Competitive Price-Matching Guarantees in an Uncertain Demand Environment
Notice bibliographique
Résumé
Price-matching-guarantees (PMGs) are offers by firms whereby they assure customers that they will match any lower price offered by the competition for an identical product. Extant economics/marketing literature assumes that a simple proof of the competitor’s lower price is sufficient to grant the price match. Under this form of PMG and deterministic customer demand, it has been shown that PMGs may actually lead to tacit collusion such that all retailers set their price and order levels like a monopolist (in a competitive setting). However, firms nowadays reserve the right to verify the availability of the product at the competitor location and decline to match the lower price if the product is not available there. This option brings stocking decisions of the firms, and hence demand uncertainty, into play. Our study focuses on these elements. We model two identical newsvendor retailers that offer PMGs in a stochastic, price-sensitive demand environment. The retailers compete by simultaneously selecting prices and stocking quantities. We present a comprehensive characterization of the equilibrium prices and stocking levels for the case when the firms verify availability before matching the price, and the case when they do not. We also investigate how retail prices and order quantities are influenced by PMGs in an uncertain demand environment, as well as how uncertainty in demand affects structural properties related to “deterministic” PMGs. Our results demonstrate that the tacit collusion outcome of deterministic models extends to a stochastic demand environment if a simple proof is deemed sufficient for a price match. However, we also show that demand uncertainty enables the retailer to price discriminate by verifying the availability of the product at competing stores before granting any price-match request. In such a case, one firm increases its price and quantity even beyond monopoly levels. By comparing the equilibria, we identify product/market characteristics under which verifying the availability is desirable to the retailers. We find that the opportunity cost of not verifying the availability increases with the uncertainty in the market. From a managerial perspective, our results indicate that verifying availability can be a significant profit-enhancing mechanism and show how the benefits vary with the product/market characteristics. We find that verifying the availability is most profitable for highly anticipated, relatively more costly, innovative products which face relatively more uncertain demand. Geographical proximity between competing retailers is another factor that makes price discrimination and verification of availability a valuable retail pricing strategy.
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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 | 0,001 | 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 | 0,001 |
| 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 ».