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Enregistrement W3038091730 · doi:10.15320/iconarp.2020.107

Critical Aspects, Motivators and Barriers of Building-Integrated Vegetation

2020· article· en· W3038091730 sur OpenAlexaboutno aff
Monder M. Almuder, Özge Süzer

Notice bibliographique

RevueIconarp International J of Architecture and Planning · 2020
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueUrban Green Space and Health
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIncentiveCertificateBusinessArchitectureScale (ratio)Architectural engineeringEnvironmental resource managementEnvironmental economicsEnvironmental planningEngineeringComputer scienceGeographyEconomics

Résumé

récupéré en direct d'OpenAlex

PurposeGreen buildings which provide improved user health conditions and environmentally responsible applications have gained significant attention, due to the increasing environmental problems, particularly caused by the construction industry at the global scale. However, vegetation is still not sufficiently integrated into buildings, even though numerous benefits of plants have been proven by many studies in literature.This research aims to find out the opinions of professionals and academicians in architecture-related fields regarding the critical aspects, as well as the motivators and barriers faced in BIV applications, namely; green roofs, green walls and interior gardens. Hence, it strives to help increase their application rates by underlining the significant issues to be considered. Design/methodology/approachAs to fulfilling these objectives, a questionnaire survey was conducted on 120 participants with varying professions including architects, landscape designers and civil engineers, from four countries.FindingsThe results of this study pointed out that, healthcare buildings were given the first priority among the building types for applying BIV. Moreover, among the motivator factors, receiving a certificate was found as an important incentive, besides the environmental, social and economic benefits of BIV. Furthermore, although the highly rated barriers were found as ‘the lack of proper regulations’ and ‘lack of demand by the user/client’, the findings showed that the highest responsibility for the implementation of these applications was placed on the architect.Research Limitations/Implications Based on the five major groups of Köppen climate classification system, the case countries were selected as one from each of the four main types, and by neglecting only Polar, as it lacks settlements. By considering diverse levels of development and economic welfare, countries were selected as; Canada (Snow: Humid-Subarctic), Libya (Dry: Desert-arid), Malaysia (Tropical: Tropical-Rain forest) and Turkey (Mild temperate: Mediterranean).Since the study covered four different countries, the survey was conducted by the use of Google Forms software program. This tool enabled the production and distribution of questionnaires, as well as the collection of data based on the responses of the participants. Furthermore, in order to provide consistency among the questionnaires applied in different countries, the survey was conducted in English language, although it was not the native language for a majority of the participants.Moreover, based on studies claiming that participants are more inclined to select the option with the mid-value in a Likert scale, which implies a neutral position, in the questionnaire, these types of questions were constructed with the forced choice method, by keeping the scales with even number of options.Practical ImplicationsIt is expected that the results of this study would be beneficial to both the academicians and professionals involved in the green building industry, as well as to the governmental and/or green building authorities. It is expected that this study will help serve as a guide for the stakeholders to increase the application rates of BIV in the construction industry.Social ImplicationsThe results of this study were also evaluated based on the findings of four case countries and certain conclusions were derived as to their underlying socio-economic and geographical reasons.Originality/value - Although studies on similar subjects have appeared in the literature, there are none which solely focuses on BIV applications by conducting a survey on the mentioned four case countries and compares its findings with the literature and presents an in-depth analysis on the issue.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0000,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,012
Tête enseignante GPT0,262
Écart entre enseignants0,250 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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