摘要
近年来，随着互联网和移动互联网的快速普及，网络零售行业得到蓬勃发展。虽然网上购物为消费者提供低价、送货上门等一些便利，然而，难以提供购物体验且运营成本较高等问题正在限制着传统电商的发展。随着消费升级的到来，消费者特别注重购物体验。单一的线上渠道已经无法满足消费者线下体验式服务的需求。为了提升购物体验，拓展市场，提高品牌影响力和保持更紧密的零售关系，越来越多的电商公司选择开通线下渠道以全渠道运营。当然不同线下模式其运营模式以及运营成本也不同，因此面对不同的线下渠道模式如何做出最优选择，对传统电商公司尤为关键。
本文在全渠道的研究背景下，以传统电商为研究对象，分析了两种常见的线下渠道模式：体验店和直营店。利用消费者效用函数构建了开设体验店和直营店前后的利润模型，对比分析了体验店和直营店模式对传统电商的定价、需求量和退货量的影响，研究了传统电商公司最优运营模式选择问题，并为其他电商公司实施全渠道运营策略提出布局三四线城市线下市场、区别产品特征、考虑消费者退货便利性具体管理建议。
论文首先对 H 电商公司运营现状进行分析，发现其现有运营模式存在线上渠道获客成本过高、线上转化率较低和线上渠道退货率高三个主要问题，为了实现更好更长远的发展，H 电商公司将开启新业务新市场和加快全渠道零售生态布局两大运营战略。然后基于消费者效用最大原则分别建立了网络零售商开设线下实体店前、开设线下体验店和直营店后的决策模型，分别分析网络零售商开设体验店和直营店后对价格、消费者需求和退货量的影响，发现：当网络零售商实施线下体验店运营模式后，消费者总需求量增加、退货量减少。若品牌溢出效应较小时，可以提高产品销售价格；当网络零售商实施线下直营店运营模式后，消费者总需求量增加、退货量增加。若到店退货交叉收益较小时，可以提高产品销售价格。最后通过数值仿真从线下渠道设施固定成本、线上退货逆向物流成本、线上退货不便利成本、产品匹配率四个角度分析传统电商最优运营模式的实施条件，结果显示：若线下直营店投入固定成本较低，但高于体验店投入固定成本时，电商公司此时反而选择开设线下直营店可从中获利。当线上退货逆向物流成本较低、消费者线上退货不便利成本较低或者产品匹配较低时，此时传统电商开设体验店占优，反之，开设直营店占优。并进一步为未实施全渠道运营策略的传统电商公司提出三点管理建议：在三四线城市开设大量的直营店迅速打开线下市场，而在一二线城市开设少量的体验店；个性化、定制化类产品实施体验店模式，而标准化、基础类产品实施直营店模式；考虑消费者退货便利性，开设直营店提供到店退货服务。
关键词： 全渠道；运营策略；体验店模式；直营店模式；退货 。
Abstract
In recent years, with the rapid popularization of the Internet and mobile Internet, the onlineretail industry has developed vigorously. Although online shopping provides consumers withsome conveniences such as low prices and door-to-door delivery, problems such as difficultyin providing a shopping experience and low operating costs are restricting the development oftraditional e-commerce. With the advent of consumption upgrades, consumers pay specialattention to the shopping experience. A single online channel has been unable to meetconsumers' demands for offline experiential services. In order to enhance the shoppingexperience, expand the market, increase brand influence and maintain closer retail relations,more and more e-commerce companies choose to open offline channels to operate in allchannels. Of course, different offline modes have different operating modes and operating costs.
Therefore, how to make the best choice in the face of different offline channel modes isparticularly critical for traditional e-commerce companies.
In the context of omni-channel research, this article uses traditional e-commerce as theresearch object and analyzes two common offline channel models: showrooms andcompany-owned sales stores. The consumer utility function was used to construct a profit model beforeand after the opening of showrooms and company-owned stores, and the influence of the modelof showrooms and company-owned stores on the pricing, demand and return volume oftraditional e-commerce companies was compared and analyzed. Traditional e-commercecompanies were studied. Optimal operation model selection, and for other e-commercecompanies to implement omni-channel operation strategies, put forward specific managementrecommendations based on the layout of offline markets in third- and fourth-tier cities,distinguishing product characteristics, and convenience for consumers to return goods.
The paper first analyzes the operating status of H e-commerce company, and finds that itsexisting operating model has three main problems: high customer acquisition costs throughonline channels, low online conversion rates, and high return rates in online channels. In orderto achieve better in the long-term development, H e-commerce company will open up newbusiness and new markets and accelerate the two major operating strategies of omni-channelretail ecological layout. Then, based on the principle of maximizing consumer utility, thedecision-making models of online retailers before opening offline physical stores, offlineshowrooms and company-owned-operated stores were established, respectively, and the onlineretailer’s impact on prices, after opening showrooms and company-owned stores were analyzed.
The impact of consumer demand and the volume of returns found that when online retailers implement the offline showroom operation model, the total demand of consumers increases andthe volume of returns decreases. If the brand spillover effect is small, the product sales pricecan be increased; when the online retailer implements the offline company-owned storeoperation model, the total consumer demand will increase and the return volume will increase.
If the cross-benefit of returning goods to the store is small, the selling price of the product canbe increased. Finally, numerical simulation is used to analyze the implementation conditions ofthe optimal operation mode of traditional e-commerce from four perspectives: fixed cost ofoffline channel facilities, online return reverse logistics cost, online return inconvenience cost,and product matching rate. The results show that: if the fixed cost of company-owned stores islower, but higher than the fixed cost of showrooms, e-commerce companies choose to openoffline company-owned stores to profit from it at this time. When the reverse logistics cost ofonline returns is low, the cost of online returns is inconvenient for consumers, or the productmatching is low, traditional e-commerce outlets have an advantage in opening showrooms. Onthe contrary, opening company-owned stores has an advantage. And further proposed threemanagement recommendations for traditional e-commerce companies that have notimplemented an omni-channel operation strategy: open a large number of company-ownedstores in three or four cities to quickly open the offline market, and open a small number ofshowrooms in first and second tier cities; personalized, Customized products implement theshowroom model, while standardized and basic products implement the company-owned storemodel; considering the convenience of consumers to return goods, open the company-ownedstores to provide offline return channels.
Keywords: Omni-channel; Operation strategy; Showroom model; Company-owned storemodel; Returns 。
第一章 绪论
1.1、研究背景和意义。
1.1.1、研究背景。
随着互联网和移动互联网的快速普及，消费者可以通过手机等移动终端随时随地进行网上购物，为此网络零售行业促使蓬勃发展。据统计局最新数据显示，2020年中国网上零售额117601亿元，相较2019年增长10.9%。网络零售业务量迅速增长促使传统实体零售公司纷纷开通线上渠道销售产品以满足消费者线上需求，例如家电零售巨头苏宁开通线上平台苏宁易购，国美推出在线商城Gome.com，国外零售巨头沃尔玛则推出了Walmart.com。近年来，虽然网络零售业一直保持增长趋势，并不意味着实体零售业将被取代，84%在线消费者认为线下实体店购物仍是零售体验的主要部分，实体店可以更好触摸、体验产品，了解到产品的质量，满足消费者及时需求、提供更好的服务[1]。
2016年，马云提出线上线下渠道与现代物流融合的“新零售”终将代替传统的纯电商模式，成为未来零售行业的变革方向和发展趋势[2]。目前，许多巨头电商公司都已经意识到只保持现有线上渠道已行不通，开始纷纷布局线下渠道，实现多渠道或者全渠道零售，以提高客户消费者体验。早在2015年11月亚马逊在美国西雅图推出首家线下实体书店，计划以后将开设300-400家新店，2017年6月收购高端生鲜供应商全食超市公司，2018年亚马逊推出无人便利店Amazon Go，计划在2021全球开设超过3000无人直营店。
2016年1月阿里巴巴推出首家线下盒马生鲜超市，目前已有214家线下门店。
2020年7月，京东家电专卖店数量已突破1.5万家，同年8月京东正式宣布全资控股五星电器，并计划2025年将在一线城市开设20家电器超级体验店。巨头电商公司们纷纷大力投入线下渠道建设，已然说明，零售不再是单一的线上渠道或者单一的线下渠道，全渠道零售模式成为了零售行业的一种主流渠道销售模式。
2019年一份关于服饰零售渠道的调查显示，从小规模服装和时装行业的技术效率来看，全渠道零售商比传统单一渠道零售商更具有17％的优势[3]。因此成为全渠道零售商是传统零售商成功的必经之路。
在电子商务交易模式下，消费者与电商公司是通过虚拟的网络实现产品的交易，存在信息不对称现象。消费者只能通过网上产品描述、图片、视频以及评论等信息了解产品，无法触摸、试用体验到真实产品，电商公司利用技术手段美化过的图片与实物严重不符导致消费者退回产品，另外产品在运输途中因人为或意外会不可避免发生破损情况。
2014年出台的《网络交易管理办法》中第十六条规定，网络商品经营者销售产品，消费者有权自收到商品之日起七日内无理由退货，不仅为消费者降低了网络购物的风险，还提供了退货换的法律支持。根据美国国家零售联合会的数据，美国的线上零售商面临的平均退货率高达30％[4]。零售商在处理退货时会产生大量成本（平均每件商品6至18美元），特别是在运输，分类和处理这些商品时。网络零售商通常需花费一笔高昂的费用在处理退货方面，因此，退货是网络购物的一个主要问题，它对于网络零售商是一个关键弊端。对于B2C消费者，在线上购物不仅仅再只是关注产品价格、产品详细信息、客户评论和运费，退货策略也成为其购买产品的主要因素，一项调查研究表明（UPS,2019）其中73％的受访消费者表示退货策略会影响他们是否继续在线购买[5]。这就意味着电商公司要想在激烈的市场竞争中取胜，必须提供灵活宽松的退货策略以刺激消费者购买，在实践中，大部分电商公司通常选择适当的退货政策来处理客户退货，例如许多商家为了降低消费者网购感知风险，提高消费者购买意愿提供部分退货运费险以弥补消费者退货时发生的运费。
为消除顾客对产品的不确定性风险、降低退货率，减少退货处理成本。还未开设线下渠道的传统电商应当尽快布局线下实体店以实现全渠道零售。全渠道零售的出现为消费者提供了更灵活，个性化和无缝的购物体验。线下和线上渠道的这种统一集成可以减少客户对产品适用性的不确定性。当然电商公司布局线下绝不是简单的传统实体店重现，目前国内外电商公司主要采取两种线下实体模式，一种是体验店模式，体验店的产品只供展示，不可售卖。消费者可以在店内浏览或评估产品，然后收集在线购买所需的足够产品信息，意味着其可能会导致产品退货大幅减少。这种先线下体验后线上购买的体验店模式在国外比较流行，例如美国最大的线上钻石电商蓝色尼罗河、在线眼镜巨头Wakby Paker、互联网男装品牌Bonobos都已经开设线下体验店。另一种是直营店模式，直营店的产品提供售卖功能，现在国内电商更多的是开设带有销售功能的直营店，例如京东家电，互联网手机品牌小米、线上服装品牌茵曼都加大线下直营店的投入。线下渠道的开设不仅为消费者新增了一个购买渠道，同时也可以为给消费者提供新的退货渠道选择。
2015年UPS一项研究调查显示当从拥有线上渠道的实体商店零售商在线购买商品时，39%的消费者倾向于将产品寄回线上渠道，而61％的消费者则倾向于将商品退还给线下商店[6]。如果客户不喜欢所购买的产品，则可以轻松地将其退回附近的实体店以获取全额退款。因此，实体店的存在将大大减少零售商的退货处理成本。国外许多零售企业J.C. Penny，Apple，宜家以及优衣库等已经实施到店退货策略，而国内目前只有苏宁实施此策略。所以全渠道背景下开设直营店不仅仅提供销售功能，还提供退货功能。
不同的线下实体模式有其不同的特点，同一种模式不能适合所有的电商公司，因此如何做出适合的选择对于传统电商至关重要。
因此，本文基于全渠道背景下，研究传统电商公司开设线下体验店和直营店对其影响以及不同因素如何影响传统电商公司选择最优运营策略。首先分析了传统电商公司开设线下体验店提供线下体验线上下单渠道后对其定价、需求量、退货量的影响。其次分析了传统电商公司开设线下直营店提供线下购买和到店退货渠道后对其定价、需求量、退货量的影响。最后进一步分析，传统电商公司如何在开设线下体验店和直营店两种运营策略中做选择，分析出在什么条件下电商公司选择开设线下体验店，什么条件下选择开设线下直营店，并为其他未开设线下渠道的传统电商公司提出管理建议供其参考。
【由于本篇文章为硕士论文，如需全文请点击底部下载全文链接】
1.1.2、研究意义
1.2 、国内外研究现状.
1.2.1、全渠道零售相关研究
1.2.2、消费者退货相关研究
1.2.3、渠道选择相关研究.
1.2.4、 研究述评
1.3、 研究内容程方
1.3.1 、研究内容,
1.3.2 、研究方法.
1.4、技术路线图
第二章 相关概念与理论模型
2.1、全渠道.
2.1.1、全渠道零售的概念及发展历程.
2.1.2、全渠道零售的特点
2.1.3、建立全渠道的策略要点.
2.2、消费者效用模型
第三章 H电商公司运营现状分析.
3.1、H电商公司简介.
3.2、H电商公司运营策略现状
3.2.1、多品牌策略
3.2.2、灵活定价策略.
3.2.3、多电商平台分销策略
3.3、H电商公司现存的问题
3.3.1、线上渠道获客成本过
3.3.2、线上转化率较低，
3.3.3、线上渠道退货率较高
3.4、H电商公司未来运营战略
3.4.1、推进“新品类"战略，开启新业务新市场探索
3.4.2、积极拓展线下渠道，以实现全渠道运营.
3.5、本章小结
第四章 运营策略分析
4.1、问题描述与模型假设.
4.2、模型建立.
4.2.1、无线下实体店情形( 基准模型)
4.2.2、开设线下体验店情形
4.2.3、开设线下直营店情形
4.3、对比分析
4.3.1、体验店模式与无实体店模式对
4.3.1、直营店模式与无实体店模式对比.
4.4、本章小结.
第五章 案例分析
5.1、线下渠道固定设施成本对利润的影响，
5.2、线上退货逆向物流成本对利润的影响
5.3、线上退货不便利成本对利润的影响
5.4、产品匹配率对利润的影响
5.5、管理建议
5.5.1、布局三四线城市线下市场.
5.5.2、区别产品特征，
5.5.3、考虑消费者退货便利性.
第六章 结论
本文考虑消费者购买以及退货行为，构建消费者效用函数得到不同行为下的需求函数，基于需求函数建立无线下实体店、开设线下体验店和直营店三种运营模式下电商公司利润模型。比较开设体验店和直营店运营模式下对定价、消费者需求、退货量的影响。
最后通过数值算例给出实施线下体验店、线下直营店运营模式的范围。具体结论如下：
（1）传统电商公司实施线下体验店运营模式下，当品牌溢出效应较小时，电商公司可以提高产品销售价格、与未开设线下实体店运营模式下相比，消费者总需求量增加、退货量减少。
（2）传统电商公司实施线下直营店运营模式下，当到店退货交叉收益较小时，电商公司可以提高产品销售价格。与未开设线下实体店运营模式下相比，消费者总需求量增加、退货量增加。
（3）若线下直营店投入固定成本较低，但高于体验店投入固定成本时，电商公司此时反而选择开设线下直营店可从中获利。但当开设线下直营店和体验店需投入高昂的固定设施，此时开设线下直营店和体验店对电商公司都是无利可图的，此时电商公司应继续保持单一线上渠道。
（4）当线上退货逆向物流成本较低时，此时零售商开设线下体验店是有利可图。相反，当线上退货逆向物流成本较高，开设线下直营店情形下利润总是优于开设线下体验店情形下利润。
（5）当消费者线上退货不便利成本较低时，此时零售商开设线下体验店是有利可图，当消费者线上线上退货不便利成本较高，此时零售商开设线下直营店占优。
（6）当产品匹配率较高时，此时电商公司应开设线下直营店，而产品匹配率较低时，电商公司开设线下体验店占优。
（7）传统电商公司在开设线下渠道时，在三四线市开设大量的直营店迅速打开线下市场，而在一二线城市开设少量的体验店；个性化、定制化类产品实施体验店模式，而标准化、基础类产品实施直营店模式；考虑消费者退货便利性，开设直营店提供线下退货渠道。
参考文献
[1] UPS. European Study./2017.
[2]吴发涛.O2O环境下制造商渠道选择与协调策略[D]浙江工商大学,2018.
[3] Oliver Wyman .McKcnzic, R, Chan, W.C. China's apparel btl: onlinc or olinc? Yes- -both.aparcl-battle pdf 201908-09.
[4] Shang, Guangzhi, ct al. Using transactions data to improve consumer returms forecasting. Journal ofOpcrations Man agement, 2020.66(3):26-348.
[5] UPS. A Con sumcr Expcricnce Study /,2019.
[6] UPSEmpowered shoppers propel retail changc. -shoppcr/ 2015.
[7] Rigby D. The future of shopping[] Harvard busincss revicw, 2011, 89(12):65-76.
[8] Bodhani A. Shops offer the c-tail expcricnce[J ].Enginccring & Technology, 2012, 7(5):46-49.
[9] 李飞全渠道零售的含义、成因及对策一- 再论迎接中国多渠道零售革命风暴[].北京工商大学学报(社会科学版)，2013(02):1-11.
[10] Lazaris C, Vrechopoulos A. From multi -chanel to“omni chane1" retailing review of the liter ature andcalls for rescarch[C ]/2nd Intcm ational Conference on Contemporary Marketing Is,(ICCMI).2014,6: 1-
[11] Bhalla R. The omni-channdl customer expericncc: Driving cengagcment through digiti sation[J]. Journalof Digital & Social Mcdia Marketing, 2014, 1(4): 365-372.
[12] Neslin S A, Jerath K, Bodapati A, et al. The interrel ation ships between brand and channel choice[J].Markcting Letters, 2014, 25(3): 319 -330.
[13] Bell D R, Gallino S, Moreno A. How to win in an omnichannel world[J]. MIT Sloan M an agementRevicw, 2014, 56(1): 45-53.
[14] 齐永智,张梦霞.全渠道零售:演化、过程与实施[J].中国流通经济2014,28(12):115-121.
[15] Verhoef P C, Kannan P K, Inman J J. From multi-channcl retailing to omni -channcl retailingintoduction to the special isue on muli channel railing[J]. Joumal of rtailing, 2015, 91(2): 174-181.
[16] Brynjolfsson E, Hu, Y.J, & Rahman, M. S. Compcting in the agc of omnichanncl retaling[J]. MITsloan management Revicw, 2013, 54(4):23.
[17] 曹班石.从苏宁到苏宁易购看全渠道零售[J ].信息与电脑, 2013, (10):34-36
[18]林疆燕新华书店借势全渠道转型升级探析[J].出版发行研究2014, (5):46-48
[19]张涛.红星美凯龙全渠道困局[J].中国商界2016(Z1 ):3841.
[20]许慧珍全渠道下传统零售商业模式创新[J ].商业经济研究，,20 15(12):20-21.
[21]高道友全渠道战略背景下的零售商业模式创新[I].商业经济研究2016( 12):129-131.
[22] Chopra S. How omni channcl can be the futurc of retailing[]. Deci sion, 20 16, 43(2): 135-144.
[23] Hibner A, Holzapfel A, Kuhn H. Distribution systems in omni-channcl rtailing[J ]. Busincss Rescarch,20 16, 9(2): 255-296.
[24]汪旭晖,赵博,刘志从多渠道到全渠道:互联网背景下传统零售企业转型升级路径一基于银泰百货和永辉超市的双案例研究刀.北京工商大学学报(社会科学版),201 8,33(04)22-32.
[25]张旭梅,吴雨禾,吴胜男,但斌.互联网环境下生鲜实体店全渠道转型路径及机理研究一基于百果园2008~2018年纵向案例研究[ J].软科学,2020.34(03):129-136.
[26] Gallino S，Moreno A . Intcgration of Onlinc and Oflinc Channcls in Retail: The Impact of SharingRcliable Inventory Avail ability Informaion[J]. Social Science Electronic Publishing, 2014, 60(6): 1434- 1451.
[27] Gallino S, Morcno A, Stamatopoulos I. Channcl intcgration, sales dispersion, and inventoryman agcment[J]. Management Scicncc, 2017, 639 ): 2813-2831.
[28] Bcll DR, Gallino S, Moreno A. Offline showooms in omnichanncl retail: Dem and and opcrationalbenefits. Management Science ,2017 ,64(4):1629-1651.
[29] Kumar A, Mchra A, Kumar S . Why do storcs drive onlinc salcs? evidencc of underlying mechanismsfrom a multichanncl retailer. Information Systems Rcscarch,20 I9 ,30( l);3 19 -338.
[30] Mahar s, Wnight P D, Bretthauer K M, ct al. Optimizing marketer costs and consumer bencfits across“clicks" and“bricks"[]. Jouna1 of the Academy of Mark eting Science, 2014, 42(6): 619-641.
[31] Harsha P, Subramanian S, Uichanco J. Omni channel revenuc m an agcment through integrated pricingand fufllment planning[R]. Ross School of Bu sincss, University of Michigan, 2016.
[32] Gao F, Su X. Omnichannel retail operations with buy-onlinc-and -pick-up-in- store[J]. ManagementScience, 2016a, 63(8): 2478-2492.
[33] Gao F, Su X. Online and fflinc information for omnichanncl retailing[]. M anufacturing & ServiceOpcrations Management, 2016b, 19(): 84 98.
[34] Gao F, Su X.Omnichanncl scrvice opcrations with onlinc and offlinc self order tochnologics.Man agement Science ,2017,64(8):359 5-3608.
[35] Govind arajan A, Sinha A, UichancoJ. Inventory optimization for fulillment intcgration in omnichannclretailing[R]. Working Paper, Ross School of Business, 2017.
[36] Govind arajan A, Sinha A, Uichanco J. Joint inventory and fulillment dcisions for omnichanncl retailnetworks[R]. Naval Research Logi stics (NRL), 2018.
[37] Nault B R, Rahman M S. Proximity to a traditional physical store: The efects of mitigating onlinedisutility costs[J]. Production and Opcrations Man agement, 2019, 28(4): 1033-1051.
[38] Li G, Zhang T, Tayi G K. Inroad into omni -channel retailing: Physical showroom deployment of anonline rctailer[J]. E uropcamn Joumal of Opcrational Research, 2020, 283(2): 676-69 I.
[39 ] Park J, Dayari an I, Montreuil B. Showeasing optimization in omnichannel retailing[J ]. European Journalof Opcrational Rescarch, 2020.
[40] LinX, ZhouY W, Hou R. Impact of a“Buy onlinc-and -pickup-in- store”Chane1 an Price and QualityDecisions in a Supply Chain[]. European Joumal of Opcrational Rescarch, 2020.
[41] Su X. Con sumer returns policics and supply chain performance[]. M anufacturing & Service OpcrationsMan agement, 2009, 11(4): 595-612.
[42] ShulmanJ D, Coughlan A T, Savaskan R C. Optimal reverse channcl structure for consumer productretums[J ]. Markcting Scicncc, 2010, 29(6): 1071-1085.
[43] Chen, J, Zhang, H. The impact of customer returms on competing chains[J]. Intem ation al Journal ofManagement Science and Engincening Management, 2011, 6(1): 58-70.
[4]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.
[45] Akgay Y, Boyaca T, Zhang D. Selling with money-back guar anees: The impact on prices, quantities,and retail prfitbility[J]. Production and Opcrations M an agcment, 2013, 22(4): 77-79 1.
[46] Hsiao L, Chen Y J. Return policy. Hassle-free ar your money-back guar antee?[J]. Naval RescarchLogi stics (NRL),2014, 61(5): 403-417.
[47] Ofek E, Katona Z, Sarvary M“Bricks and clicks" The impact of pr oduct returns on the strategies ofmulichanncl rctailers[J]. Markcting Sciencc. 2011, 30(1 ):42 60.
[48] Chen,J , Bell,P. C. Implemcnting market scgmentation u sing full-rcfund and no -refund customer returmspolicics in a dual -channcl supply chain structure[J]. In tcrnational Journal of Production Economics, 2012,136( 1):56-66
[49] Li, Y, Xu, L.. Li, D. Examining relationships bctween the returm policy, product quality, and pricingstratcgy in onlincompany ownod selling[J]. Intemnational Joumal of Production Economics, 2013,144(2):451 460.
[50]曹细玉.需求与退货价格具有相关性的双渠道供应链模型与协调[J]华中师范大学学报(自然科学版),2015,49(03 ):470-476.
[51]李建斌,李赞.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2016,3611);2811-2819.
[52] Chen B, Chen J . When to introducc an onlinc channcl, and offer moncy back guarantccs andperson alized pricing? [J] European Joum al of Opcration al Research,2017. 257(2):6 14-624.
[53] ChenJ, Chen B,Li W .Who should be pricing leader in the pre scncc of customer returns? [J]. EuropcanJourm al of Opcrational Research,20 I 8.265(2):735-747.
[54] Ertckin N. Immediate and long-tcrm bencfits of in -storc return expcricncc. [J]. Production andOperations Man agement ,2018, 27(1):121-142.
[55] Xu X, Jackson J E. Investigating the influcntial factors of returm channcl loyalty in omni-channcl .retailing[]. Intern ational Joumal of Production Economics, 2019, 216: 118-132.
[56]赵菊,张强,程薇嘉. B2C零售商退货渠道策略研究[D].运筹与管理, 2019, 028(012):130-136.
[57] Radhi M, Zhang G. Optimal cross-channcl return policy in dual channcl retailing systems. [凹].nterm: ational Journal of Production Economics ,2019,2 10: 184-198.
[58]杨道箭,张秀杰不确定需求下全渠道运营退货策略[ ].预测2020,39(02):84-89.
[59] Jin D, Caliskan-Demirag 0, ChenF Y, et al. Omnicharnel retailers' retun policy strategies in thepresence of competion[J]. Interm ational Journal of Production Economics, 2020, 225: 107595.
[60] Nagcswaran L, Cho S H, Scheller-Wolf A. Con sumer recturn policics in omnichanncl opecrations[].Man agement Science, 2020, 66(12): 5558-5575.
[61]Gao F, Agrawal V V, Cui S. The Efect of Mulichanncl and Omnichanncl Retailing on Physical Stores[].Man agement Science, 202 l:1-18.
[62] ChintaguntaP K ,Chu J, Ccbollad aJ Quantifying Transaction Costs in Online/Off-linc Grocery ChannclChoice[J]. Marketing Scicnce. 2012, 31(I): 96-114.
[63] Kons U, NeslinS A, VerhoefP C. The effect of sear ch channel elimination on purchase incidence,order size and channcl choicc[J ]. Intern ational Journal of Rcscarch in Markcting. 2014, 31(1): 49-64.
[64]周利兵,钱慧敏.二元渠道下消费者渠道选择行为研究[]统计与信息论坛201 5,30(05):105-112.
[65] Park S,Lcc D. An Empirical Study on Consumer Onlinc Shopping Channcl Choicc Bchavior in Omni-channel Environment[J]. Tclematics & Informatics, 2017, 34(8): 1398-1407.
[66] Li J, KornusU, Langerak F, et al. Customer chanel migration and firm choice: The ffcts of cross-channcl competition[J]. Intcrnation al Joumal of Electronic Commercc, 2017,21(): 8-42.
[67] Xu X, Jackson J E. Examining customer channcl sclcction intention in the omnichanncl retailcnvironment[]. Intem ation al Journal of Production Economics, 2019, 208: 434 445.
[68] Marcucci E, Gatta V, Lc Pira M,ct al. Bricks or clicks? Con sumer channel choice and its tran sport andenvironment al implications for the grocery market in Norway[J]. Citics, 2021, 110: 103046.
[69] Wang W,Li G, ChengT C E. Channel sclection in a supply chain with a multi channcl rctailer: The roleof channcl opcrating costs[J]. Intern ational Joumal of Production Economics, 2016, 173: 54-65.
[70]张鹏制造商线上分销渠道模式选择研究[ ].技术经济与管理研究2018( 10)11-16.
[7I] 李柏勋,南雅如,郭佳.考虑风险规避的渠道选择策略:直营店vs加盟店[J].数学的实践与认识201 8,48(04):58-69.
[72]颜波,刘巳.考虑消费者时间偏好和不便成本的手机企业渠道动态选择研究[D].管理工程学报2019,33(04):113-121.
[73] Zhang Y, Hczarkhani B. Compcttion in dual channcl supply chains: The manufacturers' chanclslection[J]. European Jourmal of Opcrational Rescarch, 202 l, 291(1): 244-262.
[74] Turban, E, Lee,J. K, King, D, Liang, T P, & Turban, D. Elcctronic commerce 2010. Prentice HalPress.2009
[75]齐永智,张梦霞.SOLOMO消费驱动下零售企业渠道演化选择:全渠道零售[].经济与管理研究201 5,36(07):137-144.
[76] Burdin T. Omni-channcl retailing the brick，click and mobile revolution [ EB/OL].
[77]Li Y, Xu L,Choi T M, ct al. Optimal aduac-selling stratcgy for fashion able products with opportunisticcon sumers returms[J ]. EEE Tran sactions on Systems, Man, and Cybermetics: Systems, 2013, 44(7): 938-952.
[78] GuidcJrV D R, Souza G C, Van Wasscnhove L N, ct al. Timc valuc of commercial product rctums[J].Man agement Sciencc, 2006, 52(8);: 1200-1214.
[79] Su Xuanming. Consumer rcturns policics and supply chain performance[]. M anufacturing & SericeOpcrations Man agement, 2009, 11(4): 595-612.
[80]Gao F,Agrawal V V, Cui S. The Ecct of Mulichannel and Omnichanncl Retaling on Physical Stores[J].Man agemcnt Scicnce, 202 1();1-1 8.
[8I]Cao L, Li L. The inpact of coss-charmnel inte ati om on rtailers sales growth[]. Joumal of Retaling2015, 91(2): 198-2 16.
[82] Zhang J, Farris P W, Irvin J W, et al. Crafting integrated multichannel retaling stratcgics[J]. Joumal ofintcractive markcting, 2010, 24(2): 168 180.
[83] UPS.Today's Global Online Shopper. https: /so1vers ups cam/ups-pulsc-of the onlinc-shopper/,2018.
