基于品类管理和需求外生模型的医药电商网页空间优化策略

doi:10.16381/j.cnki.issn1003-207x.2018.05.014

摘要/Abstract

摘要： 网页空间优化对电子商务企业的绩效有着显著影响。本文结合医药品的特性，利用需求外生模型从品类管理的角度研究医药电商的网页空间优化问题，即有限网页空间内的内容优化与内容布局优化。考虑存在商品缺货以及蚕食效应的情况下，本文首先基于需求外生模型使用极大似然估计法估计了商品市场份额与商品替代率，然后提出最大市场份额指标并构建了一个加权最大市场份额最大化的整数规划模型来优化医药电商网页的内容与内容布局。通过对中国知名医药电商1药网2015年8月1日到10月31日的乙肝类抗病毒药物专栏的销售数据进行实证分析，结果表明，本模型优化的推送内容和布局顺序可以有效提高1药网各药品专栏最高至27.21%的销量，乙肝其他抗病药物专栏可以提高8.06%。研究表明，本文提出的基于最大市场份额最大化的优化模型能有效决策网页空间优化来提高医药电商的销量与市场占有率。

关键词: 需求外生模型, 医药电商, 品类管理, 网页空间优化

Abstract: With the liberalization of the policy, pharmaceutical e-tailing keeps surging forward challenging the status of traditional pharmacies. Unlike the daily use products sold by traditional e-tailing, pharmaceutical products sold by pharmaceutical e-tailing have extremely high brand concentration which means the difference between similar products is brand only. In this article, the decision making problem is studied from the perspective of pharmaceutical e-tailing in order to expand its market share.Customers usually are unwilling to go through all the website space of pharmaceutical e-tailing, but only browse the home page and make the purchasing decision. Therefore, how to optimize the website space especially the home page in order to expand the market is an interesting question. Comparing with the shelf space optimization in offline channel, the website space optimization in online channel is quite different. The traditional shelf space optimization regard all the positions in single shelf is homogeneous, while the website space optimization consider the perception of viewer to define the space of website especially the home page is heterogeneous. First the market share and substitutions between products are estimated through the demand exogenous model with the input of historical sales volume. Then we the market share and substitutions between products are regarded as the input of the website space optimization in order to generate the display list and order in home page of pharmaceutical e-tailing.In traditional research of category management, Multinomial Logit model which has vulnerability that it assumes the stochastic components of utility follow independent identical distribution is adopted. In reality, there are many factors which can simultaneously affect the utility and the market share of different choices. Considering the extremely high brand concentration of pharmaceutical products, Multinomial Logit model is invalid here. Therefore, the exogenous demand model which has more degree of freedom is employed to incorporate market variables into the consumers' buying behavior.Based on the shelf management model with slotting fee and the maximum potential market share obtained by exogenous demand model, ignoring the number of exhibition,an website space optimization model of integer programming based on an brand-new concept named the biggest market share is construeted to maximize the utility of the pharmaceutical e-tailing by deciding the sequence of posted products.Meanwhile, using the sales data of 111.com during August 1^st to October 30^th in 2015, an empirical study is conducted to investigate the potential performance of the proposed website space optimization model. The data is first sifted in order to get rid of the abnormal ones and input the normal data into the estimating model. Results demonstrate that the website space optimization model we proposed can significantly improve the sales of pharmaceutical e-tailing by 8.06% in average, and up to 27.21%. Although we lack of chance to evaluate the effect of changing the display number of product in home page, we theoretically measure that fewer display may also reach the profit that pharmaceutical e-tailing expects.

Key words: exogenous demand model, pharmaceutical e-tailing, category management, website space optimization

中图分类号:

C934

李建斌, 郑宇婷, 戴宾. 基于品类管理和需求外生模型的医药电商网页空间优化策略[J]. 中国管理科学, 2018, 26(5): 138-146.

LI Jian-bin, ZHENG Yu-ting, DAI Bin. Website Space Optimization Strategy of Pharmaceutical E-tailing under Category Management and Exogenous Demand Model[J]. Chinese Journal of Management Science, 2018, 26(5): 138-146.

参考文献

[1] 冯芷艳,郭迅华,曾大军,等. 大数据背景下商务管理研究若干前沿课题[J]. 管理科学学报,2013,16(1):1-9.

[2] Kouvelis P,Xiao Yixuan,Yang Nan. PBM competition in pharmaceutical supply chain:Formulary design and drug pricing[J]. Manufacturing & Service Operations Management,2015,17(4):511-526.

[3] 易观千帆. 中国医药电商市场专题研究报告2016[EB/OL].[2016-07-08]. http://www.analysys.cn/view/report/detail.html?columnId=8&articleId=1000155.

[4] 王芳,叶作亮,杨亦行. 在线零售商运营的关键成功因素实证研究[J]. 中国管理科学,2014,22(11):409-414.

[5] 黎志成,刘枚莲. 电子商务环境下的消费者行为研究[J]. 中国管理科学,2002,10(6):88-91.

[6] 刘珊珊. 关于网站页面布局的最新方法研究[J]. 信息与电脑,2011,(2):77-77.

[7] 何丽萍. 基于网页设计的视觉信息传达有效性的研究[D]. 杭州:浙江大学,2006.

[8] 杨莉莉. 以用户体验为导向的电商购物网站界面设计研究[D]. 上海:华东理工大学,2013.

[9] 林欢. 图片优势效应在网页设计中的研究与应用[D]. 长沙:湖南大学,2014.

[10] Ghose A, Ipeirotis P G, Li Beibei. Examining the impact of ranking on consumer behavior and search engine revenue[J]. Management Science,2014,60(7):1632-1654.

[11] 章璇,景奉杰. 基于消费者购买行为的电子商务网站特性研究综述[J]. 电子商务,2012,56(4):136-142,130.

[12] 常亚平,韩丹,姚慧平,等. 在线店铺设计对消费者购买意愿的影响研究[J]. 管理学报,2011,8(6):876-884.

[13] 陈梅梅,侯晶. 基于商品品类的网络购买决策关键影响因素研究[J]. 上海管理科学,2014,36(4):78-84.

[14] 李远. 考虑网评的电商产品组选择问题研究[D]. 成都:西南财经大学,2014.

[15] Guadagni P M,Little J D C. A logit model of brand choice calibrated on scanner data[J]. Marketing Science,1983,2(3):203-238.

[16] Gaur H. Assortment planning and inventory decisions under a locational choice model[J]. Management Science,2006,52(10):1528-1543.

[17] Smith S A,Agrawal N. Management of multi-item retail inventory systems with demand substitution[J]. Operations Research,2000,48(1):50-64.

[18] Fisher M,Vaidyanathan R. A demand estimation procedure for retail assortment optimization with results from implementations[J]. Management Science,2014,60(10):2401-2415.

[19] Yang M H. An efficient algorithm to allocate shelf space[J]. European Journal of Operational Research,2001,131(1):107-118.

[20] Kök A G,Fisher M L. Demand estimation and assortment optimization under substitution:Methodology and application[J]. Operations Research,2007,55(6):1001-1021.

[21] Mahajan S,van Ryzin G. Stocking retail assortments under dynamic consumer substitution[J]. Operations Research,2001,49(3):334-351.

[22] 赵菊. 供应链环境下的货架展示与库存控制优化模型研究[D]. 合肥:合肥工业大学,2011.

[23] Johnson E J, Moe W W, Foder P S, et al. On the depth and dynamics of online search behavior[J]. Management Science,2004,50(3):299-308.

[24] 程砚秋,迟国泰. 基于核主成分分析的生态评价模型及其应用研究[J]. 中国管理科学,2011,19(3):182-192.

[25] Hübner A H, Kuhn H. Retail category management:State-of-the-art review of quantitative research and software applications in assortment and shelf space management[J]. Omega, 2012, 40(2):199-209.

[26] Hübner A, Schaol K. An integrated assortment and shelf-space optimization model with demand substitution and space-elasticity effects[J]. European Journal of Operational Research, 2017, 261(1):302-316.