E-Commerce: Compared Efficiency of Major Retailers in Brazil and Canada
Notice bibliographique
Résumé
Retail e-commerce (B2C - business-to-customer) grows more in developing markets than in developed ones, however, most studies in the area were aimed at developed markets. This thesis aimed to compare the relative efficiency of publicly traded companies that operate in the retail of physical products online in a developed market (Canada) and another in development (Brazil), separately, and to discuss the practices of each market. To this end, a new instrumental approach was proposed, based on an integrated model of Data Envelopment Analysis (DEA) and Optimal Control Theory (OCT) to measure the efficiency of total inventory costs, based on the theory lean management, integrating the concept of capacity efficiency (i.e., management of physical assets). Also, the model directly incorporated inflation and, indirectly, the gross margin. The model was applied to public data from two sets of companies classified as Retail (Var) or Non-Durable Clothing and Consumer Goods (VBCnD) - one composed of 12 Canadian companies (CA) and another by 17 Brazilian companies (BR) -, during the period from 2016 to 2019. Then, a qualitative analysis of the B2C of the companies was made. The results showed that, in both countries, Var companies were more efficient than VBCnD. There are indications that BR companies were at a more advanced stage of the digital transition. In Brazil, Var companies prioritized sales by app and marketplace (own or third parties) and VBCnD companies, by app and virtual store. In Canada, Var companies have prioritized virtual stores and apps, while VBCnD, marketplaces (third parties), and apps. Although it is a common practice for BR Var companies, no observed CA company controls a marketplace. In Brazil, there was a strategy in which two companies operated in parallel, one specialized in B2C and the other in physical retail, though they were not more efficient than the market. The results pointed to BR companies Magazine Luiza, Arezzo, Estrela, and Via Varejo as market benchmarks, so their best practices should be studied.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».