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TOWARDS UNDERSTANDING HOW REDEFINING SUPPLY SIDE CONSTRAINS COULD SHAPE INDIVIDUAL DEMAND SIDE BEHAVIOUR

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The impact of behavioural aspects on environmental solutions has received more and more recognition over the last couple of years. There is a general change of thinking away from purely technical approaches towards integrated and holistic concepts, which take especially the end user into account. Many studies have shown (e.g. [14] [16]) that technical improvements and innovations do not necessarily cause the desired outcomes due to a lack of communication with the actual end users of these technologies. Other studies, for instance on improvements of house insolation or the use of LED bulbs, caused paradox behaviour, sometimes also called “Jevon’s paradox” or “rebound effect”, where the technical improvements are eaten up by the increasing demand they caused [6]. These are just a few examples to highlight the gap between new developments in environmental sustainable technologies and the actual behaviour towards these innovations from an end-user’s perspective. The fundamental question therefore is: “How to influence people’s behaviour towards a more pro-environmental outcome, also in the long-term?” This paper will not be about another study, which proves incentives make people act in a more desired way, as long as the incentive is given [1]. All the various aspects of human behaviour have been replicated in several well executed studies [1], however none of these on their own were able to solve the problem of motivating people to change their behaviour also in the long term. So instead of reinventing the wheel over and over again, the idea presented in this paper is to use well defined behavioural theories and their inventory tools, which have been well established in psychology and the social sciences, and to integrate them into a holistic cycle of behaviour using the High Performance Cycle and the Action-Regulation Theory as foundation. We will show how the integration of these behavioural theories can be used to devise support tools for better shaping demand side behaviour towards meeting supply side constraints.
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BEHAVE 2016
4th European Conference on Behaviour and Energy Efficiency
Coimbra, 8-9 September 2016
TOWARDS UNDERSTANDING HOW REDEFINING SUPPLY SIDE
CONSTRAINS COULD SHAPE INDIVIDUAL DEMAND SIDE
BEHAVIOUR
Julia Blanke*, Christian Beder and Martin Klepal
Nimbus Centre
Cork Institute of Technology
Bishopstown, Cork
Ireland
e-mail: Julia.Blanke@cit.ie
Keywords: holistic cycle of behaviour, demand side behaviour, supply side constraints
Abstract
The impact of behavioural aspects on environmental solutions has received more and
more recognition over the last couple of years. There is a general change of thinking
away from purely technical approaches towards integrated and holistic concepts, which
take especially the end user into account.
Many studies have shown (e.g. [1][14] [16]) that technical improvements and innovations do
not necessarily cause the desired outcomes due to a lack of communication with the actual
end users of these technologies. Other studies, for instance on improvements of house
insolation or the use of LED bulbs, caused paradox behaviour, sometimes also called
“Jevon’s paradox” or “rebound effect”, where the technical improvements are eaten up by
the increasing demand they caused [6]. These are just a few examples to highlight the gap
between new developments in environmental sustainable technologies and the actual
behaviour towards these innovations from an end-user’s perspective.
The fundamental question therefore is: “How to influence people’s behaviour towards a more
pro-environmental outcome, also in the long-term?” This paper will not be about another
study, which proves incentives make people act in a more desired way, as long as the
incentive is given [1]. All the various aspects of human behaviour have been replicated in
several well executed studies [1], however none of these on their own were able to solve the
problem of motivating people to change their behaviour also in the long term. So instead of
reinventing the wheel over and over again, the idea presented in this paper is to use well
defined behavioural theories and their inventory tools, which have been well established in
psychology and the social sciences, and to integrate them into a holistic cycle of behaviour
using the High Performance Cycle and the Action-Regulation Theory as foundation. We
will show how the integration of these behavioural theories can be used to devise support
tools for better shaping demand side behaviour towards meeting supply side constraints.
Julia Blanke, Christian Beder and Martin Klepal
2
1. INTRODUCTION
Typical current energy systems assume a rather strict distinction between a consumer driven
demand side on one end and a matching supply side on the other end, with the primary
objective of always satisfying consumer demands. Although energy suppliers have always
modelled demand side behaviour to adapt their production accordingly, and certain incentive
schemes, like different tariffs, have always been in place to influence demand side behaviour
according to supply side constraints, modern communication technology enables a much more
granular and individualised approach. At the same time renewable energy sources are creating
much more unpredictable, sometimes even unintuitive, supply side constraints that would
require very specific targeted actions on the demand side, while at the same time the impact of
such demand side actions has become increasingly important due to improved insulation and
energy efficiency in general. Moreover, local generation and storage facilities have led to a
situation, where the classical consumer also takes part in the supply side, being now able to
provide this capability to the grid, effectively becoming what is called a prosumer these days.
To deal with this situation a couple of approaches have been taken: the easiest, but at the same
time least cost effective, is by maintaining sufficient overcapacity in both the grid as well as
energy production, in order to be able to always meet any possible consumer demand by
controlling production accordingly. In order to better utilise existing assets in this scenario,
modelling of consumer behaviour and other external factors, most prominently the weather,
has been a very common approach. However, supply side constraints are never communicated
to the consumer in this scenario, the energy grid is always completely transparent in this
regard. More flexible energy tariffs combined with real-time information provided to the
consumers have been proposed to overcome this issue, however smart-meters have so far not
shown the desired outcome in the long run [4].
The approach proposed in this paper aims at going one step further by not only modelling
demand behaviour as an external factor to the system, but by incorporating the individual
building occupant and his/her characteristics as an integral part of the system itself. By
developing an integrated behavioural theory we will show how demand side behaviour could
be shaped based on supply side constraints.
Starting point are the theories of Action-Regulation (ART) by Winfried Hacker [7] and
the High Performance Cycle (HPC) by Locke and Latham [9]. By integrating those two
theories into each other a holistic cycle of behaviour is obtained [3], comprising of the
basic aspects of human behaviour found in many other approaches (see Figure 1).
Through the fact that “basic aspects of human behaviour” might be based on the perspective
taken, the model tries to be sufficiently open, so that further suggestions can be taken into
account and tested within the model.
In this paper we will give a brief introduction to these concepts, but the main focus will be
on the “redefinition of task” aspect of these theories and we will show how it can be made
more specific using the Theory of Planed Behaviour (TPB) by Ajzen [2] together with
inventory tools like the environmental attitudes inventory [13] to design a probability
model focusing on the redefinition of task’s demands, norms and values and goal-setting
and anticipation aspects. Clustering individual’s responses then enables providing
Julia Blanke, Christian Beder and Martin Klepal
3
customised suggestions for the redefinition of task as well as goal-setting and -
anticipation. Based on the conjectures of ART and the HPC, more precise goals should
have a higher potential to be transformed into behaviour. We will show how this idea can
be applied to better shape demand side behaviour according to supply side constraints.
By focusing on the redefinition of task aspect (see Figure 1), we will show how it can be
supported by providing custom made suggestions based on both a supply side constraint
profile as well as our understanding of the individual prosumer’s attitudes and characteristics.
By clustering individual’s responses to the relevant inventories, we are able to react to
specific supply side constraints by customising end-user engagement and support tools
accordingly. This methodology allows to better shape demand side behaviour, thereby
moving from a purely demand-response driven approach towards a more integrated prosumer
centric approach of energy supply. Furthermore a rigorous behavioural model like the one
presented here could also lead to a better integration of demand behaviour into energy
modelling, ultimately allowing reducing the gap between predicted and actual energy
consumption.
2. THEORETICAL FOUNDATION
2.1. Introduction of the High Performance Cycle and the Action-Regulation Theory
To obtain a holistic model of behaviour the HPC serves as a foundation, which needs to be
adapted and augmented with further theories. The origin of the HPC lies in the goal-setting
theory [9] and in a nutshell goal-setting theory states that people who are trying for specific
goals perform better than people who should do their best [8] [9]. Furthermore, feedback and
goals together have a much better outcome than either one aspect alone [8].
The ART like the HPC was developed in the context of organisations and work performance
and therefor is focused on efficient and humanized work [7]. Still the basic concepts in both
theories are easy to translate into a more general behavioural model applicable to many
applications including energy efficiency.
Behaviour or activities in the ART can “…be described in terms of sequential phases and
hierarchical “levels” or modes of control. Roughly, three levels of conscious awareness of
processes and representations that simultaneously regulate…” behaviour “…can be
distinguished” [7] (see Figure 2). On top, the intellectual level is the highest level where
consciousness is required to orient on and redefine the task into a self-set goal. The second
level would be the knowledge-based level. It can be conscious and takes the surrounding
conditions and the available abilities into account to develop strategies and action schemes.
The third level is routine and sensomotoric based, which is mainly subconscious and includes
the actual execution. On all levels feedback-loops are found, which continuously report back
the level of progress towards the desired goal and eventually make adjustments on the level
required to achieve the task criteria. “The most important characteristic of action regulation is
that actions are controlled by goals that, from a cognitive perspective, can be seen as
anticipation of the results that one intends to achieve.” “These goals can be decomposed
into several partial goals that together constitute the main goal” [7].
Julia Blanke, Christian Beder and Martin Klepal
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Both theories, the ART as well as the HPC, have a humanistic background so that no
contradictions in this regards are expected (for a detailed discussion see [3]).
The integration of the two theories was the attempt to overcome each ones limitation and to
build a more holistic model of human behaviour. Following the statement of Ulich: Where
the Action-Regulation Theory has a motivational gap, the motivational theory (HPC) has a
regulation gap” [17].
We will present a short overview to describe how the two theories are supplementing each
other and can be integrated into a holistic cycle of behaviour [3] (see Figure 1).
Figure 1: The original integrated cycle of HPC and ART [3]
Both theories are starting with demands imposed on the individual, which in the energy
efficiency scenario we are tackling here translate into supply side constraints. However,
instead of going straight into action and perform, like it is done in the HPC, the important
aspect of “redefinition of the task” is added from the ART including the issue of norms and
values, which is found in both theories mentioning the influence of goal-setting [3][8]. This is
of particular importance in our scenario, so the aspect of redefinition of task” and “norms
and values will be discussed in detail after the brief description of the cycle.
After the redefinition of task, where the external demands are translated into personal
goals the goal-setting and anticipation takes place. Here the hierarchical-sequential
concept of the ART is strongly reflected, because sub-goals need to be defined and action
plans developed (see Figure 2). While the redefinition of task happens on the highest level,
goal-setting and anticipation is happening on the intermediate knowledge-based level,
followed by the aspect of performance/ action, which goes down to the sensomotoric level,
where the actual execution happens [7].
Julia Blanke, Christian Beder and Martin Klepal
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Figure 2: hierarchical sequential model of behaviour
The performance results” are then the actual achievement and the visible part of an action/
behaviour. While performance traditionally has been only measured from the outside at the
end of an action through the visible results, nowadays there are much more flexible
approaches via just-in-time analysis and feedback technologies. The new technology tries
continuously to sense and monitor end-user behaviour as well as the supply side constraints
and is capable of sending instant feedbacks to both sides to improve the interaction between
both of them. Performance results lead to external as well as internal feedback, which
influences the well-being and a level of contentment, which strongly influences the
motivation, which itself has a strong impact how someone deals with demands again,
finally closing the cycle [9][3].
Although motivation is a key aspect for human behaviour, it is beyond the scope of this paper,
and we intend to discuss key aspects like “motives”, “activation of motivation” and
“mediators”, which Locke at al. [10] defined via direction, effort, and persistence, in
subsequent works. Those three traits are often used to describe motivation and should be
discussed in that context. Mediators also include task specific strategies, but because this
aspect is already included via the moderators in the ability aspect, for the simplicity of the
behavioural model presented here we will not go into this detail here.
Finally, moderators are factors trying to explain how strong the effect between goals and
action is. The main aspects are: ability, commitment, feedback, expectancy and self-efficacy,
task complexity and situational factors [9]. While in the HPC moderators are connected to the
performance it could be reasonable to move them to a more central point in the model,
because those mentioned aspects reflect personal traits, which influence all aspects of the
cycle.
To summarise the above, behaviour always consists of two aspects: a cognitive non-visible
part and a performing - visible part. While the HPC is skipping the whole cognitive part, or
stays very unspecific about it, the ART can fill that gap with a well-defined and visualised
sub-model explained above. By tracking the end-user’s behaviour and his/hers interaction
Julia Blanke, Christian Beder and Martin Klepal
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with the implemented system, which has an underlying Bayesian probability model, the long
term goal is to be able to make conclusion about every single aspect mentioned above.
2.2. The Redefinition of the Task
In order to develop the behavioural model further and integrate other theories to supplement
missing or unclear parts, the focus of this paper will be the redefinition of task. As
mentioned before, other aspects, like motivation, are important for the applicability of the
model as well, but are beyond the scope of this paper and will be looked at in subsequent
work.
“Redefinition of the taskis a psychological concept, which focuses on the fact that different
people perceive and interpret identical tasks in different ways [7] [3]. The approach of
“redefinition” was developed by the Russian psychologist Sergei Rubinstein in 1914 [15] and
addresses the mental regulation of tasks. This “mental regulation of activity is mediated by the
object of that activity” [7] not necessarily directly but through the variety of peoples goals,
motives, knowledge, experience, norms, attitudes, and moderators. As a consequence
externally set tasks are subjectively interpreted and made into personal ones by taking under
reconsiderations personally available resources and the cognitive and emotional evaluation of
the task [7].
It is important not to confuse the “redefinition” with reflexion, because the redefinition is
based on the internalised norms and values without questioning those [3]. On the other hand
the redefinition of task is already an extension of the seeming passivity of taking over a task
within the HPC [3]. To overcome both, the non-reflective takeover as well as the seemingly
passive takeover of a task the Theory of Planned Behaviour will be discussed.
2.3. The Theory of Planned Behaviour
The TPB was proposed by Icek Ajzen [2] to improve the theory of reasoned action, which
was developed by Icek Ajzen and Martin Fishbein in 1975 [5]. The TPB is based on three
aspects, which are linking beliefs with behaviour: “behavioural beliefs”, “normative beliefs
and “control beliefs” (see Figure 3).
Behavioural beliefs are defined as “beliefs about the likely outcomes of the behaviour and
the evaluations of these outcomes” [2]. Normative beliefs are defined as “beliefs about the
normative expectations of others and motivations to comply with these expectations” [2] and
control beliefs are defined as “beliefs about the presence of factors that may facilitate or
impede performance of the behaviour and the perceived power of these factors” [2].
“Behavioural beliefs produce a favourable or unfavourable attitude toward the behaviour;
normative beliefs “result in perceived social pressure or subjective norm and control beliefs
give rise to perceived behavioural control” [2]. “In combination, attitude toward the
behaviour, subjective norm, and perception of behavioural control lead to the formation of a
behavioural intention” [2]. That leads to the assumption that “…the more favourable the
attitude and subjective norm, and the greater the perceived control, the stronger should be the
person’s intention to perform the behaviour in question” [2].
Julia Blanke, Christian Beder and Martin Klepal
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Figure 3: The theory of planned behaviour [2]
The TPB like the HPC shows a gap in the cognitive development of goals and action plans.
This is why the integration of the TPB into the holistic cycle of behaviour would give us the
opportunity to overcome this issue.
2.4. Integration of the Theory of Planned Behaviour as an approach to fill the gap
As mentioned above the ART is missing sufficient reflexion for redefining a task, while
norms and values are acquired as an active process during socialisation, they are never
questioned again [3]. The ART asserts that in the HPC values are actively acquisitioned
through experience. Locke & Henne [8] state that values can be conscious or subconscious,
hence values might become focus of reflection but no further details are given in this regard
and their model’s explanation gives the impression that demands are taken over without
questioning.
By adding the TPB to the norms and values box of the behavioural model (see Figure 4) it can
overcome the limiting aspects of being non-reflective from the ART and the latent passivity
from the HPC. But to do so the aspects “intention” and “actual behavioural control” need to
be disconnected (see Error! Reference source not found.) and added in a different location
into the cycle. The reason to do so is due to the fact that there is no real goal planning or
action regulation involved in the TPB. All that is mentioned is a behaviour, which is more or
less favourable [2]. Hence, the “redefinition of task” and the “goal-setting and -anticipation”
are a supplement to the TPB making it much more practically applicable in our scenario.
Furthermore, a strong intention to act in a certain way can be an indicator that the person
finally does so, but an intention alone does not necessarily lead to the desired behaviour [12].
Especially in the area of sustainable behaviour this phenomenon is quite common and a big
issue to solve, because on the one hand people have good intentions to behave environmental
friendly, but on the other hand the observable behaviour is not matching the claimed
intentions. This is called attitude-action-gap or value-action-gap [11] [12], which we want to
overcome by our proposed approach.
Julia Blanke, Christian Beder and Martin Klepal
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Figure 4 Integration of the TPB into the holistic cycle of behaviour (Figure 1)
By redefining a demand, which is coming in from the supply-side constraints, different
suggestions are made to facilitate the intellectual process behind it according to the ART. The
selection of a sub-goal is strongly influenced by the aspects described in the TPB.
Furthermore, beside the individualised redefinition there is a more general aspect, which
applies to all human beings and that is the tendency of “cognitive economy” [7]. This trait is
reflected in the aspect of “perceived behavioural control” described in the TPB. It would not
be wise to choose a goal, which is not achievable. The suggestions made should support the
likelihood to choose an attainable goal, to reduce possible failures, which could have a
negative impact on the motivation and further involvements of the prosumer. The suggestions
made should also give the prosumer the opportunity to visualise the desired behaviour and get
support to develop easy consecutive action plans to execute the behaviour. The visualisation
of action plans is essential to increase the intention to perform the behaviour in question. For
that reason the redefinition of task and selection of a suggested goal should be followed by
proposing different action plans in the subsequent step of goal-setting and anticipation.
Those proposed action plans should present a variety of ways, how to achieve the chosen
goal. Many theories seem to ignore this crucial aspect, although it is well-known that good
intentions (“I will conserve energy!”) will not necessarily lead to a change in behaviour. Very
specific action plans need to be developed and remembered to increase the probability to
show the behaviour in question. Especially if new behaviour needs to be learned, this in the
beginning can take a lot of cognitive capacity and is easily interrupted (see Figure 2).
Therefore facilitating new behaviour not just clear goals are mandatory [8] [9], but also a very
clear specification of the way how to get there [7] [3] as otherwise set goals are more likely to
be abandoned as predicted by the ART.
Two more aspects need to be discussed, where to place them in the integrated model: “actual
behavioural control” and “intention.” “Actual behavioural control” can be filled into the
Julia Blanke, Christian Beder and Martin Klepal
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feedback loops described in the ART, which take place on all levels and continuously report
back the level of progress towards the desired goal and eventually make adjustments on the
level required to achieve the task criteria.
Next “Intention” needs to be fitted in. “Behavioural intention is defined here as the intention
or the subjective probability of a person to perform various behaviours/ the behaviour in
question in respect to a given object [5]. In the behavioural model depicted here there are
different points where these subjective probabilities come in (see Figure 4). The first is between
the TPB block as a whole and the redefinition of task aspect. By taking “behavioural
beliefs”, “normative beliefs” and “control beliefs” into account a subjective probability/
intention is created to choose a specific suggested goal or build one on their own. Knowing
the strength of intention between the TPB and the redefinition of task it is possible to predict
the subjective probability between redefinition of task and performance as a whole using
information from previous studies or calibrating the system accordingly. The next step would
be to see, if the specification of action plans in the goal-setting and anticipation would
increase this subjective probability between the aforementioned aspect and the performance
compared to the subjective probability between the redefinition and the performance, skipping
the goal-setting and -anticipation aspect in between.
3. APPLICATION TO ENERGY EFFICIENCY BEHAVIOUR
How does the integrated theory outlined in the previous sections help an energy application?
The first contribution is the identification of relevant parameters and their mutual interaction.
It highlights the necessity to measure these parameters and act accordingly on an individual
basis, which can be achieved by dedicated communication channels to each individual
stakeholder in the system down to the prosumer level enabled by modern digital interaction
devices.
Focusing on the aspect of redifinition of task outlined above this means that adequate support
tools need to be made available, which allow the prosumer to create actionable plans for
meeting supply side constraints. In order for this to work, these support tools need to take all
the individual parameters into account, as stressed by the theories described above.
This is the key differenciator between our approach and more ad-hoc smartphone or
smartmeter based incentive schemes. Key to this approach is the ability to measure pre-cursor
variables and generate individualised support actions accordingly. This way the overall
energy performance optimiser can make more optimal use of the prosumer’s abilities to
perform actions outside of the more direct classical control mechanisms and can integrate
those into the overall control strategies, ultimately resulting in more optimal, and hence more
energy efficient operation of the overall system.
We will illustrate the above giving an example on how to optimise a district heating system
using individualised prosumer engagement. In a typical scenario heat is provided by the
district heating operator to each building through a number of substations and then used by
individual building occupants to heat up individual rooms or water storage tanks by manually
controling thermostats or radiator valves for each room. Although consumers are usually
economically incentivised to optimise this setup based on their individual needs, this rarely
Julia Blanke, Christian Beder and Martin Klepal
10
results in an optimal configuration [4].
Phrasing the above scenario in terms of the behavioral theories, supply side constraints
amount to the requirement for individual building occupants to adapt their heating behaviour
according to overall system goals, i.e. individuals are either required to increase or decrease
their heating requirements or adapt their schedules accordingly to facilitate optimal overall
use of available resources. Note, that this is more complicated than a simple requirement for
mere energy saving. Not only is peak energy supply management becoming more of an issue,
also improved heat efficiency due to better insolation has led to a situation, where behavioural
aspects become more and more important when managing heat supply and demand. However,
managing behaviour is more invovled than merely sending out control commands, unlike a
directly controllable system we are dealing with individual occupants and their energy
behaviour, which we intend to shape to meet our optimisation goals. However, we cannot
assume that everybody is always willing to fully cooperate with this, even if incentives are
given.
To do this effectivly, we propose to apply the behavioural theories developped above and start
by looking at the redifinition of task aspect, which amount to designing adequate support
tools for the management of prosumer behaviour with the ultimate goal of optimising the
overall districtg heating system. The most relevant parameters affecting the redifinition of
task have been identified to be: Supply side constraints, behavioural beliefs, normative
beliefs, control beliefs, motivation, and moderators (ability, commitment, feedback,
expectancy, self-efficacy, task complexity and situational factors).
In the context of energy efficiency behaviour the three belief parameters can for instance be
measured using well-developped inventories like for instane the Environmental Attitude
Inventory [13]. As outlined above, all these are then aggregated into a level of individual
intention to perform actions as required by the given supply side constraints. This insight can
be used to calibrate the system by finding clusters in the data collected prior to the operational
stage of the system. The three other aspects supply side constraints, motivation, as well as the
moderators are (at least partially) measureable from the actual system operation and the
individual user’s interaction with the system, resulting in correlations between the individual
parameters for each particular application. This can be used to learn the parameters of a
Bayesian network representing the mutual probabilistic relation between all variables
involved.
Using these pre-calibrated correlations in conjunction with actual measurements of the
interaction of the occupant with the heating system then enable assigning values to each of
these variables, even without going through the inventories all the time. This is important, as a
practical heating application cannot rely on continuous questinaires to be carried out on an
ongoing basis. However, it does not preclude the system operation from re-calibrating and
adapting its internal state based on occasional surveys.
The resulting calibrated Bayesian network is then able to make adequate suggestions to
individual occupants based on his or her individual characteristics, taking not only the supply
side constraints itself into account but also the other parameters descibed above. According to
the behaviour theory developped above, these suggestions are split into providing appropriate
goals followed by a choice of action plans, which increase the intention and thereby the
Julia Blanke, Christian Beder and Martin Klepal
11
probability of the desired control actions being taken by the occupant ultimately resulting in
better energy performance and predictability. The latter is the second major outcome from
applying the behavioural theories to energy efficiency application design.
The benefit of the approach outlined above is two-fold: first and foremost more appropriate
suggestions and support tools based on the individual's attitudes and personality can be
provided, which ensures better long term commitment of the participants. The second
advantage is that the district heating optimiser can select the most appropriate individuals to
perform certain control tasks, and by taking the individual’s behavioural parameters into
account has a higher probability of this action being taken ultimately resulting in more
efficient and more predictable system operation.
4. CONCLUSION
We presented a holistic model of behaviour integrating the three theories HPC, ART, and
TPB into a unified circle of behaviour and discussed how they complement each other’s
shortcomings focusing on the redefinition of task aspect. We also discussed how this type of
model can be applied to energy efficiency applications, showing how demand side behaviour
can be shaped based on supply side constraints. Two conclusion can be drawn from the
behavioural model at this stage: first we identified key parameters governing the redefinition
of supply side constraints into individual tasks, which can be taken into account when
modelling the energy system leading to more optimal operation and improved predictability.
The second conclusion is that every occupant support system should not only focus on
supporting intentions, but has to also provide very specific and individualised action plans in
order to be effective.
By enabling the energy model to take both the supply side constraints as well as the demand
side behaviour into account, and by enabling a two-way communication between energy
supplier and prosumer behaviour, a more optimal operation can be facilitated that can make
use of all available assets both on the supply as well as on the demand side. This means that
by incorporating end-users as active participants into the overall system, more efficient as
well as more predictable energy consumption, production, and distribution scheduling could
be achieved.
The applicability of the proposed approach hinges on the participation of end-users and
requires a ceratin level of mind-shift away from a pure consumer attitute towards a more
active prosumer role. While long term motivation is covered by the presented model,
consumers need to be convinced initially to take part. Therefore information, transparency,
and incentives need to be part of any deployment if we intend to build commitment and trust
on the consumer side.
The behavioural model presented above is not final; to be fully applicable there are still some
important building blocks missing. As we pointed out above, in particular the aspect of
motivation is still vague and we intend to supplement it with other more specific approaches,
like for instance self-determination theory, in the future and continously improve the
predictability of demand behaviour.
Julia Blanke, Christian Beder and Martin Klepal
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Acknowlegement
This work has received funding from the European Union’s Seventh Framework Programme
under Grant Agreement no. 608981 and the European Union’s Horizon 2020 Research and
Innovation programme under Grant Agreements no. 680517 and 696009.
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... The approach proposed in this paper aims at going one step further by presenting a behavioural model that allows not only modelling demand behaviour as an external factor to the system, but to incorporate the individual building occupant and his/her characteristics as an integral part into the system itself. By further developing the integrated behavioural theory presented in Blanke et al. [3] we will show how demand-side behaviour could be evaluated and influenced based on supply-side constraints to achieve better overall energy efficiency. Particular focus will be put on incorporating motivational factors into the proposed model. ...
... The starting point of this approach are the fused theories of action regulation (ART) by Hacker [4], the high-performance cycle (HPC) by Locke and Latham [5], the theory of planned behaviour (TPB) by Ajzen [6], as well as the social cognitive theory (SCT) by Bandura [7]. Integrating those theories into each other a holistic cycle of behaviour is obtained [3], comprising of the basic aspects of human behaviour found in many other approaches. Through the fact that the "basic aspects of human behaviour" might be based on the perspective taken, the model tries to be sufficiently open, so that further suggestions can be taken into account and tested within the model. ...
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Action Regulation Theory is not only a description tool but also a normative guide to efficient and humanized work; it became a foundation of international standards in work design. The regular mode of action regulation is knowledge-based regulation. Innovation in mental work, e.g., product development, follows a hydrid model of action regulation combining knowledge-driven opportunistic sequences with systematically planned episodes of work. Innovative work can be improved by facilitating an interaction of mental and psychomotor operations in action: Thinking in and by action is a general principle of innovative mental work. Action Regulation Theory might explain why, in product development, a hybrid type of cooperative work is more effective than both, group work or individual work.
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