考虑无缺陷退货下零售商转运的供应链回购契约研究

针对由单个供应商和同一连锁企业的两个零售商组成的供应链系统中无缺陷退货问题。在随机需求下,假设零售商努力水平与无缺陷退货率成反比,以及两个零售商之间可以相互进行库存转运,建立了期望收益决策模型。通过比较集中决策和分散决策下零售商订货量及各方期望利润,确定了零售商最优订货量和最优努力水平,并提出了改进的差异化回购契约,算例分析表明,改进的差异化回购契约能够达到供应链协调。     

含有自治复原退货物流的单周期库存问题研究

研究电子商务模式中含有自治复原退货物流的单周期库存控制问题.在考虑退货价对需求影响的基础上,通过引入可再售退货产品率,将退货品分为可再销售和不可再销售两部分进行分析,以销售商的利润最大化为目标,借助报童模型建立了自治复原退货物流下考虑退货价对需求影响的单周期库存模型,分析模型中最优订货量、退货价和利润的求解方法,通过数值分析探讨模型中各参数(退货价对需求的影响因子、退货率、可再售退货率)对利润、最优退货价和订购量大小的影响以及造成这些影响的原因.研究结果发现,商家应该在制定策略时考虑退货价对需求的影响,并大胆地提出和宣传自己的退货政策,以增加顾客对退货价的敏感度,从而获取更多的利润.     

考虑退货价格的易逝品供应链协调性研究

考虑由一个制造商和一个零售商组成的供应链,制造商以批发价格为零售商提供一种易逝品,零售商再以零售价格将产品销售给顾客;零售商以一定的退货价格回收顾客的退货产品,制造商对零售商的顾客退货产品及销售季节结束后的剩余产品进行回收,零售商的退货价格不仅对产品的需求有影响,而且对顾客的退货率也产生影响.在这样的条件下,建立了需求不确定环境下顾客退货及制造商回收的模型,结果表明,制造商简单回收顾客的退货产品和销售季节结束后的剩余产品并不能实现供应链协调,而基于回馈与惩罚策略的制造商回收策略能够实现供应链的协调.最后,给出了供应链协调下的模型优化方法,并以数值实例计算了易逝品供应链协调下的最优退货价格和最优订货量,并分析了各种参数变动对最优退货价格、最优订货量和集中式供应链最优利润的影响.     

两次生产和订货模式下的供应链契约式协调

研究了考虑供应链成员的退货处理成本和相对出清优势情形下,两次生产和订货模式 的供应链契约式协调问题,分析了退货契约和滞销补贴契约的适用条件,设计了有效的退货契 约和滞销补贴契约,以协调供应链成员的决策,使销售商的两次订货量达到集中决策的水平, 并通过数值仿真的方法发现:提高退货价格或滞销补贴,能增加销售商的期望利润和总订货 量,并且使其更趋向于在第一次订货,减少第二次的订货量;制造商第一次生产量也因销售商 订货量的增加而增加,第二次生产量则变化不大,制造商的期望利润随着退货价格的提高而不 断下降;一定数量的滞销补贴可使制造商的绩效有所提高,制造商的期望利润随着滞销补贴的 增加而下降.     

随机需求条件下产品退货政策协调与优化

本文研究了随机需求条件下基于退货的单周期单一产品逆向供应链模型.首先,研究了集中决策条件下集成厂商的利润函数,并讨论了实现利润最大化的最优性条件及其最优订货量;其次,在分散决策条件下,分别研究了制造商和销售商的利润函数,并讨论了销售商的最优性条件及其最优订货量;最后,在集中决策和分散决策模型的基础上,重点研究了供应链的协调与优化,得出了实现供应链协调的基本条件和两者之间的利润分配机制.通过制定批发价格和退货价格来实现两者之间的增加利润的任意分配.     

现货供应不确定下的优化采购策略研究

在现货市场和传统契约市场共存时,研究了现货供应的不确定性和销售商的风险规避态度对于销售商的采购策略的影响。首先,在现货供应充足和供应不确定两种情况下分析了实现供应链协调的最优订购量和退货价格,以及销售商的风险规避态度对于订购量的影响.然后,通过数值计算进行了分析和验证.结果表明,现货供应充足时的订购量总是低于现货供应不确定时的订购量;但现货供应充足时供应链的期望利润高于现货供应不确定的情况.现货市场存在下,风险厌恶因子对订购量的影响趋势与单纯契约市场下正好相反.     

基于无缺陷退货下的三阶层易逝品供应链的协调性研究

通过将销售努力对需求和退货率的影响引入三阶层易逝品供应链,建立了需求不确定环境下顾客退货及制造商、分销商分级回收模型,指出分散式供应链在三方没有任何缔结契约条件下并不能实现协调,而基于回馈与惩罚策略下逐层回收顾客的退货产品及销售季节结束后的剩余产品能够实现供应链的协调。     

一个关于供应链利润分配的分析——基于模型和实验的对比

供应链的协调问题是供应链管理的一个重要方面,基于可部分退货的供应链契约,从契约模型和实验两个方面分析供应链利润的分配状况.结果表明,实验中供应链的平均利润与供应链的最大期望利润非常接近,但在这两种情形下供应链利润的分配比例差异较大.在理论模型中销售商占有供应链利润的绝大部分,而在实验中供应商占有供应链利润的绝大部分,并且销售商的订货量与批发价格之间不像通常认为的那样具有较强的负相关性,最后对产生这些差异的原因做了简单分析.     

产品预售、退货策略和消费者无缺陷退货行为

本文研究了在产品需求和消费者产品估价均不确定的情况下,报童零售商的预售策略和无缺陷退货问题.零售商可以提供三种销售策略:不提供预售、提供部分退款退货服务的预售策略和提供全额退款退货服务的预售策略,所有预订产品在正常销售季节交付.研究发现,预订产品的全额退款退货策略和不提供退货策略都可能导致库存风险和估价不确定风险的不合理分摊,而最优的退货策略是部分退款退货策略,且最优退货价格为产品的残余价值.此外,全额退款和部分退款的退货策略只影响零售商的预售利润和销售季节退货量,并不影响零售商在正常销售季节的期望利润.研究还表明,预售需求和正常销售需求的相关性越高,预售优势越明显.     

考虑跨渠道退货的双渠道供应链最优策略

基于零售商线上线下销售与消费者退货并存的双渠道供应链,构建考虑退货的双渠道供应链定价模型以及考虑跨渠道退货策略的双渠道供应链定价决策模型。通过理论分析和数值实验对比,研究集中决策与分散决策下的零售商最优定价策略以及总利润的变化情况,同时分析在不同退货策略下顾客偏好以及退货率对零售商定价和收益的影响。结果表明：零售商渠道的最优价格设置与顾客对渠道的偏好成正比,与退货率成正比。当顾客对某一渠道偏好程度高时,分散决策下的利润要高于集中决策,并且随着该渠道退货率的提高,这种利润差距会进一步扩大,因此零售商应实施分散决策的渠道策略,鼓励线上线下两个渠道进行竞争,从而获得更大的收益。从仿真结果可以看出,对于一般的服装产品,提供跨渠道退货服务的零售商总利润更高,在一定条件下跨渠道服务水平的投入会增加零售商的收入,但这种投入应该控制在一个合理的水平上,并保持服务与顾客回报之间的正相关关系。     

网购环境下在线零售商的退货运费承担策略研究

在电子商务环境下，宽松的退货政策能够刺激需求，促进货品销量的增长，但与此同时也导致了退货量的增多。在面临高退货，特别是无缺陷退货不断攀升的挑战下，在线商家应如何制定合理的退货策略成为值得研究的一个问题。本文主要针对退货运费承担问题，重点比较消费者承担退货运费、商家承担退货运费、双方共同承担退货运费三种策略，探讨不同策略下在线零售商的最优定价及其盈利能力。研究结果表明：为实现利润最大化，在线零售商应根据商品的无缺陷退货比例特征选择相应的策略。具体而言，当商品的无缺陷退货比例较低时，宜采用消费者承担退货运费策略；当无缺陷退货比例高时，宜采用商家承担退货运费策略；当无缺陷退货比例居中时，宜采用共同承担退货运费策略。值得注意的是，退货政策的目的是为了刺激需求的增长，但有时退货政策对需求的促进作用不够理想，不能抵消退货的负面影响，那么这种情况下则无论无缺陷退货占比如何，在线零售商的最佳退货策略只能是让消费者承担退货运费，以此避免更多非理性退货行为的发生。     

Effect of Inventory Information Discrepancy in a Drop‐Shipping Supply Chain

This article investigates the impact of information discrepancy between a drop‐shipper and an online retailer on the drop‐shipping supply chain performance. The inventory information misalignment between them contributes to the failure of order fulfillment and demand satisfaction, and hence the associated penalties are incurred. In this article, we first analyze the penalties of ignoring such information discrepancy on both the drop‐shipper and the online retailer. We then assess the impact of information discrepancy on both parties when the drop‐shipper understands the existence of the information discrepancy but is not able to eliminate the errors. The numerical experiments indicate that both parties can have significant amount of the percentage cost reductions if the information discrepancy can be eliminated, and the potential savings are substantial especially when the errors have large variability. Furthermore, we observe that the online retailer is more vulnerable to information discrepancy than the drop‐shipper, and the drop‐shipper is likely to suffer from the online retailer's underestimation of the physical inventory level more than the problem of its overestimation. Moreover, even if eliminating errors is not possible, both parties could still benefit from taking the possibility of errors into consideration in decision making.     

全渠道零售下“Showrooms”对需求分布、定价和收益的影响研究

作为一种新兴的线下体验、线上购买的商业运作模式,展厅（Showrooms）在全渠道零售领域发展迅速。基于消费者效用分别建立单一网络渠道和"网络+实体"渠道下零售商开设Showrooms前后的利润模型,对比分析固定销售价格和优化定价两种情形下Showrooms对定价、市场需求、利润和退货率的影响。研究表明：（1）单一网络渠道下,网络渠道价格固定时,开设Showrooms可使市场总需求增加,总利润在展厅运营成本较低时增加;网络渠道价格优化时,开设Showrooms可使网络渠道价格、总需求和总利润在展厅运营成本较低时增加,但固定价格情形下总利润的增幅更大。（2）"网络+实体"渠道下,开设Showrooms可使总需求和总利润均在展厅运营成本较低及网络退货率和网购不便利成本较高时增加,而且仅优化网络渠道价格时的增幅最大,网络和实体渠道价格均固定时次之;价格优化的最终趋势是全渠道同款同价。（3）开设Showrooms可使零售商总的网络退货率和退货量都下降。     

考虑退货的定价和订货优化及信息发布美化策略

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。     

不对称信息下线上零售商定价与O2O渠道策略研究

针对由制造商和线上零售商组成的供应链，考虑消费者退货行为以及产品退货会给企业造成退货损失，且线上零售商退货损失为其私有信息，研究不对称信息下的供应链定价、O2O渠道策略以及合同设计问题，分析线上零售商引入O2O渠道的可行条件及其对供应双方最优决策和消费者剩余的影响，考察不对称信息对各个企业、供应链系统利润的影响。研究表明，线上零售商引入O2O渠道存在可行条件，取决于退货损失的大小；当线上零售商引入O2O渠道时，制造商和供应链系统的期望利润水平均能得到有效提升；O2O渠道策略有利于提高消费者剩余，但到体验店体验产品的消费者不一定能够得到更高的消费者剩余；如果满足一定条件，则线上零售商会选择信息共享谈判与制造商共享其私有信息，进而实现"双赢"。     

Optimal Pricing,Ordering, and Return Policies for Consumer Goods

Our research addresses a firm that sells a product to consumers who are sensitive to both price and return policy. The operational decisions of interest are the selling price, return policy, and quantity of new product to purchase. We model a single selling season that is split into two periods where the boundary between periods is delineated by the opportunity to recover product returns and resell them. That is, returns in the first period can be recovered and sold in the second period. Returns also arise in the second period, but these may only be salvaged. We first analyze both deterministic and stochastic models, finding that the deterministic results largely carry over to the stochastic case. In addition, our results indicate that the model is quite insensitive to errors in the estimates of the parameter values, except for purchase cost and parameters related to demand. Finally, we perform an analysis on the value of various investments to improve financial performance. Results indicate that investments to reduce the recovery cost of returns or reduce returns uncertainty are minimal, while investments to increase recovery speed, reduce market uncertainty, and reduce the return rate can be quite valuable.     

Consumer return policies in presence of a P2P market

Retailers selling products with valuation uncertainty often offer return policies to consumers to stimulate demand. However, some products that do not meet consumers’ expectations cannot be returned to the retailers either because of retailers’ strict restrictions on returns or because of short trial period. With the development of e-commerce, consumers who cannot return their products to retailers can resell them directly to others through electronic peer-to-peer (P2P) second-hand goods markets. This paper examines the effect of the presence of a P2P market on a retailer’s optimal return policy when the consumers are strategic and uncertain about their valuations. As a benchmark, we first examine the retailer’s optimal return policy when there is only a retailer-run resale market. Then, we analyze the retailer’s optimal return policy in presence of both the retailer-run resale market and the P2P market. Theoretical and numerical results show that, first, the presence of the P2P market is detrimental to the retailer in most cases. The presence of the P2P market is beneficial to the retailer only when the unit purchasing cost is very high, the consumers’ acceptance of products in the P2P market is relatively high and the transaction cost in the P2P market is relatively low; second, the consumer surplus is improved by the presence of P2P market; third, when the retailer-run resale market is the only second-hand products market, returned products are sold out; while in presence of the P2P market, the retailer will hold some inventory when the unit purchasing cost is very low; fourth, the selling price of new products is increased and the selling price of second-hand products in the retailer-run resale market is decreased with the emergence of the P2P market while the refund amount is increased in most cases.     

The Impact of Product Returns and Retailer's Service Investment on Manufacturer's Channel Strategies*

We study the distribution channel decision of a manufacturer who considers whether to add an online channel (direct channel) to its brick‐and‐mortar retailer (indirect channel). The retailer faces the opportunity to invest in store assistance to help consumers choose products and thus reduce product returns. Special attention is given to the impact of product returns and retailer's store assistance investment on manufacturer's dual channel decision. We examine conditions under which the manufacturer uses dual channels and how various relevant factors affect its channel decision under two settings, depending on whether the retailer has its own online store or not. When the retailer does not have its online store, we find that (i) the addition of the direct channel raises the wholesale price; (ii) the direct channel addition hurts the retailer if the nonreplacement rate is low; (iii) the manufacturer has a lower incentive to add the direct channel when the retailer's service cost is lower or its returns reduction rate from service investment is higher; and (iv) the manufacturer should treat its own returns handling cost as a key factor in its channel structure decision. In addition, when the retailer operates an online store, we find that the manufacturer may have an incentive to add a direct channel such that both firms own direct channels.