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

Qiaoling Wang, Ziyu Kou, Xiaodan Sun, Shanshan Wang, Xianjuan Wang, Hui Jing and Peiying Lin
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Qiaoling Wang: Beijing Academy of Educational Sciences, Beijing 100036, China
Ziyu Kou: College of Teacher Education, Capital Normal University, Beijing 100048, China
Xiaodan Sun: Institute of Education, University College London, London WC1E 6BT, UK
Shanshan Wang: Department of Foreign Language, Guangdong University of Science & Technology, Dongguan 523070, China
Xianjuan Wang: Beijing Academy of Educational Sciences, Beijing 100036, China
Hui Jing: National Center for Schooling Development Programme, Ministry of Education, Beijing 100032, China
Peiying Lin: College of Teacher Education, Capital Normal University, Beijing 100048, China

IJERPH, 2022, vol. 19, issue 15, 1-14

Abstract: 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.

Keywords: decision-tree model; college student pro-environmental behaviour; predictive analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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