaction Detection) method. Trees are connected acyclic graphs fundamental to create data structures, classification tools, decision theories and prediction models. Each node can be thought of as a cluster, tree prediction models add two ingredients: the predictor and predicted variables labeling the nodes and branches. Results and discussions/conclusions: The proposed approach divided the respondents in four groups showing four different behaviors towards the sustainability. The survey highlights the need for more widespread information to create a widely disseminated culture of sustainability that appears as a concept not yet fully defined.

Angelone, R., Mariani, P., Marletta, A., Zenga, M. (2024). The definition of sustainability for Italian stakeholders: evidences from a survey. Intervento presentato a: Data Science and Social Research (DSSR) 2024, Napoli, Italia.

The definition of sustainability for Italian stakeholders: evidences from a survey

Angelone, R;Mariani, P;Marletta, A
;
Zenga, M
2024

Abstract

Summary of background data: The concept of sustainability has been spread like one of the most cited and interesting trend topics giving a lot of definitions and good practices to perceive it. In this context, the perception of sustainability for the population and the companies is one of the aspects less frequently faced. In this work, this issue has been analysed using results from a survey in which a sample of 2,000 respondents answered to the perception of sustainability for Italian companies. Objectives: The main aim of the work is to detect to measure the sustainability concept level of understanding and the perception of the role played by the companies in this field. This objective was achieved asking the population how much they are informed about sustainability, SDGs and how much they are available to pay to choose a sustainable company respect to one not sustainable. Methods: Segments of respondents have been achieved using decision trees. The decisional rule used to obtain the nodes was the CHAID (Chi-squared Automatic Interaction Detection) method. Trees are connected acyclic graphs fundamental to create data structures, classification tools, decision theories and prediction models. Each node can be thought of as a cluster, tree prediction models add two ingredients: the predictor and predicted variables labeling the nodes and branches. Results and discussions/conclusions: The proposed approach divided the respondents in four groups showing four different behaviors towards the sustainability. The survey highlights the need for more widespread information to create a widely disseminated culture of sustainability that appears as a concept not yet fully defined.
abstract + slide
sustainability, sample survey
English
Data Science and Social Research (DSSR) 2024
2024
2024
open
Angelone, R., Mariani, P., Marletta, A., Zenga, M. (2024). The definition of sustainability for Italian stakeholders: evidences from a survey. Intervento presentato a: Data Science and Social Research (DSSR) 2024, Napoli, Italia.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/469259
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