Abstract:In recent years, the market economy has been booming, and the demand of consumers has begun to become diversified. Consumers’ preferences for products, the sensitivity of product prices, and other factors can often affect the market demand and also make enterprises realize the importance of consumer preferences. The decision-making model of the supply chain with consumer preference composed of a retailer and a third-party presale platform is established, and we analyze the implementation of a single presale mo… Show more
“…Hasan et al [10] proposed a decision-making method for e-commerce retailers who sell deteriorating products under the presale system by studying the optimal price and replenishment cycle when customers purchase products and pay through an online system during the presale period. Cao et al [11] classified consumers based upon whether they were provided with information about presales and considered their preferences. They proposed four basic models and coordination models and compared the decisions of retailers and third-party platforms when considering the possible strategies adopted by supply chain members.…”
In this study, we investigate inventory allocation and pricing strategies for retailers by incorporating demand information into the issue of inventory allocation during the presale period. In a presale system, retailers offer presale goods at a price lower than the retail price. By offering products at a discount, retailers may attract additional demand. In addition, this system enables retailers to reduce the uncertainty of market demand and establish a strategy for inventory allocation based on the results of presales. A Bayesian approach was employed to analyze and update demand information, and inventory allocation was formulated as a newsvendor problem to determine the optimal policy that maximizes retailer profit. A numerical analysis was conducted to validate the effectiveness of the proposed strategy. Results suggest that the proposed strategies can support retailers by more accurately predicting demand and achieving higher profits with less inventory. Furthermore, retailers can experience greater benefits from risk-averse customers than from risk-neutral customers.
“…Hasan et al [10] proposed a decision-making method for e-commerce retailers who sell deteriorating products under the presale system by studying the optimal price and replenishment cycle when customers purchase products and pay through an online system during the presale period. Cao et al [11] classified consumers based upon whether they were provided with information about presales and considered their preferences. They proposed four basic models and coordination models and compared the decisions of retailers and third-party platforms when considering the possible strategies adopted by supply chain members.…”
In this study, we investigate inventory allocation and pricing strategies for retailers by incorporating demand information into the issue of inventory allocation during the presale period. In a presale system, retailers offer presale goods at a price lower than the retail price. By offering products at a discount, retailers may attract additional demand. In addition, this system enables retailers to reduce the uncertainty of market demand and establish a strategy for inventory allocation based on the results of presales. A Bayesian approach was employed to analyze and update demand information, and inventory allocation was formulated as a newsvendor problem to determine the optimal policy that maximizes retailer profit. A numerical analysis was conducted to validate the effectiveness of the proposed strategy. Results suggest that the proposed strategies can support retailers by more accurately predicting demand and achieving higher profits with less inventory. Furthermore, retailers can experience greater benefits from risk-averse customers than from risk-neutral customers.
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