Open innovation methods to co-operate for CC?

Towards sustainable consumption: A framework for a houshold environmental management system.

Pedro Baptista and Nuno Videira

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The encouragement of proactive behavior from consumers is vital to promote a sound implementation of sustainable production and consumption policies. To address this challenge, this paper explores an innovative framework supporting the conceptualization of a tool to evaluate and continuously improve the environmental performance of households - the Household Environmental Management System (HEMaS).

One of the distinguishing features of the analysis is the consideration of rebounding effects, which was facilitated by the use of indicators of environmental impacts per euro of products. Unlike conventional simulators of environmental impacts of private consumption, the proposed framework considers all consumption and not only priority categories. In this way, the rebound effect is considered, which promotes the environmental optimization of the application of disposable income, as opposed to a simple “reduction of consumption” policy. HEMaS receives input data on expenditures and household activities, and then generates an environmental profile and personalized measures for improving household environmental performance. The paper concludes with a discussion on the potential advantages and limitations of the tool in supporting sustainable consumption policies and voluntary adoption of performance improvement measures by responsible consumers.

1. INTRODUCTION

Today’s society is facing a major challenge on its quest for sustainability and we are living in a moment of social, economic and ecological unrest. In many parts of the world the welfare is not increasing, the gap between rich and poor is rising, the markets are facing great instability, and natural resources are being over-exploited (Sanne, 2007).

According to Sanne (2007), the efforts put on environmental policies have only brought marginal ecological improvements in contrast with what is said by the political discourse, given the fact that the persisting political-economic paradigm is still one of unfettered economic growth. Within this context, there is a particular need to rethink strategies to address the growing levels of production and consumption (TNO et al., 2008).

In spite of economic growth our quality of life has not improved (Sanne, 2007), so it is crucial to redefine progress working more closely with consumers. The encouragement of proactive behavior from consumers is vital to promote a sound implementation of sustainable production and consumption policies. According to the Eurobarometer (DGE, 2008) the main challenge at the consumer level is to translate the Europeans’ green attitudes into environmentally friendly behaviour and concrete actions. This paper will address this issue by presenting a tool (Baptista, 2008) – HEMaS, Household Environmental Management System, to assist households in improving their environmental performance with respect to consumption practices, based on an innovative analytical framework which accounts for rebound effects¹.

Section 2 of this paper briefly presents the rebound effect and develops the analytical framework that supports the conceptualization of HEMaS (Section 3). On Section 4 we discuss the potential advantages and limitations in implementing HEMaS.

2. FRAMEWORK FOR ANALYSIS

The rebound effect is a major concern of environmental policy and for the pursuit of sustainability. The rebound happens every time environmental gains from increasing efficiency are offset by the consequential rise on demand for goods and services. Thus, technological progress is not sufficient for promoting sustainable development (Sanne, 2000; Binswanger, 2001), since the prevalent economic paradigm will tend to the limits of exploration of Earth’s resources.

Hence it is fundamental that environmental policies combine technological progress with sustainable lifestyles and quality of life improvement (Herring & Roy, 2007). The rebound effects are significant and should be considered on the designing of Sustainable Consumption and Production (SCP) policies (Sanne, 2000). Within this context, focusing on the role of consumers is expected to leverage the effectiveness of policies, avoiding rebound effects (EEA, 2008). This background suggests the need for a new and more holistic (TNO et al., 2008) framework for sustainability analysis of SCP policies.

In line with these arguments, Sanne (2000) presented a roadmap with some options to avoid the rebound effect, which may be translated in the following consumer-oriented guidelines:

• 
  Reduction of working hours to limit production and to improve the quality of life;
  
• 
  Reduction of the environmental impacts per euro (EI/€) of products through increased efficiency, administrative and economic means;
  
• 
  Redirection of consumption from environmental harmful products to more friendly ones.
  

The actual net environmental gains of SCP policies and measures are dependent of the types of products that are replaced (e.g. substitution of travels by train with car due to its efficiency improvements), by products that are purchased with the financial savings, and the readjustment of the whole economy. To this extent, the consumers’ financial resources should shift from the consumption of certain products to others with less EI/€. This approach is potentially valuable at a micro level but to define concrete actions at a macro level it requires a better comprehension of the environmental impacts (EI) of various activities and their price and income elasticities (Sanne, 2000).

• 
  It manages better the redirection of consumption to minimize the EI from the application of household’s disposable income. What matters is the difference of EI between the products substituted, either by reducing or promoting consumption;
  
• 
  It has potential to serve as a platform for the operationalization of sustainability strategies (e.g. linked with markets of environmental compensation, management of data and of information on organizations’ environmental accounting).
  

HEMaS is a systemic tool which uses data on consumption patterns and on certain household activities as an input, generating environmental performance information and concrete proposals for action as outputs. It monitors household consumption patterns, behaviour and respective EI. After this procedure a consumer profile is analyzed to produce an action plan to be reported. This cyclic operation of HEMaS provides all elements necessary for the continuous environmental improvement. The timescale of this cyclical process is flexible (e.g. monthly, quarterly) depending on the specific objectives of the initiative. HEMaS is composed of five steps: 1) characterization of a household expenditure patterns; 2) characterization of consumer activities; 3) evaluation of the associated EI; 4) assessment of the measures’ significance; 5) communication of an action plan.

The structure and detail of the characterization of a household expenditure patterns (step1) must be in accordance with the study provider of EI/€ data. The use of reference classifications like COICOP (Classification of Individual Consumption According to Purpose) minimizes errors from allocation of data. Additionally, the number of classes of products considered depends also on the initiative’s objectives. The characterization of the expenditure patterns may be obtained through questionnaires (online or personal), or through methods of automatic monitoring. If only questionnaires are used the number of categories that may be monitored is more limited. Therefore, the automatic monitoring option is more promising although it requires a major infrastructure. Nevertheless both options can be complementary allowing the gradual expansion of the infrastructure for automatic monitoring. For example, at an inception stage of HEMaS implementation, some data on household expenses may be obtained through a dedicated credit card, or through customers’ accounts of various retailers.

The second step of HEMaS has two purposes: a) to consider the variability of the EI of products according to the household practices (e.g. sending or not a product for recycling); b) to provide a more functional perspective of consumption by distributing key products (e.g. water, energy) through household activities (e.g. washing, watching TV). This last feature allows for a better analysis of a household profile, subsequently generating more targeted measures for improving environmental performance. The characterization of household activities (step 2) can be developed through complementary methods: audits, questionnaires, and instant monitoring. The audits are more suitable to make the inventory of household infrastructures (e.g. characteristics of appliances, existence of tap aerators). Nevertheless, the characterization of the “actual” household activities has to be based on questionnaires and instant monitoring. In order to ease this process, the use of mobile phones (see project mobGAS²) to register instantly the activities can be an option.

After the household profile has been drawn (i.e. expenditure patterns and characterization of activities) it is possible to estimate the associated EI. This third step of HEMaS is an algorithmic procedure where expenditure patterns are multiplied by EI/€ indicators. As a result, it is presented the EI of each category of consumption products, and also it is allocated EI of key products (e.g. water, energy) to the respective activities where the consumption takes place. The EI/€ of products can be extracted from studies such as EIPRO (Tukker et al., 2006; see more on Tukker & Jansen, 2006). EIPRO is the most detailed study of this sort for the scope of EU-25, providing EI/€ (abiotic depletion, acidification, ecotoxicity, global warming, eutrophication, human toxicity, ozone layer depletion, and photochemical oxidation) for 282 categories of products.

On the fourth step of HEMaS the environmental profile and the characteristics of the household are analyzed in order to generate personalized measures. The measures consist of promoting green behaviour (e.g. recycling), consumption of low EI/€ products, and/or reducing the consumption of high EI/€ products³. The determination of the significance of measures is based on the criteria of bringing more environmental gains with less consumer resistance. Such approach has the advantage to improve the acceptability of measures and also to establish consumption thresholds (e.g. at a certain stage, a household cannot improve anymore its profile on food consumption despite it still has significant EI). To identify the areas with more potential to act, an analytic procedure may be carried out through which a household environmental profile is compared with reference values or benchmarks. These may be modeled for different types of consumer lifestyles or derived from the profiles of similar households with better environmental performances. Adopting the latter alternative confers an empirical apprenticeship nature to HEMaS. As more and more consumers use this tool, the system will be able to compute the more adequate measures based on the historic analysis of similar households. This approach may be deployed through DataMining techniques.

1. 
   The number of categories of consumption determines HEMaS’s detail. The more categories considered the less variability of EI between the individual products in each category, leading to smaller errors on the household’s EI estimates. However, a more detailed HEMaS require almost exclusively the automatic monitoring for the household’s pattern of expenditure characterization. Also, it is important that the EI/€ are periodically calculated so that HEMaS goes along with the evolution of markets.
   
2. 
   At a maximum detail, HEMaS may account for the EI of single products. Until then it is important to differentiate the products with added-value (e.g. green labels) from the conventional products of each category in order to correct the EI estimated from that consumption. If this is overlooked, the added-value products would have the same EI/€ of the conventional products, and therefore adjustment coefficients are needed to avoid this limitation.
   
3. 
   Households may be indirectly contributing to EI even when they are not consuming. Such is the case of savings deposited in banks, which are then used in financial applications. This begs for the analysis of the environmental effects arising from decisions and policies adopted by financial institutions.
   
4. 
   EI in HEMaS are estimated directly from household expenditure patterns. Nevertheless, this may include sometimes “unusual” consumption like vacancies or a car purchase. This is translated in a high variation of the household’s environmental profile through time. To overcome this, the EI of some categories of consumption should be distributed along a certain period of time. One option is to operate HEMaS at a higher temporal scale (e.g. quarterly, yearly). Other way is to distribute the EI of products by their approximate lifetime.
   
5. 
   HEMaS’s second step (where household activities are characterized) may require too much effort, namely: a) on the quantification of coefficients to adjust the EI/€ according to consumers’ behaviour (e.g. when the household recycles); b) on the audit to collect the characteristics of the household appliances (e.g. power), in order to link the activities with the consumption of electricity, for example. Therefore it is suggested to use standard values in these situations as reference starting point.
   
6. 
   Options for improving the generation of measures are twofold: a) allowing the consideration of household’s opportunity for change (analysis of its accessibilities, such as an assessment of the public transport network as a realistic option instead of private transport); b) evaluation of when investments on more efficient appliances becomes environmentally beneficial (e.g. answering questions such as “Is it better to substitute my refrigerator or should I wait for the end of its lifetime to do so?”).
   

Other limitations worth mentioning are related with monitoring of household consumption (e.g. possible concerns for disclosing private information to the system) and assuring household’s commitment to implement the suggested measures for improving their environmental performance. As such, given the voluntary nature of this tool, managers of the system (e.g. local governments, NGO’s, firms, environmental national authorities) should prepare programs to encourage household participation, such as local communities’ environmental awards, analogies to the concept of voluntary initiatives coordinated by consumers (e.g. Eco-Teams⁴, Environmental Home Guard⁵), integration with markets of environmental compensation, among others.

The tool conceptualized in this paper (HEMaS) aims to evaluate and continuously improve the environmental performance of households, supported by an innovative analysis which accounts for rebound effects in consumption activities. The indicators of EI/€ proved their potential to avoid these effects, although further research is needed on its prospective application in areas such as organizations’ sustainability reporting, assessment of environmental subsidies, and internalization of externalities.

Additionally, the approach adopted in HEMaS may be linked with other sustainability concepts such as participated democracy through civil society organizations, voluntary internalization of environmental costs (association to carbon offsetting companies), data management for organizations’ sustainability reporting. This is particularly relevant since nowadays the overburden of information and lack of standardization is working against the efforts for proper provision of information to consumers.

Despite the advances this paper may bring to research on how to avoid the rebound effects it does not respond unequivocally which are the best directions towards sustainability. To achieve this, further research is needed in order to understand the macro implications of concrete actions, overtaking sustainability barriers and confronting prevailing growth paradigms – the very core of the rebound effects.

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