Motivating energy conservation in organisations: smart metering and the emergence and diffusion of social norms

ABSTRACT

This study presents results from a smart metering intervention that provided detailed individual desk-based energy feedback to help individuals reduce energy in an organisation. Although the intervention was based on the study of individuals, this paper explores how the technology was socialised, and was set to explore changes in normative influence (descriptive and injunctive norms) around specific energy services, before and after the intervention. Results from the study identify that social norms around certain energy services changed as a result of the intervention, and the level of descriptive norms was found to have a direct effect on energy efficiency of participants. Interviews were carried out during the study and provided insight into social construction and social comparison processes occurring during the intervention as these are key to understanding the emergence and diffusion of social norms. Strong interaction between technologies/technology policy and social context was found.

KEYWORDS:

• Smart metering
• social norms
• energy
• feedback

Acknowledgements

We thank the funders for their support. We also wish to thank participants with the study as well as the wider REDUCE project. Thank you also to Ian Christie and Professor Don Webber for your useful comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Peter Bradley is lecturer in Economics at Bristol Business School, the University of the West of England. He was previously at the University of Surrey, Centre for Environmental Strategy (CES) in 2006 as an EPSRC research fellow. He has a BSc degree in Environmental Science, an MSc in Economic Management and Policy (University of Strathclyde) and a PhD in Ecological Economics (University of Surrey). Research projects in which he has been a researcher include: RESOLVE (research group on lifestyles, values and environment); REDUCE (reshaping energy demand of users by communication technology and economic incentives). He is currently the principal investigator for a project titled: Understanding and assessing business models for sustainability.

Shane Fudge is a Lecturer in Energy Policy at the University of Exeter. Projects that he has been involved in since beginning work in the area of sustainability include: RESOLVE (research group on lifestyles, values and environment; BARENERGY (barriers and opportunities to changing consumer behaviour at the EU level); UNLOC (understanding local and community governance of energy); CRISP (creating innovative sustainability pathways); and REDUCE (reshaping energy demand of users by communication technology and economic incentives). He has also been involved in consultancy work, the latest one commissioned by AMDEA into the relationship between technology and behavioural practices around household energy use.

Matthew Leach is a Professor of Energy & Environmental Systems. He joined the Centre for Environmental Strategy in 2007 and became Director of CES in 2008. An engineer by training, he holds a bachelor's degree in Mechanical Engineering from the University of Southampton, an MSc in Environmental Technology from Imperial College London and a PhD in Energy Policy also from Imperial. He is Vice President of the Energy Institute and past Chair of Council of the British Institute of Energy Economics.

Notes

1. ‘My superior(s)/Colleagues/people in my private life who are important to me think I should {e.g., switch off the monitor … ]’ rated on a scale ranging from disagree to agree, with an additional option I really don't know. The descriptive norm items included two items stating ‘My superiors/colleagues [switch off their monitor … .}’, rated on a scale ranging from never to always and the option I really do not know (765, line 6).

2. Goodman and Haisley (2007) identify that there are a number of ways to classify social comparison processes. They identify initiation, selection of referents and an evaluation process as important.

3. In the conclusion of their work Cialdini, Kallgren, and Reno (1991) identify that norms can be demonstrated to effect action systematically and powerfully and that individual behaviour is likely to conform to the type of norm that is the present point of focus – even when alternative norms dictate different conduct. Cialdini et al state that, due to the possible influences of the three different types of norm, one must be careful in specifying the particular type of norm that is being made salient by a given technique or mechanism.

4. To see more detail on the feedback tool (MEF), please see Appendix 2 and Muthagher et al. (2013).

5. Social norms in relation to certain energy services were measured in surveys using Likert scale questions.

6. As one participant put it:

‘turn the lights off’, ‘keep off the grass’ – you see signs like this everywhere. Yeah, but ‘turn off your monitor’, ‘turn off your computer' … this is very recent. People are not used to that, eh, culture. There is a culture of turning off the light. There is no culture for turning off the computer. (participant 4)

7.

‘the sum total of a complex of institutions and interrelated habitual models of thinking, acting, and feeling (including the corresponding valuations, norms and interpretations of the world of a particular epoch)-thus comprises the man-made learned and transmitted adaptive tools which form the prerequisites of human life and survival. In order to survive and exist, each individual must learn and master the system of institutionalised behaviour patterns that his group or society transmits to him in the process of enculturation.’

8. The results align with energy feedback which was desk based (computers and monitors and other desk- based items).

9. We did not have data for the particular variable for one of the 18 participants.

10. This was chosen as opposed to monitors as computers use significantly more energy than monitors.

11. Participant 3 also recalled a negative perception of the start of the project and how it was introduced.

12. Participant 1 identified that there was a positive attitude. Participant 1 further identified common agreement on taking part in his office (question 6). Participant 5 identified that he did not know of anyone refusing to take part, or joking/procrastinating, but identified that it may happen (question 6). The response from participant 8 to question 4 was: ‘It was not bad’.

13. The introduction made by the management was an unplanned impromptu face-to-face introduction to the project to participants (beyond that made by electronic communication).

14. When asked question 3, participant 3 responded: ‘The academics thought it was very important.’ Question 6 was not answered directly by participant 3. Participant 7 gave the following account for question 3:

‘Have not heard much, but think it has just become a part of things. I don't think people were very enthusiastic about it, and I have not seen much concern about it.’ And question 4: ‘Initially, there was not much enthusiasm. After some time, people were willing.’

15. Participant 2 (PhD student) and 4 (researcher) tend to ‘hang out’ with other researchers within their department.

16. Of the data that we have for these latter participants, descriptive norms only increase for two of the four energy services (participant … ); participant 3 saw a small increase in all norms. The latter participant did use MEF, the former did not.

17. The current authors identify that it may effect referent selection and evaluation processes in social comparison.

Additional information

Funding

The research was funded by the Digital Economy Programme of the Research Councils UK (a cross-council initiative led by EPSRC and contributed to by AHRC, ESRC and MRC) under the REDUCE Project [grant number EP/I000232/1].