SMART METERS OR SMART CAMPAIGNS?

Vincent Carragher, Tipperary Energy Agency

Paul Kenny, Tipperary Energy Agency

Richard Moles, CES, University of Limerick

ABSTRACT

The case for strategic education type interventions and moving beyond one

dimensional technological fixes is very strong (Pilkington et al, 2011). However, poor

engagement prior to environmental campaigning is a serious obstacle to behaviour

change and a recent Irish example of this has been critiqued (ESRI, 2013).

Furthermore, a relatively poor behavioural change response has been recorded by

Smart Metering Campaigns (ACEEE, 2012). Facilitating engagement through

ownership of community endeavour is crucial to driving behaviour change (DEFRA,

2007). The need for behaviour change is great in Ireland as Ireland’s CO2 emissions

in 2009, at 13.8tonnes per capita, were the second highest in Europe (CSO, 2012).

Here, methods for facilitation of community engagement are reviewed, with specific

reference to a successful four year intervention within a Irish community led by the

author.

Introduction

The need for behaviour change is great in Ireland as recent CO2 emissions, at

13.8tonnes per capita, were the second highest in Europe (CSO, 2012). The

relatively high energy use within Irish households (ODYSSEE, 2009 and ADEME,

2012) has been well documented. Irish resource use as estimated by Domestic

Material Consumption is 48t per person, while the EU average is one third of this

(DECLG, 2012). Our Sustainable Future estimates 3 planets are required to support

Irish lifestyles and related greenhouse gas emissions have steadily increased since

the origin of the agricultural and industrial revolutions.

Despite this there has been relative inertia at governmental level to move beyond

efficiency type solutions & parallel “Growth of Limits” reasoning. The following

challenges contribute to the efficiency gap and mean that gains in efficiency do not

necessarily convert to energy savings and sustainable change:

1. The rebound effect

2. Simplistic assumptions and analysis belie the large variations in measured

consumption meaning that a one size fits all approach fails (Weber &

Matthews, 2008 and Wiedenhofer et al, 2013). Variations can sometimes be

explained by disparities in the built environment but authors also note that

behaviour of occupants also plays a strong part (Morley and Hazas, 2011).

3. Householder’s poor interaction with technology illustrated here by poor use of

programming features of heating systems (Peffer et al, 2011). Authors relate

that this is due to the poor understanding of heating systems by householders

(Huebner et al, 2013).

4. Relatively poor energy saving recorded by Smart Metering Campaigns

(ACEEE, 2012 and Vassileva et al, 2013). Savings were recorded in the

range 0 - 9.3% with an average saving of just 3.8% (ACEEE, 2012). In other

evaluation control groups with no smart meters saved more than

householders with them (Alexander and Hunt, 2013).

The prominent focus within behaviour change literature focuses at the individual

scale and though this line of enquiry has value, humans are a social animal and

relationships, interactions, discourses and effects within social networks are diverse.

It is in this context that a systems approach to analysis is essential, because the

components cannot easily be separated as conventional study often argues.

Conventional information campaigns and above the line marketing campaigns follow

the reasoning of the Expectancy Value Models (EVMs). The attitude behaviour gap

defines poor correlation between attitude and behaviour and necessitates the

expansion of EVMs beyond information provision as a behavioural determinant

(Newton & Mayor, 2013).

To avoid the poor response to campaigns such as the Power of One (ESRI, 2013)

engagement and ownership are key to success and potential behaviour change

(DEFRA, 2007). In one of 5 guiding principles for sustainability NESC (2013)

advocate positive community participation. There is a burgeoning realisation

illustrated in the Green Paper on Energy Policy in Ireland placing huge importance

on informed engagement by the public mentioning the latter some 32 times.

Facilitating engagement leverages ownership of community endeavour shortening

the participation gap and this is crucial to driving behaviour change and sustainability

(ENECE, 1998 & DEFRA, 2007). At the practioners level this has been critical to

multiple examples and one pan-European example is Energyneighbourhoods.

Authors also find that social community-based-intervention impacts resource-saving-

behaviour (Hori et al, 2013 & Doyle & Davies, 2013).

Against this background this paper intends to narrow the gaps mentioned identifying

factors which drive sustainability assessment and resource saving action. Such

identification may have implications to those working with communities across the

Social, Economic, Policy, Technology and Behavioural Psychology spectra. Here,

factors are first identified after which their relevance is tested on 2 groups of

householders.

Methods

A desktop and evidence based investigation, to identify factors which drive

sustainable behaviour change at the local level, was carried out over the last 10

years. The desktop research reviewed academic literature while the evidence based

investigation firstly reviewed collating-resources such as the DG environment

website, the DG Energy and Transport, ‘Science for Environment Policy’ publication,

Doug McKenzie-Mohr’s Fostering Sustainable Behaviour initiative and Listserv, the

Managenergy program, the Intelligent Energy Europe program and the Transition

Towns scheme. Secondly field investigation including consultation, conferences,

seminars and workshops with relevant stakeholders and Bridging Organisations

(BOs) were utilised to identify factors. The evidence based research was enriched by

collaboration with the partners (BOs) of European projects including

Energyneighbourhoods, Mobilise Energy Awareness and Grundtvig.

Subsequent to identification the factors are tested for utility on 2 groups of

householders in Tipperary. The first group, a community in Tipperary (N=659) are

asked using a census style survey which of the factors they regard as having been

most relevant in driving their sustainable change. This survey succeeded the

application of a resource saving intervention which was applied once yearly for four

years. This four year intervention involved annual measurement of householder

resource consumption using an Ecological Footprint Survey and was followed by a

resource saving campaign (EF-EAC). The community reduced its stated

consumption by 28% over the four year intervention and so this community provides

an ideal context for testing factors which drive sustainable change.

The second group of households (N=500) were subject to a Local Authority retrofit

scheme part of which was the installation of wireless smart meter technology. This

installation was followed by a 15 minute induction familiarising each householder

with the use and functionality of the meters. A survey establishing meter use was

conducted post-retrofit using a random sample of the houses according to the

proportions in Table 1. This survey was door step, conducted 12 months after the

retrofit and simply enquired as to the whether the householder used the meters and

if so what they used them for. The survey was followed by a check with the principal

and relevant engineers in the Local Authority as to their experience of the

technologies uptake.

Table 1: Population size classes and percentage households sampled (Foley,

2006)

Population size

(no. of people)

Minimum % of sampled

households

491-1260 10 %

1261-2699 8 %

2700-11098 4 %

11099-22051 2.5 %

22052-86998 1.75 %

Results

(1) Factor List

A list of 58 factors were reviewed (Table 2) and these include 16 actors, 29 drivers

and 13 messaging factors relevant to community sustainable change. Actors that

enliven resource saving action include three types of learning environments Schools,

Universities and further education providers. Programs at this level are too numerous

to catalogue but include the Green Schools, Eco-Schools Programme and the

Community Carbon Reduction Project. Faith Organisations or networks such as

Noah’s Alliance or The Regeneration Project are also relevant. Locally based

environmental champions are key to sustainable change and their impacts have

been shown in numerous projects such as Energneighbourhoods, Klimaatwijken and

Tools of Change. Local Agenda 21 formulates a sustainable role for Local Authorities

and underlines their importance in devolution of sustainable governance. Berkes

(2009) points to the importance of Bridging Organisations and co-management in

sustainable change.

Indicators or measurement support the ascription of responsibility for consumption

with the user (Delmas et al, 2013) as does customised feedback (Barr, 2004).

Bridging metaphors make technical information more understandable and are also of

benefit in sustainable change. Inauen et al (2013) report that increasing commitment

strength provides benefit. Authors inter alia Mizobuchi & Takeuchi (2013) advocate

incentives as drivers while Abassi (2006) discusses the importance of rivalry. The

incorporation of descriptive and personal norms into intervention material and

process is also significant (Goldstein et al, 2008).. Authors, inter alia Leiserowitz,

advocate that immediacy has a role in effective communication. Inclusion of ‘other

benefits’ such as health (Leiserowitz in Moser and Dilling, 2007), local improvements

(Burningham and Thrush, 2004) and jobs, household or self-improvements (UNEP,

2005) is also important. While Ek & Soderholm (2010) discuss the specific

advantages offered by practical benefits. Increasing agency (one’s belief in one’s

ability to bring about change) (Darnton, 2004) and referring to place also has

significant benefits for sustainable change (Goldstein et al, 2008).

A strong example of effective policy and regulation in Ireland are the iterations of the

plastic bag tax. Infrastructural benefits are underlined by the increase in recycling

services and centres which support the greening of waste habits. Social capital

indicates social interaction and structure and its increase also increases

sustainability. Many believe that targeting specific audiences can be of huge benefit

in effective communication for sustainable change. On the other hand it has been

argued that an enormous range of motivations should be included in advice for

“almost everyone” to embark on sustainable change (NEF, 2008). Some authors

designate money saving potential as the strongest driver for sustainable change

(Huebner et al, 2013 and Han et al, 2013). Berkes (2009) discuss the importance of

Bridging Organisations and co-management while Lejano et al (2013) show the

importance of integrating local narrative and reinterpretation. Modelling,

benchmarking and the example set by exemplar communities are also important and

skilled facilitation provides a structure for and enables experiential learning providing

a strong driver for sustainable change.

Due to the confines of space and the extent of this research the above is a short

summary of identified factors and more in depth discussion of the relevance of these

factors can be found in Carragher (2011).

Table 2: Reviewed Factors

No. Actors No. Actors

1 Human actors 9 Higher Education Institutions

2 Religious groups 10 Business actors

3 Community/focus/local groups 11 Networks

4 Energy/environmental champion 12 Bridging Organisations

5 Project manager 13 Government

6 Local Authorities 14 European/Global actors

7 First /second level educators 15 Further education providers

8 Social Media 16 Exemplar/model communities

No Drivers No Drivers

1 Public disaffection 16 Effective communication

2 Social capital & participation 17 Feedback

3 Population pressure & land demand 18 Commitment

4 Environmental damage & global

warming

19 Indicators/measurement/audits

5 Public opinion and dialogue 20 Compliance & incentives

6 Norms 21 Agency

7 Local circumstances 22 Policy

8 Infrastructure 23 Technology

9 Local Agenda 21 24 Rivalry

11 Ascription of responsibility 26 Identify and target barriers

12 Financial 27 Skilled facilitation

13 Training 28 Surveys

14 Regulation 29 Moral dilemma

15 Experiential Learning

No Messaging Factors No Messaging Factors

1 Internalising the message 8 Narrative threads

2 Economic benefits 9 Bridging metaphors

3 Descriptive norms 10 Immediacy

4 Modelling 11 Recognition & personal norms

5 Solution orientated messaging 12 Other benefits (jobs, health etc.)

6 Practical benefits 13 Audience demographics

7 Importance of place

(2) Factor Test

The factors which caused sustainable change in the tested community (N=659; RR =

35%) are presented in Figures 1 and 2. Figure 1 shows the reported factors which

were most salient to the intervention and its sustainable behaviour change according

to the residents sampled. Figure 2 shows the most important factors which were

present in the community and so not specifically part of the intervention study. Given

the intervention worked with Bridging Organisations present in the community there

is certain overlap between the 2 figures.

Figure 1: The factors relevant to the community which were included in the EF-

EAC intervention

Figure 2: The factors relevant to the community which were external to the EF-

EAC intervention

(3) Meter Use Survey

The survey showed a 5% use of meters for energy monitoring by the Local Authority

householders (N=500). The engineers who manage the households for the Local

Authority and who are familiar with the households and their occupants agreed with

the 5% survey finding. The survey found a general mistrust and fatigue of such

technology amongst those sampled. A number of the meters were not used for

energy monitoring but had instead been utilised as a clock. The potential beneficiary,

of using meters, was challenged by a number of householders. The utility of remote

meters versus that presented by existing utility meters was also an issue. The

question of the economics of using such meters was a worry for some of those

sampled. These challenges and the poor technology use existed despite the

technology induction for each householder.

Conclusions

A list of factors useful for those involved in resource conservation within communities

has been identified. The list is not definitive but instead representative of the

communities, literature and views sampled in this research. It is therefore

recommended that the list is reviewed and extended by others in order to benefit

those working on or within communities. Figure 1 shows local BOs, measurement,

feedback and bridging metaphors to be important. While Figure 2 shows recycling

depots (infrastructure) and moral dilemma as significant factors in sustainable

change. It is apparent from the factor testing that a customised list should be framed

for each community.

These factors will have implications to those working on conservation of resources

with communities across the Social, Economic, Policy, Technology, Communication

and Behavioural Psychology spectra. An example of a direct implication of this

research is the need for research on wireless meter technology in relation to

communication and engagement. Testing the energy saving potential of this

technology against various drivers such as immediacy would be hugely beneficial.

To this end inter-disciplinary learning between those representing technology,

communication, social science and behavioural psychology would be no small

benefit. Supporting the integration of knowledge and combination between the

disciplines is vital for sustainability. A multi-track approach will be essential to move

beyond one dimensional fixes and to support sustainable change.

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