The paper describes patterns of resource use related to German households' equipment. Using cluster analysis and material flow accounting, data on socio-demographic characteristics, and expenditures on fuel, electricity and household equipment allow for a differentiation of seven different household types. The corresponding resource use, expressed in Material Footprint per person and year, is calculated based on cradle-to-gate material flows of average household goods and the related household energy use. Our results show that patterns of resource use are mainly driven by the use of fuel and electricity and the ownership of cars. The quantified Material Footprints correlate to social status and are also linked to city size, age and household size. Affluent, established and/or younger families living in rural areas typically show the highest amounts of durables and expenditures on non-durables, thus exhibiting the highest use of natural resources.
In the face of growing popularity of eco-feedback innovations, recent studies draw attention to the relevance of the human factor for a more effective design of eco-feedback. This paper explores these challenges more deeply by employing a mixed methods approach. We provide in-situ insights from a Living Lab experiment on the effect of smart home systems and traffic light feedback on heating energy consumption in private households. Our results from an interrupted time series analysis of logged data on indoor room temperature, CO2 concentration and consumption of natural gas show that the interventions do not affect heating as expected, neither for automating behaviour via high-tech smart home systems nor via low-tech traffic light feedback. Smart home systems do not promise a significant reduction of heating energy consumption and a traffic light feedback on indoor air quality does not lead to a reaction of indoor CO2 concentrations, but may reduce heating energy consumption. Qualitative interviews on heating practices of participants suggests that comfort temperatures, lack of competences and inert heating systems do override expected effects of the feedback interventions. We propose that high-tech smart home systems should carefully consider the handling competences of users. Low-tech feedback products on the other hand should by design stronger address user experience factors like comfort temperatures.
Die Sustainable Development Goals (SDGs) schlagen zur Indikation verantwortungsvoller Konsum- und Produktionsstrukturen bzw. zum nachhaltigen Management und der effizienten Nutzung natürlicher Ressourcen den Material Footprint pro Kopf vor. Zudem sollen SDG-Indikatoren prinzipiell in der Lage sein, zwischen verschiedenen Bevölkerungsgruppen (etwa nach Einkommen oder Alter) unterscheiden zu können. Wir stellen einen Indikator aus der Nachhaltigkeitsstrategie NRW zum Ressourcenverbrauch des privaten Konsums auf der Grundlage von Mikrodaten vor. Der größte Ressourcenverbrauch der privaten Haushalte in NRW bleibt Wohnung, Nahrungsmittel und Verkehr vorbehalten. Dabei ist zwischen 2003 und 2013 die größte Steigerung des Ressourcenverbrauchs in Post und Telekommunikation zu verzeichnen, wobei sich insgesamt der Ressourcenverbrauch leicht reduziert hat. Der Indikator zum Ressourcenverbrauch der privaten Haushalte erfüllt die Anforderungen an Indikatoren der Sustainable Development Goals sowie der Nachhaltigkeitsstrategie des Landes NRW. Gleichzeitig empfehlen wir eine weitere Disaggregierung des Material Footprints nicht nur nach Bevölkerungsgruppen, sondern auch in Gütergruppen auf der Basis von Lebenszyklusanalysen.
The article argues for a need to overcome a conventional notion of product design. In this regard, the article offers an integrative and systemic approach to sustainable design. Instead of focusing on objects, a user-centred perspective is adopted. A sustainable design of products and services requires the integration of production-orientated (efficiency and consistency) and consumption-orientated (sufficiency) strategies. The article introduces the concept of an indicator that is capable of comprehending a lifecycle-wide analysis of products and that favours the integration of existing sustainability strategies. The goal is not to design sustainable products but rather to design systems that manage to foster sustainable lifestyles. The article illustrates the usability of the introduced concept by showing examples of strategic integrative thinking in sustainable design from the Sustainable Summer Schools.
We present the results of a regression analysis of a large-scale integrated user online application that surveys natural resource use and subjective well-being in Germany. We analyse more than 44,000 users who provided information on their natural resource consumption (material footprint) as well as their personal socio-economic and socio-psychological characteristics. We determine an average material footprint of 26 tonnes per person per year. In addition, we endeavour to determine how much environment humans need by regressing natural resource use as well as relevant socio-economic and socio-psychological features on subjective well-being. We establish a slightly negative correlation between subjective well-being and material footprints. A higher material footprint is associated with lower subjective well-being. We conclude that consumer policies seeking to promote sustainable behaviour should highlight the fact that a lower material footprint may result in greater subjective well-being.
Measure or management? : Resource use indicators for policymakers based on microdata by households
(2018)
Sustainable Development Goal 12 (SDG 12) requires sustainable production and consumption. One indicator named in the SDG for resource use is the (national) material footprint. A method and disaggregated data basis that differentiates the material footprint for production and consumption according to, e.g., sectors, fields of consumption as well as socioeconomic criteria does not yet exist. We present two methods and its results for analyzing resource the consumption of private households based on microdata: (1) an indicator based on representative expenditure data in Germany and (2) an indicator based on survey data from a web tool. By these means, we aim to contribute to monitoring the Sustainable Development Goals, especially the sustainable management and efficient use of natural resources. Indicators based on microdata ensure that indicators can be disaggregated by socioeconomic characteristics like age, sex, income, or geographic location. Results from both methods show a right-skewed distribution of the Material Footprint in Germany and, for instance, an increasing Material Footprint with increasing household income. The methods enable researchers and policymakers to evaluate trends in resource use and to differentiate between lifestyles and along socioeconomic characteristics. This, in turn, would allow us to tailor sustainable consumption policies to household needs and restrictions.
This paper argues that the contemporary growth paradigm needs to be reconsidered on a micro level of consumption and product service-systems. This becomes necessary since a dynamic link between macro strategies and micro implementation of sustainable growth is missing up to date. Therefore, mainstream sustainability strategies of efficiency and consistency are extended by sufficiency in order to integrate strategies for individual welfare within their social environment. Limits to and drivers for growth are revised and updated socially in terms of qualitative values, diminishing marginal utility or symbolic social distinction. We elaborate a definition of sustainable growth that fosters individual welfare by enhancing social enactment within the boundaries of environmental space. Shifting focus on social aspects in design fosters more sustainable production and consumption patterns while sustaining individual welfare. We derive latent indications for eco-intelligent product service-arrangements and evaluate to concepts by referring to introduced definitions and according indications. With doing so, we illustrate new pathways for the translation of sustainable growth and strategies into product service-systems.
Recent research on the natural resource use of private consumption suggests a sustainable Material Footprint of 8 tons per capita by 2050 in industrialised countries. We analyse the Material Footprint in Germany from 2015 to 2020 in order to test whether the Material Footprint decreases accordingly. We studied the Material Footprint of 113,559 users of an online footprint calculator and predicted the Material Footprint by seasonally decomposed autoregressive (STL-ARIMA) and exponential smoothing (STL-ETS) algorithms. We find a relatively stable Material Footprint for private consumption. The overall Material Footprint decreased by 0.4% per year between 2015 and 2020 on average. The predictions do not suggest that the Material Footprint of private consumption follows the reduction path of 3.3% per year that will lead to the sustainable consumption of natural resource
The effectiveness of sustainable product and service innovations is often restricted by limited market acceptance or unexpected consumption patterns. The latter includes rebound effects, which occur when resources liberated by savings are used for further consumption. Recently emerging research from the Living Lab is striving to address and anticipate challenges in innovation design by integrating users in prototyping and field testing product and service innovations. The paper presents findings from a literature review on rebound effects and expert interviews identifying methods to monitor and measures to mitigate rebound effects in early innovation design via Living Lab research.
We find that monitoring and mitigating rebound effects in Living Lab research includes technological and behavioural triggers as well as socio-psychological and time use effects in addition to economic re-spending effects. The experts have confirmed that Living Labs contain the potential to observe complex demand systems of users within experimental designs, encompassing indirect rebound effects in terms of expenditure as well as time use. In this respect, Living Lab research can facilitate support for sustainable innovations, which aim to encourage changes in consumer behaviour, considering re-spending and time use effects simultaneously.