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Promoting behaviour change through personalized energy feedback in offices a
a
a
Michael J. Coleman , Katherine N. Irvine , Mark Lemon & Li Shao
b
a
Institute of Energy and Sustainable Development , De Montfort University , The Gateway , Leicester , LE1 9BH , UK b
School of Construction Management and Engineering , University of Reading , PO Box 217, Whiteknights , Reading , RG6 6AW , UK E-mail: Published online: 23 Jul 2013.
To cite this article: Building Research & Information (2013): Promoting behaviour change through personalized energy feedback in offices, Building Research & Information To link to this article: http://dx.doi.org/10.1080/09613218.2013.808958
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BUILDING RESEARCH & INFORMATION 2013 http://dx.doi.org/10.1080/09613218.2013.808958
RESEARCH PAPER
Promoting behaviour change through personalized energy feedback in o⁄ces Michael J. Coleman1, Katherine N. Irvine1, Mark Lemon1 and Li Shao2
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1
Institute of Energy and Sustainable Development, De Montfort University,The Gateway, Leicester LE1 9BH,UK E-mails:
[email protected],
[email protected] and
[email protected] 2
School of Construction Management and Engineering,University of Reading, PO Box 217, Whiteknights, Reading RG6 6AW,UK E-mail:
[email protected]
A body of research suggests that the provision of energy feedback information to building users can elicit significant energy reductions through behaviour change. However, most studies have focused on energy use in homes and the assessment of interventions and technologies, to the neglect of the non-domestic context and broader issues arising from the introduction of feedback technologies. To address this gap, a non-domestic case study explores the delivery of personalized energy feedback to office workers through a novel system utilizing wireless technologies. The research demonstrates advantages of monitoring occupancy and quantifying energy use from specific behaviours as a basis for effective energy feedback; this is particularly important where there are highly disaggregated forms of energy use and a range of locations for that activity to take place. Quantitative and qualitative data show that personalized feedback can help individuals identify energy reduction opportunities. However, the analysis also highlights important contextual barriers and issues that need to be addressed when utilizing feedback technologies in the workplace. If neglected, these issues may limit the effective take-up of feedback interventions. Keywords: behaviour, energy demand, energy monitoring, feedback, human agency, offices, wireless technologies Un corpus de recherche sugge`re que la fourniture d’informations de feedback e´nerge´tique aux utilisateurs d’immeubles peut susciter des re´ductions importantes de la consommation d’e´nergie par des changements de comportement. Cependant, la plupart des e´tudes ont porte´ principalement sur la consommation d’e´nergie dans les logements et sur l’e´valuation des interventions et des technologies, au de´triment du contexte non re´sidentiel et des questions plus larges de´coulant de l’introduction des techniques de feedback. Pour combler cette lacune, une e´tude de cas non re´sidentiel examine la fourniture d’un feedback e´nerge´tique personnalise´ a` des employe´s de bureau au moyen d’un syste`me nouveau utilisant les technologies sans fil. Les recherches de´montrent les avantages d’un suivi de l’occupation et d’une quantification de la consommation d’e´nergie a` partir des comportements spe´cifiques comme base pour un feedback e´nerge´tique efficace; ceci est particulie`rement important la` ou` existent des formes fortement de´sagre´ge´es de consommation d’e´nergie et un e´ventail de lieux ou` cette activite´ peut se de´rouler. Les donne´es quantitatives et qualitatives montrent que le feedback personnalise´ peut aider les individus a` identifier les possibilite´s de re´duction de la consommation d’e´nergie. Ne´anmoins, cette analyse met e´galement en e´vidence les obstacles contextuels importants et les questions qu’il convient de traiter lors de l’utilisation de techniques de feedback sur le lieu de travail. Si elles sont ne´glige´es, ces questions pourraient limiter l’adoption effective des interventions de feedback. Mots cle´s: comportement, demande e´nerge´tique, suivi e´nerge´tique, feedback, interme´diation humaine, bureaux, technologies sans fil
Introduction Energy use in buildings is recognized as a significant contributor to greenhouse gas (GHG) emissions. In # 2013 Taylor & Francis
the UK, it is estimated that buildings accounted for approximately 38% of GHGs by end-use in 2009 (Department of Energy and Climate Change (DECC),
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Coleman et al.
2011). As a consequence, energy reduction has become a key focus amongst multiple stakeholders with initiatives to reduce energy use in existing buildings viewed as an important way to meet UK carbon-reduction commitments (Janda, 2011; Lomas, 2010). One area receiving renewed consideration is the provision of feedback about energy consumption to the user. Reviews of previous research, largely conducted in the domestic sector, suggest that providing building users with more timely and engaging feedback information could deliver significant energy reductions through behaviour change. Darby (2006) argues that reductions of around 5– 15% can be achieved from direct feedback (i.e. real-time feedback, such as that provided by in-home displays) and between zero and 10% from indirect feedback where information has been processed before being viewed by the recipient (e.g. enhanced energy bills). Similarly, Ehrhardt-Martinez, Donnelly, & Laitner (2010) and Fischer (2008) report that electricity savings of between 4– 12% and 5– 12%, respectively, can be realized through the effective provision of feedback in homes. Underpinning the use of feedback is the notion that more specific information increases the visibility of energy consumption, raises people’s awareness of the opportunities for reduction, and allows people to experiment and manage their energy use more effectively (Darby, 2008). The literature from domestic feedback research suggests several key attributes to optimize behaviour change including accuracy of information, prolonged and frequent feedback (e.g. real-time), disaggregation to specific energy end-uses (e.g. appliances), and an interactive, understandable and appealing content that is tailored to the contexts of people’s energy use (Darby, 2006; Ehrhardt-Martinez et al., 2010; Fischer 2008). It is also apparent that additional interventions may be required to improve users’ motivation and knowledge (Darby, 2010; Raw & Ross, 2011). There is particular interest in the delivery of energy feedback through new technologies, such as in-home displays that often utilize wireless communication to provide real-time information (Ehrhardt-Martinez et al., 2010). The introduction of feedback displays, along with the rollout of smart meters, now appears to be a central policy mechanism to encourage energy saving in buildings through behaviour change – the UK government aims to have smart meters in all homes by 2019 and is mandating feedback displays (DECC, 2011). However, the majority of empirical feedback studies have focused on electricity use in dwellings, raising questions about the transferability of findings to the non-domestic setting. Furthermore, research has often concentrated on the effectiveness of interventions, to the neglect of broader issues arising from the introduction of feedback technologies. 2
In light of this gap, this paper seeks to examine reactions to the use of feedback technologies in the workplace for promoting behaviour change. More specifically, it explores a novel approach that utilizes wireless technologies to deliver personalized feedback information. The work was undertaken as part of the multidisciplinary ‘Wireless Behaviour Information (Wi-be) Systems’ project (for a project overview, see Shao et al., 2013). Before describing the research methods and results, the following section explores the key contextual differences between domestic and non-domestic buildings and how wireless technologies offer new opportunities to deliver energy feedback information.
Energy feedback information and wireless technologies in the non-domestic context Relatively few feedback studies have been undertaken in the workplace, where contextual differences may inhibit the applicability of findings from the domestic setting (Carrico & Riemer, 2011; Coleman, Irvine, Lemon, & Shao, 2012a). Energy use in non-domestic buildings can be far more varied and complex than in homes; this is reflected in the wide range of built forms, building size and the mix of activities that can take place (Bruhns, 2008). Most users of non-domestic buildings have limited influence over the energy efficiency of their buildings, with responsibility often being assumed by designated managers and influenced by building characteristics and systems (Lehrer, 2009). For most building users, day-to-day curtailment behaviours are also likely to be influenced by differences in social contexts, such as an individual’s role, rules of conduct and normative expectations (Nye & Hargreaves, 2009). Employees’ interest in reducing energy use may also be influenced by the fact that they are not paying the bills and do not profit directly from energy-saving actions (Siero, Bakker, Dekker, & van den Burg, 1996). However, despite such barriers the workplace may be an environment conducive to behaviour change, because the workforce can form a captive audience and there is potential for influence by peers (Carrico & Riemer, 2011). Several workplace studies suggest that savings are achievable. For example, in a study of comparative feedback between two units in a metallurgical company, Siero et al. (1996) found a reduction in ‘energy-wasting’ behaviour. In a separate study Carrico & Riemer (2011) found an energy reduction of around 7% following the delivery of group-level feedback among university employees. Action research undertaken by Schwartz, Betz, Ramirez, & Stevens (2010) introduced feedback from appliance-level monitoring equipment and observed overnight reductions in electricity consumption during the intervention, although savings decreased following removal
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of the feedback. Thus, there is some optimism that behaviour change reported through the use of feedback in homes may also happen in the workplace. Similar to the increased availability of in-home displays, the development of low-power wireless sensors has also enabled energy monitoring systems to be introduced relatively easily, and at low cost (i.e. avoiding cabling costs), into non-domestic buildings to monitor and control a variety of equipment (Oksa, Soini, Syda¨nheimo, & Kivikoski, 2008). This can range from a building’s heating and cooling systems to individual electrical appliances. The information from these systems can support energy managers’ decision-making, improve building automation, and provide the opportunity to give more detailed energy feedback about specific rooms, equipment and times of use. This additional detail is important because it raises individual awareness about the results of specific changes in behaviour (Fischer, 2008).
materials were piloted and reviewed by the university’s ethics committee. Participants received a study description sheet detailing anonymity and confidentiality; written consent was obtained. The first phase of the study included in-depth interviews with 11 employees (five male, six female; subsequently referred to as ‘interview participants’) at the case study site. The interviews explored respondents’ experiences of energy use in the workplace, their perceptions of Wi-be technologies and preferences for personalized energy feedback. Purposive and snowball sampling recruited participants with a range of responsibilities for energy use in buildings: two energy managers with formal responsibilities to reduce energy use; two individuals with informal responsibilities as ‘environmental champions’; and seven individuals with no designated energy-related responsibilities.
Wireless technologies can also be used to gather occupancy data to optimize the control and automation of lighting, space heating and ventilation (Dong et al., 2010; Li, Calis, & Becerik-Gerber, 2012). However, many forms of occupancy sensors, such as passive infrared (PIR) and CO2 sensors and door contacts, are unable to identify the exact number of individuals in a specific location. To achieve greater accuracy other occupancy technologies, such as wearable tracking devices, can be used (Li et al., 2012). Work in domestic dwellings has highlighted that such technologies can aid post-occupancy evaluation by providing detailed insights into the use of building spaces (Gillott, Holland, Riffat, & Fitchett, 2006; Gillott, Spataru, & Hall, 2009). When combined with energy monitoring, occupant tracking can produce a more thorough understanding of occupants’ energy-related behaviours by identifying how much energy is used in specific locations and which individuals are responsible for the energy use (Gillott, Rodrigues, & Spataru, 2010).
The second study phase evaluated the use of a Wi-be system installed in a single department. Four individuals (referred to as ‘feedback participants’) were recruited, based on availability for the evaluation period, and monitored for energy use and occupancy. Practical constraints (e.g. installation and adjustment of the monitoring equipment) led to the system being installed in the research team’s department, which undertakes academic work in the energy field. Consequently, the feedback participants had above-average levels of energy literacy and knowledge about the management of energy demand in buildings. They also had been subject to various forms of anonymized department-level occupancy and energy monitoring for research purposes (e.g. PIR, door contacts, temperature sensors, and department-level energy monitoring). Personalized energy feedback was provided weekly and was derived from monitoring data and developed to encourage energy-saving behaviour. Interviews explored the experience of using the Wi-be system, the content of feedback received and any observed behaviour change identified through the monitoring data.
This monitoring approach can also be used to develop what has been termed a ‘Wireless Behaviour Information (Wi-be) System’, which uses wireless technologies to deliver truly ‘personalized’ feedback information. Thus, personalized feedback goes beyond the disaggregation of energy use to personal appliances, locations and times of use by linking consumption to a specific person.
Nineteen interviews were conducted and analysed in the two study phases; one with each of the 11 interview participants and two interviews with each of the four feedback participants. All interviews were semi-structured, conducted face to face and lasted 30 –90 min. Interviews were recorded digitally and through handwritten notes, transcribed verbatim and analysed thematically (King, 2013).
Research design
Energy and occupancy monitoring
A mixed-method approach was developed for a university-based case study into the actual and perceived use of wireless technologies for providing energy feedback. The study consisted of two phases and all study
The core objective behind the study was to use wireless technologies to provide feedback of actual energy use to individuals within the workplace. Objective data were collected by monitoring electricity consumption 3
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and the activities and physical location of the feedback participants (for further details, see Shao et al., 2013). The study used a wireless energy monitoring system developed for the residential sector (Alertme, 2013). This consisted of a ‘smart hub’ that collected power load data from 20 plug-in loggers, at 1-min intervals, via a ZigBee wireless communications protocol (ZigBee Alliance, 2013). Loggers recorded a variety of appliances, including: workstation equipment (i.e. computers, monitors, desk lamps); kitchen equipment (i.e. microwave oven, refrigerator); and printing equipment (i.e. photocopier, laser printers). Initial testing of the system suggested a reasonable degree of accuracy. However, the loggers were unable to detect some low power loads, e.g. monitors and computers that were switched off but still connected to a mains power source. Given that the main patterns of energy-related behaviour could be identified from the data, the accuracy of the system was considered sufficient for the aims of this study; although energy consumption figures are likely to underestimate some low power loads. A location tracking system allowed individuals’ movement throughout the study area to be recorded and provided detailed information about occupancy patterns. This was relatively cost-effective due to its capability to utilize a building’s existing wireless infrastructure (i.e. Wi-Fi access points) to locate wearable radiofrequency identification (RFID) badges (Ekahau, 2012). The system’s accuracy was subject to several factors that can affect the Wi-Fi propagation (Shao et al., 2013). As a result, ‘location beacons’ were utilized; small battery-powered infrared (IR) transmitters that can provide sub-1-metre accuracy (Ekahau, 2012). These were positioned at participants’ desks and other areas about which there were limited data. However, the IR detection relies on the badges always having a line of sight, a situation that often failed to occur due to obstruction by clothing or participants’ alignment while working. Another problem was that the badges required charging on a daily basis; on occasions some participants forgot to charge their tags, which necessitated charging at work. These issues led to occasions when appliances were used without the location badge being operational or worn (resulting in difficulty ascertaining from the monitoring data whether the participant was actually using the desk equipment) and periods of poorquality data (e.g. an individual appearing to be located in the wrong area). This led to extensive manual screening of the data to remove obvious inaccuracies and, on occasions, some participants were consulted to ensure that the feedback information provided was as accurate as possible. Electricity consumption and occupancy data for each participant were manually processed and analysed by 4
spreadsheet. Key electricity consumption values were calculated for the personal equipment used by each participant and communally used appliances. Where possible, energy values were separated into ‘on’ and ‘standby’ power modes to highlight energy-use patterns. However, identifying when computers were in standby modes can be difficult due to the range of ‘on’ mode power loads. Thus, some standby use from computers may have been attributed (and fed back to feedback participants) as ‘on’ consumption. These energy data were combined with occupancy data such that energy use could be apportioned to an individual’s patterns of occupancy. Based on the tracking systems’ level of accuracy each 1-min interval of electricity use was apportioned to one of three key categories of occupancy: (1) unoccupied (i.e. the participant was not in the office); (2) workstation (i.e. the participant was at their desk); and (3) office – excluding workstation (i.e. the participant was in the office department but not at their desk).
Feedback information Feedback participants were provided with indirect feedback due to the necessity of combining, and manually screening, the energy and occupancy monitoring data. To understand the usefulness of such feedback, for promoting energy reduction, a variety of feedback information was developed; this differed by units, visual format and advice provided. Initial feedback was informed by the literature (e.g. Fischer, 2008; Karjalainen, 2011; Roberts & Baker, 2003; Wood & Newborough, 2007). For example, units used in previous feedback studies have included kilowatt-hours (kWh), watts (W), CO2 emissions (kgCO2) and monetary cost (£). An additional unit incorporated in this study was ‘hours of use’; this has received little attention to date, yet it emerged from a preliminary analysis of interview participants’ comments as a possible way to present information that avoids both technical and monetary terms (Coleman et al., 2012a). The feedback given to the participants was collected over two one-week monitoring periods and focused on workstation electricity consumption, as this was the only energy end-use over which participants had complete behavioural control. This information was disaggregated about individual appliances and presented on paper in charts, tables and graphs. Information to highlight potential energy-saving actions and to motivate participants to adjust their behaviour was also included. An example of the latter is the provision of yearly or scaled-up electricity consumption estimates that were derived from the monitoring data. Feedback participants received the information at interviews at the end of both weeks; this facilitated conversation about the feedback content and experiences of using the Wi-be system. The second interview
Promoting behaviour change through personalized feedback
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Table 1 Total workstation appliance use of the week1monitoring period (feedback participant 3) kWh/ week
Cost (»)/ week
CO2 (kg)/ week
Hours’ use/ week
Computer
2.4
0.24
1.2
27.4
Monitor
0.7
0.07
0.4
23.9
Lamp
0.1
0.01
0.04
1.8
Kettle
0.3
0.03
0.2
0.4
Total
3.5
0.35
1.8
^
also facilitated investigation of any observed changes in energy consumption. Examples of actual feedback given to participants are shown in Table 1 and Figures 1– 5 with discussion following in the Results section.
Results Results are presented in two sections: the first reports electricity and occupancy monitoring coupled with relevant insight from interviews with the four feedback participants; the second results section presents findings from both sets of interviews.
Observed individual-level energy use
As mentioned above, electricity use from workstation appliances was the focus of the energy feedback and was compared between two one-week periods. Table 2 summarizes the specific appliances that were monitored and the general occupancy levels for each participant. Occupancy patterns varied across the participants and between the two weeks due to flexible working hours, working from home and out-of-office meetings. Figures 6 and 7 illustrate electricity consumption for the three main occupancy categories using two different metrics: total consumption and percentage of use. From Figure 6, it is clear that the majority of the energy used by three of the feedback participants (2 – 4), in both weeks, occurred while they were at their workstations. Interviews with these individuals identified that none of them left their equipment on overnight or over the weekends; they also reported that this was their usual behaviour.
Figure 1 Total electricity consumption from workstation appliances in the week 1 monitoring period apportioned to three main occupancy categories (feedback participant 3)
It is noticeable that for feedback participant 1 around 77% (7.7 kWh) of the workstation electricity consumption, in week 1, occurred while the individual was away from that workstation (Figure 6). Interview findings identified that the computer was often left on overnight, although other workstation equipment was often turned off when not in use. This pattern of
Figure 2 ‘Power load pro¢le’, feedback chart showing computer and monitor power loads with workstation occupancy for a 24-h period in the week 1 monitoring period (feedback participant 2) 5
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occupancy for week 3 was estimated to be similar to the previous weeks; Table 2).
Figure 3 ‘Daily hours of use’ feedback chart for showing the total hours appliances were ‘on’ alongside workstation occupancy for the week 1 monitoring period (feedback participant 4)
Although there is a noticeable energy saving for feedback participant 1, increases in energy use were noted for the other three participants (Figure 6). For participant 2 it is clear that longer working hours (Table 2) contributed to an increase in total energy consumption. It is also apparent for participant 3 that the percentage of electricity used while not at the workstation reduced slightly in week 2, suggesting increased energy-saving behaviour. However, the differences in energy use for participants 2 – 4 are likely to be the effect of the short monitoring periods, which are influenced by ‘natural’ variations in working patterns reported by participants; longer periods of monitoring would reduce this noise in the data to allow a more reliable comparison.
behaviour was due in part to the type of work being conducted, which sometimes required simulations to be conducted overnight, but also due to convenience, habit and the assumption that the computer was automatically entering a low power mode after a period of inactivity. All four participants stated that their concern for the sustainability agenda was an important influence on the largely ‘energy saving’ patterns of consumption recorded.
The monitoring phase highlights that Wi-be systems can provide detailed personalized energy feedback to office employees and suggests that in some cases this can elicit energy-saving behaviour (e.g. feedback participant 1). However, the in-depth interviews raise important issues for consideration before Wi-bebased feedback can be disseminated more widely; these are considered in the following sections.
Feedback participant 1 was the only individual to reduce workstation electricity consumption noticeably in week 2, following receipt of the feedback (Figures 6 and 7). Interviews identified that this change in behaviour took the form of manually hibernating the computer, although it was evident from data collected during week 2 that further savings could be made. A third week of appliance monitoring provided additional data for this participant. Figure 8 shows that following receipt of feedback at the end of week 2, total workstation electricity use in a third week of appliance monitoring was reduced to around 40% of week 1 (office
Perceptions and experiences of using Wi-be systems
Three key themes, with related subthemes, emerged from analysis of the qualitative interviews with both sets of participants. The first two focus on the concept of, and content for, personalized feedback; the third highlights some of the ethical issues that were raised about the Wi-be system. Reactions to the concept of personalized feedback
This theme captured opinions about the provision of personalized feedback and highlighted two clear
Figure 4 ‘Average hourly use pro¢le’ feedback chart for showing the average time that a computer was ‘on’and workstation occupancy, for each hour of the day, over the week 1 monitoring period (feedback participant 1) 6
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Promoting behaviour change through personalized feedback
Figure 5 ‘Average hourly use pro¢le’ feedback chart for showing the average time that a monitor was ‘on’ and workstation occupancy, for each hour of the day, over the week 1 monitoring period (feedback participant 1)
Table 2 Summary of workstation appliances monitored and participants’ general occupancy patterns over a two-week period Feedback participant
Workstation appliances
Working pattern
O⁄ce occupancy, days (total hours) Week 1
Week 2
Week 3
1
Desktop computer; LCD display; desk lamp
Full-time
5 (28.6)
5 (25.0)
5 (29.3)a
2
Desktop computer; LCD display; desk lamp
Part-time
2 (8.0)
3 (20.7)
^
3
Desktop computer; LCD display; desk lamp; kettle
Full-time
4 (32.7)
4 (33.2)
^
4
Desktop computer with an LCD monitor combined (from one mains power source); desk lamp
Full-time
5 (38.8)
5 (39.5)
^
Notes: aO⁄ce occupancy hours for week 3 is an estimate based on the number of hours of monitor use. LCD ¼ liquid crystal display
might encourage energy-saving behaviour and could complement existing building-level energy feedback reports (monthly gas and electricity use). Eight of the other interview participants also thought that feedback about personal consumption would be useful to assist efforts to save energy and six of these thought the additional information provided by the Wi-be approach could be beneficial. An ‘environmental champion’ employee explained this as follows:
Figure 6 Feedback participants’ total workstation electricity consumption apportioned to three main occupancy categories for the two weeks of monitoring
subthemes: control and motivation. For the majority of participants, the notion of feedback about one’s personal energy use was thought to have advantages. Both energy managers indicated that the extra detail
[. . .] I think that feedback [Wi-be approach] would be helpful [. . .] first of all for my understanding of my own energy use anyway. And secondly, it might help to demonstrate that what I do is actually useful, and that might then be something that I can encourage other people to look at. (academic) These perceptions were corroborated by the four feedback participants who reported that the personalized 7
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Figure 7 Feedback participants’ percentage of total workstation electricity consumption apportioned to three main occupancy categories for the two weeks of monitoring
reduce his workstation energy use, still considered it to be ‘tinkering at the edges’.
Control
Figure 8 Total workstation electricity consumption for three weeks of energy monitoring (feedback participant 1). Personalized feedback was provided just before weeks 2 and 3
feedback they received was of interest and had the potential to assist efforts both to raise awareness and promote energy reduction. However, while the interviews suggest that personalized feedback would be of interest, comments also suggest that it may not necessarily lead to energy savings. Feedback participant 2 believed that the feedback would be most beneficial to employees who were less embedded in energy issues. Similarly, one of the energy managers stated that such feedback may be of little use in departments where employees seldom wasted energy – this is an observation illustrated by the three feedback participants whose existing patterns of behaviour provided little opportunity to reduce workstation energy use. A further limitation, highlighted by the feedback participants, was the relatively small amount of energy consumed by individual electrical appliances when compared with other end-uses, such as heating and lighting. Feedback participant 1, although pleased to 8
The level of control over energy end-uses was perceived by many as a barrier to energy saving. Participants often felt that the only energy consumption under their direct control was their workstation equipment (e.g. computers, monitors, desk lamps). Space and water heating, communal lighting, printers, photocopiers, and kitchen equipment were viewed as dependent upon both collective behaviour and technical considerations (e.g. automated space heating and ventilation, and lighting controlled by PIR sensors). This highlights an important question about the adoption of Wi-be systems in offices: should personalized energy information be fed back to an individual when that individual has no way to reduce their consumption? As emphasized by an interview participant, a feedback loop is only useful when you can actually control that system. Participants suggested several ideas about how to address issues associated with control. Two of the feedback participants suggested that collective feedback on communal energy end-uses should be provided, thus bringing some control over these types of appliances by encouraging collective action. An energy manager also highlighted how providing an additional feedback loop, one that encouraged occupants to report poorly performing equipment (e.g. space heating) to his department, might improve the feedback system’s ability to address energy use perceived to be outside occupants’ control. Other respondents also suggested that improved communication and feedback with
Promoting behaviour change through personalized feedback
energy managers could be a way to reduce unnecessary energy use.
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Motivation
Participants discussed different motivations, both internal and external, that might influence energy use. All the interviewees indicated that they felt some concern for the environment, and that this often led them to attempt energy reductions. Many of these, particularly those with designated energy roles, also highlighted issues that could impede energy saving with some describing frustration that others in the organization did not attempt to reduce their energy use. One such barrier to emerge relates to ‘work focus’: your mind-set is on accomplishing the task you’re employed to accomplish [. . .] you’re more interested in why you’re there [. . .] than whether the lights are switched off or on [. . .]. (technician) An additional motivation pertained to the cost of energy. While participants noted that many employees may have less financial incentive to save energy at work, several suggested that indirect incentives might motivate energy-saving behaviour. Concerns were expressed over job security and the need to link the monetary savings arising from energy reduction with the financial position of the organization in the current economic climate. Organizational structures, both informal (e.g. social norms, internal culture(s)) and formal (e.g. explicit policy statements and management structures), were both identified as being influential on existing energy behaviour and having the potential to motivate people to respond to feedback and take action. For example, one interview participant felt that the social norms of the work group prevented them from being outspoken about energy saving. In contrast, another suggested that the organization’s ‘environmental champions’ initiative had led to an office culture where people would turn other people’s equipment off. Reflected in these ‘social’ themes was the desire for increased formal support from management, a position taken by the majority of the interviewees. Unlike the domestic sector, there is an opportunity to motivate energy saving in the workplace through managerial structures and leadership. Participants often suggested that more visible management support would lend authority to the process and thereby motivate energy saving: [. . .] The recycling message, because that really came from top down [. . .] that behaviour has caught on and people recycle more, I’m sure of it. Because that message is there, it’s being reinforced every day. (administrator)
This section has highlighted the importance of getting beyond the technical attributes of personalized feedback and into the organizational structures that may be fundamental to underpin any feedback initiative. The nature of that feedback is considered below. Feedback content
Participants in this study indicated that if information provided is to be acted upon, feedback needs to be visually appealing, accessible and meaningful. Four themes encapsulate the respondent’s views on how feedback should be delivered: units of analysis, comparative information, knowledge building and focus. Units
A variety of preferences for feedback units were outlined by the interview participants, but only four of whom (excluding the energy managers) were familiar with technical units (e.g. kWh, W, kgCO2). Although all the feedback participants understood the technical terms, they still expressed some unease over their use. For instance, feedback participants 3 and 4 thought kgCO2 values were too abstract. One approach to circumvent this lack of understanding is to adopt monetary terms; however, this was also seen to have problems associated with it. Despite some interviewees linking monetary savings from energy reduction to helping the organization and job security, there was a general scepticism about the use of such measures, when users in a non-domestic setting typically do not pay for energy directly. This point was reinforced by the perception that the monetary sums involved for personal behaviour change were small and relatively inconsequential. A number of approaches were explored in the second study phase to sidestep this problem, such as estimating feedback participants’ annual energy use and scaling up personal consumption to the departmental and organizational level. One approach simply used an ‘hours of use’ metric (Figures 3– 5), which appeared to be useful for the Wi-be system because it allowed occupancy patterns to be compared directly with appliance use: I find it more useful [. . .] because it’s in the same format, you know, these are minutes at the desk, these are minutes [of] my computer. (feedback participant 2) User comparison
There was evidence that both historical and normative (i.e. social) comparisons are a useful way to present personalized feedback: I think people like to be able to compare themselves with others, but they also really like to compare themselves to past times, so, they know 9
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what they’ve done themselves, and that makes it easier for them to make sense of the figures. (energy manager) Historical feedback is important because it provides a way to identify the effect of changes in behaviour. Support for this aspect of feedback was evident in feedback participants’ interest in the ‘power load profile’ charts (Figure 2). Feedback participant 2 explained that although averages provide an overview of energy behaviour, the profiles identified specific behaviours undertaken at specific times, e.g. appliances left on over lunch breaks. The interviews also suggested that normative comparison was important: ‘what am I doing that the others aren’t?’ (administrator). Concurrently, however, they felt that such comparisons must be treated with a degree of caution, e.g. direct comparison ‘would probably raise a few heckles’ (administrator), and may be perceived as unfair when one person’s role involved the operation of more energyintensive information technology equipment.
Knowledge and additional information
The majority of interviewees felt that coupling energy feedback with additional information enhances employees’ knowledge of what can be done, how to do it and why they should take action in the first place. The following comment was made about the limitations of receiving energy use information alone: [. . .] So what do you want me to do about it? I think that would be a lot of people’s response. They would sort of say ‘and?’ (academic) A similar sentiment was expressed by another employee who described how the lack of controls and knowledge of the building’s heating system could sometimes result in occupants opening a window when the room became overheated. This was perceived as easier than attempting to interfere with the heating system directly. In respect to feedback content, feedback participants also explained that providing additional information that states obvious energy saving hints and tips might be perceived as condescending and the provision of too much information could be off-putting. The four feedback participants were keen to ensure that advice, and any targets to motivate energy saving, were realistic and took into account that people cannot have perfectly corresponding energy use and occupancy (e.g. it would be inconvenient to turn appliances off for relatively short periods of time). They emphasized that failure to do so could undermine motivation and be counterproductive to the aim of the feedback intervention. 10
Personal versus collective feedback
Interviewees highlighted the notion of integrating the delivery of personalized feedback into a broader team approach and, as identified previously, suggested that potential limitations were the small energy savings from personal-level feedback and frustration at receiving feedback about energy use that was outside an individual’s control. This suggested the need to present personal and collective feedback separately: I think you need to feed back at the level that the use is. So the monitor and the computer it’s good to feed-back personally because that’s me and I’m in control of that [. . .] if you feed-back about the printer it needs to be to the department because that is who uses the printer. (feedback participant 2) Participants were also concerned that expanding personalized feedback to incorporate more of the communal end-uses could be counterproductive if it was not undertaken in a sensitive manner. Feedback participant 2 explained that any energy use attributed to individuals from communal equipment, that they did not use, could discourage other energy-saving activities. Participant 1 also thought ‘it would feel a bit patronising’ if every form of energy was being monitored (e.g. the use of a kettle or microwave).
Ethical concerns
Concern about the ethical issues associated with the collection of personal energy and occupancy data was a prominent theme to emerge from the interview data. Ten of the interview participants and all four of the feedback participants expressed concern that the system could be used for surveillance and misused to assess work performance. For example, one employee said: I can imagine a lot of people straightaway would get their backs up about that [. . .] sort of ‘Big Brother’ is watching you [. . . but] so long as I was fully confident that a device like this was being used for the purpose for which it was intended, that would be fine. (administrator) When asked what colleagues would think about the use of tracking for energy-saving purposes, one interviewee responded that: [. . .] I can see some people being annoyed with it and saying, ‘Well why do we have to do this?’ If they were forced to do it, they might not be happy with it [. . .]. (technician)
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This sentiment was reflected in comments that personalized feedback would be viewed negatively if it was compulsory or perceived as criticizing existing work behaviour. Responses highlighted that such concerns were only natural, because the tracking was ‘essentially stalking [. . .] an electronic version of having somebody follow you’ (feedback participant 4) and ‘people like to feel that their liberty isn’t being encroached upon’ (feedback participant 2). One other interview participant had even stronger feelings: [. . .] I think it’s absolutely shocking, I think it’s a level of surveillance that is encroaching on civil liberties. [. . .] I think it’s one thing to be providing feedback to individuals about their appliances, I think it’s quite another [to track occupancy . . .]. (academic) This respondent also felt that the trade unions would need to be consulted about the collection of such personal data at work; however, for this participant there was nothing that would make tracking acceptable. Interestingly, all the feedback participants felt that the ethical considerations were less significant to the energy monitoring than the tracking, despite the electricity consumption data from computer monitors often providing a reasonably accurate overview of when people were at their workstation (as evident in Figures 2 and 5). There was also some evidence that any attempt to assess work performance with energymonitoring data could be counterproductive. For instance, a feedback participant explained that the misuse of data could encourage people to leave on personal equipment to hide occupancy patterns. A further ethical concern linked to the effects of wireless technologies on health. Although most participants perceived no negative health implications, others expressed a degree of uncertainty: It does concern me. I did go ahead and have wireless broadband at home but, you know, I do think about it and wonder how it’s affecting us. [. . .] I just don’t think we should trust everything that’s available to us. [. . .] Everything seems to be wireless these days and it is that, that kind of bothers me a bit [. . .]. (administrator) Overall, these concerns indicate the need for robust measures to ensure employees’ privacy, confidentiality and civil liberties. Suggestions about such measures included restricting the access to tracking data to the user; using the system on a short-term basis (e.g. two weeks); ensuring the data were only used for its intended purpose (not work performance); voluntary involvement; ensuring users were not reprimanded for their level of energy use; transparency on how
and why the system was used; and maintaining anonymity and confidentiality.
Discussion and conclusions Findings are presented from a feasibility study into the use of wireless technologies to deliver personalized energy feedback information in offices. The small sample sizes and above-average energy literacy of some of the participants prevents the findings from being generalized to the broader population. The focus on electrical appliances and the short monitoring periods also prevent definitive conclusions being drawn about the extent of long-term energy reductions arising from the feedback intervention. For example, recent longitudinal research suggests that initial energy reductions from feedback can diminish in the longer term (Hargreaves, Nye, & Burgess, 2013; van Dam, Bakker, & van Hal, 2010). Nevertheless, the mixedmethods approach and in-depth nature of the project supported both social and technical insights. The location of the case study also had practical benefits, including: ease of access allowed technical adjustments to be made; regular contact with participants facilitated behavioural observations; and the establishment of good faith between the research team and the participants helped to mitigate potential ethical concerns. Consequently, the results raise a number of pertinent issues for researchers, practitioners and policymakers involved in the introduction of feedback technologies in non-domestic buildings, particularly for systems that are capable of producing highly disaggregated feedback. From a technical perspective, the study demonstrates that it is feasible to integrate wireless technologies into a personalized ‘Wi-be’ feedback system. There was also evidence that the system can help raise awareness and identify specific opportunities to save energy, through behaviour change, that are not apparent from building-level feedback. However, the technologies used in this study proved considerably time intensive for producing the feedback required. Technical and behavioural issues were also identified that led to a degree of inaccuracy in the information provided and impeded the use of the devices (e.g. the need to recharge the location badges regularly). These issues make the system impractical for wider deployment without further development. Providing feedback about energy use when computers were in standby modes was also difficult due to the range of ‘on’ mode power loads. This not only illustrates a challenging aspect to the delivery of appliance-level feedback, but also highlights the need to improve the energy efficiency of computing equipment and networks through the design of better power management functions (Coleman, Brown, Wright, & Firth, 2012b). 11
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More fundamental were the insights that question whether the approach itself is suitable for wider rollout. For instance, it was clear that the extent of energy reductions from individual-level behaviour change was largely limited to the use of workstation equipment. For the four feedback participants in this study, being the exclusive users of their workstation equipment, it was unclear whether the provision of occupancy data produced energy reductions beyond the use of appliance-level energy monitoring alone. Furthermore, in some situations, information technology managers may be better able to target behaviour initiatives for reducing energy demand from computers without the use of additional sensors, for instance by introducing better power management protocols or identifying computers regularly left on overnight (Brown, Bull, Faruk, & Ekwevugbe, 2012). It was also apparent that there are a number of social barriers (e.g. the influence of work colleagues) to the adoption of the system.
reductions to their workstation energy consumption. Although this finding may reflect the sample characteristics (i.e. existing knowledge and motivation levels), it also points to an apparent paradox associated with delivering personalized feedback in offices – the disaggregation can facilitate the identification of specific energy-saving actions, but there is often limited control to undertake these actions. Efficiency behaviours (e.g. procurement of low-energy equipment) were the responsibility of designated managers and participants perceived little control over the curtailment of energy demand for space and water heating, and communal lighting and appliances – these were dependent upon collective behaviour and other external considerations, such as building systems and automation. As a result, the small amount of energy or cost fed back at the personal level could appear insignificant and discourage individuals from undertaking energy saving. This raises the question of whether to deliver personalized feedback in the office setting.
Similar to findings from domestic research, it is evident that the content of feedback needs careful consideration (e.g. Karjalainen, 2011; Roberts & Baker, 2003; Wood & Newborough, 2007) and there was evidence that people require additional support to improve their knowledge of how to control energy using equipment and to motivate them to take action (Darby, 2010; Raw & Ross, 2011). Previous domestic studies also suggest that people have difficulty understanding how scientific units such as watts, kWh’s and CO2 emissions relate to energy use (Karjalainen, 2011) and prefer to receive information in monetary terms (Anderson & White, 2009; Raw & Ross, 2011). This study also found this was often the case, but financial cost may not be easily transferable to the workplace because employees do not directly pay energy bills and the small amount of cost perceived at the personal level. One approach used by this study was to feed back information about durations of use (i.e. hours of use), which was viewed favourably by participants and also allowed occupancy and appliance use to be compared together; this is an aspect that warrants further research.
Previous research into energy use in buildings indicates that substantial amounts of electricity are used unnecessarily in the workplace; this is often due to computers and other office electrical equipment being left on continuously by occupants (Ecos, 2008/2011; Marans & Edelstein, 2010; Masoso & Grobler, 2010; Webber et al., 2006). This suggests that influencing individual-level action through personalized feedback is potentially worthwhile; however, the limitations highlighted above suggest that it may be better to use personalized feedback as part of a broader ‘collective’ strategy within which individual actions make a contribution. The feedback participants suggest that it is important to deliver personal and communal energy use separately, at the levels of control and influence. Applying a collective approach may also provide an opportunity to take advantage of normative (peer) influences and organizational structures to motivate employees; the latter could be underpinned by clear support, and ideally action, from senior managers. For instance, peer support and management supervision have been reported as important ways to encourage behaviour change in other nondomestic energy feedback studies (Carrico & Riemer, 2011; Siero, Boon, Kok, & Siero, 1989).
Normative comparison (i.e. to other energy users) has been used previously in the workplace to encourage competition and energy-saving behaviour (Siero et al., 1996). Participants in this study often viewed normative comparison as a potentially motivational form of feedback; however, personal comparisons must be made with a degree of caution to maintain employees’ anonymity and to account for different levels of energy use associated with work roles. The neglect of these issues could potentially lead to mistrust in the information and introduce an underlying message that is perceived as discriminatory. A key issue is that only one of the four feedback participants had the opportunity to make significant 12
A further expansion of the system, one that could help address control issues, would be an additional feedback loop between building occupants and energy managers, allowing occupants to report unnecessary energy use from equipment outside their control (e.g. faulty equipment, poorly performing automation leading to unnecessary heating or lighting). Some support for this approach can be found from a survey of US industry professionals (with expertise in energy monitoring and analysis) which found that 90% of respondents would welcome a systematic way to communicate with building users to address an
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information need that is often overlooked (Lehrer & Vasudev, 2010). The use of social media (e.g. Twitter, Facebook, etc.) to coordinate this feedback loop is an area worthy of research because it has the potential to engage employees and relay supportive information from energy managers (Lehrer & Vasudev, 2011). Perhaps the most prominent barrier was concern over ethical issues such as privacy, surveillance and the misuse of data; this was particularly relevant to the radiofrequency identification (RFID) location tracking system. Research into the use of this type of technology in healthcare organizations has identified similar concerns, leading to tensions between staff and management (Fisher & Monahan, 2008; Thuemmler, Buchanan, Fekri, & Lawson, 2009). Fisher & Monahan (2008) emphasize that these technologies need to be better understood: within their social contexts and not as external forces applied discretely to social problems. (p. 181) This assertion should also apply to feedback developed exclusively from personal energy monitoring. Although most feedback participants were less concerned about the monitoring of personal appliances, the potential of these data for surveillance purposes must also not be overlooked – it was apparent that general patterns of occupancy could be inferred from the electricity consumption of computing equipment. A previous study by Schwartz et al. (2010) found that employees were concerned over the misuse of appliance energy monitoring data to assess work performance. The authors recommend that employees must retain the ownership of their information and govern its flow, because it could be misinterpreted and motivate misuse.
technologies in a context of ethically approved use (e.g. voluntary participation, anonymity and confidentiality). This context may help explain why these individuals were willing to take part in the study and were largely unconcerned with the wider use of personal appliance monitoring. However, it can be envisaged that employees unaccustomed to a degree of surveillance at work or having negative experiences of how data are managed may be more resistant towards the use of feedback technologies. These reflections highlight that feedback information is not merely a neutral form of information, but has meaning within the social and cultural context with which it is provided (Hargreaves, Nye, & Burgess, 2010). In conclusion, the installed Wi-be system was found to help individuals evaluate their energy-related behaviours and identify personal actions that are not apparent from aggregated building-level feedback. However, although combining energy consumption and occupancy data provides detailed feedback information, it is unclear whether this approach elicits long-term energy reductions that go beyond that of appliancelevel monitoring alone; this is an area that would require additional research. It is also apparent that the extent of energy savings from personalized feedback in the workplace can be restricted by a variety of contextual barriers. This finding echoes research on energy reduction in the domestic sector, which suggests that in-home displays are unlikely to deliver deep cuts in the long-term without addressing more fundamental social and contextual issues (Hargreaves et al., 2010, 2013). That is not to argue that personalized feedback is unhelpful, but that a broader, more integrative, approach is required that delivers information at levels of control and influence, recognizes the underlying systems that lock people into patterns of energy consumption, and exploits the contextual drivers that could facilitate energy-saving behaviours.
Findings from this study support these concerns about control and data misuse; they also suggest that concerns over health must be managed sensitively. Establishing and maintaining a user’s trust in the technology, and the management of data derived from it, is fundamental to the success of Wi-be systems (or any other disaggregated feedback system). Given that such a system relies on individuals using the devices correctly, the feedback would become completely counterproductive if users attempt to hide occupancy patterns by leaving badges on desks or personal appliances on continuously.
The identified importance of context supports previous assertions that studies should give increased attention to understanding the process of behaviour change and the interaction among the context of energy use, such as the technologies available for monitoring and informing users, and the outputs of behaviour change interventions and policy (Nye & Hargreaves, 2009). Moreover, with findings from domestic feedback studies being broadly applied to the workplace, it highlights the urgent need to conduct research specifically within non-domestic buildings.
A further dimension of ethical concern relates to the existing level of surveillance, which could potentially influence people’s experiences or perceptions of the use of feedback technologies. In this study, the four feedback participants worked in a department that already utilized occupancy and energy-monitoring
Importantly, practitioners and policy-makers need to be aware that, unlike aggregated or building-level feedback, the energy data necessary for personal-level feedback can reveal detailed information about people’s patterns of occupancy and as such highlight concerns about the use of such data for surveillance purposes. Privacy 13
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concerns have already been raised regarding data security for smart meters (Darby, 2012; DECC, 2012; Go´mez Ma´rmol, Sorge, Ugus, & Martı´nez Pe´rez, 2012; McDaniel & McLaughlin, 2009; McKenna, Richardson, & Thomson, 2012; Ofgem, 2011) and research into inhome displays suggests the potential for new types of surveillance from feedback technologies (Hargreaves et al., 2010). These ethical issues have received relatively little attention in the feedback literature and also warrant further research. Finally, the approach taken to this study demonstrates the need for a more comprehensive understanding of the ‘receptivity’ to technological feedback interventions. It follows that if digital feedback technologies are to reach their potential, in the drive towards more sustainable energy use, there must be trust in those technologies, the information derived from them and the perceived uses to which that information is put. This is a broader issue than encouraging more efficient energy use and one that warrants considerably more attention if it is not to undermine current policy initiatives.
Acknowledgements The ‘Reduction of Energy Demand in Buildings through Optimal Use of Wireless Behaviour Information (Wi-be) Systems’ project was funded by the Engineering and Physical Sciences Research Council (EPSRC) (Grant Number EP/I000259/1) as part of the ‘Transforming Energy Demand through Digital Innovation (TEDDI)’ programme. The authors would also like to acknowledge the anonymous referees for their helpful comments as well as the participants for their time. Responsibility for all content is the authors’ alone.
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