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Enregistrement W3208915846 · doi:10.32920/ryerson.14645481.v1

Design Principles For Retail Return Policies

2021· preprint· en· W3208915846 sur OpenAlexaff
Konstantin Loutsenko

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineBusiness, Management and Accounting
ThématiqueSustainable Supply Chain Management
Établissements canadiensToronto Metropolitan University
Organismes subventionnairesnon disponible
Mots-clésProfitability indexOrder (exchange)Customer satisfactionProduct (mathematics)Process (computing)BusinessSupply chainMarketingIndustrial organizationComputer scienceFinance

Résumé

récupéré en direct d'OpenAlex

Based on an analysis of prior literature on consumer behaviour and reverse logistics, this study proposes a model for the design of returns policies that includes considerations for costs, logistics requirements, and consumer behaviour. The case study investigations yielded several important findings. Product characteristic concerns seem to have a low level of importance in the decision-making process of return policy establishment. Practitioners that are responsible for creating effective return policies seem to not place great importance on either product characteristics or supply chain optimization. Using case analysis, this study explored the decision-making process of return policy creation and found that customer satisfaction and organization-specific concerns have a high level of importance in the returns creation process. The results indicate that the current models and frameworks for return policies need to be re-examined, in order to reflect the practical realities of the environment and constraints in which organizations operate. A review of the literature suggests that retailers consider a product's return policy a source of competitive advantage that can increase customer satisfaction and overall profitability. However, the existing research into returns policies focuses mainly on optimizing product flows and minimizing the financial cost of returns, rather than examining the inter-relationships between multiple constructs such as customer satisfaction, product characteristics, logistic constraints and consumer behaviour. This is problematic because it creates a disconnect between the considerations that the practitioners take into account and the considerations that are included in the current models for returns policy establishment. For retail organizations, the returns process can have a significant impact on costs and customer satisfaction due to the unique logistics costs and customer interactions in the returns process. Based on an analysis of prior literature on consumer behaviour and reverse logistics, this study proposes a research framework for the design of returns policies for retailers that considers the impacts of a specific return policy on costs, logistics requirements, and consumer behaviour. The study uses the proposed framework to identify, highlight, and catalog the different influences and considerations that retail and manufacturing organizations face during the creation of a return policy in the retail environment. The case study investigations yielded several important findings. First, product characteristic concerns seem to have a low level of importance in the decision-making process of return policy establishment. The study finds that practitioners that are responsible for creating effective return policies do not place great importance on either product characteristics or supply chain optimization. Second, this study found that most of the current models on return policy creation do not include customer satisfaction and organizational concerns. Using case analysis, this study explored the decision-making process of return policy creation in three retail organizations and found that customer satisfaction and organization-specific concerns actually have a high level of importance in the returns creation process. By using current models on return policy establishment and using empirical results, this study proposes a tentative theory by outlining the propositions for the design of a returns policy in retail organizations. The results of this study are based on organizational data as well as interviews conducted with persons who are directly involved in the returns process for their organization. The results indicate that the current models and frameworks for return policies need to be re-examined, in order to reflect the practical realities of the environment and constraints in which organizations operate.

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)0,005
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,052

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,007
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,004
Communication savante0,0070,007
Science ouverte0,0020,003
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0150,004

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 Opus0,077
Tête enseignante GPT0,260
Écart entre enseignants0,183 · 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'étudeThéorique ou conceptuel
Domainenon disponible
GenreMéthodes

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
Publié2021
Routes d'admission1
Résumé présentoui

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