考虑退货的定价和订货优化及信息发布美化策略
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摘要
考虑顾客由感知差异引起的退货行为,以及促销期与日常销售期不同的行为特点,对日常销售期和促销期顾客购买率和退货率分别进行了解析表述.在此基础上分析了确定需求下信息发布美化策略对最大利润的影响.建立了随机需求下在线零售商的期望利润模型,对定价和订货量进行联合优化.最后通过算例分析了在感知价值和感知差异服从更为一般的分布形式且存在相关性条件下,最优策略下的预期利润随信息发布美化程度的变化规律,以及相关性对信息发布美化策略有效性的影响.研究结果表明,基于感知价值和感知差异构建的购买率和退货率模型可较好解释已有实证研究结果,以此为基础对定价和库存进行联合优化更符合实际,优化条件下的最大利润随信息发布美化程度的提高先增后降,取得最大利润的信息美化值促销期大于日常销售期,且线性相关程度越高的产品取得最大利润的信息美化值越大。
One of the remarkable differences between online retail and traditional physical storefront operation is that there are a lot of consumer returns caused by non-quality reasons.The proper analytical expression of returns in the e-commerce environment is a key issue of inventory and pricing optimization and the effective product information disclosure strategy.The online shopping behavior could be divided into two-stage decision processes of the purchase decision and the return decision.The decisions are mainly based on the estimated valuation observed by consumers through browsing introduction pages and the perception differences revealed after obtaining the product.Based on the mechanism of returns,the uniform distribution of perceived value in Hotelling model and existing research is hypothesized,and the characteristics of the purchase probability and the return probability in both daily sales period and promotion period are analyzed.Expected profit models are established,and analytical solutions of the optimal order quantity are derived.Computational methods for the optimal solutions of the price in daily sales period,the price discount in promotion period,and the maximum expected profits are also demonstrated.Taking the cost parameters in existing joint pricing and inventory optimization study for reference,a set of numerical examples is made,in which perceived value and perception differences are verified to obey the more general distribution with different correlation coefficients.The change rule of the maximum profit with the information distribution beautification degree,and the influence of the correlation on the effectiveness of the beautification strategy are studied.The research shows that:customer returns in the promotion period are affected by two reverse effects,which are the increase of return rate due to the impulse buying and the decrease of return rate caused by the loss of returns due to opportunity costs,and the probability of impulsive buying increases with higher prices;the purchase and return rate model in e-commerce environment built from the perspective of perceived value and perception difference is in accordance with the existing empirical study that the return rate increase with the price,and it can also explain the reason for the high return rate after steep price reduction;when the selling price,the purchase price and the residual value meet certain conditions,the merchants adopt the appropriate information disclosure beautification strategy can improve the profit to some extent;the degree of information beautification increases with the price and the residual value,and the extent to information beautification in promotion period is higher than that in the daily sales period;the profit of the product with moderate linear correlation between perceived value and perceived difference is lower than that of the product with low or high linear correlation;Information beautification strategy is more effective on products with higher linear correlation.The return model from the perspective of perceived value and perception difference is built,which is more consistent with the actual situation and the results of empirical studies.Based on that return model,the research of the pricing and ordering optimization and the beautification strategy of information disclosure can provide better decision support for online retailers.
One of the remarkable differences between online retail and traditional physical storefront operation is that there are a lot of consumer returns caused by non-quality reasons.The proper analytical expression of returns in the e-commerce environment is a key issue of inventory and pricing optimization and the effective product information disclosure strategy.The online shopping behavior could be divided into two-stage decision processes of the purchase decision and the return decision.The decisions are mainly based on the estimated valuation observed by consumers through browsing introduction pages and the perception differences revealed after obtaining the product.Based on the mechanism of returns,the uniform distribution of perceived value in Hotelling model and existing research is hypothesized,and the characteristics of the purchase probability and the return probability in both daily sales period and promotion period are analyzed.Expected profit models are established,and analytical solutions of the optimal order quantity are derived.Computational methods for the optimal solutions of the price in daily sales period,the price discount in promotion period,and the maximum expected profits are also demonstrated.Taking the cost parameters in existing joint pricing and inventory optimization study for reference,a set of numerical examples is made,in which perceived value and perception differences are verified to obey the more general distribution with different correlation coefficients.The change rule of the maximum profit with the information distribution beautification degree,and the influence of the correlation on the effectiveness of the beautification strategy are studied.The research shows that:customer returns in the promotion period are affected by two reverse effects,which are the increase of return rate due to the impulse buying and the decrease of return rate caused by the loss of returns due to opportunity costs,and the probability of impulsive buying increases with higher prices;the purchase and return rate model in e-commerce environment built from the perspective of perceived value and perception difference is in accordance with the existing empirical study that the return rate increase with the price,and it can also explain the reason for the high return rate after steep price reduction;when the selling price,the purchase price and the residual value meet certain conditions,the merchants adopt the appropriate information disclosure beautification strategy can improve the profit to some extent;the degree of information beautification increases with the price and the residual value,and the extent to information beautification in promotion period is higher than that in the daily sales period;the profit of the product with moderate linear correlation between perceived value and perceived difference is lower than that of the product with low or high linear correlation;Information beautification strategy is more effective on products with higher linear correlation.The return model from the perspective of perceived value and perception difference is built,which is more consistent with the actual situation and the results of empirical studies.Based on that return model,the research of the pricing and ordering optimization and the beautification strategy of information disclosure can provide better decision support for online retailers.
引文
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[2]Mostard J,Teunter R.The newsboy problem with resalable returns:A single period model and case study[J].European Journal of Operational Research,2008,169(1):81-96.
[3]李新军,达庆利.随机需求条件下产品退货政策协调与优化[J].中国管理科学,2007,15(3):56-60.
[4]李群霞,张群,朱晓宁,等.缺陷品可完全退货的库存控制模型的研究[J].中国管理科学,2009,17(6):116-121.
[5]Chen J,Bell P C.Coordinating a decentralized supply chain with customer returns and price-dependent stochastic demand using a buyback policy[J].European Journal of Operational Research,2011,212(2):293-300.
[6]汪峻萍,杨剑波,贾兆丽.基于无缺陷退货的网上销售易逝品供应链协调模型[J].中国管理科学,2013,21(6):47-56.
[7]张霖霖,姚忠.考虑顾客退货时在线企业的定价与订货策略[J].管理科学学报,2013,16(6):10-21.
[8]孙军,徐路恒,刘宇.退货问题下的在线零售商最优采购量研究[J].管理科学,2014,27(6):114-120.
[9]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.
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[11]Lee K S,Tan S J.E-retailing versus physical retailing:A theoretical model and empirical test of consumer choice[J].Journal of Business Research,2003,56(11):877-885.
[12]Vohs K D,Faber R J.Spent resources:Self-regulatory resource availability affects impulse buying[J].Journal of Consumer Research,2007,33(4):537-547.
[13]Lawton C.The war on returns[N].Wall Street Journal,2008-08-18(6).
[14]Ofek E,Katona Z,Sarvary M,et al."Bricks and clicks":The impact of product returns on the strategies of multichannel retailers[J].Marketing Science,2011,30(1):42-60.
[15]王崇,刘健,吴价宝.网络环境下消费者感知效用模型的构建与研究[J].中国管理科学,2011,19(3):94-102.
[16]Wood S L.Remote purchase environments:The influence of return policy leniency on two-stage decision processes[J].Journal of Marketing Research,2013,38(2):157-169.
[17]曹细玉,宁宣熙.考虑退货价格的易逝品供应链协调性研究[J].管理科学,2007,20(2):31-35.
[18]翟春娟,李勇建.B2C模式下的在线零售商退货策略研究[J].管理工程学报,2011,25(1):62-68.
[19]Chen J,Bell P C.The impact of customer returns on pricing and order decisions[J].European Journal of Operational Research,2009,195(1):280-295.
[20]Su Xuanming.Consumer returns policies and supply chain performance[J].Manufacturing&Service Operations Management,2009,11(4):595-612.
[21]申成霖,张新鑫,卿志琼.服务水平约束下基于顾客策略性退货的供应链契约协调研究[J].中国管理科学,2010,18(4):56-64.
[22]Swinney R.Selling to strategic consumers when product value is uncertain:The value of matching supply and demand[J].Management Science,2011,57(10):1737-1751.
[23]李勇建,许磊,杨晓丽.产品预售、退货策略和消费者无缺陷退货行为[J].南开管理评论,2012,15(5):105-113.
[24]Akcay Y,Boyaci T,Zhang D.Selling with moneyback guarantees:The impact on prices,quantities,and retail profitability[J].Production&Operations Management,2013,22(4):777-791.
[25]Hu W,Li Y,Govindan K.The impact of consumer returns policies on consignment contracts with inventory control[J].European Journal of Operational Research,2014,233(2):398-407.
[26]杨光勇,计国君.存在战略顾客的退货策略研究[J].管理科学学报,2014,17(8):23-33.
[27]Hsiao L,Chen Y.Retailer's rationale to refuse consumer returns in supply chains[J].Naval Research Logistics,2015,62(8):686-701.
[28]黄宗盛,聂佳佳,赵映雪.基于消费者满意的双渠道销售商退款保证策略研究[J].中国管理科学,2016,24(2):61-68.
[29]Chen Yingju.Optimal selling scheme for heterogeneous consumers with uncertain valuations[J].Mathematics of Operations Research,2011,36(4):695-720.
[30]陈灿,刘杰.基于消费者购买前后感知价值差异下的卖方最优订货量与定价分析[J].中国科学技术大学学报,2015,(8):692-701.
[31]Chen Yubo,Xie Jinhong.Online consumer review:Word-of-mouth as a new element of marketing communication mix[J].Management Science,2008,54(3):477-491.
[32]Shulman J D,Coughlan A T,Savaskan R C.Optimal restocking fees and information provision in an integrated demand-supply model of product returns[J].Manufacturing&Service Operations Management,2011,11(4):577-594.
[33]张涛,李刚,罗美玲,等.考虑无缺陷退货的在线商品信息发布策略[J].运筹与管理,2017,26(3):123-130.
[34]贾丽.双十一退货率高达25%购物狂欢后物流业遭遇尴尬[N].证券日报,2013-11-14(C02).
[35]Hotelling H.Stability in competition[J].The Economic Journal,1929,39(153):41-57.
[2]Mostard J,Teunter R.The newsboy problem with resalable returns:A single period model and case study[J].European Journal of Operational Research,2008,169(1):81-96.
[3]李新军,达庆利.随机需求条件下产品退货政策协调与优化[J].中国管理科学,2007,15(3):56-60.
[4]李群霞,张群,朱晓宁,等.缺陷品可完全退货的库存控制模型的研究[J].中国管理科学,2009,17(6):116-121.
[5]Chen J,Bell P C.Coordinating a decentralized supply chain with customer returns and price-dependent stochastic demand using a buyback policy[J].European Journal of Operational Research,2011,212(2):293-300.
[6]汪峻萍,杨剑波,贾兆丽.基于无缺陷退货的网上销售易逝品供应链协调模型[J].中国管理科学,2013,21(6):47-56.
[7]张霖霖,姚忠.考虑顾客退货时在线企业的定价与订货策略[J].管理科学学报,2013,16(6):10-21.
[8]孙军,徐路恒,刘宇.退货问题下的在线零售商最优采购量研究[J].管理科学,2014,27(6):114-120.
[9]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.
[10]Hess J D,Mayhew G E.Modeling merchandise returns in direct marketing[J].Journal of Direct Marketing,1997,11(2):20-35.
[11]Lee K S,Tan S J.E-retailing versus physical retailing:A theoretical model and empirical test of consumer choice[J].Journal of Business Research,2003,56(11):877-885.
[12]Vohs K D,Faber R J.Spent resources:Self-regulatory resource availability affects impulse buying[J].Journal of Consumer Research,2007,33(4):537-547.
[13]Lawton C.The war on returns[N].Wall Street Journal,2008-08-18(6).
[14]Ofek E,Katona Z,Sarvary M,et al."Bricks and clicks":The impact of product returns on the strategies of multichannel retailers[J].Marketing Science,2011,30(1):42-60.
[15]王崇,刘健,吴价宝.网络环境下消费者感知效用模型的构建与研究[J].中国管理科学,2011,19(3):94-102.
[16]Wood S L.Remote purchase environments:The influence of return policy leniency on two-stage decision processes[J].Journal of Marketing Research,2013,38(2):157-169.
[17]曹细玉,宁宣熙.考虑退货价格的易逝品供应链协调性研究[J].管理科学,2007,20(2):31-35.
[18]翟春娟,李勇建.B2C模式下的在线零售商退货策略研究[J].管理工程学报,2011,25(1):62-68.
[19]Chen J,Bell P C.The impact of customer returns on pricing and order decisions[J].European Journal of Operational Research,2009,195(1):280-295.
[20]Su Xuanming.Consumer returns policies and supply chain performance[J].Manufacturing&Service Operations Management,2009,11(4):595-612.
[21]申成霖,张新鑫,卿志琼.服务水平约束下基于顾客策略性退货的供应链契约协调研究[J].中国管理科学,2010,18(4):56-64.
[22]Swinney R.Selling to strategic consumers when product value is uncertain:The value of matching supply and demand[J].Management Science,2011,57(10):1737-1751.
[23]李勇建,许磊,杨晓丽.产品预售、退货策略和消费者无缺陷退货行为[J].南开管理评论,2012,15(5):105-113.
[24]Akcay Y,Boyaci T,Zhang D.Selling with moneyback guarantees:The impact on prices,quantities,and retail profitability[J].Production&Operations Management,2013,22(4):777-791.
[25]Hu W,Li Y,Govindan K.The impact of consumer returns policies on consignment contracts with inventory control[J].European Journal of Operational Research,2014,233(2):398-407.
[26]杨光勇,计国君.存在战略顾客的退货策略研究[J].管理科学学报,2014,17(8):23-33.
[27]Hsiao L,Chen Y.Retailer's rationale to refuse consumer returns in supply chains[J].Naval Research Logistics,2015,62(8):686-701.
[28]黄宗盛,聂佳佳,赵映雪.基于消费者满意的双渠道销售商退款保证策略研究[J].中国管理科学,2016,24(2):61-68.
[29]Chen Yingju.Optimal selling scheme for heterogeneous consumers with uncertain valuations[J].Mathematics of Operations Research,2011,36(4):695-720.
[30]陈灿,刘杰.基于消费者购买前后感知价值差异下的卖方最优订货量与定价分析[J].中国科学技术大学学报,2015,(8):692-701.
[31]Chen Yubo,Xie Jinhong.Online consumer review:Word-of-mouth as a new element of marketing communication mix[J].Management Science,2008,54(3):477-491.
[32]Shulman J D,Coughlan A T,Savaskan R C.Optimal restocking fees and information provision in an integrated demand-supply model of product returns[J].Manufacturing&Service Operations Management,2011,11(4):577-594.
[33]张涛,李刚,罗美玲,等.考虑无缺陷退货的在线商品信息发布策略[J].运筹与管理,2017,26(3):123-130.
[34]贾丽.双十一退货率高达25%购物狂欢后物流业遭遇尴尬[N].证券日报,2013-11-14(C02).
[35]Hotelling H.Stability in competition[J].The Economic Journal,1929,39(153):41-57.