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Enregistrement W3168668401 · doi:10.55016/ojs/sppp.v14i1.72317

Why Existing Regulatory Frameworks Fail in the Short-term Rental Market: Exploring the Role of Regulatory Fractures

2021· article· en· W3168668401 sur OpenAlexafffund
Lindsay M. Tedds, Anna Cameron, Mukesh Khanal, Daria Crisan

Notice bibliographique

RevueThe School of Public Policy Publications · 2021
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueBanking stability, regulation, efficiency
Établissements canadiensUniversity of Calgary
Organismes subventionnairesReal Estate Foundation of British ColumbiaAlberta Real Estate Foundation
Mots-clésTerm (time)RentingBusinessRisk analysis (engineering)Engineering

Résumé

récupéré en direct d'OpenAlex

With historical roots in the once-common practices of lodging and boarding, short-term rentals (STRs) have become in recent years a prominent feature of the global travel accommodation space. Worth roughly US$40 billion in 2010, the global value of the STR market reached US$115 billion in 2019. Despite a significant hit on business as a result of the COVID-19 pandemic, the STR market is showing strong signs of rebounding. The increased popularity and accessibility of the STR market can be largely attributed to the emergence of digital sharing economy platforms, such as Airbnb and Vrbo, which play the role of mediator in simplifying interactions and transactions between hosts and guests from around the world. As this platform-facilitated STR market has grown, home sharing has garnered increasing attention. Many have celebrated such innovation in the hospitality sector for the benefits it has delivered, among them lower prices, increased consumer choice, local economic development, community revitalisation, and a reliable income stream for property owners. However, others have been quick to decry the practice, accusing STR platforms of engaging in anti-competitive behaviour, exacerbating issues of over-tourism and a lack of affordable housing, and undermining the habitability of communities. Of notable concern among many STR skeptics is a potential shift in practice away from individual hosts renting a primary residence or space therein, and towards commercialization, whereby corporate entities are buying up what were once residential properties to list in the more lucrative STR market. The above picture of costs and benefits points to a market that is rife with tensions. Naturally, this reality has produced calls for regulation and government involvement, and in some cases, has even fuelled campaigns for all-out ban of the practice.As governments have stepped into the regulatory fold, however, they have faced significant challenges. This is because STR activity, different in composition and dynamics from that which plays out in traditional markets, pushes conventional policy boundaries, undermining in some cases the effectiveness of standard legal, regulatory, planning, and governance processes. Regulatory struggles can be attributed to three key factors. First, most conceptions of home sharing employed in the regulatory space treat the STR market as conventional and thus two-sided; that is, as encompassing interactions between those supplying the service (hosts) and those accessing it (guests). Such understandings fail to capture the involvement of additional players—digital STR platforms, most notably, but more recently professional property managers as well— not to mention the nature, extent, and implications of their involvement. Importantly, STR platforms are more than passive facilitators of market activity, and not only influence the contours and dynamics of the market, but also actively shape the regulatory space. Second, attempts to regulate home sharing have been hampered by the widespread tendency, within both policy and academic circles, to treat the market as a monolith. Yet, an assessment of drivers of participation and dynamics among guests, hosts, and platforms makes manifest the complexity of the STR market and the diversity of activity that plays out within it. Notably, STR hosting spans a spectrum of activity, from low- or no-fee home sharing in the spirit of collaborative consumption, to renting a suite in a primary residence, to the commercial multi-hosting referenced above. Drivers of guest participation in the market are similarly diverse. Far from passive, platform involvement is shaped by the desire to create and benefit from network effects, and thus spans partnership development, bridging to distinct but related markets, and even the pursuit of socially minded or philanthropic endeavours. The above diversity suggests that one-size-fits-all approaches to management are destined to fail. Third, governments and policymakers have relied on traditional regulatory concepts and parlance, such as the notion of regulatory violation, to characterize various forms of STR market activity. However, in the case of platform-mediated home sharing, the concept of regulatory fractures—instances in which new modes of activity do not map well onto existing frameworks, thus disrupting regulatory effectiveness—is more apt. The conceptual frame of regulatory fractures enables one to uncover the tensions and complications that are produced when novel activity arises within the context of longstanding institutions and processes, and underscores the extent to which reimagined regulatory and policy approaches, tailored to the unique features of the STR market, are vital. Further, if not addressed, regulatory fractures will not only undercut the intent and effectiveness of regulation but will also curtail the potential benefits of home sharing activity. Going forward, successful management of the STR market will hinge on the ability of policymakers to confront the factors currently hindering the effectiveness of policy and regulatory approaches, namely an under-developed understanding of the STR market and its dynamics, and a continued use of tools ill-suited to novel economic activity. Fortunately, governments ready to innovate in the regulatory space and reimagine management strategies will learn that a number of less conventional approaches show promise. Among such emerging approaches is co-regulation, a tactic employed with success throughout the European Union in particular. Given their prominent role in the market, as well as their desire to influence regulation to maintain network dominance, platforms could make willing and effective partners in co-regulation, just as some other industries are entrusted with a degree of self-regulation. Though it would require the development of a robust framework to ensure effectiveness, co-regulation could help governments to overcome existing issues, such as those related to compliance and enforcement, while also enabling access to more comprehensive data, without which tailored policy and regulatory solutions are significantly hampered.

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)0,045
score de la tête « metaresearch » (Gemma)0,081
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,237

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0450,081
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,003
Études des sciences et des technologies0,0140,050
Communication savante0,0320,031
Science ouverte0,0060,009
Intégrité de la recherche0,0180,017
Charge utile insuffisante (le modèle a refusé de juger)0,0210,003

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 Opus0,054
Tête enseignante GPT0,283
Écart entre enseignants0,229 · 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'étudeQualitatif
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

Citations2
Publié2021
Routes d'admission2
Résumé présentoui

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