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Enregistrement W4388230372 · doi:10.15396/eres2023_97

Analysis of the portrait of sustainable building management practices used in 2022 by the public sector property asset managers in Quebec

2023· article· en· W4388230372 sur OpenAlexaboutno aff
Andrée De Serres, Hélène Sicotte, Cynthia Aubert

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueSustainable Building Design and Assessment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésReal estateProperty managementBusinessSustainable developmentAsset (computer security)Corporate social responsibilityPublic sectorAsset managementOperationalizationPrivate sectorEnvironmental resource managementEnvironmental planningFinanceEconomicsEconomic growthEconomyPublic relationsPolitical science

Résumé

récupéré en direct d'OpenAlex

Sustainable development, the fight against climate change and the protection of biodiversity have become essential considerations in all the different business sectors. They particularly affect the construction and real estate sectors, which contribute to nearly 38% of all global carbon dioxide emissions (UNEP, 2023). Sustainable development has been transposed to real estate by the concept of sustainable or green building. Property asset managers must therefore adopt effective practices to comply with good sustainable building practices and to manage the social, economic, and environmental impacts generated by their buildings. Green building literature provides a clear framework on the range of practices, indicators, measures, and methods to assess the sustainable performance of a building (Nilashi et al. 2015; Zhao et al., 2019). However, scientific literature makes few distinctions between private and public sector buildings (Baird et al., 2022). The purpose of this research is to paint a portrait of the practices used in 2022 by public sector property asset managers in Quebec, who are essential stakeholders to be mobilized to succeed in the transition to more sustainable buildings. They are indeed major owners of real estate portfolios, and they are called upon to demonstrate the State’s exemplarity. Some 88 public sector property asset managers responded to a survey of 188 questions distributed in Quebec between December 2021 and March 2022 relating to: (1) the description of their organization and their real estate portfolio; (2) the practices operationalized by their organization in property management; (3) the practices to manage environmental impacts and (4) the practices to manage social impacts. The analysis of the responses to the survey shows that respondents consider themselves effective in terms of managing internal risks relating to their buildings without, however, concretely considering the impacts they generate on external stakeholders. Waste, water, and greenhouse gas (GHG) emissions management practices are given more priority than energy management practices. This is explained by the low cost of hydroelectricity in Quebec. These environmental impact management practices are, however, supplanted by the interest in practices for managing the health, safety, comfort, and well-being of internal building stakeholders, which can be explained by the consequences resulting from the COVID-19 crisis. To perform better, respondents point out that they would need training in sustainable building management and budgetary resources, particularly for the maintenance and upkeep of their assets. The sustainable development objectives pursued by the organizations of the respondents still need to be integrated into the contracts with the various suppliers. Finally, the fight against climate change and the development of resilience to natural disasters are not or hardly integrated into the management of their operations. This research could be replicated in different parts of the world to compare these practices with those used in Quebec. It could also be taken up in Quebec to analyze the evolution in time of sustainable institutional building management practices.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,173
Score d'incertitude au seuil0,993

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,006
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,258
Écart entre enseignants0,241 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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