Social barriers to the adoption of smart homes

Energy Policy 63 (2013) 363–374

Contents lists available at ScienceDirect

Energy Policy journal homepage: www.elsevier.com/locate/enpol

Social barriers to the adoption of smart homes Nazmiye Balta-Ozkan a,n, Rosemary Davidson b, Martha Bicket a, Lorraine Whitmarsh c a b c

Policy Studies Institute at the University of Westminster, 50 Hanson Street, London, W1W 6UP, UK Health Services Research, School of Health Sciences , City University London, Northampton Square, London, EC1V OHB, UK Cardiff University, School of Psychology, Tower Building, 70 Park Place, Cardiff, CF10 3AT, UK

H I G H L I G H T S







Smart homes and related technologies can provide a variety of benefits. Technologies need to be reliable and fit into householders’ lifestyles. Public concerns relate to cost, control and privacy. Trust in energy companies and government is important.

art ic l e i nf o

a b s t r a c t

Article history: Received 17 December 2012 Accepted 10 August 2013 Available online 2 September 2013

The aim of this paper is to explore social barriers to the adoption of smart homes through the analysis of expert views and public attitudes. Smart home services aim to improve the comfort, convenience and safety of householders, as well as allowing them to use energy more efficiently and cope with increasing costs. Despite the existence of smart homes and smart home technologies for some time, their prevalence is not widespread, and thus their potential largely untapped. Using a combination of indepth deliberative public workshops, expert interviews and a review of the existing literature, this paper explores social barriers to smart home diffusion, including how these vary by expertise, life-stage and location. The research highlights the importance of barriers such as control, security, and cost, providing insights for policymakers as well as smart-home designers and developers as to how these might be addressed. & 2013 Elsevier Ltd. All rights reserved.

Keywords: Public perceptions Smart homes Social barriers

1. Introduction Smart homes and other smart technology, such as smart grids and smart meters, have existed as concepts for many years, but have gained increasing attention over the last decade. Policy objectives encouraging or mandating energy efficiency, climate change objectives at both the national and the EU-level, as well as advancements in communication technologies such as high-speed internet and wireless devices, have driven recent developments. The smart home provides a new way of looking at the role energy plays in everyday life, the evolving relationship between energy utilities and consumers, and its development may create opportunities for consumers and utilities alike. Today, the “traditional home” has appliances that are operated locally and manually, usually by flipping a switch or pushing a button. These devices have limited controls and managing energy use can be difficult. The smart home, on the other hand, allows for remote electronic control and management of smart appliances

n

Corresponding author. Tel.: þ 44 207 911 7537; fax: þ44 207 911 7501. E-mail address: [email protected] (N. Balta-Ozkan).

0301-4215/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.enpol.2013.08.043

(heaters, air conditioners, washing machines etc) and represents the convergence of energy efficient appliances and real-time access to energy usage data, facilitated by a network of sensors and computers (ITU, 2010). Increased visibility of energy and cost information through interactive displays can enable consumers to proactively monitor and manage energy use in ways that are convenient, cost-effective, and environmentally beneficial. This is consistent with the wealth of literature focusing on how provision of feedback to households on energy use data can facilitate energy savings (Darby and McKenna, 2012; Hargreaves et al., 2010; Hargreaves et al., 2013; Meyers et al., 2010). Complementary to this, the deployment of smart meters may enable householders to benefit further from more differentiated, dynamic tariffs and demand response programs more directly as part of transition to a smart grid (Darby and McKenna, 2012; Faruqui et al., 2010). Smart homes can also deliver other services such as assisted living, home security or entertainment, as well as facilitating two-way communication between the grid and electric vehicles and any onsite micro-generation (e.g. rooftop solar panels). Finally, they can contribute to the delivery of social policy goals by helping provide better living standards for elderly, sick, and disabled homeowners (Pragnell et al., 2000).

364

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

Despite all these benefits, the literature informs us that the impacts of new technologies are often unexpected and predicted benefits may not be realised, as insights about important interactions between technology and society are neglected (Geels and Smit, 2000). More specifically for smart homes, their development is subject to further interdependencies between policy (type of incentives to enable the uptake of technologies), regulatory (who can access consumer data, at what frequency, enabling of emergence of new actors and services), commercial and market frameworks as well as investment conditions (having the funds for the installation of communications and grid infrastructures). For a discussion on the importance of these issues on the development of smart home market in the UK, please see (Balta-Ozkan et al., 2013). Hence, it is not surprising an extensive body of literature focuses on how innovations take place as a result of the interplay of these factors (for instance, a multi-level framework as advocated by (Geels, 2005), diffusion curves by (Rogers, 2010), and a constructive technology assessment framework by (Schot and Rip, 1997)). Yet, the importance of public values, beliefs, skills and practices in respect of energy consumption and management is well documented (Hargreaves et al., 2013; Nye et al., 2010; Whitmarsh et al., 2011). Specifically for smart homes, though, few studies have examined challenges facing the industry or, specifically, social aspects of smart home technology adoption and diffusion (Edwards and Grinter, 2001). Furthermore, given that smart homes encompass diverse technologies (sensors, communication platforms, appliances, etc.), products and services (time-of-use tariffs, remote monitoring, efficiency, etc.), no attempt has so far been made to draw together insights from disparate disciplines or expertise to understand how these technologies/services and challenges may interact with values, behaviour and society. In particular, whether smart homes, through these technologies/services and products, have the potential to reduce social inequalities or exacerbate them. The fact that disadvantaged social groups have limited means (including financial, physical or educational) to interact with these systems needs to be analysed further. The aim of this paper is to contribute to understanding the social barriers to adoption of smart homes, including shedding light on their implications for social equity, based on expert interviews and public deliberative workshops. In doing this, we begin by taking a holistic approach to smart home services, with a view to drawing out conclusions for energy consumption and management services. The study contributes to the literature by grounding, comparing and contrasting social barriers highlighted in the literature to those identified through expert interviews and public workshops. The paper is structured as follows: Section 2 reviews the literature with regards to both definition of smart homes and social barriers; methodology is discussed in Section 3; Section 4 presents the results from both the expert interviews and the public deliberative workshops; and Section 5 concludes with lessons for the energy industry as to how addressing these challenges may affect the future of the smart home market and, to a large degree, the energy industry as a whole: “Successful innovation is the result of a specific socio-economic and technological constellation, i.e. the right product, on the right market, at the right time and in the right combination where specific requirements in terms of user needs, user-friendliness, price, attractive supply, standards, interoperability, and so on have to be met. If they are not, the commercialization will certainly fail.” (Friedewald et al., 2005).

2. Background Through a review of existing literature on the subject, this section sets out the context to this paper, providing a working

definition for the term ‘smart home’; illustrating the types of services smart homes might provide; and identifying potential social barriers arising from the wider challenges acknowledged to be facing smart home development today.

2.1. Definition of smart home A smart home is a residence equipped with a high-tech network, linking sensors and domestic devices, appliances, and features that can be remotely monitored, accessed or controlled, and provide services that respond to the needs of its inhabitants (Chan et al., 2008; King, 2003; Li et al., 2004; Reinisch and Kofler, 2011; Taylor et al., 2007). The term ‘smart home’ may, in principle, refer to any form of residence, for example, a standalone house, an apartment, or a unit in a social housing development. In the definition set out here, sensors may be used to detect the location of people and objects, or collect data about states (e.g. temperature, energy usage, open windows); domestic devices, appliances and features can include anything from washing machines or lighting to a user interface providing access to and control of smart home data and services; and smart home services are the benefits that the smart home provides to the user. The network, through which each of the technological components and information about them is connected and coordinated, is what distinguishes the smart home from simply the high tech-equipped residence.

2.2. Smart home services Smart home services are the benefits that the smart home provides to the user and the system provider (e.g. the ability to manage demand), facilitated by the smart home′s network of technological components. Services may be categorised based on the user′s needs they target, e.g., security, assisted living, health, entertainment, communication, convenience and comfort, and energy efficiency. An assisted living smart home, for example, might provide an elderly or disabled occupant and their friends and relatives with greater independence and peace of mind, monitoring the occupier′ s activity and contacting a nominated carer in case of unusual activity (e.g., not turning on the kettle in the morning) signalling a potential accident or illness. Of the literature examined, a substantial proportion focuses predominantly on the assisted living applications of smart homes1 (e.g. (Chan et al., 2009, 2008; Demiris and Hensel, 2008; Ding et al., 2011; Eriksson and Timpka, 2002). Smart home security services, on the other hand, might offer the ability, using sensors, to monitor movement in the home and identify potential intruders, to be alerted about open doors and windows, or to program random room lighting patterns to deter thieves from a temporarily unoccupied property. Smart home energy efficiency services assist homeowners in reducing energy demand, whether directly (through automated energy-saving mechanisms, such as reducing the heating on hot sunny days) or indirectly (e.g., by providing the user with centralised access to data about their real-time energy usage and energy bill). Table 1 presents a selection of smart home features and services from the literature and a range of case studies. This wide variety of services 1 One of the UK experts also made a distinction that while ‘assisted living’ covers all that smart technology might offer in health terms, ‘tele-health’ and ‘telecare’ are different. The former refers to statutory services that are paid for by the health services at source and is generally free at the point of use (being paid for by through taxation). Tele-care on the other hand is paid for by users and charged for by the social services or by the companies providing it.

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

365

Table 1 Summary of smart home services and case studies identified in the literature. Service type(s)

Smart home technology/feature

Service details

Case study details

e-health; assisted living e-health

Wrist actigraph Biometrics monitoring system

Monitors features of lifestyle, e.g., time spent in and out of bed Monitors vital signs such as pulse or respiration

Energy efficiency; assisted living Assisted living

Lifestyle monitoring system

Able to monitor abnormal activity or appliance use

Lifestyle monitoring system

Monitors person’s location, and their current activity

Assisted living

Panic button on a pendant

Enables users to easily contact others in case of emergency

e-health; assisted living

Infra-red (IR), light, temperature and pressure sensors, microphones, and appliance power meters Ultrasonic sensors, radio-frequency (RF) technology, video, floor sensors

Monitors the user’s physiological signs as well as interactions Australia with their home environment

Convenience/ comfort; assisted living Entertainment

Communications; convenience/ comfort Energy efficiency; convenience/ comfort Energy efficiency

Communication; e-health; convenience/ comfort Assisted living

Builds a model of the user’s habits and behaviour

The Aware Home Research Initiative, Georgia Institute of Technology System guides the user to specific RFHelps the user find lost objects The Aware Home tagged objects, with audio instructions. Research Initiative, Georgia Institute of Technology. Allows services to be tailored to user’s movements around the Microsoft EasyLiving A video tracking system identifies the shape of a person and tracks them in real- home, e.g., a speaker system uses those speakers which are project best positioned to give optimal sound based on the user’s time as they move through the home. location IR ‘Active badges’ Tracks people inside an office building, allowing for real-time Pandora, the Olivetti tracking for more efficient running of the office and calendar Research Institute and meeting management A profile-based control strategy for thermal Heating is made more efficient by tracking user comfort A handheld device monitoring daily electricity use.

Allows users to set a daily electricity budget and to monitor energy usage of individual appliances

Digital ‘Family Portrait’ flat panel display

Family members can monitor each other’s engagements and health, enhancing social communication

Provides services and longer independence for patients with Enable Project, (England, System monitors and controls bath and sink water levels and temperature, and use early dementia, and provides peace of mind for friends and Ireland, Finland, Lithuania, and Norway) relatives of stove burners 2001 Pressure pads in the bed monitor user Provides energy services, e.g., automatic activation of lights, Tiger Place. University of activity, respiration and pulse as well as biometric analysis, e.g., measuring ‘restlessness’ in Missouri-Columbia 2003 bed Central control of lights and heating

Home robot: a dialogue-based interface

Acts as an interface between user and smart-home

can be aggregated under three broader, overarching categories: safety, energy management, and lifestyle support. 2.3. Challenges for smart home development Certain key technical, conceptual, and management issues pose barriers to smart home development and, consequently, the public appeal and uptake of smart homes. These challenges and the literature surrounding them are introduced and discussed here. They include: fit, interoperability; administration; reliability; and privacy and security. 2.3.1. Fit to the current and changing lifestyles While the smart home has been defined to be essentially a residence equipped with a network of technological components,

Adami et al. (2003) Andoh et al. (2004) Barnes et al. (1998) Perry et al. (2004) Colombo (2001) Celler et al. (1995) Kidd et al. (1999)

Kidd et al. (1999)

Brumitt et al. (2000)

Reinisch and Kofler (2011) UEA Carbon Connections- Hargreaves et al. (2010) funded ‘Visible Energy Trial’ (VET) Georgia Institute of Kidd et al. Technology, USA, 1999 (1999)

e-health; convenience/ comfort Convenience/ comfort; energy efficiency Security Intruder motion detector: video camera at Provides enhanced security and peace of mind entrance Convenience/ comfort

Source

Welfare Techno-House project, Japan, 1995

Cash (2004)

Demiris et al. (2006) Boman et al. (2007) Boman et al. (2007) Tatsuya (2005)

there are two further features that emerge from the literature and which can be thought of as central to the concept of the successful smart home: integration and the potential to evolve both of which can be captured in broad terms as ‘fit′. Without these qualities, the lasting usefulness of the smart home to the user is undermined, and the smart home and its services risk becoming redundant or in the worst case, not being adopted at all in sufficient numbers. The smart home′s technology and services should be well integrated into the design, lifestyle and general sense of home (Edwards and Grinter, 2001; Fitzpatrick et al., 2006; Li et al., 2012). Technology that does not fit in with the surroundings, pre-existing norms or know-how is less likely to appeal to the homeowner and consumer (Fitzpatrick et al., 2006), and may contribute to a feeling of being ‘out of control’. The home is an expression of identity (Davidoff et al., 2006). Smart home technology should therefore ‘fit in’ physically in terms of being suitably installed and integrated

366

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

into the structure of the residence and its contents. To some degree, it should also fit in aesthetically in terms of the look, shape and colour of the various components. For example, in one smart home study, the poor aesthetic qualities of a radio were enough to discourage a user from using it altogether (Fitzpatrick et al., 2006). Above all, the technology must fit in conceptually with common or acceptable routines. In other words, despite the fact that the presence of new technology in the daily routine may lead to changes in routines or social norms2, the smart home technology that requires any such significant changes may be perceived by the consumer to be more bother than it is worth, or may make them feel out of control. In particular, the user should not have to develop technological expertise in order to be able to use and control the smart home system. Rather than needing to be managed by an external expert, control and use of smart home systems should be intelligible to the user who will be interacting with them (Chikhaoui and Pigot, 2010; Li et al., 2012). Poorly integrated smart home technology may become redundant, remaining unused, perceived to add to the hassle and complexity of daily life rather than helping to reduce it. The smart home should also be an evolvable system; the system ought to be able to adjust in order to meet the evolving needs, demands and preferences of its occupant users. To avoid becoming redundant, the smart home also needs be able to accommodate the integration of new technological components, and the software upgrades that accompany the ever-changing landscape of the technology industry (Edwards and Grinter, 2001; Hu et al., 2011). 2.3.2. Administration A second challenge concerns the expertise and know-how required for system maintenance. As technology permeates into the home, who is responsible for installing, upgrading and maintaining the smart home′s software and hardware? Can such expert knowledge be demanded of the smart-home user? This is the administration problem. The operational and management needs of a smart home cannot be fully dealt with by a third party developer or service provider. This is because there are some devices and services for which the required configuration may be highly subjective. In other words, it may not be feasible for a third party to fully grasp or anticipate the specifics of a particular individual′s needs or how they interact with certain devices (Edwards and Grinter, 2001). The user will therefore require a minimum level of expertise in how to manage and troubleshoot the smart home′s systems and technology. Since one purpose of the smart home is to contribute to improving quality of life rather than complicate it, there is a need for a type of smart home system that is outwardly intuitive and easy to use. This ease of understanding however may be supported in part by third party smart home support providers. The administration problem is as much a concern for developers as retailers; systems should be designed to be as robust and simple to troubleshoot as possible. However, this may constrain the level of complexity of services that the smart home can realistically provide. 2.3.3. Interoperability The successful smart home must evolve and adapt to changing preferences, demands and needs, especially if technology in the smart home is to be acquired in a ‘piecemeal′ way (Edwards and 2 The arrival of the washing machine, for example, contributed to a systemic change in washing habits. The frequency with which people deem it appropriate to wash their clothes has increased to fill the time initially freed up by the washing machine’s introduction (Edwards and Grinter, 2001).

Grinter, 2001; Fitzpatrick et al., 2006). As such, the system should be able to easily assimilate new devices added to the smart home network. For the network to function successfully, its devices need to be able to communicate with one another. However, with different device manufacturers favouring different types of network media and communications protocols, often this is not the reality. This is the problem of interoperability. Despite being identified as a concern nearly a decade ago, interoperability continues to act as a barrier to smart home development, posing a challenge to consumer electronics retailers as to the functionality and therefore the appeal of, demand for, and delivery of, smart home services (Perumal et al., 2011, 2008). Recent literature highlights two ways in which the sought-after consistency and coherence within smart home systems might be achieved: (1) the adoption of universal standards for communications protocols for smart home devices; or (2) the development of a ‘gateway’—a central node that connects and acts as an interpreter between the different smart home devices and their protocols.

2.3.4. Reliability In the integrated smart home, the interconnecting of technologies with different tolerances for technical errors poses a concern. For example, boiler designers and home computer developers work under different assumptions about the appropriate tolerance level for crashes. Combining the two different products introduces room for complications; otherwise insignificant malfunctions in the home computer could potentially cause dangerous malfunctions in the boiler it is networked up to. Certain services in the home, such as security, or the sounding of a fire alarm upon detection of a fire, are more crucial than others. In their design, smart home systems must aim to be robust and dependable in this respect (Friedewald et al., 2005). The reliability of service provided by a smart home does not depend solely on the likelihood that the technology will not malfunction; in order for smart homes to provide the intended services reliably, they must accurately interpret the householder′s desired outcome. In other words, a smart home whose technical components are functioning without flaw may still provide an unreliable service, because the system is not intelligent enough to correctly understand or correctly anticipate the needs of its occupiers. At present, the ability of smart homes to predict human behaviour correctly is limited. In Japan, over one year, a family′s activity was monitored around their home for ‘unusual states′ (unusual behaviour such as falls or significantly reduced activity). Of a total 73 unusual states detected by the smart home over the year, only 19 of these corresponded to what the family deemed to be changes from their normal routine (Chan et al., 2008).

2.3.5. Privacy and security In order to tailor its systems to best support the inhabitant′s lifestyle, a smart home may collect information about them, such as: their movement (e.g., using sensors or video cameras), energy use and bills, purchases or even music preferences. The industry faces the challenge of ensuring that personal data is adequately safeguarded. Similarly, with the possibility of remote control of security services (opening the garage door, or turning lights or heating on or off using a mobile phone), efforts will also be needed to ensure that control of the network′s sensitive systems cannot easily be compromised. As a result, security concerns will differentiate preferences for the different smart home technologies available. For example, in biometric access control technology – likely to become affordable for homeowners within the next few years – voice recognition is

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

less secure than alternatives such as fingerprint and iris recognition (Adami et al., 2003). 2.4. Consumer perceptions of smart homes The fact that the smart home is not a technology in itself but rather an application underpinned by different sensors, devices and appliances communicating with one other has led to some smart home services and functionalities being studied in greater depth than others. Among these, energy consumption and management services are a common focus, reflected by a variety of demonstration projects taking place around the globe as part of the drive to transition to a smarter grid. A wide variety of consumer attitudes and perceptions in relation to smart home energy consumption and management services are reported in the so-called ‘demand response′ literature. Among these, Darby and McKenna (2012) review of demand response programs highlights the importance of consumer willingness to accept automation and to contribute to network flexibility. Yet, if householders are used to flat rates, they argue that they may not understand the rationale for load-shifting. Kim and Shcherbakova (2011) similarly argue that as householders have little practical knowledge about the functioning of electricity markets, they suffer from knowledge deficit. Other consumer barriers include: ‘response fatigue’; availability, financing and cost of demand response technologies; transaction costs involved in seeking out price and consumption information; relative share of savings compared to total expenditures and satisficing behaviour in switching patterns; and difficult user interfaces (Meyers et al., 2010). Given that smart homes and related technologies are still in the early stages of development and deployment, maybe it is unsurprising that householders perceive a technical gap between their expectations and current solutions (Bonino and Corno, 2011). Most user expectations about smart homes involve comfort and household tasks, most of which can be addressed by existing commercial systems or a combination of them. Based on survey and interview data, Krishnamurti et al. (2012) summarise the main concerns of the U.S. mid-Atlantic consumers towards smart meters: less control over electricity use, violations of privacy and increased costs. Bartusch et al. (2011), on the other hand, explore consumer′s perception of time-of-use tariffs through in-depth interviews with ten households. Despite a fairly high opinion of these tariffs, they reveal that convenience rather than financial savings is more important to some households after adjusting their energy behaviours to these tariffs. Another U.S. study takes a wider perspective and explores consumer attitudes towards smart grid investments (Lineweber, 2011). In a representative US residential market, 1100 households were surveyed. Almost half of the respondents support such investments and believe that the associated benefits of smart grids, which will come about through some form of smart homes, will be beneficial. However, an important finding is the sharp (one third) decline in the number of households who believe that they will actually see these benefits. The overall conclusion is that rather than ‘educating customers’ on the benefits of smart grids, industry should focus more on reassuring them that they can and should trust utility companies.

3. Methodology The study used both expert interviews and public deliberative workshops to provide insights into consumer acceptance and preferences for smart homes and technologies. The interviews were deemed necessary to access new and up-to-date information, both in terms of identifying what kind of smart home services and products can be developed in the future (to be used in public

367

workshops subsequently) and key barriers and drivers arising from the UK context. On the other hand, smart homes are new technologies with which the householders are not very familiar. Hence, it was not deemed possible to get informed feedback from the public on their acceptance of and concerns about smart homes in a limited time of a conventional focus group. The public deliberative workshops offered a more interactive setting where information via different means was provided to the public and their feedback and reflections were explored in detailed and structured discussions. The workshop format also allowed the recruitment of a diverse range of people at different life stages who could interact together and be addressed as a whole but could also be split into smaller groups for discussion. This dual design allowed us to get a more nuanced and informed understanding of social barriers for the development of smart home market in the UK. 3.1. Expert interviews Expert data was collected through semi-structured interviews. This semi-structured approach is particularly relevant for novel topics or experimental technologies (Verbong et al., 2013). The interview topic guide focused on identifying services that smart home technologies should deliver and the risks associated with their development; challenges for delivery of smart home services; how they can be addressed; types of business models for their development; drivers for the development of smart home markets; smartening of existing homes versus newly-built ones; and the socio-economic dimensions for which consumer appeal might vary. Initially, experts known in the domain were contacted. Further stakeholders were then identified through a ‘snowballing’ method. Out of 12 experts identified, eight agreed to take part in the study, representing a range of sectors related to smart home technology and services, including telecommunications, IT, healthcare, consultancy and start-up companies working on development of in-home display units, as well as delivery of smart home services. All interviewees are UK-based, with excellent understanding of the UK context, though some of them are involved in other international smart home projects and initiatives. On average, each interview lasted 1 to 1.5 h. 3.2. Public deliberative workshops 3.2.1. Locations and participants Two deliberative workshops, each comprising three smaller groups, were convened in two UK locations, London (large city) and Bridgend (small city). London, as capital city of the UK, has a population of approximately 8 million and is located in the South East of England. In contrast, Bridgend is a small town situated about 22 miles west of Cardiff, the Welsh capital. The town has a population of approximately 40,000. In addition to seeking contrasting geographic locations, workshop participants were further subdivided into three smaller groups based on age and life stage. These groups were identified as ‘pre-family’ (participants under 30 without children), ‘family’ (participants 30 to 50, usually with children) and ‘post-family’ (participants who were over 50 with no children, or no children living at home). Within these broad age groups, recruitment focused upon ensuring an even gender split and a range of job types, reflecting differing socio-economic status. Recruitment was undertaken through a research recruitment company. Each workshop involved around 30 participants (divided into three sub-groups of 10). 3.2.2. Methods and materials Participants were welcomed and asked to complete a consent form and a short pre-workshop questionnaire with questions

368

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

about demographics (education, gender, age, profession, household composition), their home (type, tenure, age, length of residence, internet access, level of satisfaction) and interest in relevant topics (new technologies, home security, home energy use, health monitoring, assisted living and environment). In their smaller sub-groups, participants were then asked about their views on and understanding of their home, appliance and energy use, energy saving, and future homes. This stage aimed to establish existing understandings and associations before any information on smart homes was provided and more informed opinions elicited. Two short videos and a presentation were then given to participants (in plenary) on smart homes. The stop-motion videos (produced by one of the academic project partners) presented contrasting perspectives on the benefits and disadvantages of smart technologies/systems (e.g., smart meters, variable tariffs, electric vehicles, efficient appliances) in terms of how an individual (video 1) or family (video 2) household might experience them. A brief Powerpoint presentation then outlined the range of smart technologies and services that might be introduced (or, in some cases, already exist), focussing on the domains of healthcare, home security and energy consumption and management (including appliances, space/water heating, lighting/entertainment, cooking and transport). In smaller groups again, participants then responded to the videos and presentation, and their attitudes to the smart technologies and services presented. Cards were provided, each illustrating a particular smart home service or technology, along with a large piece of paper depicting a house, and participants were asked to sort the cards according to whether they would like the technologies/services in their house or not. Blank cards were also provided for participants to suggest technologies/services that were not listed on the existing cards. Throughout this exercise, participants were asked to explain why they would or would not like the service/technology in their home, and whether they saw particular advantages or disadvantages. Participants were also asked how they would like the services/technologies to be provided (i.e. bought or rented; individual services/technologies or pre-defined packages, e.g., ‘healthcare’) and their preferred providers (energy companies, retailers, third party, etc.) Finally, participants returned to plenary for a short feedback session in which sub-group facilitators showed the card sort results and summarised key points. Participants completed a post-workshop questionnaire eliciting understanding of, experience with, and attitudes to, smart homes; attitude change due to the workshop; and any comments on the workshop, before being paid for their time. In total, the workshops lasted 4–4½ h each.

4. Results 4.1. Social barriers to smart home adoption: Expert views Here we present experts’ views on the factors that might hinder the adoption of smart homes in broad categories that emerged from thematic interview analyses. 4.1.1. Fit to current and changing lifestyles It was suggested there was a gulf between those developing the technology and what people actually want in their homes: ‘smart homes people all see this thing as the technological issue, you know, the bigger the broadband, the more powerful the wi-fi […] the better it’s going to be. No, it’s only if you can put in reliable, robust services that people want to use that, you know, the smart home market will take off’. Modelling was seen to help predict the consequences of people ‘doing silly things, both intentionally and

unintentionally’, while behavioural scientists could become increasingly involved in understanding the ‘fit’ of consumers, products and business models, which is an on-going trend in energy and technology companies. 4.1.2. Reducing complexity Overall there was agreement among the experts that smart home technologies need to be invisible to the consumer due to smart home programmes complexity. They called for these technologies be ‘more self-learning, more intelligent so that saving happens within the appliance’ without people having to get involved. One expert called this ‘seamless’ technology, with analogy to car technology that even though there are many sensors built into them, users are not aware of them. Experts identified reducing this complexity as a massive challenge. They articulated that this could take the form of a three-step journey: information so people can make informed decisions; control via a ‘nice user interface’; and automation to simplify use. 4.1.3. Interoperability Experts pointed out that, in addition to different appliances talking to each other (i.e. interoperability), the concern ‘will they interfere with each other?’ needs to be addressed. Some experts suggest that verification/testing is more important than standards. For example, an independent kite mark or verification system could be developed as part of a consumer engagement programme to underwrite the security of services, guaranteeing, ‘yes, this service works in a way that it doesn’t interfere with others’ as a sign of confidence to reassure consumers. Conversely, those services/devices without a kite mark would signify ‘buyer beware’, hopefully warning consumers. 4.1.4. Reliability Experts also highlighted that in general technologies being used in smart homes are reliable and products are being designed for a five to ten year product life. Nonetheless providers of smart home services would have to guarantee reliability—‘heating can be a matter of life and death’. However one interviewee highlighted that when different systems are in place in a home setting, there could be ‘unintended consequences’ (e.g., turning off all energy circuits, either because of an emergency or to save energy, in a home where a life support machine is connected). The interviewee suggested that these consequences could be avoided by building inherent control systems in the devices so that only certain people can access and control their operation, as if they have ‘a Do Not Touch label on them’. Similarly, the risk of malfunctioning wirelessly connected or battery operated sensors may be minimised by having a manual override, to ensure for example, that occupants can get back into their homes even if their operating system is stopping them. With reliability of service dependent also on the smart home’s ability to correctly predict the needs of its occupiers, there was general agreement among experts that behaviour recognition would form an important aspect of smart home technology and services. This becomes more important especially as the smart home moves towards the mass market and is driven by the fact that ‘people don’t want to be involved in having to make day-by-day, minute-by-minute, control decisions’ (acknowledging response fatigue as Kim and Shcherbakova (2011) point out). However, one interviewee made a distinction between predicting human behaviour versus knowing where a person is and where they are heading and responding intelligently to this information. He argued that people are not very predictable, but with intelligent mobile devices smart home systems can infer their

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

whereabouts (whether inside or outside the home) and their energy use can be optimised in response (e.g., turning the heat off if somebody has left the home or turn it on if they are returning home). In contrast, an expert from a start-up company cited evidence that consumers do make ‘quite significant changes’ in their lifestyles, having monitored 60,000 customers who use the company’s displays and web services (although the sample may be biased as these people have opted to have energy monitors in their homes). Services offering tele-health or assisted living may encourage consumers to modify their behaviour if they can quickly see a result and the technology directly helps them in some way. 4.1.5. Privacy and security While some experts viewed security as a technical problem with simple solutions, others saw privacy as the most challenging risk to smart home development. Companies may offer a free service in return for customer data, but consumers would have to understand the nature of this exchange otherwise companies would face ‘reputational risk’. Making consumer information available to other parties may be fraught with difficulty. It is possible that data may fall into the ‘wrong hands’, or that one piece of ‘innocent data’ combined with a second piece of ‘innocent data’ becomes a piece of ‘non-innocent’ data. Finally, experts noted that companies other than utilities have a better understanding of data privacy and the implications, particularly supermarkets and retailers who have been gathering similar customer data for many years. Experts also emphasised the importance of physical security ensuring that systems are not hacked or compromised. One interviewee highlighted possible tension between interoperability and security as if the same protocols are used and shared, the risk of them being compromised is higher than having a totally standalone system. The fact that the UK energy market is complex, with different actors operating along the supply chain (i.e. transmission system operators, distribution network operators, retailers), raised further concerns in addressing this issue. Experts envisioned that the service supply chain could potentially be ‘incredibly complicated’ with call centres and record keeping systems, and ‘unless all the bits are individually robust the chain will only be as strong as its weakest link’. It was also pointed out that if consumers lack confidence in the system they would not use it. One possibility is to have security mechanisms built into smart home delivery systems. One interviewee suggested that security can be ensured with a ‘few sensible precautions’ like strong encryption software, similar to that used in internet banking. 4.2. Social barriers to smart home adoption: Public views Before dealing with the concerns and barriers to smart home adoption that emerged from the public workshops, it is important to note that while respondents expressed concerns, they were not wholly negative about the prospect of a living in a smart home. On the contrary, many raised potential benefits to quality of life and energy saving. Participants across all groups tended to favour smart home services they perceived as practical and with the potential to improve quality of life. Fire, air quality, carbon monoxide detection, and security systems tended to fall into this category. Participants liked the idea of automatic lighting, keyless locks, remote programming via mobile phone and selling energy back to the grid. Smart home technology was seen as having the potential to increase leisure time, save money, make life easier, and provide support for assisted living as participants grew older. The prospects for reducing energy use appealed across groups, particularly for bill-payers, and economic motivations emerged as the key driver of participants’ current interest in energy saving. To a lesser extent, environmental motivations were evident,

369

though some were concerned to reduce their carbon emissions. Knowing energy consumption per room (as opposed to by device) was viewed as useful as it would help households to pinpoint and reduce their energy consumption. On the other hand, the public workshops revealed several concerns and potential barriers to the uptake of smart home services and products. These concerns include loss of control and apathy; reliability; viewing smart home technology as divisive, exclusive or irrelevant; privacy and data security; cost; and trust. 4.2.1. Loss of control and apathy When discussing smart home services, participants across all groups expressed reservations around loss of control. Labour saving devices were equated with losing daily household routines, a lack of movement and exercise, and becoming lazy. Some respondents suggested a creeping adoption of American lifestyles where ‘everything’s automated’ and ‘no one will exercise’. Smart home services would result in people ‘dumbing down’ and engendering complacency as householders increasingly rely on external experts to fix problems. In addition, monitoring of daily habits was perceived as too intrusive, controlling, restrictive, ‘big brother-like’ and engendering paranoia. Respondents expressed discomfort at ‘having complete strangers know when you’re in your house’. Many participants were underwhelmed by smart home services, which they viewed as non-essential, luxuries, or ‘gadgetry’, and resisted companies having ‘too much’ information. Participants were often concerned about living in a virtual world, becoming insular and dependent on technology and vulnerable to power cuts and high repair costs. 4.2.2. Reliability While exploring different aspects of smart home services, a key concern was reliability and what would happen if things went wrong. The ‘Pre-Family City’ sub-group (under 30, London residents) talked about sensors going off by mistake and security systems malfunctioning. Concerning connectivity, the ‘Pre-Family Town’ participants (under 30, Bridgend residents) speculated that if one device broke down, everything would malfunction. Similarly, if a remote control designed to operate several household functions broke down, the household would be in limbo. The ‘Family City’ group worried about being left with no heating in the winter if home systems broke down. The ‘Family Town’ group questioned what would happen if the network went down: Your oven might be on for days and you won’t be able to turn it off! Your refrigerator might be off so you’d have to cook everything! The ‘Post-Family City’ group drew parallels with recent problems experienced with IT systems at a couple of UK banks: We’re a slave to them and that worries me a little bit. Echoing this, the ‘Post-Family Town’ group talked of an increasing reliance on electricity and computer systems: The thing that worries me is our reliance on all this electric as well […] because everything is run, all our computers, I mean look at the crash with the banks. 4.2.3. Smart technology as divisive, exclusive, or irrelevant All groups talked about the ways in which they would be excluded from smart home technology, or cited other social groups as either beneficiaries or losers. Older housing and smart technology was viewed as incompatible as older properties would be difficult to update. To compound the problem, new build properties were perceived as lacking character, and therefore undesirable

370

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

and bland. Both ‘Pre-Family’ and ‘Family City’ groups viewed smart home services as for homeowners who were settled in the same property for a number of years. This excluded them as renters, and smart technology was also seen as out of the reach of first time buyers who would struggle to afford smart home services. Within this context, it is unsurprising to find that younger participants saw smart home technology as a luxury. The ‘Family Town’ group predicted that smart technology would lead to various social groups experiencing financial exclusion: My kids are going to be with me in their 30 s and 40 s. I’ve got visions of my kids being with me permanently because they won’t be able to afford these bills. Energy efficiency efforts were seen as unfairly distributed by the ‘Post-Family City’ group, who suggested that with the advent of smart technology, the more affluent would be less conscientious regarding energy saving, leaving ‘poorer people to use less so the richer people can use more’. Also, technology would exclude those who are not computer literate, notably older people. It would also be more suited to younger people who would have a 10–20 year period to recoup costs. Young people were seen to ‘live’ for technology, such as mobiles, and iPads, contrasting with the elderly who are less likely to own computers and would struggle unless devices had a more user-friendly design. Also, as people grow older, there was the perception that it becomes increasingly difficult to keep up: By the time we get to 75–80, there’s a barrier and you just can't assimilate. The ‘Post-Family Town’ group pointed out that many older people do not own mobile phones, yet smart home services seem to assume smart phone ownership. The type of information generated by smart home technology could make the elderly ‘quite fearful’ leading to excess worrying: ‘oh my god, I can’t afford this, I can’t afford that’. As a result, smart technology would be better suited to young people who ‘are going to grow up with this’. 4.2.4. Privacy and data security All groups were prompted on their views on how smart home data would be collected and used. Both younger and older participants saw the personal information that would be collected on households as akin to the type of data collected on a supermarket reward or loyalty card. Although this may imply that participants were untroubled, a critical distinction was made between the monitoring of external and internal activities. For example, CCTV can monitor people in public spaces whereas smart technology has the potential to invade private lives: [CCTV is] when you’re outside. In your own home you expect to be secure and what goes on around these four walls, stays in these four walls. In this context, the data collected via smart home technology was a step too far. Participants expressed concern over third parties knowing daily routines and occupancy, data falling into the wrong hands, and the potential of smart systems to be hacked into. A strong theme throughout the groups equated the household monitoring involved with smart technology with ‘big brother’ watching them. Smart home technology was often viewed as a further invasion of, or threat to, privacy in a society where already too much personal information is collected and stored. The ‘PostFamily Town’ group speculated over whether the companies responsible for smart home services would sell on personal data as they would be in receipt of ‘all this free information from millions of homes every month’. Interconnectivity of various smart

systems also implied the sharing of too much personal information for a number of participants. One participant wondered if the lack of perceived privacy would be worth it for cheaper heating bills. The older groups in both town and city suggested that the monitoring required as part of smart health services would be too intrusive. However certain aspects of health services, such as alerting a carer if problems were detected, were viewed more positively. In general, respondents liked the idea of services that could support an ageing population, but expressed grave concerns about the potential downsides. The ability to monitor blood pressure remotely generated concern because of the type and volume of personal data that would accumulate: [If] somebody somewhere gets hold of your blood pressure [data], it could knock you ever getting life insurance on the head. One of the younger groups (‘Pre-Family Town’) suggested that health services such as pressure sensors had the potential to invade privacy, leading to consumers being bombarded with marketing. With monitoring, it was difficult for participants to imagine where the boundaries should be fixed: It’s hard to know where to draw the line […] they could monitor everything couldn’t they… 4.2.5. Cost Concerns were raised across all the groups over the costs of different aspects of smart home technology. The cost of installation emerged as one barrier, and was perceived as worthwhile only for longer term home owners who had the necessary funds, automatically excluding those on low incomes and tenants living in privately rented or council properties. Smart repairs and maintenance were perceived as costly and complicated, and fears were expressed of being committed to a smart contract, leading consumers vulnerable to rising energy prices. Regarding potential cost savings, respondents would want to see substantial savings for it to be worthwhile: saving ‘a few pence’ would be meaningless. There was speculation that smart home technology would leave people ‘constantly worrying’ and feeling guilty. Running appliances when electricity is cheaper was often perceived as pointless if savings were minimal, as well as requiring inconvenient changes to household routines. Participants tended to favour reasonably priced, energy-efficient appliances that were shown to have significantly cheaper running costs. Questions were raised as to why costs could not be controlled at source by utility companies or through government regulation rather than responsibility for reducing costs falling squarely on the consumer: I’m concerned—it looks as though we’re getting lots of control but I question how much control we’ve actually got, even with that information. Some participants suggested the introduction of grants and means-tested schemes, or including the costs of smart technology into homeowner’s mortgages. 4.2.6. Trust The issue of cost also triggered broader discussions about trust in government and industry across the groups. Participants questioned whether smart technologies and services would really save customers money in the long run, since energy suppliers and technology producers would ultimately be motivated by profit and suspected that any financial savings made by utility companies would not be passed on to the consumer:

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

And being a bit cynical too, isn't there a vested interest on the part of energy companies to make money and yet we're told that they're trying to encourage us to use less energy? I don't think that's being particularly honest. Finally, participants expressed cynicism over the extent to which the UK government prioritises environmental issues. Some commented that the government should be leading by example: You don't see any solar panels on the Houses of Parliament do you?…if the government's going to promote this and push this, they should be seen to be doing three times the amount of what we do. 4.3. Contextualizing social barriers as identified by the experts and the public A summary of social barriers, as highlighted in the literature (both smart home and demand-side) and articulated by experts and the public is provided in Table 2. As can be seen from the table,

371

some of the barriers emerging from demand-side literatures overlap with those highlighted in ‘smart home’ literature. As expected, experts identified issues that are neglected in the literature (e.g. interference vs interoperability in a home setting; tension between security and interoperability). The scope and breadth of public concerns summarised give an indication of areas to be addressed for smart technology to be accepted and fully utilised within households and should serve as an aide memoir for key decision makers.

5. Conclusions 5.1. Understanding social barriers to smart home deployment Our study analyses social barriers for the development of smart home markets. Expert interviews, which broadly supported findings from previous literature on smart home development, indicated these barriers relate to: fit to current lifestyles; technological complexity; interoperability and standards; reliability; privacy and security. These perspectives only partly correspond to those of

Table 2 Summary of social barriers. Literature Smart Demandhome side Fit to current and changing Integration of technology and services into the design, lifestyle and general sense of home lifestyles Meeting the evolving needs, demands and preferences of its occupants Accommodating the integration of new technological components Accepting automation and contributing to network flexibility Convenience more important than financial savings Role of behavioural scientists to understand the ‘fit’ of consumers, products and business models Technical gap between expectations and current solutions Loss of control and apathy Smart home services as non-essential, luxurious, or ‘gadgetry’ Smart technology as divisive (exclusive to tenants, elderly, computer illiterate, smart phone users, people living in older properties) Smart technology leaving people ‘constantly worrying’ and feeling guilty Smart homes making more affluent people less conscientious regarding energy saving Administration Expertise for operational and management needs of smart homes Knowledge deficit Response fatigue Satisficing behaviour in switching patterns Difficult user interfaces Reducing complexity Less control over electricity use Information fatigue for elderly in particular Interoperability Communicating with other devices and technologies Interference of devices with each other in a home setting Reliability Malfunctioning Inference of householders’ desired outcome Avoiding unintended consequences Behaviour recognition forming key aspect of smart homes Sensors going off by mistake Due to break down of remote control units house going in limbo Communications network breaking down and other systems getting out of control Privacy and security Ensuring safety and security of private data Violations of privacy Data falling into wrong hands Combining two sets of innocent data leading to ‘non-innocent’ data Tension between interoperability and security Big brother-like monitoring as too intrusive Concerns over third parties knowing daily routines and occupancy Systems being compromised Companies responsible for smart home services selling on personal data Lack of perceived privacy would not worth it for lower bills Smart health services invading privacy by leading to consumers being bombarded with marketing Trust Lack of trust that financial savings made by utility companies will be passed onto the consumers Prioritisation of issues by the UK Government Costs Transaction costs to seek out price and consumer information Installation costs High repair and maintenance costs

Experts Public

√ √ √ √ √

√ √

√ √ √ √ √ √ √ √ √ √ √

√

√ √ √ √ √ √ √

√ √ √ √ √ √

√ √ √ √ √

√ √ √

√

√ √ √ √ √ √ √ √ √ √

372

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

consumers. From our deliberative workshops, we found the public’s main concerns pertain to: loss of control and apathy; reliability; viewing smart home technology as divisive, exclusive or irrelevant; privacy and data security; cost; and trust. Thus, while both experts and the public appeared to agree on some of the more practical social barriers (e.g., reliability, security), deeper, moral concerns about human nature, inequality, and trust were a stronger feature of public discussions. These social barriers need not prevent the development of the smart home market. Rather, as articulated by experts, consumer acceptance is dependent on their having a clear sense of smart home benefits; but the relatively limited financial savings they can provide is not enough of a strong drive on its own. In addition to concerns over the cost of smart home technologies (Meyers et al., 2010), our study highlights how perceived higher maintenance costs are another important barrier. While costs and other concerns around privacy can be dealt with through some financial incentives (e.g., loans, grants) and rules and regulations about how data is collected and used by different parties (e.g., developing a home energy gateway managed by a service provider, rather than the utility company; (Dugerdil, 2011), there are other areas where the solutions are not so straightforward. In particular, strong concerns about the exclusivity of smart homes for tenants and those on low incomes (lack of financial means), the elderly (due to computer illiteracy and long waiting times to recoup costs) as well as people living in older properties (lack of their compatibility to install smart technologies) point to possibly increasing social divisions in the short to medium term. With changing patterns of energy use and levels of demand as part of transition to smart grids, some studies claim that infrastructure characteristics can also contribute to this further where householders on neighbouring streets face different electricity prices depending on the constraints on the grid at that time (UKERC, 2011). In the long term, though, the fact that society and technology co-evolve in a complex and non-linear manner leading to reshaping of homes and routines by technologies in radical ways (among others (Cockburn and First-Dilic, 1994; Cowan, 1983; Oldenziel and Zachmann, 2009) there remains a question mark over whether smart homes can fulfil the promise of reducing energy use and whether other unintended consequences might prevail. It is very likely that householders might utilise new smart home technologies in such different ways (and not those imagined by designers) that new habits and conventions may emerge. Some habits formed may reinforce potentially unsustainable and energy intensive lifestyles, in turn becoming new norms and practices (Shove, 2003). Another longer-term risk might be around excessive automation and ‘dumbing down’ of people (as in portrayed in the film Wall-E (2008)), creating other social and health problems such as reduced levels of social interactions and obesity. Nonetheless, in order to utilize the potential of smart home technologies to contribute to decarbonisation of UK energy system, the study suggests that financial benefits are likely to be insufficient if consumers are required to significantly adapt daily routines (e.g., dealing with laundry in the morning before going to work) or experience any perceived reduction in quality of life. If these technologies cannot increase consumers’ sense of control and personal agency in managing their energy use, they are unlikely to adopt them. More challenging still will be how to overcome the public’s profound distrust in the ability of government to regulate and of industry to pass on any benefits, which is likely to require new ways of engaging with customers, as we discuss below.

what it is that actually is of interest to a customer’. While both experts and, to some extent, public acknowledge smart home benefits for saving energy and improving quality of life, challenges and perceived drawbacks remain. Furthermore, studies of how smart technologies have been used suggest reported benefits may be overstated. For example, Hargreaves et al. (2010, 2013) report a variety of behaviours observed from the introduction of smart energy monitors, including how they soon become invisible and normal household routines are re-established. If the industry does not address such challenges, the functionalities and capabilities offered by smart home technologies and services may share the same destiny whereby they are manually overridden or moved out of sight so that they are also out of mind. Hence there are important lessons for the smart home industry:


Householders are interested in reducing their energy use and










technologies/services that will help them to achieve this would help with their adoption at mass scale if only they are not required to significantly adapt daily routines. The expected benefits of smart technology would have to be explicitly stated and demonstrated, as well as how they would be realised and delivered. As was found in the other studies (Lineweber, 2011), the fact that consumers do not believe they will receive benefits from smart homes calls for energy industry to find ways of engaging with the customers beyond billing periods. Trust is constructed through mutual interaction and progressively proven. Energy companies need to develop strategies, services and products that offer continuity, transparency and are responsive to the needs of their customers. In this regard, accurate billing of consumers for their energy use via the rollout of smart meters can make significant contributions towards building trust. On the other hand, development of technologies and services that increase control and agency of consumers is crucial as otherwise they might face consumer resistance. In this respect, adoption of user-centred design principles (Haines et al., 2007; Rohracher, 2003) can help with addressing these issues and enabling the transformation of the smart home market from a ‘technology push’ (Haines et al., 2007; Harper, 2003) model to a ‘market pull’ one. Concerns about data privacy need to be dealt with appropriately, for example via standards or ‘privacy friendly’ techniques (McKenna et al., 2012). However, a too tightly regulated market was felt by experts potentially to ‘kill a whole industry’; while the UK Government does not have a good track record of safe data keeping practices.

5.3. Lessons for policy-makers Lack of trust in government may partly be dealt with through long-term engagement processes and institutional reform (e.g., Whitmarsh et al., 2011). Specifically, though, in respect of energy efficiency and environmental protection, householders in this study suggested that government and business need to lead by example (e.g., putting solar panels on public buildings). Communication efforts should thus not only establish householder benefits of smart home technologies, but also the societal benefits and efficacy of collective action to transform energy systems to become more sustainable and smarter. 5.4. Future directions

5.2. Lessons for industry One expert defined the current state of the smart home market very succinctly, that it is a young industry ‘trying to understand

This study represents initial work to map diverse societal perspectives on smart technologies, but there is much scope to build on this in future research. For example, while our expert and

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

public samples were relatively small and our investigation was exploratory, future research may utilise more quantitative techniques to provide a more representative view of smart home responses amongst public and expert communities, compare responses across nations or different sub-national groups, or investigate how different social or psychological factors (e.g., income, gender, values, experience) may shape responses to smart technologies.

Acknowledgements The study presented here is funded by E.ON SE as part of The International Research Initiative 2012, titled ‘Consumer preferences for smart homes: a comparative study between the United Kingdom, Germany and Italy’. We thank the anonymous reviewers for their comments. References Adami, A.M., Hayes, T.L., Pavel, M., 2003. Unobtrusive monitoring of sleep patterns. In: Proceedings of the 25th Annual International Conference of the Ieee Engineering in Medicine and Biology Society, 1–4 pp. 25, 1360–1363. Andoh, H., Watanabe, K., Nakamura, T., Takasu, I., 2004. Network health monitoring system in the sleep. In: SICE 2004 Annual Conference, 1–3, pp. 1421–1424. Balta-Ozkan, N., Davidson, R., Bicket, M., Whitmarsh, L., 2013. The development of smart homes market in the UK. Energy, http://dx.doi.org/10.1016/j.energy.2013. 08.004. Barnes, N.M., Edwards, N.H., Rose, D.A.D., Garner, P., 1998. Lifestyle monitoring— technology for supported independence. Computing & Control Engineering Journal 9, 169–174. Bartusch, C., Wallin, F., Odlare, M., Vassileva, I., Wester, L., 2011. Introducing a demand-based electricity distribution tariff in the residential sector: demand response and customer perception. Energ Policy 39, 5008–5025. Boman, I.L., Tham, K., Granqvist, A., Bartfai, A., Hemmingsson, H., 2007. Using electronic aids to daily living after acquired brain injury: a study of the learning process and the usability. Disability and Rehabilitation: Assistive Technology 2, 23–33. Bonino, D., Corno, F., 2011. What would you ask to your home if it were intelligent? Exploring user expectations about next-generation homes. Journal of Ambient Intelligence and Smart Environments, 3. Brumitt, B., Meyers, B., Krumm, J., Kern, A., Shafer, S., 2000. EasyLiving: technologies for intelligent environments. Handheld and Ubiquitous Computing Proceedings 1927, 12–29. Cash, M., 2004. Assistive technology and people with dementia. Reviews in Clinical Gerontology 13, 313–319. Celler, B.G., Earnshaw, W., Ilsar, E.D., Betbeder-Matibet, L., Harris, M.F., Clark, R., Hesketh, T., Lovell, N.H., 1995. Remote monitoring of health status of the elderly at home. A multidisciplinary project on aging at the University of New South Wales. International Journal of Bio-Medical Computing 40, 147–155. Chan, M., Campo, E., Estève, D., Fourniols, J.-Y., 2009. Smart homes—current features and future perspectives. Maturitas 64, 90–97. Chan, M., Esteve, D., Escriba, C., Campo, E., 2008. A review of smart homes—present state and future challenges. Computer Methods and Programs in Biomedicine 91, 55–81. Chikhaoui, B., Pigot, H., 2010. Towards analytical evaluation of human machine interfaces developed in the context of smart homes. Interacting with Computers 22, 449–464. Cockburn, C., First-Dilic, R. (Eds.), 1994. Open University Press, Buckingham. Colombo, M., 2001. Gerontechnology: Why and How? T.L. Harrington, M.K. Harrington, (Eds.); 2000. Cowan, R.S., 1983. More Work for Mother: The Ironies of Household Technology from the Open Hearth to the Microwave. Basic Books, New York. Darby, S.J., McKenna, E., 2012. Social implications of residential demand response in cool temperate climates. Energ Policy 49, 759–769. Davidoff, S., Lee, M.K., Yin, C., Zimmerman, J., Dey, A.K., 2006. Principles of smart home control. Ubicomp 2006. Ubiquitous Computing Proceedings 4206, 19–34. Demiris, G., Hensel, B.K., 2008. Technologies for an aging society: a systematic review of “smart home” applications. Yearbook of medical informatics, 33–40. Demiris, G., Skubic, M., Keller, J., Rantz, M.J., Oliver, D.P., Aud, M.A., Lee, J., Burks, K., Green, N., 2006. Nurse participation in the design of user interfaces for a smart home system. Smart Homes and Beyond 19, 66–73. Ding, D., Cooper, R.A., Pasquina, P.F., Fici-Pasquina, L., 2011. Sensor technology for smart homes. Maturitas 69, 131–136. Dugerdil, B., 2011. Home Energy Gateway: The Gatekeeper of Smart Grid, ETSI Smart Grids Workshop, 5–6 April 2011, Sophia Antipolis, France. Edwards, W.K., Grinter, R.E., 2001. At home with ubiquitous computing: seven challenges. In: Proceedings of the Third International Conference on Ubiquitous Computing. Springer-Verlag, Atlanta, Georgia, USA, pp. 256-272.

373

Eriksson, H., Timpka, T., 2002. The potential of smart homes for injury prevention among the elderly. International Journal of Injury Control and Safety Promotion 9, 127–131. Faruqui, A., Harris, D., Hledik, R., 2010. Unlocking the €53 billion savings from smart meters in the EU: how increasing the adoption of dynamic tariffs could make or break the EU’s smart grid investment. Energy Policy 38, 6222–6231. Fitzpatrick, G., Stringer, M., Harris, E., 2006. Lessons for the future: experiences with the installation and use of today’s domestic sensors and technologies. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A.J. (Eds.). Pervasive Computing: Proceedings of the 4th International Conference. Springer-Verlag, Dublin, Ireland, pp. 383–399. Friedewald, M., Costa, O.D., Punie, Y., Alahuhta, P., Heinonen, S., 2005. Perspectives of ambient intelligence in the home environment. Telematics and Informatics 22, 221–238. Geels, F.W., 2005. Processes and patterns in transitions and system innovations: refining the co-evolutionary multi-level perspective. Technological Forecasting and Social Change 72, 681–696. Geels, F.W., Smit, W.A., 2000. Failed technology futures: pitfalls and lessons from a historical survey. Futures 32, 867–885. Haines, V., Mitchell, V., Cooper, C., Maguire, M., 2007. Probing user values in the home environment within a technology driven Smart Home project. Personal and Ubiquitous Computing 11, 349–359. Hargreaves, T., Nye, M., Burgess, J., 2010. Making energy visible: a qualitative field study of how householders interact with feedback from smart energy monitors. Energ Policy 38, 6111–6119. Hargreaves, T., Nye, M., Burgess, J., 2013. Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term. Energ Policy 52, 126–134. Harper R., (Ed), 2003, Inside the smart home. Springer; London. Hu, H., Yang, D., Fu, L., Xiang, H., Fu, C., Sang, J., Ye, C., Li, R., 2011. Semantic Webbased policy interaction detection method with rules in smart home for detecting interactions among user policies. Communications, IET 5, 2451–2460. ITU, 2010. Applications of ITU-T G.9960, In: Paper, I.T.U.T. (Ed.), ITU-T G.9961 Transceivers for Smart Grid Applications: Advanced Metering Infrastructure, Energy Management in the Home and Electric Vehicles, (ITU-T, 06/2010) ed. International Telecommunication Union Technical Paper. Kidd, C.D., Orr, R., Abowd, G.D., Atkeson, C.G., Essa, I.A., MacIntyre, B., Mynatt, E., Starner, T.E., Newstetter, W., 1999. The Aware Home: a living laboratory for ubiquitous computing research. Cooperative Buildings 1670, 191–198. Kim, J.-H., Shcherbakova, A., 2011. Common failures of demand response. Energy 36, 873–880. King, N., 2003. Smart home—a definition. Intertek Research & Testing Center, Milton Keynes. Krishnamurti, T., Schwartz, D., Davis, A., Fischhoff, B., de Bruin, W.B., Lave, L., Wang, J., 2012. Preparing for smart grid technologies: a behavioral decision research approach to understanding consumer expectations about smart meters. Energ Policy 41, 790–797. Li, J., Da-You, L., Bo, Y., 2004. Smart home research, machine learning and cybernetics, 2004. In: Proceedings of 2004 International Conference, 652, pp. 659–663. Li, W., Lee, Y.-H., Tsai, W.-T., Xu, J., Son, Y.-S., Park, J.-H., Moon, K.-D., 2012. Service-oriented smart home applications: composition, code generation, deployment, and execution. Service Oriented Computing and Applications 6, 65–79. Lineweber, D.C., 2011. Understanding residential customer support for – and opposition to – smart grid investments. The Electricity Journal 24, 92–100. McKenna, E., Richardson, I., Thomson, M., 2012. Smart meter data: balancing consumer privacy concerns with legitimate applications. Energ Policy 41, 807–814. Meyers, R.J., Williams, E.D., Matthews, H.S., 2010. Scoping the potential of monitoring and control technologies to reduce energy use in homes. Energy and Buildings 42, 563–569. Nye, M., Whitmarsh, L., Foxon, T., 2010. Sociopsychological perspectives on the active roles of domestic actors in transition to a lower carbon electricity economy. Environment and Planning A, 42. Oldenziel, R., Zachmann, K. (Eds.), 2009. MIT Press, Cambridge, Mass. Perry, M., Dowdall, A., Lines, L., Hone, K., 2004. Multimodal and ubiquitous computing systems: supporting independent-living older users. IEEE Transactions on Information Technology in Biomedicine 8, 258–270. Perumal, T., Ramli, A.R., Leong, C.Y., 2011. Interoperability framework for smart home systems. IEEE Transactions on Consumer Electronics 57, 1607–1611. Perumal, T., Ramli, A.R., Leong, C.Y., Mansor, S., 2008. Interoperability for Smart Home Environment Using Web Services. Pragnell, M., Spence, L., Moore, R., 2000. The Market Potential For Smart Homes, York Publishing Services, Published for the Joseph Rowntree Foundation. Reinisch, C., Kofler, M.J., 2011. ThinkHome energy efficiency in future smart homes. EURASIP Journal on Embedded Systems 2011, 1–18. Rogers, E.M., 2010. Diffusion of innovations. Simon and Schuster. Rohracher, H., 2003. The role of users in the social shaping of environmental technologies. Innovation: the European Journal of Social Science Research 16, 177–192. Schot, J., Rip, A., 1997. The past and future of constructive technology assessment. Technological Forecasting and Social Change 54, 251–268. Shove, E., 2003. Converging conventions of comfort, cleanliness and convenience. Journal of Consumer Policy 26, 395–418.

374

N. Balta-Ozkan et al. / Energy Policy 63 (2013) 363–374

Tatsuya, Y., 2005. Ubiquitous home. Real-Life Testbed for Home Context-Aware Service, 54–59. Taylor, A.S., Harper, R., Swan, L., Izadi, S., Sellen, A., Perry, M., 2007. Homes that make us smart. Personal and Ubiquitous Computing 11, 383–393. UKERC, 2011. Policy, Regulatory and Social Aspects of Smart Grids and Applications, Workshop Report, 13–14th December 2011, Royal Society, London.

Verbong, G.P.J., Beemsterboer, S., Sengers, F., 2013. Smart grids or smart users? Involving users in developing a low carbon electricity economy. Energ Policy 52, 117–125. Whitmarsh, L., Upham, P., Poortinga, W., Darnton, A., McLachlan, C., Devine-Wright, P., Sherry-Brennan, F., 2011. Public attitudes to a low-carbon energy—research synthesis. Research Councils UK.