Optimal Control of Selling Channels for an Online Retailer with Cost‐per‐Click Payments and Seasonal Products

The problem studied in this paper is a predigestion of the decision faced by online retailers (etailers) that advertise on publisher or comparison‐shopping websites. An etailer may sell its product not only through its online and bricks‐and‐mortar stores, but also through the websites of one or more third parties (e.g., Yahoo.com). However, the etailer has to pay a certain amount to such third parties in an action‐based payment scheme, such as a cost‐per‐click (CPC) scheme. Under the CPC scheme, payment is based solely on click‐throughs, which means that the etailer pays only when a shopper clicks through to the product page of its website. Only a fraction of such clicks lead to actual sales. The extra cost that is associated with shoppers who first click through to the third‐party websites makes them less attractive as customers than those who directly visit the etailer's online store. Moreover, the CPC rate for a prominent placement is normally set by competitive bidding, and thus varies over time. Therefore, the etailer needs to decide dynamically whether or not to list on a third‐party website. The structural properties of the optimal policy are discussed, and numerical examples are given to show the revenue impact of dynamic listing control.     

在线关键词广告研究综述:新的研究方向

作为拍卖理论在电子商务领域的又一成功应用,在线关键词广告已经成为学术界和企业界共同关注的一个热点问题,近年来一直处于快速发展中。本文首先对在线关键词广告的实践创新进行了介绍;其次,就在线关键词广告的理论探索从拍卖机制、广告商策略行为与点击欺诈这三个重要研究问题的最新研究动态进行了分析与综述,并对国内学者在该方向的理论研究进行了总结;最后,文章对在线关键词广告的研究前景进行了探讨。     

Generalized choice models for categorical time series

The NDARMA models of Jacobs and Lewis (1983) allow the modeling of categorical processes with an ARMA-like serial dependence structure. These models can be represented through a backshift mechanism, and we analyze marginal and bivariate properties of the resulting backshift process. Motivated by this backshift mechanism, we define the new class of generalized choice (GC) models, which include the usual NDARMA models as a special case, and we derive results describing the marginal and bivariate distribution of the GC model. We discuss implications concerning DMA(∞) models and the serial dependence structure of NDARMA models. Examples show that the family of GC models allows creating sparsely parametrized models for categorical processes with different types of serial dependence structure.     

网络点击合同下在线消费者权益保护的法律问题研究

网络点击合同的出现是网络垄断势力不断扩张的结果。网络管理的非中心化强迫在线消费者被动服从网络服务商制订的不公平、不合理规则,使合同利益向己方倾斜。在线消费者公平交易权、知情权、隐私权、退换货及求偿权、人身财产安全保障权是未来《消费者权益保护法》、《合同法》等亟待完善的方面。行业自律、行政及法律手段三方并举,是切实保护在线消费者合法权益、维护法律正义、减少网络行为盲目性的理智选择。     

电商平台商品标题优化的有效性及其杠杆机制

与搜索引擎优化相似,商品标题优化作为提升搜索结果排名和产品曝光率的重要手段引起理论与实践的普遍关注,尤其是被期待能够在产品销量上获得进一步提升。但对其真实的营销效果现有研究并未深入分析。基于数字经济时代消费行为的5A模型和内容营销理论,采用联立方程模型,以天猫旗舰店某品牌小型家电为研究对象,在充分考虑产品价格、价格波动、产品推广、数值型口碑信息等因素的基础上,分析了电商平台商品标题优化与在线销售的关系,并从内容营销理论出发,基于“由外而内”的观点深入剖析了客观维度文本评论内容在电商平台商品标题优化的营销效果与在线销售间的杠杆作用。结果发现:电商平台商品标题优化对在线销售无显著影响,基于客观维度的文本评论中的产品属性情感倾向、售前与售后服务情感倾向、重购与推荐次数及重复购买提及次数有效地推进了电商平台商品标题优化带来的点击量向在线销售转化。     

手机APP广告点击意愿的影响因素研究

基于用户的角度,以整合信息技术模型（UTAUT）为基础,通过对手机用户关于APP广告态度的访谈结果以及有效问卷的数据分析,探讨了用户对于手机APP广告点击意愿的影响因素,并对如何更好促进国内手机APP广告行业发展提出了建议。     

搜索引擎用户对商品搜索结果的点击行为研究

探索消费者利用搜索引擎进行商品搜索时对于搜索出来的结果条目的点击行为。基于启发式和系统式信息处理模式理论,构建一个研究模型,即消费者对商品的熟悉程度会影响其在搜索结果中的点击位置,通过设计和实施两个实验室实验,以有上网经验的在校大学生为实验对象,对提出的模型和假说进行检验。研究结果表明,对于不同产品的搜索结果,消费者对于搜索结果的点击位置有显著差异。具体地说,对于消费者熟悉的那些产品,他们更多地点击靠近中间位置的选项,而对于消费者不太熟悉的商品,他们更多地点击搜索结果中比较靠前的选项。