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数据分析与知识发现  2018, Vol. 2 Issue (9): 10-21     https://doi.org/10.11925/infotech.2096-3467.2018.0164
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
品牌对商品在线销量的影响*——基于海量商品评论的在线声誉和品牌知名度的调节作用研究
刘丽娜1,2,4, 齐佳音2,3(), 张镇平5, 曾丹1
1北京邮电大学经济管理学院 北京 100876
2北京邮电大学可信分布式计算与服务教育部重点实验室 北京 100876
3上海对外经贸大学工商管理学院 上海 201620
4北京邮电大学民族教育学院 北京 102209
5北京邮电大学理学院 北京 100876
Analyzing Impacts of Brand Reputation on Online Sales Based on Massive Commodity Reviews and Brand
Liu Lina1,2,4, Qi Jiayin2,3(), Zhang Zhenping5, Zeng Dan1
1School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
2Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education,Beijing 100876, China
3School of Management, Shanghai University of International Business and Economics, Shanghai 201620, China
4School of Ethnic Minority Education, Beijing University of Posts and Telecommunications, Beijing 100876, China
5School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
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摘要 

【目的】研究海量商品评论所隐含的商品在线声誉值对于品牌对商品在线销售量影响的调节作用。【方法】以京东商城手机商品的销售为背景, 通过自然语言处理和机器学习等技术, 利用联合分析法, 精准而全面地计算商品的在线声誉值, 并构建模型探究品牌的两个维度(品牌竞争力和品牌来源国(地区))对于商品销量的影响, 以及在线声誉和品牌知名度对上述影响的调节作用。【结果】在电子商务时代, 品牌竞争力依然是影响商品销量的重要因素, 在线声誉对于品牌竞争力对商品销售的影响起到正向调节作用, 而商品知名度则会削弱品牌来源国(地区)对商品销量的影响。【局限】只针对搜索型商品进行相关分析, 而体验型商品并未涉及。【结论】使用本文方法计算出的商品在线声誉加强了品牌竞争力对销售的影响, 可以为电商平台的在线声誉系统提供更加客观而有益的补充, 具有较高的商业化推广前景。

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刘丽娜
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曾丹
关键词 品牌海量商品评论在线声誉机器学习商品销量    
Abstract

[Objective] The paper studies the impacts of brand reputation on the online sales volume of commodities. [Methods] First, we retrieved the sales data of mobile phones from Jingdong Online Mall. Then, we used conjoint analysis to calculate the online reputation of commodities with the help of natural language processing and machine learning technologies. Third, we built a model to explore the impacts of brand competitiveness and its country-of-origin on sales. [Results] We found that brand competitiveness was an important factor influencing the sales of commodities. Online reputation increased the impact of brands’ competitiveness, and brand awareness weakened the impacts of brand country-of-origin. [Limitations] The paper only analyzed the search products, which did not include the experience products. [Conclusions] The online reputation calculated by the proposed method enhances the impacts of brand competitiveness on sales. This study could help e-commerce platforms improve their online reputation management system.

Key wordsBrand    Massive Commodity Reviews    Online Reputation    Machine Learning    Sales of Commodities
收稿日期: 2018-02-08      出版日期: 2018-10-25
ZTFLH:  分类号: C931  
基金资助:*本文系国家自然科学基金重大研究计划项目“大数据驱动的管理与决策研究”培育项目——“大数据驱动的三类典型工商市场主体风险识别决策研究”(项目编号: 91546121)和国家社会科学基金重大研究课题项目“面向国家公共安全的互联网信息行为及治理研究”(项目编号: 16ZDA055)的研究成果之一
引用本文:   
刘丽娜, 齐佳音, 张镇平, 曾丹. 品牌对商品在线销量的影响*——基于海量商品评论的在线声誉和品牌知名度的调节作用研究[J]. 数据分析与知识发现, 2018, 2(9): 10-21.
Liu Lina,Qi Jiayin,Zhang Zhenping,Zeng Dan. Analyzing Impacts of Brand Reputation on Online Sales Based on Massive Commodity Reviews and Brand. Data Analysis and Knowledge Discovery, 2018, 2(9): 10-21.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2018.0164      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2018/V2/I9/10
  本研究的概念模型
属性
评论
属性1 属性2 属性3 属性n
评论1 1 -1 NA 0
评论2 0 1 1 -1
评论3 -1 -1 0 1
NA 1 1 NA
评论p -1 0 -1 1
  产品属性评价矩阵
  产品属性词典和评价情感词典构建流程
属性值 权重值 属性值 权重值
系统 0.341805 相机 0.046815
其他 0.090546 功能 0.046389
信号 0.083553 屏幕 0.04296
容量 0.079986 价格 0.033945
电池 0.064467 版本 0.024334
手感 0.060609 CPU 0.018114
外观 0.048572 物流 0.017905
  手机产品属性的权重值
手机编号 在线美誉度 百度搜索指数 在线声誉
1 0.593745 2146 4.554828570
2 0.656940 468 4.039172058
3 0.835454 294 4.748369351
4 0.616323 2146 4.728038432
5 0.750180 2300 5.806895190
101 0.685705 837 4.614673349
  各款手机的在线美誉度、百度搜索指数及在线声誉值
变量 含义 N 平均值 标准差 最小值 最大值
销量排名 手机的销售排名 101 58.46535 38.69898 1 101
品牌竞争力 手机品牌是否在“中关村在线”中的“手机品牌排行榜”位于前10名 101 0.3366337 0.4749153 0 1
品牌来源国(地区) 是否为中国本土品牌 101 0.6831683 0.4675616 0 1
上架时间 手机的上架时间, 以月为单位 101 10.1188119 3.5856897 0 15
价格 手机的价格 101 1306.931 138.3024 1049 1499
促销活动 手机是否有促销活动 101 0.346535 0.478239 0 1
评论数量 手机的评论总数 101 2014.545 2909.118 30 12473
差评率 评论星级为1星或2星的评论总数占总评论数的百分比 101 3.594059 2.665251 0 19
平均星级评分 评论星级的平均分 101 4.467924 0.173498 3.549296 4.828897
在线声誉 手机的在线声誉 101 4.3813679 0.9660922 2.2591451 6.5364787
网络知名度 手机的网络知名度 101 1043.545 1688.895 46 13489
  描述性统计结果
变量 模型I 模型II
估计值 显著性p 估计值 显著性p
β (常量) 5.030504 0.365 5.543441 0.285
brand_rec -0.49758** 0.005 -0.87397** 0.001
brand_cou 0.058222 0.729 1.310094** 0.009
time_of_rel -0.83646** 0.007 -0.83077** 0.005
ln(price) -0.37169 0.568 -0.44783 0.463
discount 0.191785 0.240 0.068835 0.662
ln(num_of_review) -0.32641*** 0.000 -0.3217*** 0.000
ratio_of_bad 0.028483 0.406 0.031214 0.329
avg_rating 0.934582 0.085 0.947879 0.066
brand_rec×reputation 36.66385* 0.036
brand_cou×ln(awareness) -0.20379** 0.005
R2 0.527 0.598
调整R2 0.486 0.553
观测样本 101 101
AIC[43] 2.109 1.986
显著性水平 0.000 0.000
  模型I和模型II的回归结果
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