Identifying household effects on individuals’ environmental behaviours in the UK – a multilevel modelling approach

Publication type

Conference Paper

Series

Understanding Society Scientific Conference 2017, 11-13 July 2017, University of Essex, Colchester, UK

Author

Publication date

July 11, 2017

Summary:

This study analyses factors influencing individuals’ pro-environmental behaviours in the UK using data from wave 4 of the Understanding Society, UK Household Longitudinal Study. General pro-environmental behaviours, as well as home-, transport- and purchasing-related environmental behaviours are considered. A particular focus of this study is to identify the role of households on these behaviours. Although pro-environmental behaviours have been widely studied at the individual level, behaviours are likely to be influenced by other members living in the same household. This hierarchical structure has so far not been analysed. Furthermore, resulting from the complex sampling design and data collection method, households are clustered into both geographical areas and interviewers. The impact of interviewers on survey responses has been well-documented in the survey methodology literature. This study proposes, for the first time, a cross-classified multilevel model to incorporate the household, interviewer and area effects to account for the complex hierarchical structure of the survey data. Results show that household, interviewer and area have significant effects on the reported individuals’ pro-environmental behaviours after controlling for the socio-demographic factors at the individual level. The findings also suggest that individuals’ values, environmental attitudes and political beliefs have significant impacts on their environmental behaviours. Finally, the study also confirms that different types of environmental behaviours are not necessarily correlated and these behaviours can be motivated by different individuals and households’ factors.

Subjects

Link

https://www.understandingsociety.ac.uk/scientific-conference-2017/papers/153

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