Please wait a minute...
Advanced Search
现代图书情报技术  2013, Vol. Issue (6): 76-84    DOI: 10.11925/infotech.1003-3513.2013.06.12
  应用实践 本期目录 | 过刊浏览 | 高级检索 |
在线商品评论系统功能需求的Kano模型分析——以我国主要购物网站为例
孙霄凌1, 赵宇翔2, 朱庆华2
1. 南京大学工程管理学院 南京 210093;
2. 南京大学信息管理学院 南京 210093
Analyzing the Demand of Online Product Review System’ s Features Using Kano Model: An Empirical Study of Chinese Online Shops
Sun Xiaoling1, Zhao Yuxiang2, Zhu Qinghua2
1. School of Management & Engineering, Nanjing University, Nanjing 210093, China;
2. School of Information Management, Nanjing University, Nanjing 210093, China
全文: PDF(798 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 以网络口碑作用机制以及信息系统构建的核心问题为理论框架,对我国主要购物网站进行调研,获取商品评论系统的主要功能。以此为基础借助Kano模型对商品评论系统的功能需求进行分类。研究结果表明商品评论系统具备多样化功能,但消费者对大部分功能的需求感不强,只对针对评论内容和效价进行深度挖掘的功能,如基于文本挖掘的标签云和多维效价,体现出一定的现实和潜在需求。这一结果对改进商品评论系统的功能设计具有较强的参考价值。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
赵宇翔
孙霄凌
朱庆华
关键词 网络购物网络口碑在线评论系统信息组织Kano模型电子商务    
Abstract:Based on the impact of electronic word-of-mouth and critical issues of online information system design, this paper conducts a feature package of online product review system by a survey of mainstream Chinese online shops. Kano model then employs to classify customer demand about these features. The result indicates that among various features most of them are dispensable except of features which making deep mining on argument quality and valence such as tag clouds based on text mining as well as multiple valences. It can be important reference when dealing with system design and improvement.
Key wordsOnline shopping    Electronic word-of-mouth    Online review system    Information organizing    Kano model    Electronic commerce
收稿日期: 2013-04-16     
:  G350  
基金资助:本文系国家社会科学基金重点项目“互联网用户群体协作行为模式的理论与应用研究”(项目编号:10ATQ004)和江苏省普通高校研究生科研创新计划项目“社会化商务社区中消费行为建模与激励机制设计”(项目编号:CXZZ11_0055)的研究成果之一。
通讯作者: 孙霄凌     E-mail: sxl.shining@gmail.com
引用本文:   
孙霄凌, 赵宇翔, 朱庆华. 在线商品评论系统功能需求的Kano模型分析——以我国主要购物网站为例[J]. 现代图书情报技术, 2013, (6): 76-84.
Sun Xiaoling, Zhao Yuxiang, Zhu Qinghua. Analyzing the Demand of Online Product Review System’ s Features Using Kano Model: An Empirical Study of Chinese Online Shops. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2013.06.12.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2013.06.12
[1] Park D, Lee J. eWOM Overload and Its Effect on Consumer Behavioural Intention Depending on Consumer Involvement[J]. Electronic Commerce Research and Applications, 2008, 7(4):386-398.
[2] Chevalier J A, Mayzlin D. The Effect of Word of Mouth on Sales: Online Book Reviews[J]. Journal of Marketing Research, 2006,43(3):345-354.
[3] 龚诗阳,刘霞,刘洋,等.网络口碑决定产品命运吗——对线上图书评论的实证分析[J]. 南开管理评论,2012,15(4): 118-128.(Gong Shiyang, Liu Xia, Liu Yang, et al. Does Online Word-of-Mouth Determine Product’s Fate: An Empirical Analysis of Online Book Review[J]. Nankai Business Review, 2012,15(4):118-128.)
[4] 马玉涛,蔡淑琴,叶波,等.基于DOC视角的在线客户评论加工模型研究[J]. 情报学报,2011,30(12): 1293-1301.(Ma Yutao, Cai Shuqin, Ye Bo, et al. Study on the Processing Model of Online Customer Reviews from DOC Perspective[J].Journal of the China Society for Scientific and Technical Information, 2011, 30(12):1293-1301).
[5] Liu Q, Karahanna E, Watson R T. Unveiling User-generated Content: Designing Websites to Best Present Customer Reviews[J].Business Horizons, 2011,54(3):231-240.
[6] 戴维·迈尔斯.社会心理学(英文版)[M].北京:人民邮电出版社, 2012: 228-244.(Myers D G. Social Psychology[M].Beijing: Post & Telecom Press, 2012: 228-244.)
[7] Cheung C M K, Thadani D R. The Impact of Electronic Word-of-mouth Communication: A Literature Analysis and Integrative Model[J]. Decision Support Systems, 2012, 54(1): 461-470.
[8] 蔡淑琴, 邱洁, 王旸,等.互联网点评信息的有序性与序化方法研究[J]. 情报杂志, 2012, 31(3): 168-173, 167.(Cai Shuqin, Qiu Jie, Wang Yang, et al. Order and Ordering Methods of Online Customer Reviews[J]. Journal of Intelligence, 2012, 31(3):168-173,167.)
[9] Mudambi S M, Schuff M. What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com[J]. MIS Quarterly, 2010, 34(1): 185-200.
[10] Purnawirawan N, Pelsmacker P D, Dens N. Balance and Sequence in Online Reviews: How Perceived Usefulness Affects Attitudes and Intentions[J]. Journal of Interactive Marketing, 2012, 26(4): 244-255.
[11] Sikora R T, Chauhan K. Estimating Sequential Bias in Online Reviews: A Kalman Filtering Approach[J]. Knowledge-Based Systems, 2012, 27:314-321.
[12] Hu N, Zhang J, Pavlou P A. Overcoming the J-shaped Distribution of Product Reviews[J]. Communications of the ACM, 2009, 52(10):144-147.
[13] Qiu L Y, Wang W Q. The Effects of Message Order and Information Chunking on eWOM Persuasion[C]. In: Proceedings of the 15th Pacific-Asia Conference on Information Systems (PACIS 2011), Brisbane, Australia.2011.
[14] Schlosser A E. Can Including Pros and Cons Increase the Helpfulness and Persuasiveness of Online Reviews? The Interactive Effective Effects of Rating and Arguments[J]. Journal of Consumer Psychology, 2011, 21(3): 226-239.
[15] Yatani K, Novati M, Trusty A, et al. Review Spotlight: A User Interface for Summarizing User-generated Reviews Using Adjective-noun Word Pairs[C]. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’11), Vancouver, Canada. New York: ACM Press, 2011:1541-1550.
[16] Kano N, Seraku N, Takahashi F, et al. Attractive Quality and Must-be Quality[J]. Journal of the Japanese Society for Quality Control (in Japanese), 1984, 14 (2): 39-48.
[17] Xu Q, Jiao R J, Yang X, et al. An Analytical Kano Model for Customer Need Analysis[J]. Design Studies, 2009, 30(1):87-110.
[18] 唐中君, 龙玉玲.基于Kano模型的个性化需求获取方法研究[J]. 软科学, 2012, 26(2): 127-131.(Tang Zhongjun, Long Yuling. Research on Method of Acquiring Individual Demand Based on Kano Model[J]. Soft Science, 2012, 26(2): 127-131.).
[19] Shen X X, Tan K C, Xie M. An Integrated Approach to Innovative Product Development Using Kano’s Model and QFD[J]. European Journal of Innovation Management, 2000, 3(2):91-99.
[20] Tontini G. Integrating the Kano Model and QFD for Designing New Products[J]. Total Quality Management & Business Excellence, 2007, 18(5): 599-612.
[21] Lee Y C, Huang S Y. A New Fuzzy Concept Approach for Kano’s Model[J].Expert Systems with Applications, 2009,36(3): 4479-4484.
[22] von Dran G M, Zhang P, Small R. Quality Websites: An Application of the Kano Model to Website Design[C]. In: Proceedings of AMCIS 1999, Milwaukee, USA. 1999: 314.
[23] Zhang P, von Dran G M. User Expectations and Rankings of Quality Factors in Different Web Site Domains[J]. International Journal of Electronic Commerce, 2002, 6(2): 9-33.
[24] Kuo Y F. Integrating Kano’s Model into Web-community Service Quality[J]. Total Quality Management & Business Excellence, 2004, 15(7): 925-939.
[25] Berger C, Blauth R, Boger D, et al. Kano’s Method for Understanding Customer-defined Quality[J]. Center for Quality of Management Journal, 1993,2(4):3-35.
[26] Brynjolfsson E, Hu Y J, Smith M D. From Niches to Riches: Anatomy of the Long Tail[J]. MIT Sloan Management Review, 2006, 47(4):67-71.
[27] Brynjolfsson E, Hu Y J, Simester D. Goodbye Pareto Principle, Hello Long Tail: The Effect of Search Costs on the Concentration of Product Sales[J]. Management Science, 2011, 57(8): 1373-1386.
[28] Khare A, Labrecque L I, Asare A K. The Assimilative and Contrastive Effects of Word-of-Mouth Volume: An Experimental Examination of Online Consumer Ratings[J]. Journal of Retailing, 2011, 87(1): 111-126.
[29] Walther J B, Liang Y, Ganster T, et al. Online Reviews, Helpfulness Ratings, and Consumer Attitudes: An Extension of Congruity Theory to Multiple Sources in Web 2.0[J]. Journal of Computer-Mediated Communication, 2012,18(1): 97-112.
[30] Willemsen L M, Neijens P C, Bronner F. The Ironic Effect of Source Identification on the Perceived Credibility of Online Product Reviewers[J]. Journal of Computer-Mediated Communication, 2012,18(1): 16-31.
[31] Wang Y, Fesenmaier D R. Towards Understanding Members’ General Participation in and Active Contribution to an Online Travel Community[J]. Tourism Management, 2004, 25(6):709-722.
[32] Lampel J, Bhalla A. The Role of Status Seeking in Online Communities: Giving the Gift of Experience[J]. Journal of Computer-Mediated Communication, 2007, 12(2):434-455.
[33] Eagly A H, Chaiken S. The Psychology of Attitudes[M]. Orlando: Harcourt Brace Jovanovich College Publishers, 1993: 325.
[34] McKinney V, Yoon K, Zahedi F M. The Measurement of Web-customer Satisfaction: An Expectation and Disconfirmation Approach[J]. Information Systems Research, 2002, 13 (3): 296-315.
[1] 李晓峰,马静,李驰,朱恒民. 基于XGBoost模型的电商商品品名识别算法研究 *[J]. 数据分析与知识发现, 2019, 3(7): 34-41.
[2] 梁晓蓓,徐真,李晶晶. 共享短租平台商家属性对消费者网络口碑的影响研究*[J]. 数据分析与知识发现, 2018, 2(11): 46-53.
[3] 王宇,李秀秀. 基于电子商务评论的商家信誉维度构建*[J]. 数据分析与知识发现, 2017, 1(8): 59-67.
[4] 薛福亮,刘君玲. 基于用户间信任关系改进的协同过滤推荐方法*[J]. 数据分析与知识发现, 2017, 1(7): 90-99.
[5] 朱鹏, 赵笑笑, 伍薇. 移动电子商务消费者决策偏好影响因素实证研究*[J]. 数据分析与知识发现, 2017, 1(3): 1-9.
[6] 吴小兰,章成志. 基于菜谱与微博用户评论的饮食社区挖掘研究*[J]. 现代图书情报技术, 2016, 32(6): 54-62.
[7] 刘洪莲,张鹏翼,王军. 多会话商品信息搜寻行为、情境及影响因素研究*[J]. 现代图书情报技术, 2016, 32(4): 1-7.
[8] 张文君, 王军, 徐山川. 电商用户需求状态的聚类分析——以淘宝网女装为例[J]. 现代图书情报技术, 2015, 31(3): 67-74.
[9] 何跃, 宋灵犀, 齐丽云. 负面事件中的品牌网络口碑溢出效应研究——以“圆通夺命快递”事件为例[J]. 现代图书情报技术, 2015, 31(10): 58-64.
[10] 高劲松, 梁艳琪, 李珂, 肖涟, 周习曼. 面向关联数据的电子商务信用信息服务模型研究[J]. 现代图书情报技术, 2014, 30(6): 8-16.
[11] 余本功, 顾佳伟. 基于Folksonomy和RDF的信息组织与表示[J]. 现代图书情报技术, 2014, 30(11): 24-30.
[12] 沈洪洲, 宗乾进, 袁勤俭. 应用Google云消息框架C2DM实现商务信息推送服务[J]. 现代图书情报技术, 2012, 28(6): 78-83.
[13] 李慧, 刘东苏. 消除用户主观评价差异的电子商务信誉模型[J]. 现代图书情报技术, 2012, 28(2): 48-52.
[14] 寇继虹, 戴亦舒, 刘芳, 吴珺, 徐承欢, 曹倩. 动态思维导图软件TheBrain的功能机制分析[J]. 现代图书情报技术, 2012, (12): 45-51.
[15] 崔金红, 汪凌韵. 在线反馈系统中消费者网络口碑传播动机的实证研究[J]. 现代图书情报技术, 2012, (10): 55-60.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 2015 《数据分析与知识发现》编辑部
地址:北京市海淀区中关村北四环西路33号 邮编:100190
电话/传真:(010)82626611-6626,82624938
E-mail:jishu@mail.las.ac.cn