7
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      The primary drivers of private-sphere pro-environmental behaviour in five European countries during the Covid-19 pandemic

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Nowadays, when fighting climate change and other global environmental issues is of utmost urgency, the understanding of what drives pro-environmental behaviour has become a hot topic in both academic and practical circles. Some earlier studies unravelled the complexity of the underlying factors of pro-environmental conduct, yet more studies are needed to understand the socio-cultural premises of such behaviour in different countries. The main aim of this paper is to offer a comprehensive analysis of the importance of pro-environmental behaviour drivers across five countries in Europe, namely Greece, Poland, Portugal, Sweden, and the United Kingdom. The survey using computer-assisted web interviews (N = 2502) was implemented in July 2020, the first summer of the Covid-19 pandemic. Hierarchical linear models were employed to analyse individuals’ behaviour, defined as self-perceived declaration of the willingness to contribute to environmental conservation. The results showed that attitudinal and value-related factors are more significant than demographics. Biospheric values and relationship to nature generally affect pro-environmental behaviour positively. Similarly, the experience of Covid-19 exerted a positive influence. In terms of country-level predictors, greenhouse gas emissions were found to affect pro-environmental behaviour negatively, while the share of renewable energy sources influenced it positively. The cumulative country Covid-19-related mortality at the time of investigation did not have discernible impact. Moreover, the findings showed that, in order to foster PEB, a stronger emphasis on environmental education and attitudes towards nature should be employed.

          Related collections

          Most cited references96

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            The connectedness to nature scale: A measure of individuals’ feeling in community with nature

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Scaling regression inputs by dividing by two standard deviations.

              Interpretation of regression coefficients is sensitive to the scale of the inputs. One method often used to place input variables on a common scale is to divide each numeric variable by its standard deviation. Here we propose dividing each numeric variable by two times its standard deviation, so that the generic comparison is with inputs equal to the mean +/-1 standard deviation. The resulting coefficients are then directly comparable for untransformed binary predictors. We have implemented the procedure as a function in R. We illustrate the method with two simple analyses that are typical of applied modeling: a linear regression of data from the National Election Study and a multilevel logistic regression of data on the prevalence of rodents in New York City apartments. We recommend our rescaling as a default option--an improvement upon the usual approach of including variables in whatever way they are coded in the data file--so that the magnitudes of coefficients can be directly compared as a matter of routine statistical practice. (c) 2007 John Wiley & Sons, Ltd.
                Bookmark

                Author and article information

                Journal
                J Clean Prod
                J Clean Prod
                Journal of Cleaner Production
                Published by Elsevier Ltd.
                0959-6526
                1879-1786
                2 February 2023
                2 February 2023
                : 136330
                Affiliations
                [a ]Collegium Civitas, pl. Defilad 1, 00-901, Warsaw, Poland
                [b ]Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Novo Edifício do Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, S/N, 4450-208, Matosinhos, Portugal
                [c ]Agricultural University of Athens, Iera odos 75, T.K., 11855, Athens, Greece
                [d ]Swedish University of Agricultural Sciences SLU, School for Forest Management, BOX 43, 739 21, Skinnskatteberg, Sweden
                Author notes
                []Corresponding author.
                Article
                S0959-6526(23)00488-2 136330
                10.1016/j.jclepro.2023.136330
                9894177
                36748039
                c08d0f0e-2561-4e8b-9955-f3ed9111ace6
                © 2023 Published by Elsevier Ltd.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 30 September 2022
                : 16 January 2023
                : 2 February 2023
                Categories
                Article

                pro-environmental behaviour,environmental awareness,environmental information sources,nature connectedness,value–belief–norm theory,hierarchical linear model

                Comments

                Comment on this article