Tipo de interés nominal de los Bonos y disposiciones relativas al pago de los intereses

Feedback is the core principle of most HEMS. The effect of feedback on household energy consumption has been studied for a number of decades with varying degrees of intensity and success. Feedback was introduced from a psychological perspective to influence behaviour, and the first studies commonly used written messages or bills to relay feedback or written requests to participants to self-report meter readings. This was a rather costly and time-intensive process that sometimes necessitated daily visits to households (Seligman et al., 1978). An additional drawback was that the feedback was given at fixed points in time that were often few and far between and had been unnaturally orchestrated by a researcher. The potential to apply products to relay the energy feedback to households soon became apparent. The advantage of a HEMS is that it can give real-time feedback at any moment of day, whenever the user chooses. This provides users with additional flexibility in their utilization of feedback.

In the first instance, the ‘HEMS’ that relayed the feedback were low-tech solutions, such as a Lucite frame in which plastic numbers could be inserted (Seligman and Darley, 1977) or a blue indicator light (Seligman et al., 1978) that flashed under certain conditions. The application of digital displays introduced a whole new range of possibilities. The Fitch electricity monitor (Funk, 1978) was a forerunner in its application within scientific research (McClelland and Cook, 1979), and the first research on a gas monitor was published in 1989 (van Houwelingen and van Raaij, 1989, based on gas monitor presented in van Beurden, 1982). Little interest was shown in HEMS in the 1990s, but in recent years their potential to reduce the energy consumption of households has drawn an increasing amount of attention. Numerous

companies and start-ups are developing new HEMS and they are the subject of increased research.

However, the inclusion of a HEMS in the case study design and the flexibility a HEMS gives households in their use of the feedback, warrants the study of the specific influence of the HEMS itself and of its use by households. However, this has received limited attention. HEMS were initially implemented by the domain of social psychology, with a predominant focus on the effectiveness of the feedback. This chapter fills this gap by reporting on the findings from the second and third case studies on the use of HEMS.

§ 6.4

Setup

This section describes the setup of the interviews. The setup of the second and third case studies and the other qualitative data collection methods can be found in § 5.2.3

, § 5.3.3, and Appendix A I-A IV where it was explained that during the course of the two case studies a usability study among 14 potential users, 5 focus groups, a usability test and co-design session among 11 participants for a conceptual interface, and 19 interviews were conducted. Twelve users participated in multiple elements, which gave extra richness to the data and provided a longitudinal perspective. The insights from these 64 personal interactions with 50 unique participants form the basis of this chapter. However, due to the setup and nature of the different forms of qualitative data gathered, the classification of users and their use of HEMS mainly draws on the 19 interviews with users of the two types of HEMS. This is because more in-depth knowledge and background information was gained through the semi-open interviews. Nonetheless, the other data remain essential, because they underpin the findings and give them solidity.

§ 6.4.1

Setup of the interviews

The interviews were conducted in a semi-structured manner with the help of a list of open questions. They were held at people’s homes and lasted roughly 1–1½ hours. Two interviews were conducted by telephone. The protocol can be found in Appendix A III. The results and conclusion of the first case study in Chapter 4 as well as the literature review in Chapters 2 and 3 formed the basis for the questions. Both studies used the

same set of questions; only some adjustments were made due to the differences in the type of HEMS. The aim of the interviews was to gain an overall understanding of the users, their households, and their use of the HEMS and household appliances. Questions about motivation, reasons, goals and expectations concerning the trial and the HEMS were asked. Interviewees were also asked about their use and other household members’ use of the HEMS, as well as about the HEMS itself and its location. Furthermore, questions about family dynamics, household’s energy consumption, whether the interviewee was aware of how much money the household spent or how much energy it used (in the past), whether the HEMS had made the interviewee aware of a certain consumption, and whether and, if so, how he or she had tried to adjust household consumption. Attention was also paid to how the interviewees used household appliances, the choices they made therein, and the contextual barriers and enablers. Finally, they were asked about their technical background, education, jobs, family size, and age.

The interviews were conducted with ten households that were using an energy management device and nine that were using a multifunctional HEMS. Two single- person households were interviewed; one was a single male, the other a single female. Three couples without children were interviewed. The majority (14 households) were couples with children. Of these households, in two cases only the mother was interviewed, in five cases only the father was interviewed, and in seven cases both the father and the mother were interviewed (although in several of these cases, the mother did not actually use the HEMS). In all cases, the main user was present and in most homes there was only one main user, that is, a person who used the feedback from the HEMS significantly more than the rest. The households using the energy management device were participants in a 5-month study and the households using the multifunctional HEMS were participants in a 6- to 12-month study. At the time of the interview, all users had had the HEMS in their homes for between 6 weeks and 10 months. A full overview of the participants is given in Appendix A V.

§ 6.4.2

Coding

A coding system was used to identify the participants. Each participant received a unique number (1–50). After the number, letters indicated which HEMS the participant had used, which research group he or she was in, and what type of qualitative research he or she had participated in.

In the case of the multifunctional HEMS, the letters that were used indicate, in order of use, the multifunctional HEMS (MF), whether they were in the smart (S) group, analogue (A) group or used the HEMS only in a lab setting (blank), and whether they participated in the usability study (u), one or two focus groups (f or ff), the concept test (c) and/or the interview (i).

Participants in the second trial using the energy management device have the letters (EM) and an additional letter indicating they were in the group with only plugs (P) or in the group that also had the Eee top (E). Interviewees are indicated by an (i). The bold letter indicates from which data the citation came. In the cases where two adults were interviewed within one household, an “(M)” or “(F)” indicates whether the comment is from the male or the female.

§ 6.4.3

Type of HEMS

The two HEMS that were used by the participants were an energy management device and a multifunctional HEMS. A full technical description is given in § 5.2.1, § 5.3.1, and § 8.3.1.

§ 6.4.4

Method of data analysis

This section details the method used to analyse the data and categorize the users and their use and application of HEMS. The recordings, transcriptions and field notes made of the direct communications with participants during the two case studies were analysed and condensed using a recursive abstraction approach. Striking and distinct comments in two areas – namely the user and the dynamics between the user and his or her energy consumption; and the dynamics between the user and his or her HEMS – were particular focal points when condensing the data. As such, special attention was paid to the user’s background, upbringing, interests and attitude towards technical

appliances. Knowledge of, affinity with, and handling of energy consumption and the money spent on it, the appliances related to that energy consumption, and the behaviour and choices of the household members causing the energy consumption were also distilled. Finally, reasons for wanting to participate in the trial, how they used or did not use the HEMS, and how this related to other household members, were extracted. Defining statements of participants were left intact as far as possible for use in the presentation of the results.

Although strong differences in the use of HEMS emerged from the data, similarities between participants also became apparent. To effectively convey the broad range of data gathered while retaining the rich and individual characteristics of the users, their use of HEMS and the surrounding context, the extracts from the communications with participants were categorized by grouping together similar users and their types of use. Nine characteristics formed the basis for the classification: six relate to user characteristics that have indirect effects on their use of HEMS, and three directly relate to their use of the HEMS. These nine characteristics are:

Users distinctive and key characteristics and their perceived responsibility for/

organization of energy, appliances, money and parenting-related household tasks. How mindful or aware they are of energy and their willingness and perceived capability to save.

•

Whether they had a technical background (e.g. in their job or schooling).

•

Whether they were or had been keeping track of their meter readings (e.g. weekly or monthly, using their memory, a note pad or an Excel spreadsheet).

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What their motivations were to participate in the case study.

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Whether they had underlying motives (e.g. altruistic, economic or fire safety motives) and, if so, how strong they were.

•

Whether they were more inclined to implement technical energy saving solutions (e.g. implementing time switches, powerstrips with flip switches, energy saving or energy producing equipment) or behavioural energy saving solutions (e.g. reducing unnecessary use, using products less) to keep their consumption under control with the help of the HEMS.

•

Why they use the HEMS (their goal).

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Whether their goal-related interest in the HEMS seemed short term or longitudinal.

•

Whether certain specific desires surfaced related to the HEMS.

In doing so, five clusters of users and their use of HEMS surfaced. Table 10 gives a short overview of the nine characteristics and how the five types of users and their use of HEMS vary in relation to these characteristics.

’techie’ ‘one-off user’ ‘manager’ ‘thrifty spender’ ‘joie de vivre’ Key characteristics Data geek, energy

conscious, tech- nical, interested in gadgets, maintai- ner (and installer) of appliances and equipment Goal-oriented, technical, inte- rested in gadgets, maintainer (and installer) of appliances and equipment Controlling, strict parenting, managing family members (and administration/ money), energy conscious Frugal, sober upbringing, does administration, keeps track of money. Want to economize, though not sure how to.

Enjoys life, laid- back, relaxed parenting style, likes new designs, keeps overview of money. Unmindful of energy Technical back- ground ++ ++ +/- -- -- Interest in gadgets ++ ++ +/- +/- +

Kept track of meter readings ++ +/- +/- +/- -- Motivation to participate Fun/sport, gadget appeal

Looking for saving opportunities, fun

Check on other family members

Free, find ways to save money

Gain insight, Suspi- cion checker Underlying motives Predominantly

environmental, also economic

Predominantly environ-mental and fire safety

Environ-mental or economic, both strong

Economic, strong Environ-mental or economic but not very dominant

Goals Discovering con-

sumption (of appli- ances), reducing as much as possible, keeping track of consumption Discovering consumption pre- ferably of individual appliances. Find (technical) reducti- on measures Discover energy consumption, keep track of whether applian-ces are left on unneces- sarily and who is responsible

Save money Find phantom

loads, global over- view/ indication for bill at the end of the year Short-term or lon- ger-term (goal-re- lated) interest in HEMS Discovering and reducing: mainly initial use. Keeping track: lon- ger-term (frequent)

Short term Discovering: mainly initial use Keeping track: Lon- ger-term (frequent)

Phantom loads: short-term over- view: Longer term (infrequent) Behavioural or

technical soluti- ons/ control

Technical Mainly technical Mainly behavioural Behavioural Neither

Desires Raw, exportable,

detailed data, prognosis, shower use data

Raw, detailed data Control mecha- nism, baseline check, shower use data Information, perso- na-lized advice, insights Certainty, referen- ce, overview Table 10

Classification of users according to nine characteristics

This categorization has similarities with personas and overlapping aims to the ease with which this research can be implemented within design practice. The aim of personas is to give designers a better awareness of the user (Fulton Suri, 2003b). This is because personas are effective in helping “understand its target audience as well as aid in design and development decisions” and “focus attention on aspects of design and use that other methods do not” (Pruitt and Grudin, 2003). However, the classification in this chapter is specifically based on the observations during the case studies and therefore might not be representative of the whole population. As such, this chapter does not profess that the findings are generalizable to the whole population, in contrast

to personas (Chapman and Milham, 2006). Nonetheless, it does investigate the extent to which past research has found similar results, which might give indications that the findings are applicable to a larger population. The five types of users and their use and application of HEMS from the classification are discussed in further detail in the following section.

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