Nachhaltiges Produzieren und Konsumieren
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Footprint calculators are efficient tools to monitor the environmental impact of private consumption. We present the results of an analysis of data entered into an online Material Footprint calculator undertaken to identify the socioeconomic drivers of the Material Footprint in different areas of consumption, from housing to holidaymaking. We developed regression models to reveal (1) the impact of socioeconomic characteristics on Material Footprints of private households and (2) correlations between the components of Material Footprints for different arrays of consumption. Our results show that an increasing Material Footprint in one array of consumption comes with an increasing Material Footprint in all other arrays, with the exception of housing and holidaymaking. The socioeconomic characteristics of users have a significant impact on their Material Footprints. However, this impact varies by the array of consumption. Households only exhibit generally bigger Material Footprints as a result of higher incomes and larger dwellings. We conclude that indicators which strive to monitor resource efficiency should survey disaggregated data in order to classify the resource use to different population groups and arrays of consumption.
Green Information Systems in general, and footprint calculators in particular, are promising feedback tools to assist people in adopting sustainable behaviour. Therefore, a Material Footprint model for use in an online footprint calculator was developed by identifying the most important predictors of the Material Footprint of the calculator's users. By means of statistical learning, the analysis revealed that 22 of the 95 predictors identified accounted for 74% of the variance in Material Footprints. Ten predictors out of the 95, mainly from the mobility domain, were capable of showing a prediction accuracy of 61%. The authors conclude that 22 predictors from the areas of mobility, housing and nutrition, as well as sociodemographic information, accurately predict a person's Material Footprint. The short and concise Material Footprint model may help developers and researchers to enhance their information systems with additional items while ensuring the data quality of such applications.
Das Wuppertal Institut hat das Forschungsformat der Reallabore
konzeptionell und praktisch entscheidend mitgeprägt. Insbesondere in den
letzten fünf Jahren erlebt dieses Format einen ungeahnten Aufschwung.
Vor diesem Hintergrund blickt der vorliegende In Brief auf die Perspektiven für die künftige Forschung in Reallaboren. Drei Forderungen sind dabei von zentraler Bedeutung:
(1) die Besinnung auf die ursprünglichen Kern-Charakteristika der Reallabor-Idee,
(2) der systematische Capacity-Aufbau für Reallabore im Wissenschaftssystem und
(3) die Etablierung von langfristiger angelegten Reallaborstrukturen.
To contribute to a better understanding of consumer food leftovers and to facilitate their reduction in out-of-home settings, our study analyzes the effects of two common intervention strategies for reducing leftovers in a holistic behavioral model. Based on a quasi-experimental baseline-intervention design, we analyzed how the display of information posters and the reduction of portion sizes take an effect on personal, social and environmental determinants in a structural equation model. Applying data from online surveys and observations among 880 guests (503 baseline, 377 intervention) during two weeks in a university canteen, the suggested model allows to assign effects from the two interventions on plate leftovers to specific changes in behavioral determinants. Portion size reductions for target dishes are found to relate to lower levels of plate waste based on conscious perception, represented in smaller portion size ratings. Effects from seeing information posters are found to base on changed personal attitudes, subjective norms and perceived behavioral control. However, depending on how an individual reacts to the information (by only making an effort to finish all food or by making an effort and additionally choosing a different dish in the canteen) there are opposite effects on these determinants and consequently also on plate leftovers. Overall, the differentiated results on intervention effects strongly support the benefits of more holistic and in-depth analyses of interventions to reduce plate leftovers and therefore to contribute to more sustainable food consumption in out-of-home settings.
