有限期无理由退货条件下网络零售产品与运费的联合定价
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摘要
针对网络零售商提供有限期的无理由退货政策,研究产品与送货服务的分割定价和捆绑定价问题。参照网络交易规则,刻画消费者的购买效用盈余,构建需求函数,以商家的利润最大化为目标,确定产品价格和运费。证明了消费者可接受的运费相对产品价格的占比存在阈值,以及无理由退货时间期上界和下界值的存在性,并给出计算表达式。当消费者实际可接受的运费占比小于阈值,分割定价应将无理由退货期限设定在下界值附近;反之,可以延长无理由退货期限,抬高(降低)运费价格、降低(抬高)产品价格使支付总价维持不变。在产品属性、成本和送货服务质量等相同的情形下,分割定价相对捆绑定价是占优策略,在消费者可接受的范围内,提高运费同产品价格的占比虽然影响销量但能促进总利润增长。当运费占比足够小或趋于零,二者具有无差异性。
For no-reason return policy with a finite period provided by online retailers, this paper studies the partitioned pricing and bundled pricing issues of products and delivery services. Referring to online trading rules, the consumer's purchasing utility surplus is described, and the demand function is formulated. The profit of the online retailer is maximized to determine the price of products and shipping fees. It is proved that there is a threshold of the acceptable shipping fee ratio relative to product prices for consumers, the upper and lower bounds of the existence of the no-reason return period, as well as the calculation expressions are obtained. When the actual acceptable shipping fee ratio of the consumer is less than the threshold, the partitioned pricing should set the no-reason return period near the lower bound; otherwise, it is favorable that the extension of the no-reason return period, raising(lowering) the shipping fee and lowering(raising) the price of the product to keep the total price unchanged. If products attribute, cost and delivery service quality are same, partitioned pricing contrasting to bundled pricing is a dominant strategy. In the acceptable range of the shipping fee to consumers, increasing the proportion of shipping fee to product price, while affecting sales, can promote total profit growth. When the shipping fee ratio is small enough or tends to zero, there is no difference between partitioned pricing and bundled pricing.
For no-reason return policy with a finite period provided by online retailers, this paper studies the partitioned pricing and bundled pricing issues of products and delivery services. Referring to online trading rules, the consumer's purchasing utility surplus is described, and the demand function is formulated. The profit of the online retailer is maximized to determine the price of products and shipping fees. It is proved that there is a threshold of the acceptable shipping fee ratio relative to product prices for consumers, the upper and lower bounds of the existence of the no-reason return period, as well as the calculation expressions are obtained. When the actual acceptable shipping fee ratio of the consumer is less than the threshold, the partitioned pricing should set the no-reason return period near the lower bound; otherwise, it is favorable that the extension of the no-reason return period, raising(lowering) the shipping fee and lowering(raising) the price of the product to keep the total price unchanged. If products attribute, cost and delivery service quality are same, partitioned pricing contrasting to bundled pricing is a dominant strategy. In the acceptable range of the shipping fee to consumers, increasing the proportion of shipping fee to product price, while affecting sales, can promote total profit growth. When the shipping fee ratio is small enough or tends to zero, there is no difference between partitioned pricing and bundled pricing.
引文
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[2] Xia L,Monroe K B.Price partitioning on the internet[J].Journal of Interactive Marketing,2004,18(4):63～73.
[3] Kauffman R J,Lee D.Price rigidity on the internet:New evidence from the online bookselling industry[C]//International Conference on Information Systems,Washington,D.C.,2004:843～848.
[4] Schindler R M,Morrin M,Bechwati N N.Shipping charges and shipping-charge skepticism:Implications for direct marketers' pricing formats[J].Journal of Interactive Marketing,2005,19(1):41～53.
[5] Hossian T,Morgan J.Plus shipping and handling:Revenue equivalence in field experiment on eBay[J].Advances in Economic Analysis & Policy,2006,6(2):1～27.
[6] Kim H M.The Effect of salience on mental accounting:How integration versus segregation of payment influences purchase decisions[J].Journal of Behavioral Decision Making,2006,19(4):381～391.
[7] Burman B,Biswas A.Partitioned pricing:Can we always divide and prosper?[J].Journal of Retailing,2007,83(4):423～436.
[8] Leng M,Becerril-Arreola R.Joint pricing and contingent free shipping decisions in B2C transactions[J].Production and Operations Management,2010,19(4):390～405.
[9] Becerril-Arreola R,et al.Online retailers’ promotional pricing,free-shipping threshold,and inventory decisions:A simulation-based analysis[J].European Journal of Operational Research,2013,230(2):272～283.
[10] Yao Y,Zhang J.Pricing for shipping services of online retailers:Analytical and empirical approaches[J].Decision Support Systems,2012,53(2):368～380.
[11] Gümü? M,et al.Shipping fees or shipping free?A tale of two price partitioning strategies in online retailing[J].Production & Operations Management,2013,22(4):758～776.
[12] Jiang Y,Shang J,Liu Y.Optimizing shipping-fee schedules to maximize e-tailer profits[J].International Journal of Production Economics,2013,146(2):634～645.
[13] Lei Y,Jasin S,Sinha A.Dynamic joint pricing and order fulfillment for e-commerce retailers[J].Manufacturing & Service Operations Management,2018,20(2):269～284.
[14] 华国伟,李健,田歆,杨丰梅.带有免费送货选择的最优订货策略[J].系统工程理论与实践,2010,(3):506～512.
[15] 魏涛,王宜举,华国伟.带全量价格折扣的供应商最低免运费订货批量研究[J].中国管理科学,2012,20(6):70～77.
[16] 周永圣,王磊,何明珂.供应商免费送货条件下零售商的订货策略选择研究[J].系统科学与数学,2012,32(3):288～296.
[17] 李建斌,李赟.无理由退货政策下的在线定价及补偿优化策略[J].系统工程理论与实践,2016,36(11):2811～2819.
[18] 李娟,濮阳小娟.具有折扣销售期的网络零售商定价策略分析[J].管理工程学报,2017,31(3):149～154.
[19] Debo L G,et al.Market segmentation and product technology selection for remanufacturable products[J].Management Science,2005,51(8):1193～1205.
[20] Shi H,et al.Consumer heterogeneity,product quality,and distribution channels[J].Management Science,2013,59(5):1162～1176.
[21] 阿里巴巴淘宝网.运费问题的争议处理[EB/OL].https://consumerservice.taobao.com/self-help?spm =a21pu.8253649.0.0.4fc378d5H70X6T#page=issue-detail&knowledge Id=5611064.
[22] 搜狐网.京东取消七天无理由退货真实原因曝光[EB/OL].www.sohu.com/a/233538795100057122,2018-5-31.