A cascading model for nudging employees towards energy-efficient behaviour in tertiary buildings

dc.contributor.authorKalamaras, Ilias
dc.contributor.authorSánchez Corcuera, Rubén
dc.contributor.authorCasado Mansilla, Diego
dc.contributor.authorTsolakis, Apostolos C.
dc.contributor.authorGómez Carmona, Oihane
dc.contributor.authorKrinidis, Stelios
dc.contributor.authorBorges Hernández, Cruz E.
dc.contributor.authorTzovaras, Dimitrios
dc.contributor.authorLópez de Ipiña González de Artaza, Diego
dc.date.accessioned2024-11-15T08:24:40Z
dc.date.available2024-11-15T08:24:40Z
dc.date.issued2024-05
dc.date.updated2024-11-15T08:24:40Z
dc.description.abstractEnergy-related occupant behaviour in the built environment is considered crucial when aiming towards Energy Efficiency (EE), especially given the notion that people are most often unaware and disengaged regarding the impacts of energy-consuming habits. In order to affect such energy-related behaviour, various approaches have been employed, being the most common the provision of recommendations towards more energy-efficient actions. In this work, the authors extend prior research findings in an effort to automatically identify the optimal Persuasion Strategy (PS), out of ten pre-selected by experts, tailored to a user (i.e., the context to trigger a message, allocate a task or providing cues to enact an action). This process aims to successfully influence the employees' decisions about EE in tertiary buildings. The framework presented in this study utilizes cultural traits and socio-economic information. It is based on one of the largest survey datasets on this subject, comprising responses from 743 users collected through an online survey in four countries across Europe (Spain, Greece, Austria and the UK). The resulting framework was designed as a cascade of sequential data-driven prediction models. The first step employs a particular case of matrix factorisation to rank the ten PP in terms of preference for each user, followed by a random forest regression model that uses these rankings as a filtering step to compute scores for each PP and conclude with the best selection for each user. An ex-post assessment of the individual steps and the combined ensemble revealed increased accuracy over baseline non-personalised methods. Furthermore, the analysis also sheds light on important user characteristics to take into account for future interventions related to EE and the most effective persuasion strategies to adopt based on user data. Discussion and implications of the reported results are provided in the text regarding the flourishing field of personalisation to motivate pro-environmental behaviour change in tertiary buildings.en
dc.description.sponsorshipMinistry of Economy, Industry and Competitiveness of Spain for IoP, under Grant No.: PID2020-119682RB-I00en
dc.identifier.citationKalamaras, I., Sánchez-Corcuera, R., Casado-Mansilla, D., Tsolakis, A. C., Gómez-Carmona, O., Krinidis, S., Borges, C. E., Tzovaras, D., & López-De-Ipiña, D. (2024). A cascading model for nudging employees towards energy-efficient behaviour in tertiary buildings. PLoS ONE, 19(5 May). https://doi.org/10.1371/JOURNAL.PONE.0303214
dc.identifier.doi10.1371/JOURNAL.PONE.0303214
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/20.500.14454/1886
dc.language.isoeng
dc.publisherPublic Library of Science
dc.rights© 2024 Kalamaras et al.
dc.titleA cascading model for nudging employees towards energy-efficient behaviour in tertiary buildingsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.issue5 May
oaire.citation.titlePLoS ONE
oaire.citation.volume19
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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