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Wal-Mart N'est Pas Une Banque

2016· article· fr· W2560479638 sur OpenAlexaboutno aff
Marco Pagani, Asbjørn Osland, Andrew Borchers

Notice bibliographique

RevueJournal of case studies · 2016
Typearticle
Languefr
DomaineEconomics, Econometrics and Finance
ThématiqueBanking stability, regulation, efficiency
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBusinessFinancial servicesMarketingValue propositionValue (mathematics)FinTechAdvertisingCommerceFinance
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Introduction Ceci n'est pas une pipe (i.e., this is not a pipe) (Magritte, 1928-29) was a playful painting that represented an image of a pipe. In like manner, Wal-Mart in the U.S. was not a bank. Nevertheless, it has offered U.S. customers a large array of financial services for more than a decade. Moreover, Wal-Mart owned commercial banks in Mexico and Canada (Wal-Mart, 2014). How did Wal-Mart start offering financial services? What have been the differences in the offering of financial services between the US and other North-American markets? How did these services help Wal-Mart meet its strategic objectives? Rather than taking the trouble to establish financial services in a piece-meal fashion, why not just invite established banks to open small branches in its stores? Financial services offered by Wal-Mart in the US market Historically, Wal-Mart focused on providing value to its customers through cost-cutting, innovation, technology and widespread geographical presence. The company always targeted a customer-centric approach and provided a friendly shopping experience. In fact, Wal-Mart stated (FORM 10-K Annual Report, 1 April 2015) that its value proposition was as follows: Wal-Mart ... helps people around the world save money and live better--anytime and anywhere--in retail stores or through our e-commerce and mobile capabilities. Through innovation, we are striving to create a customer-centric experience that seamlessly integrates digital and physical shopping.... Our strategy is to lead on price, invest to differentiate on access, be competitive on assortment and deliver a great experience. The presence of a large group of potential customers at the margins of the financial services industry was very appealing for many corporations aiming to increase the number of customers. According to the FDIC (2014, p. 3, Executive Summary): The existence of unbanked and underbanked households presents an opportunity for banks to expand access to their products and services and forge relationships with these underserved groups, ultimately increasing economic inclusion. Such economic inclusion was crucial for a company like Wal-Mart to attract new shoppers and create new sources of revenue. In the late 1990s, Wal-Mart started offering financial services in response to customer demand especially from customers who did not have access to traditional banking products (Manning, 2010). Many consumers, rejected by traditional depository institutions (commercial banks and credit unions) or who were unhappy with the high costs of checking accounts, started turning toward Wal-Mart for basic financial transactions. The unbanked and under-banked, who represented twenty-two percent of U.S. consumers (Gross, Hogarth & Schmeiser, 2012), were usually individuals with limited financial means who could not afford traditional banking products. However, some were well-paid individuals considered as credit risks, according to credit bureaus like ChexSystems, Inc., 2014. The unbanked had no traditional bank accounts and, according to the FDIC, the under-banked were those that had accounts but also used alternative financial services outside of the banking system (FDIC, 2014). Wal-Mart initially started offering check cashing and bill payments as ancillary customer services. Then, given the success of its initial foray into financial services, it opened in-store MoneyCenters where customers could benefit from a vast array of financial services like prepaid cards, debit cards, credit cards, and small business loans. Lately, Wal-Mart has strengthened its involvement in financial and banking services with the Wal-Mart2Wal-Mart funds transfer service (Berr, 2014) and the offering of a checking account in conjunction with Green Dot. The Wal-Mart2Wal-Mart money transfer service allowed clients to send or receive up to $900 at any US Wal-Mart store. …

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)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,691
Score d'incertitude au seuil0,848

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
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 Opus0,041
Tête enseignante GPT0,272
Écart entre enseignants0,231 · 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'étudeSans objet
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
Publié2016
Routes d'admission1
Résumé présentoui

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