| Literature DB >> 25191841 |
José Manuel Ortega-Egea1, Nieves García-de-Frutos1, Raquel Antolín-López1.
Abstract
The urgency of climate change mitigation calls for a profound shift in personal behavior. This paper investigates psycho-social correlates of extra mitigation behavior in response to climate change, while also testing for potential (unobserved) heterogeneity in European citizens' decision-making. A person's extra mitigation behavior in response to climate change is conceptualized--and differentiated from common mitigation behavior--as some people's broader and greater levels of behavioral engagement (compared to others) across specific self-reported mitigation actions and behavioral domains. Regression analyses highlight the importance of environmental psychographics (i.e., attitudes, motivations, and knowledge about climate change) and socio-demographics (especially country-level variables) in understanding extra mitigation behavior. By looking at the data through the lens of segmentation, significant heterogeneity is uncovered in the associations of attitudes and knowledge about climate change--but not in motivational or socio-demographic links--with extra mitigation behavior in response to climate change, across two groups of environmentally active respondents. The study has implications for promoting more ambitious behavioral responses to climate change, both at the individual level and across countries.Entities:
Mesh:
Year: 2014 PMID: 25191841 PMCID: PMC4156351 DOI: 10.1371/journal.pone.0106645
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Demographic profile of respondents.
| Demographic variables | Total sample (n = 30,170) |
|
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|
| d.f. |
| Phi/Cramer's V | ||||
| Gender | 7.72 | 1 | 0.005 | 0.016 | |||
| Male | 45.6% | 44.9% | 46.5% | ||||
| Female | 54.4% | 55.1% | 53.5% | ||||
| Age | 150.39 | 5 | <0.001 | 0.071 | |||
| 15–24 | 12.6% | 10.8% | 15.1% | ||||
| 25–34 | 15.1% | 15.0% | 15.2% | ||||
| 35–44 | 17.2% | 18.0% | 16.2% | ||||
| 45–54 | 17.3% | 17.9% | 16.5% | ||||
| 55–64 | 16.9% | 17.7% | 15.8% | ||||
| 65+ years | 20.9% | 20.7% | 21.2% | ||||
| Education ( | 528.37 | 5 | <0.001 | 0.132 | |||
| No full-time education | 0.5% | 0.2% | 0.8% | ||||
| 15– years | 21.9% | 19.7% | 24.8% | ||||
| 16–19 | 41.7% | 41.3% | 42.3% | ||||
| 20+ years | 25.3% | 29.5% | 19.7% | ||||
| Still studying | 8.4% | 7.7% | 9.3% | ||||
|
| 2.2% | 1.6% | 3.1% | ||||
| Political ideology | 659.16 | 3 | <0.001 | 0.148 | |||
| Left/liberal | 24.1% | 27.1% | 20.3% | ||||
| Moderate | 30.2% | 31.7% | 28.3% | ||||
| Right/conservative | 24.6% | 25.3% | 23.8% | ||||
|
| 21.0% | 16.0% | 27.7% | ||||
Socio-demographic associations with extra mitigation behavior (model set 2).
| Independent variables |
|
| |||||||
| Parameter estimates ( | Wald |
| Parameter estimates ( | Wald |
| ||||
|
| |||||||||
| Gender | 57.2 | 3.9e-14 | 61.1 | 5.3e-15 | |||||
| Male | −0.083 | (−7.566) | −0.086 | (−7.819) | |||||
| Female | 0.083 | (7.566) | 0.086 | (7.819) | |||||
| Age | 82.4 | 2.6e-16 | 87.3 | 2.5e-17 | |||||
| 15–24 | −0.370 | (−6.924) | −0.380 | (−7.132) | |||||
| 25–34 | −0.073 | (−2.635) | −0.084 | (−3.013) | |||||
| 35–44 | 0.095 | (3.848) | 0.097 | (3.906) | |||||
| 45–54 | 0.163 | (6.688) | 0.157 | (6.427) | |||||
| 55–64 | 0.120 | (4.804) | 0.132 | (5.276) | |||||
| 65+ years | 0.066 | (2.595) | 0.078 | (3.079) | |||||
| Education | 147.7 | 8.2e-32 | 157.8 | 5.6e-34 | |||||
| 15– years | −0.285 | (−9.638) | −0.300 | (−10.097) | |||||
| 16–19 | −0.038 | (−1.682) | −0.051 | (−2.276) | |||||
| 20+ years | 0.125 | (5.469) | 0.119 | (5.182) | |||||
| Still studying | 0.198 | (3.827) | 0.232 | (4.490) | |||||
| Political ideology | 19.7 | 5.4e-05 | 20.3 | 3.9e-05 | |||||
| Left/liberal | 0.058 | (3.774) | 0.064 | (4.138) | |||||
| Moderate | 0.008 | (0.539) | −0.002 | (−0.108) | |||||
| Right/conservative | −0.066 | (−4.030) | −0.062 | (−3.781) | |||||
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| Materialism/post-materialism (country groups) | 542.8 | 1.3e-118 | |||||||
| Materialist countries | −0.395 | (−21.925) | |||||||
| Countries with mixed values | 0.102 | (6.610) | |||||||
| Post-materialist countries | 0.294 | (19.231) | |||||||
| Wealth (country groups) | 684.6 | 2.1e-149 | |||||||
| Low | −0.296 | (−12.530) | |||||||
| Intermediate | −0.125 | (−6.311) | |||||||
| High | 0.421 | (26.050) | |||||||
Note: Models 2a and 2b separately include each of the two country-level variables, along with the four individual-level demographics.
Parameter estimates represent category-specific associations, of each independent variable, with extra mitigation behavior; z-values in brackets.
Behavioral characterization of “extra vs. common” mitigation behavior.
| Relative sizes/Mitigation actions | Segment membership probabilities | ||
| Segment 1: | Segment 2: | ||
| Relative size of segments | 0.7706 | 0.2294 | |
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|
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| qe6.1 | You have purchased a car that consumes less fuel, or is more environmentally friendly | 0.1345 | 0.2973 |
| qe6.2 | You are reducing the use of your car, for example by car-sharing or using your car more efficiently | 0.1651 | 0.4316 |
| qe6.3 | You have chosen an environmentally friendly way of transportation (by foot, bicycle, public transport) | 0.2654 | 0.4769 |
| qe6.4 | You are reducing your consumption of energy at home (for example by turning down air conditioning or heating, not leaving appliances on stand-by buying energy efficient products such as low-energy bulbs or appliances) | 0.5842 | 0.9254 |
| qe6.5 | You are reducing your consumption of water at home (for example not leaving water running when washing the dishes, etc.) | 0.5116 | 0.7926 |
| qe6.6 | Where possible you avoid taking short-haul flights | 0.0570 | 0.2958 |
| qe6.7 | You have switched to an energy supplier or tariff supplying a greater share of energy from renewable sources than your previous one | 0.0537 | 0.1558 |
| qe6.8 | You are separating most of your waste for recycling | 0.6284 | 0.9305 |
| qe6.9 | You are reducing the consumption of disposable items (for example plastic bags, certain kind of packaging, etc.) | 0.2618 | 0.8318 |
| qe6.10 | You buy seasonal and local products to avoid products that come from far away, and thus contribute to CO2 emissions (because of the transport) | 0.1500 | 0.6398 |
| qe6.11 | You have installed equipment in your own home that generates renewable energy (for example, a wind turbine, solar panels) | 0.0411 | 0.1051 |
Conditional (marginal) probabilities clarifying how segment-membership relates to each climate change mitigation action.
Psychographic associations with extra mitigation behavior (model set 1).
| Independent variables | Parameter estimates ( | Wald |
| Wald ( = ) |
| ||||
| Class 1 | Class 2 | ||||||||
| Model 1a: | |||||||||
| qe5… |
| ||||||||
| qe5.1 | Climate change is an | −0.04 | (−2.56) | −0.04 | (−2.56) | 6.5 | 0.011 |
| |
| qe5.2 | The | n.s. | −0.30 | (−2.52) | 6.4 | 0.012 | - | - | |
| qe5.3 |
| −0.10 | (−5.51) | n.s. | 30.4 | 3.5e-08 | - | - | |
| qe5.4 | Fighting climate change can have a | n.s. | 0.26 | (1.80) | 3.3 |
| - | - | |
| qe5.5 |
| 0.19 | (2.55) | −1.07 | (−3.24) | 71.2 | 3.5e-16 | 20.5 | 6.1e-06 |
| Model 1b: | |||||||||
| qe7… |
| ||||||||
| qe7.1 | You think that | 0.14 | (12.3) | 152.0 | 6.4e-35 | ||||
| qe7.2 | You think that it is | 0.08 | (7.36) | 54.2 | 1.8e-13 | ||||
| qe7.3 | You are very concerned about the | 0.18 | (16.9) | 286.6 | 2.8e-64 | ||||
| qe7.4 | You think that taking these actions will | 0.09 | (7.78) | 60.5 | 7.5e-15 | ||||
| qe7.5 | You have been | n.s. | 0.9 |
| |||||
| Model 1c: | |||||||||
| qe3… |
| ||||||||
| qe3.1 | The different | −0.20 | (−1.36) | 0.67 | (2.35) | 9.8 | 0.007 | 9.5 | 0.002 |
| qe3.2 | The different | 0.40 | (3.06) | −0.40 | (−1.33) | 17.4 | 0.000 | 8.4 | 0.004 |
| qe3.3 |
| −0.16 | (−1.28) | 0.41 | (2.27) | 7.2 | 0.027 | 7.2 | 0.007 |
Parameter estimates represent class-specific associations, of each independent variable, with extra mitigation behavior; z-values in brackets.