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Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model

The emergence of the COVID-19 pandemic has hindered the achievement of the global Sustainable Development Goals (SDGs). Pro-environmental behaviour contributes to the achievement of the SDGs, and UNESCO considers college students as major contributors. There is a scarcity of research on college stud...

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Autores principales: Wang, Qiaoling, Kou, Ziyu, Sun, Xiaodan, Wang, Shanshan, Wang, Xianjuan, Jing, Hui, Lin, Peiying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367762/
https://www.ncbi.nlm.nih.gov/pubmed/35954760
http://dx.doi.org/10.3390/ijerph19159407
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author Wang, Qiaoling
Kou, Ziyu
Sun, Xiaodan
Wang, Shanshan
Wang, Xianjuan
Jing, Hui
Lin, Peiying
author_facet Wang, Qiaoling
Kou, Ziyu
Sun, Xiaodan
Wang, Shanshan
Wang, Xianjuan
Jing, Hui
Lin, Peiying
author_sort Wang, Qiaoling
collection PubMed
description The emergence of the COVID-19 pandemic has hindered the achievement of the global Sustainable Development Goals (SDGs). Pro-environmental behaviour contributes to the achievement of the SDGs, and UNESCO considers college students as major contributors. There is a scarcity of research on college student pro-environmental behaviour and even less on the use of decision trees to predict pro-environmental behaviour. Therefore, this study aims to investigate the validity of applying a modified C5.0 decision-tree model to predict college student pro-environmental behaviour and to determine which variables can be used as predictors of such behaviour. To address these questions, 334 university students in Guangdong Province, China, completed a questionnaire that consisted of seven parts: the Perceived Behavioural Control Scale, the Social Identity Scale, the Innovative Behaviour Scale, the Sense of Place Scale, the Subjective Norms Scale, the Environmental Activism Scale, and the willingness to behave in an environmentally responsible manner scale. A modified C5.0 decision-tree model was also used to make predictions. The results showed that the main predictor variables for pro-environmental behaviour were willingness to behave in an environmentally responsible manner, innovative behaviour, and perceived behavioural control. The importance of willingness to behave in an environmentally responsible manner was 0.1562, the importance of innovative behaviour was 0.1404, and the perceived behavioural control was 0.1322. Secondly, there are 63.88% of those with high pro-environmental behaviour. Therefore, we conclude that the decision tree model is valid in predicting the pro-environmental behaviour of college student. The predictor variables for pro-environmental behaviour were, in order of importance: Willingness to behave in an environmentally responsible manner, Environmental Activism, Subjective Norms, Sense of Place, Innovative Behaviour, Social Identity, and Perceived Behavioural Control. This study establishes a link between machine learning and pro-environmental behaviour and broadens understanding of pro-environmental behaviour. It provides a research support with improving people’s sustainable development philosophy and behaviour.
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spelling pubmed-93677622022-08-12 Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model Wang, Qiaoling Kou, Ziyu Sun, Xiaodan Wang, Shanshan Wang, Xianjuan Jing, Hui Lin, Peiying Int J Environ Res Public Health Article The emergence of the COVID-19 pandemic has hindered the achievement of the global Sustainable Development Goals (SDGs). Pro-environmental behaviour contributes to the achievement of the SDGs, and UNESCO considers college students as major contributors. There is a scarcity of research on college student pro-environmental behaviour and even less on the use of decision trees to predict pro-environmental behaviour. Therefore, this study aims to investigate the validity of applying a modified C5.0 decision-tree model to predict college student pro-environmental behaviour and to determine which variables can be used as predictors of such behaviour. To address these questions, 334 university students in Guangdong Province, China, completed a questionnaire that consisted of seven parts: the Perceived Behavioural Control Scale, the Social Identity Scale, the Innovative Behaviour Scale, the Sense of Place Scale, the Subjective Norms Scale, the Environmental Activism Scale, and the willingness to behave in an environmentally responsible manner scale. A modified C5.0 decision-tree model was also used to make predictions. The results showed that the main predictor variables for pro-environmental behaviour were willingness to behave in an environmentally responsible manner, innovative behaviour, and perceived behavioural control. The importance of willingness to behave in an environmentally responsible manner was 0.1562, the importance of innovative behaviour was 0.1404, and the perceived behavioural control was 0.1322. Secondly, there are 63.88% of those with high pro-environmental behaviour. Therefore, we conclude that the decision tree model is valid in predicting the pro-environmental behaviour of college student. The predictor variables for pro-environmental behaviour were, in order of importance: Willingness to behave in an environmentally responsible manner, Environmental Activism, Subjective Norms, Sense of Place, Innovative Behaviour, Social Identity, and Perceived Behavioural Control. This study establishes a link between machine learning and pro-environmental behaviour and broadens understanding of pro-environmental behaviour. It provides a research support with improving people’s sustainable development philosophy and behaviour. MDPI 2022-07-31 /pmc/articles/PMC9367762/ /pubmed/35954760 http://dx.doi.org/10.3390/ijerph19159407 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Qiaoling
Kou, Ziyu
Sun, Xiaodan
Wang, Shanshan
Wang, Xianjuan
Jing, Hui
Lin, Peiying
Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title_full Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title_fullStr Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title_full_unstemmed Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title_short Predictive Analysis of the Pro-Environmental Behaviour of College Students Using a Decision-Tree Model
title_sort predictive analysis of the pro-environmental behaviour of college students using a decision-tree model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367762/
https://www.ncbi.nlm.nih.gov/pubmed/35954760
http://dx.doi.org/10.3390/ijerph19159407
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