基于在線購買歷史聚合的B2C電子商務差異化折扣模型
發(fā)布時間:2019-01-14 12:40
【摘要】:眾多B2C網(wǎng)站已建立起會員等級制度,并據(jù)此向買家提供價格折扣。但會員等級制模型僅考慮買家交易金額,無法全面反映買家在線購買歷史(online purchase history),故不能準確提供差異化折扣。針對上述問題,提出了一種面向B2C電子商務的差異化折扣模型,該模型包含能體現(xiàn)買家在線購買歷史的交易、退單、推薦購買、曬單等四個指標,將買家在線購買歷史聚合為一個綜合值,進而通過min-max標準化方法進行線性轉(zhuǎn)換,將轉(zhuǎn)換后的聚合值與會員等級基準折扣結(jié)合得到最終的差異化折扣,從而使得B2C網(wǎng)站可向同級別會員實施更精準的一對一營銷和價格歧視策略。以京東商城為背景的仿真實驗結(jié)果證明了本文新模型的有效性。
[Abstract]:Many B-C websites have established a membership rating system and offer price discounts to buyers accordingly. However, the membership hierarchy model only considers the buyer's transaction amount, and can not fully reflect the buyer's online purchase history of (online purchase history), so it can not accurately provide differential discount. In order to solve the above problems, a differential discount model for B2C e-commerce is proposed. The model includes four indexes: transaction, repurchase, recommended purchase, and drying order, which can reflect the buyer's online purchase history. The buyer's online purchase history is aggregated into a comprehensive value, and then the linear conversion is carried out through the min-max standardization method. The final differential discount is obtained by combining the converted aggregate value with the membership grade benchmark discount. So that B2C website can implement more accurate one-to-one marketing and price discrimination strategy to members at the same level. The simulation results based on JingDong Mall show the validity of the new model.
【作者單位】: 四川師范大學計算機科學學院;匹茲堡大學Katz商學院;四川師范大學圖書與檔案信息中心;
【基金】:國家自然科學基金項目(71202165) 四川省哲學社會科學規(guī)劃項目(SC13C019)
【分類號】:F724.6
[Abstract]:Many B-C websites have established a membership rating system and offer price discounts to buyers accordingly. However, the membership hierarchy model only considers the buyer's transaction amount, and can not fully reflect the buyer's online purchase history of (online purchase history), so it can not accurately provide differential discount. In order to solve the above problems, a differential discount model for B2C e-commerce is proposed. The model includes four indexes: transaction, repurchase, recommended purchase, and drying order, which can reflect the buyer's online purchase history. The buyer's online purchase history is aggregated into a comprehensive value, and then the linear conversion is carried out through the min-max standardization method. The final differential discount is obtained by combining the converted aggregate value with the membership grade benchmark discount. So that B2C website can implement more accurate one-to-one marketing and price discrimination strategy to members at the same level. The simulation results based on JingDong Mall show the validity of the new model.
【作者單位】: 四川師范大學計算機科學學院;匹茲堡大學Katz商學院;四川師范大學圖書與檔案信息中心;
【基金】:國家自然科學基金項目(71202165) 四川省哲學社會科學規(guī)劃項目(SC13C019)
【分類號】:F724.6
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4 潘t,
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