Synergies and conflicts on the Synergies and conflicts on the landscape of domestic energy landscape of domestic energy consumption: beyond metaphor consumption: beyond metaphor Alternate title Alternate title “What the heck is a What the heck is a “ ‘Bayesian Belief Network Bayesian Belief Network’ ’? ?” ” ‘ David Shipworth David Shipworth University of Reading University of Reading
Overview Overview Paper contains three interrelated elements: Paper contains three interrelated elements: Theoretical: Theoretical: 1. 1. Operationalising the concept of the concept of ‘ ‘barriers barriers’ ’ Operationalising through linking ‘ ‘socio socio- -technical landscapes technical landscapes’ ’ to to through linking complex systems theory and BBNs BBNs. . complex systems theory and Methodological: Methodological: 2. 2. Why Bayesian Belief Networks may be useful Why Bayesian Belief Networks may be useful for modelling home energy use. for modelling home energy use. Method: Method: 3. 3. How to construct a Bayesian Belief Network How to construct a Bayesian Belief Network
Context Context � UK UK ‘ ‘Carbon Vision Carbon Vision – – Buildings Buildings’ ’ [2005 [2005- -2008] 2008] � � £ £5M from Carbon Trust; EPSRC; ESRC 5M from Carbon Trust; EPSRC; ESRC � � Three Consortia: Three Consortia: � � BMT BMT ‘ ‘Building Market Transformation Building Market Transformation’ ’ ~£ £1M 1M ~ � � TARBASE TARBASE ‘ ‘Transforming the Asset Base Transforming the Asset Base’ ’ ~ ~£ £1M 1M � � CaRB: CaRB: ‘ ‘Carbon Reduction in Buildings Carbon Reduction in Buildings’ ’ ~ £ £3M 3M ~ � CaRB: Non- -domestic; domestic; � CaRB: Non � CaRB: Longitudinal � CaRB: Longitudinal � CaRB: Community � CaRB: Community � CaRB: Socio- -Technical (~ Technical (~£ £0.8M) 0.8M) � CaRB: Socio � � University of Reading & University of Newcastle University of Reading & University of Newcastle �
Research Question Research Question � Same house + differing occupants = Same house + differing occupants = � radically differing energy use. Why? radically differing energy use. Why? Energy Use
Differing perspectives, Differing perspectives, epistemologies and data- -types types epistemologies and data � Perspectives Perspectives � � Architectural (Passive solar design Architectural (Passive solar design… …) ) � � Engineering (Envelope & services Engineering (Envelope & services… …) ) � � Economic (Rational action model Economic (Rational action model… …) ) � � Psychological (Attitude Psychological (Attitude- -Behaviour Behaviour… …) ) � � Sociological (Context & contingency Sociological (Context & contingency… …) ) � � Epistemologies Epistemologies � � From na From naï ïve realism to utility maximisation to social ve realism to utility maximisation to social � constructivism constructivism � Need Need ‘ ‘common ground common ground’ ’/ /‘ ‘common language common language’ ’ � � Data types Data types � � qualitative, quantitative, discrete, continuous qualitative, quantitative, discrete, continuous �
Complex interrelated factors Complex interrelated factors � Household size; Income; Floor area; Household size; Income; Floor area; � � Income; Education level; Gender Income; Education level; Gender � � Environmental Environmental ‘ ‘attitudes attitudes’ ’; Energy practices ; Energy practices � � Market segmentation differences Market segmentation differences � � Energy Energy ‘ ‘visibility visibility’ ’; Specific knowledge ; Specific knowledge � � Grandmother Grandmother’ ’s shoe size? s shoe size? �
Mediating & Conditioning variables Mediating & Conditioning variables � Education Education is + is +ve ve correlated with correlated with income income. . � � Income Income is + is +ve ve correlated with correlated with product ownership product ownership � (mediating variable) (mediating variable) � Product ownership Product ownership is + is +ve ve correlated with correlated with Home Home � energy use energy use � Education Education is + is +ve ve correlated with correlated with Environmental Environmental � awareness awareness � Awareness Awareness is is – –ve ve correlated with correlated with energy use energy use in in � some market segments market segments (conditioning variable) (conditioning variable) some
Representation (‘ ‘Netica Netica’ ’) ) Representation ( +ve +ve +ve -ve but strength conditional on MS +ve
Bayesian Belief Networks Bayesian Belief Networks � Integration of qualitative and quantitative data from Integration of qualitative and quantitative data from � experts, case studies, data- -sets and models; sets and models; experts, case studies, data � Integrate of new data as it becomes available; Integrate of new data as it becomes available; � � Use of categorical and continuous variables; Use of categorical and continuous variables; � � Highlight conflicts or synergies between variables. Highlight conflicts or synergies between variables. � � Intuitive display of relationships between variables; Intuitive display of relationships between variables; � � Straightforward sensitivity testing. Straightforward sensitivity testing. � � ‘ ‘Subjective probability Subjective probability’ ’ provides common epistemological provides common epistemological � ‘common ground common ground’ ’ between social and engineering between social and engineering ‘ approaches approaches � Create consensus based decision support systems; Create consensus based decision support systems; �
Network Construction: Phase 1 Network Construction: Phase 1 A Realist Review of the literature A Realist Review of the literature � � Stakeholder engaged Stakeholder engaged � � Stresses context and contingency Stresses context and contingency � � Tests ‘ ‘theories theories’ ’ against the evidence base against the evidence base � Tests � Data extraction templates tailored to BBN. Data extraction templates tailored to BBN. � � Focus on factors influencing home energy Focus on factors influencing home energy � � use, their strength, direction and evidence use, their strength, direction and evidence base base
Network Construction: Phase 2 Network Construction: Phase 2 Sensitivity analysis : Which variables are key? : Which variables are key? Sensitivity analysis 1. 1. Uncertainty analysis : Does the network as a : Does the network as a Uncertainty analysis 2. 2. whole remain within expected bounds. whole remain within expected bounds. Pruning : Delete insensitive variables and links. : Delete insensitive variables and links. Pruning 3. 3. Refining : Additional quantitative analysis to : Additional quantitative analysis to Refining 4. 4. reassess key probabilities. reassess key probabilities. Extending : : Extending 5. 5. Primary qualitative research to extend the network � Primary qualitative research to extend the network � and refine contingencies and refine contingencies Primary quantitative research is conducted to � Primary quantitative research is conducted to � populate new nodes with probability data. populate new nodes with probability data. Go to step 1(repeat ‘ ‘till money or time runs out!) till money or time runs out!) Go to step 1(repeat 6. 6.
Representation Representation +ve ‘Frustrated’ pathways +ve (takeback) +ve -ve but strength conditional on MS +ve
Fitness landscape Fitness landscape http://www.talkorigins.org/design/faqs/nfl/sm.jpg www.talkorigins.org/design/faqs/nfl/sm.jpg http://
Socio- -technical landscape technical landscape Socio (Sahal Sahal, 1985: p.79 cited in , 1985: p.79 cited in Geels Geels 2001) 2001) (
Conclusions Conclusions � Provides Provides policy focused decision support policy focused decision support � � Supports evidence based policy making Supports evidence based policy making � � Transdisciplinary research epistemology Transdisciplinary research epistemology � � K Knowledge synthesis nowledge synthesis consistent with Realist consistent with Realist � Review method Review method � Models Models ‘ ‘learn learn’ ’ through through continual integration of data continual integration of data � � Provides Provides ‘ ‘cross cross- -fertilisation fertilisation’ ’ between fields between fields � � Models specific Models specific ‘ ‘take take- -back back’ ’ effects effects � � Allows for identification of very specific Allows for identification of very specific ‘ ‘barriers barriers’ ’ � and programme interventions to rectify them. and programme interventions to rectify them.
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