在线评论对消费者感知与购买行为影响的实证研究
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摘要
过去十几年中,随着互联网技术发展与应用的深化,以互联网为平台的在线口碑的传播凸显其巨大的影响力和重要性。用户发表的对特定商品的在线评论(简称在线评论),作为在线口碑的一种,正深刻改变着消费者的经济行为模式、企业的赢利性及其市场策略。尽管在线评论的实践已经开始,但学术界对这个新兴的信息媒体如何影响消费者决策的回答并不充分。而弄清此问题对消费者参考在线评论提高决策的效率和效果,企业有效地开展在线评论的管理与营销,最终推动企业实现更大赢利具有重要的现实意义和价值。
     本论文以行为导向为研究范式,结合定性和定量分析,从消费者的感知和购买行为两个层面出发探讨在线评论对消费者的影响,对在线评论如何影响消费者对评论有用性的感知以及消费者最终购买行为进行了实证研究。其中,围绕消费者对在线评论的有用性如何感知开展了两个方面的研究:(1)针对带有有用性投票统计信息的在线评论,结合文本挖掘技术和统计回归分析,基于评论的文本特征及发表时间等静态线索探索了在线评论感知有用性(以评论的有用性投票统计信息作为测度指标)的影响因素,并在此基础上研究了自动快速识别评论有用性的方法。(2)针对缺少有用性投票统计信息的一类特殊的在线评论,基于在线评论信息处理阶段,定性分析了这类特殊评论缺少有用性投票的原因及影响因素,并基于二分类Logistic回归比较这类评论与带有有用性投票信息的评论在影响因素上的差异,据此定量化地揭示消费者对这类评论是如何感知的以及这类特殊评论的特征是什么。另外,围绕这些有价值的在线评论如何进一步影响消费者的最终购买行为,从消费者个体与总体两个层面进行了研究:(1)以消费者个体为研究单元,根据归因理论、前景理论、感知风险理论、信息可获得性及诊断性理论,研究了在商品类型、接收者专业知识两个因素的调节作用下,在线评论的情感极性(正向或负向)对消费者个体购买行为的影响,基于实验设计和协方差分析对研究假设进行了实证检验。(2)以消费者总体为研究单元,采用面板数据建模,以商品销售额作为消费者总体购买行为的测度指标,探索了在线评论的数量和情感极性两个维度对消费者总体购买行为的绝对影响以及这种影响随商品生命阶段变化的动态性,另外通过与其他信息媒体专家评论的影响相比较,进一步揭示在线评论的相对影响和价值。本论文试图在以下方面做出有理论和实践价值的创新性成果。
     第一,基于面板数据建模,实证检验了在线评论的数量和情感极性两个维度对消费者总体购买行为的绝对影响以及(与专家评论相比)的相对影响,并探索和发现了影响随时间变化的动态性特点。研究模型可以更准确地揭示在线评论与消费者总体购买行为之间的现实关系及其随时间变化的一般规律。研究结果可为企业在多种信息推广方式中是否应该重点关注在线评论、在商品不同生命阶段如何有效地管理在线评论提供指导。
     第二,首次围绕在线评论的情感极性,探索了商品类别、接收者专业知识对在线评论情感极性影响消费者个体购买行为的调节作用及其具体形式,发现了商品类别调节作用的不对称性。研究结果可为企业在资源有限的情况下基于特定的现实情境更有效地管理不同情感极性的在线评论提供具体指导。
     第三,将搜索型商品的相关研究成果扩展到体验型商品领域,在已有研究基础上考察评论文本语义特征等静态线索的影响,分析并建立了在线评论感知有用性的影响因素模型,所建模型对评论有用性具有更强的分类识别能力。此研究一方面可实现从海量评论中自动识别有用评论,帮助消费者快速识别高质量商品,促进企业销售增长;另一方面可指导企业发表有影响力的评论,开展更有效的口碑营销。
     第四,首次针对没有有用性投票的一类特殊评论,定量化地研究了影响消费者未对在线评论有用性进行投票的原因及因素,揭示消费者对这类特殊评论有用性的感知。另外,尝试基于在线评论文本特征等一手数据揭示消费者复杂的心理行为,为消费者在线行为领域相关研究提供了新的视角、方法和手段。
Over the past ten years, as the growing depth of Internet technologydevelopment and application, the online word-of-mouth with Internet ascommunication platform has begun to show its tremendous influence andsignificance. User-generated online product reviews, as one form of onlineword-of-mouth, is bringing a profound change in consumer behavior patterns, theprofit margin and market strategy of the enterprise. Related theoretical study onhow this emerging media affect consumers' perception and purchasing behavior isnot sufficient. Clearing this question can help consumers improve decision makingefficiency and effectiveness, help enterprise manage online reviews effectively topromoteprofits, andmake a good use of the advantage of online reviews.
     Taking behavior orientation as the research paradigm, from two views ofconsumers’perceptions and buying behaviors, applying both qualitative andquantitative analysis, this paper empirically studys how online reviews impact theconsumers’perception on reviews helpfulness and consumers’purchase behaviors.The four questions are studied. Two parts refer to reviews helpfulness: (1)Combining text mining technologywith regression analysis, we explored the impactfactors for consumers’perception on reviews helpfulness (including the textcharacteristic and published time of reviews, etc.), and further studied the methodof automatically identify review helpfulness. (2) We qualitiviely discussed thecause and impact factors of some online reviews having no helpfulness votes, andquantitatively analyzed the differences in these impact factors between the reviewswith no helpfulness votes and ones with helpfulness votes based on binaryclassification Logistic regression, the results of which are studied to further revealwhy no votes. Contents of the other two parts include: (1) Taking the individualconsumer as the research unit, we studied the moderating effects of product type,consumer expertise on the impact of the online reviews valence, according toattribute theory, prospect theory, perceived risk theory and informationavailability/diagnosticity theory.Applying the experiment design andANCOVA, wetested the moderating effects related hypothese. (2) Takingthe consumer populationas the research unit, we explored the effect of online reviews numbers and valence on product sales (used to measure the buying behaviors of the overall consumergroup) and the variation ofthe impacts with time using panel data. We also revealedthe relative effect of online reviewscompared with expertise reviews.
     This paper attempts to achieve theoretical and practical innovation in thefollowing four aspects.
     First, based on the panel data model, we empirically tested the absolute andrelative (compared with expertise reviews) effects of online reviews numbers andvalences on the overall consumer purchase behaviors. We also explored andvalidated the dynamic variation nature of the impacts with time. Our study modelcan reveal the realistic relation between online reviews and consumer populationbehaviors, offering an expalanation for present disconsistent research conclusions.These researches can also richen the relative theories and researches on the impactof online reviews and overall consumer behaviors
     Second, we first explored how product type, consumer expertise moderate theimpact of online reviews valence on individual consumer purchase behaviors. Wealso analyzed the detailed forms of moderating effects and found the asymmetriccharacteristics of moderating role of product type. Our study offers detailedsuggestions for enterprise to effectively manage online reviews under limitedresources.
     Third, extending researches for search goods to experience goods, weestablished one model for the impact factors of reviews perceived helpfulness. Thismodel significantly improves the forcast effect for the helpfulness of online reviews.This study can help consumers identify high quality products quikly which furtherenhance product sales.Besides, our findings can offer suggestions for enterprise onhow to post high-impact reviews and improve online word-of-mouthmarketing.
     Fourth, we first fill the research gap in quatitatively analyzing the causes andimpact factors of reviews not being voted for helpfulness. Besides, we attempted toreveal consumers’complex psychology and behaviors through first-hand textfeatures data of reviews, which provides a new perspective, method and means forstudying online consumer behaviors.
引文
1 D. Godes, D. Mayzlin. Using online conversations to study word of mouthcommunication. Marketing Science. 2004, 23 (4): 545~560
    2 Katz, E., Lazarsfeld P. F. Personal Influence: The Part Played by People in theFlow of Mass Communication. NewYork: The Free Press, 1964
    3 Day, Ralph L.. Marketing models: behavioral science applications. Scranton,Intext Educational Publishers, 1971
    4 Bristor, J.M.. Enhanced explanations of word-of-mouth communications: Thepower of relationships. Research in consumer behavior. 1990, 4: 51~83
    5 Zhu, F. and Zhang, X.Q. The Influence of Online Consumer Reviews on theDemand for Experience Goods: The Case of Video Games. Twenty-SeventhConference on Information Systems(ICIS), Milwaukee, 2006
    6 iPerceptions. Industry Statistics. Available at: http://www.bazaarvoice.com/industry Stats. html.Accessed on May 29, 2008
    7 CIC网络口碑研究咨询公司.洞察网络口碑主题一:网络口碑在购买决策中扮演的角色.网络口碑白皮书系列, 2009: 5~11
    8 Deloitte & Touche. Industry Outlook. http://www.deloitte.com/dtt/article/0,1002,cid%253D186937,00.html.Accessed on May 28, 2008
    9 LosAngeles Times. Everyone IsACritic in Cyberspace. Dec 1999,A1
    10陈蓓蕾.基于网络和信任理论的消费者在线口碑传播实证研究.浙江大学博士论文. 2008:25~26
    11 Wilson, E.J., D.L. Sherrell. Sources Effects in Communication and PersuasionResearch:AMeta-Analysis of Effect Size. Journal of theAcademy of MarketingScience. 1993, 21: 101~112
    12 Hanson, W.A. Principles of Internet Marketing. Ohio: South-Western CollegePublishing, 2002
    13 Reichheld, F. The One Number You Need to Grow. Harvard Business Review.,2003, 81(12): 46~54
    14 Thompson, N. More Companies Pay Heed to Their 'Word of Mouse' Reputation.The NewYork Times, June 23, 2003
    15 Mayzlin, D. Promotional Chat on the Internet. Yale School of ManagementWorking Paper #MK-14, January 31, 2003
    16周耿.《封杀王老吉》——成功的网络事件营销. 2008年11月25日.http://nubs.nju.cn/zg/?p=95
    17 New York Times. Amazon Glitch Unmasks War of Reviewers. Feb. 14, 2004,A1
    18 GhoseA, Ipeirotis PG. Designing ranking systems for consumer reviews: Theimpact of review subjectivity on product sales and review quality. Workshop onInformation Systems and Economics (WISE), 2006
    19 GhoseA, Ipeirotis PG. Designing novel review ranking systems: predicting theusefulness and impact of reviews. Proceedings of the ninth internationalconference on Electronic commerce. NewYork, NY, USA:AssociationComputing Machinery(ACM), 2007: 303~310
    20 Hu, N., Pavlou, P.A., and Zhang, J. Can online reviews reveal a product's truequality? Empirical findings and analytical modeling of online word-of-mouthcommunication. In Proceedings of the 7thACM conference on Electroniccommerce (EC'06), 2006: 324~330
    21 Yang Liu, Xiangji Huang,AijunAn, and Xiaohui Yu. ReviewsAre Not EquallyImportant: Predicting the Helpfulness of Online Reviews. Technical ReportCSE-2008-05, Department of Computer Science and Engineering,YorkUniversity, 2008
    22 Harrison-Walker L.J. The Measurement of Word-of-Mouth Communication andan Investigationof Service Quality and Customer CommitmentAs PotentialAntecedents. Journal of Service Research. 2001, 4(1): 60~75
    23 J. Jacoby, D. E. Speller, C. K. Berning. Brand Choice Behavior as a Function ofInformation Load: Replication and Extension. Journal of Consumer Research.1974, 1(1): 33~42
    24 Y. Zhou and W. B. Croft. Document quality models for web ad hoc retrieval. InProceedings of theACM Fourteenth Conference on Information and KnowledgeManagement, 2005: pages 331~332
    25 H. Kim and J. Seo. High-performance faq retrieval using an automaticclustering method of query logs. Information Processing and Management. 2006,42(3):650~661.
    26 J. Jeon, W. B. Croft, J. H. Lee, S. Park.Aframework to predict the quality ofanswers with non-textual features. Proceedings of the 29th annual internationalACM SIGIR conference on Research and development in information retrieval.Seattle, Washington, USA, 2006: 228~235
    27 M. Weimer, I. Gurevych, M. Mühlh?user.Automatically assessing the postquality in online discussions on software. Proceedings of the 45thAnnualMeeting of theACLon Interactive. Prague, Czech Republic, 2007: 125~128
    28 J. Liu,Y. Cao, C.Y. Lin,Y. Huang, M. Zhou.Low-quality product reviewdetection in opinion summarization. Proceedings of the 2007 Joint Conferenceon Empirical Methods in Natural Language Processing and ComputationalNatural Language Learning, Prague, June 2007: 334~342
    29 Skowronskij, Carlston D. Negativity and extremity biases in impressionformation: a review of explanations. Psychological bulletin.1989, 105(1):131~142
    30 Homer PM,Yoon S. Message framing and the interrelationships among adbasedfeelings, affect, and cognition. JAdvert 1992, 21(1):19~33
    31 Arndt J. Role of product-related conversations in the diffusion of a new product.Journel of Marketing Ressearch. 1967, 4(3): 291~295
    32 Richins ML. Negative word-of-mouth by dissatisfied consumers: a pilot study.Journal of Marketing. 1983, 47(Winter): 68~78
    33 Weinberger Marc G,Allen Chris T, Dillon William R. Negative information:perspectives and research directions. In: Monroe Kent, editor.Advances inConsumer Research.AnnArbor, MI:Association for Consumer Research, 1981:398~404
    34 Brown Jacqueline Johnson, Reingen Peter H. Social ties and word-of-mouthreferral behavior. Jounral of Consumer Research.1987, 14(December): 350~62
    35 Y. Liu. Word of Mouth for Movies: Its dynamics and impact on box officerevenue. Journal of Marketing. July, 2006, (70): 74~89
    36 W. J. Duan, B. Gu,A. B. Whinston. Do online reviews matter?An empiricalinvestigation of panel data.Decision Support Systems. 2008a, 45(4): 1007~1016
    37 W. J. Duan, B. Gu,A. B. Whinston. The dynamics of online word-of-mouth andproduct sales- an empirical investigation of the movie industry. Journal ofRetailing. 2008b, 84(2): 233~242
    38 P.Y. Chen, S.Y.Wu, J.Yoon. The impact of online recommendations andconsumer feedback on sales. Proc. Internat. Conf. on Inform. Systems (ICIS),Washington, D.C., 2004: 711~724
    39 Charlett, D., R. Garland, and N. Marr. How damaging is negative word of mouth?Marketing Bulletin,1995(6): 42~50
    40 J. Chevalier, D. Mayzlin. The effect of word of mouth online: Online bookreviews. Journal of Marketing Research. 2006, 43(3): 345~354
    41 Feldman, J. M., and Lynch, J. G.. Self-generated Validity and Other Effects ofMeasurement on Belief, Attitude, Intention and Behavior. Journal of AppliedPsychology,August 1988, (73): 421~435
    42郭国庆,杨学成,张杨.口碑传播对消费者态度的影响:一个理论模型.管理评论, 2007,19 (3): 20-26
    43郑小平.在线评论对网络消费者购买决策影响的实证研究.中国人民大学硕士论文,北京:中国人民大学, 2008.
    44郭小钗,陈蓓蕾.在线口碑效应的影响因素实证研究.北京理工大学学报(社会科学版), 2009, 11(2): 31~35
    45方艳宏.网络口碑传播对电子产品消费决策的影响研究.厦门大学硕士论文. 2009
    46金立印.网络口碑信息对消费者购买决策的影响:一个实验研究.经济管理,2007, 29(22):36~42
    47 Park, D. H., and I. Han. Integrating Conflicting Reviews:AttributionalHypotheses of Consumer Response to Information Uncertainty depending onPrior BrandAttitude. Proceedings of the Proceedings of the 41stAnnual HawaiiInternational Conference on System Sciences. IEEE Computer Society.Washington DC, USA, 2008.
    48 Park, D.H., J. Lee, and I. Han. eWOM overload and its effect on consumerbehavioral intention depending on consumer involvement. Electronic Comme-rce Research andApplications. Winter 2008, 7(4): 386~398
    49 Park, D.H. and S. Kim. The effects of consumer knowledge on messageprocessing of electronic word-of-mouth via online consumer reviews. ElectronicCommerce Research andApplications. Winter 2008, 7(4): 399~410
    50 Park, C., and T. M. Lee. Information direction, website reputation and eWOMeffect:Amoderating role of product type. Journal of Business Research. 2009,(62): 61~67
    51 Mun Ellison, G., D. Fudenberg. Word-of-mouth communication and sociallearning. Quart. J. of Econom. 1995,110: 93~125
    52 C. Dellarocas, N.Awad, M. Zhang.Using online ratings as a proxy of word-of-mouth in motion picture revenue forecasting.Working Paper. May, 2004.Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=620821
    53 C. Dellarocas, X. Q. Zhang, N. Awad. Exploring the value of online productreviews in forecasting sales: The case of motion pictures. Journal of InteractiveMarketing. 2007, 21(4): 23~45
    54 X. Q. Zhang, C. Dellarocas, N.Awad. Estimating word-of-mouth for movies-theimpact for online movie reviews on box office performance. Workshop onInformation Systems and Economics(WISE), Dec., 2004, College Park, MD
    55 X. Q. Zhang, C. Dellarocas. The lord of the ratings: how a movie’s fate isinfluenced by reviews? Twenty-Seventh International Conference on Inform-ation Systems (ICIS), Milwaukee, 2006
    56 W. J. Duan, B. Gu, A. B. Whinston. Informational cascades and softwareadoption on the Internet: an empirical investigation. MIS Quarterly. 2009, 33(1):23~48
    57 Chen Lin, Khim Yong Goh. Estimating the Impact of Online Reviews on theBox Office Performance: A Three-Stage-Least-Squares Model. Working Paper,2007.available at: http://www.utdallas.edu/~murthi/Papersubs/Chen_lin_ESTIMA~1.doc
    58 EK Clemons, GG Gao, LM Hitt. When online reviews meet hyperdifferentiation:A study of the craft beer industry. Journal of Management Information. 2006,23(2): 149~171
    59 Hoffman D. L., Novak T. P. Marketing in hypermedia computer2mediatedenvironments: concep tual foundations. Journal of Marketing. 1996, 60 (3): 50~68
    60 Gelb B. D., Sundaram S. Adapting to word ofmouse. Business Horizons. 2002,45 (4): 21~25
    61 J. Tanimoto, H. Fujii. A study on diffusional characteristics of information on ahuman network analyzed by a Multi-Agent simulator. The Social ScienceJournal. 2003, 40(3): 479~485
    62 Y. Chen, J. Xie. Online Consumer Review: Word-of-Mouth as a New Element ofMarketing Communication Mix. Management Science. 2008, 54(3): 477~491
    63 Bickart B., Schindler R.M. Internet forums as influential sources of consumerinformation. Journal of InteractiveMarketing.15(3): 31 ~ 40
    64 Haubl G., Murry K.B. Intelligent double agent. MIT SloanManagement Review.2006, 43(3): 8 ~12
    65 B. Pang, L.Lee, S. Vaithyanathan. Thumbs up? Sentiment Classification UsingMachine Learning Techniques. 2002 Conference on Empirical Methods inNatural Language Processing, Philadelphia, USA, 2002:79 ~86
    66 General Inquirer Website. General Inquirer Home Page. http://www.wjh.harvard.edu/~inquirer/.Accessed on March 11, 2007
    67 G. A. Miller, R. Beckwith, C. Fellbaum, D. Gross, K.J. Miller. Introduction toWordnet: An Online Lexical Database. Journal of Lexicography. 1990, 3(4):235~244
    68 P. D. Turney, M.L. Littman. Measuring Praise and Criticism: Inference ofSemantic Orientation from Association. ACM Transactions on InformationSystems. 2003, 21:315~346
    69 Kennedy, D. Inkpen. Sentiment Classification of Movie Reviews UsingContextual Valence Shifters. Computational Intelligence.2006, 22(2):110~125
    70 Andreevskaia, S. Bergler. Mining Wordnet for a Fuzzy Sentiment: SentimentTag Extraction from Wordnet Glosses. In Proc. of the 11th Conf. of theEuropean Chapter of the Association for Computational Linguistics, Budapest,2003: 209~216
    71 K. Dave, S. Lawrence, D.M. Pennock. Mining the Peanut Gallery: OpinionExtraction and Semantic Classification of Product Reviews. Proceeding of 12thinternational conference on World Wide Web, Budapest. Hungary, 2003. ACMPress, 2003: 519~528
    72 J. Kamps, M. Marx, R.J. Mokken, M. De Rijke. Using WordNet to MeasureSemantic Orientation of Adjectives. In Proceedings of the 4th InternationalConference on Language Resources and Evaluation European LanguageResourcesAssociation, Paris, 2004:1115~1118
    73 J. Wiebe. Learning Subjective Adjectives from Corpora. Proceedings of 17thNational Conference on Artificial Intelligence. Menlo Park, California, 2000.AAAI Press, 2000: 735~740
    74 E. Riloff, J. Wiebe, T. Wilson. Learning Subjective Nouns Using ExtractionPattern Bootstrapping. Proceedings of the Seventh Conference on Computati-onal Natural Language Learning,Alberta, Canada, 2003:25~32
    75 E. Riloff, J. Wiebe. Learning Extraction Patterns for Subjective Expressions.Proceedings of the 2003 Conference on Empirical Methods in Natural LanguageProcessing, Sapporo, Japan, 2003:105~112
    76 Yu, V. Hatzivassiloglou. Towards Answering Opinion Questions: SeparatingFacts from Opinions and Identifying the Polarity of Opinion Sentences.Proceedings of the 2003 Conference on Empirical Methods in Natural LanguageProcessing, Sapporo, Japan, 2003:129~136
    77张莹,孙明贵.西方网络口碑传播效应研究进展.财贸研究. 2008, 19(5):109~115
    78张强,李乃和.网络口碑研究现状及未来发展初探.江西农业学报. 2008,20(4): 147~149
    79赖胜强,朱敏.网络口碑研究述评.财贸经济. 2009 (6): 127~131
    80 Qiang Ye, Ziqiong Zhang, and Rob Law. Sentiment classification of onlinereviews to travel destinations by supervised machine learning approaches.Expert Systems withApplications.April 2009, 36 (3): 6527~6535
    81李实,叶强,李一军, Rob Law.挖掘中文网络客户评论中的产品特征方法研究.管理科学学报, 2009, 12(2): 142~152
    82章晶晶.网络环境下口碑再传播意愿的影响因素研究.浙江大学硕士论文,2007
    83钱斌.餐饮类论坛中口碑再传播现象的实证研究与仿真模拟.中国人民大学硕士论文, 2008
    84刘建新,陈雪阳.口碑传播的形成机理与口碑营销.财经论丛, 2007, (5):96~102
    85陈明亮,章晶晶.网络口碑再传播意愿影响因素的实证研究.浙江大学学报(人文社会科学版), 2008, 38(5): 127~135
    86罗时鑫.口碑沟通对购买决策的影响研究.浙江大学硕士论文, 2007
    87李慧.负面口碑对酒店顾客购买决策的影响研究.浙江大学硕士论文, 2008
    88 Fogg,B.J.& Tseng. Credibilityand Computing technology. Communieations ofAssoeiation for Computing Machinery,1999,42(5): 39~44
    89 Hovland, C. I. & Weiss, W. The influence of source credibility on commu-nieation effectiveness. The public Opinion Quarterly. 1951, 5(15): 635~ 650
    90 Whitehead,J.L.Faetors of souree credibility.QuarterlyJournal of Speech. 1968,(54): 59~63
    91 Ohanian,R. Construction and validation of a scale to measure celebrity. JoumalofAdvertising,1990,19(3): 39~52
    92 Gilly, M.C.,Graham,J.L.,Wolfinbarger,M.F.&Yale,L.J.Adyadic studyofinterpersonal information seareh.Academy of Marketing Seienee. 1998,26(2):83~100
    93 Bansal, H. S. & Voyer,P. A. Word-of-mouth Proeesses within a servicesPurehase deeision context.Jounlal of Service Researeh, 2000,3(2): 166~167
    94 Sun, T.,Youn.S.,Wu.G. H.& Kuntaraporn, M. Online word-of-mouth(or mouse):an exploration of its antecedents and consequences. Journal of Intemet MediatedCommunieaiion. 2006, (11): 1104~1127
    95 Paul M. Herr, Frank R. Kardes, and John Kim. Effects of Word-of-Mouth andProduct-Attribute Information on Persuasion: An Accessibility-DiagnosticityPerspective. Journal of Consumer Research. 1991, 17(4): 454~462
    96 Alden,D.L.,Mukherjee,A.& Hoyer,W. D. The effeets of ineongruity: surpriseand Positive moderators on Pereeived humor in television advertising .JoumalofAdvertising, 2000, 2(29): l~15
    97 Chen, Q. & Rodgers, S. Development of an instrument to measure websitePersonality.Journal of InteraetiveAdvertising, 2006, 7(l): 47~64
    98 Negash.S., Ryanb, T. & Igbariab, M. Quality and effeetiveness in Web-basedcustomer support systems. Information and Management, 2003 (40): 757~76899
    99 MeMillan, S.J. Effects of struetural and perceptual factors on attitude towardthe website. Journal ofAdvertising Research, 2004, 43(04): 400~421
    100 Ahluwalia R, Burnkrant RE, Unnava HR. Consumer Response to NegativePublicity: The Moderating Role of Commitment. Journal of Marketing Research.2000, 37(2): 203~214
    101 Chen, Pei-Yu, Dhanasobhon, Samita and Smith, Michael D.All Reviews are NotCreated Equal: The Disaggregate Impact of Reviews and Reviewers atAmazon.Com. May, 2008.Available at SSRN: http://ssrn.com/abstract=918083
    102 JW Alba, JW Hutchinson. Dimensions of Consumer Expertise. Journal ofconsumerresearch. 1987, 13(4): 411~454
    103 Brucks, M. The effects of product class knowledge on information searchbehavior. Journal of Consumer Research. 1985, 12(1): 1~16
    104 PF Bone. Word-of-mouth effects on short-term and long-term productjudgments. Journal of Business Research. 1995, 32(3): 213~223
    105 Chatterjee P. Online reviews: do consumers use them? Advance of ConsumerRessearch. 2001, 28:129–134.
    106 JL Zaichkowsky. Measuring the involvement construct. Journal of consumerresearch. 1985, 12(3): 341~352
    107 F Xue, JE Phelps. Internet-facilitated consumer-to-consumer communication:the moderating role of receiver characteristics. International Journal of InternetMarketing andAdvertising. 2004, 1(2): 121~136
    108韦福祥,姚亚男.顾客性别与口碑传播相关关系研究.天津工业大学学报.2007, 26(1): 73~77
    109 E Garbarino, M Strahilevitz. Gender differences in the perceived risk of buyingonline and the effects of receiving a site recommendation. Journal of BusinessResearch. 57(7): 768~775
    110 Senecal S., J. Nantel. The influence of online p roduct recommendations onconsumers’online choices. Journal of Retailing. 2004, 80(2): 159~169
    111 Shamdasani Prem N, Stanaland Andrea JS, Tan Juliana. Location, location,location: insights for advertising placement on the Web. J Advert Res 2001,41(4): 7~21
    112 Money R. B., Gilly M. C., Graham J. Explorations of national culture andword-of-mouth referral behavior in the purchase of industrial services in theUnited States and Japan. Journal of Marketing. 1998, 62 (October): 76~87
    113 Bruce, Money R.. Word of mouth Referral Sources for Buyers of InternationalCorporate Financial Services. Journal of World Business. 2000, 35(3): 314~329
    114 Fong J., Burton S. Electronic word-of-mouth: a comparison of stated andrevealed behavior on electronic discussion boards. Journal of InteractiveAdvertising. 2006, 6(2): 61~70
    115徐伟青,黄孝俊.口碑传播的影响力要素及其对营销创新的启示.外国经济与管理. 2004, 26(6): 26~30
    116 Sundaram D.S., Webster C. The role of brand familiarity on the impact ofword-of-mouth communication on brand evaluations. Advances in ConsumerResearch. 1999, 26: 664~670
    117 Bei, L. T., E. Y. I. Chen, and R. Widdows. Consumers' Online InformationSearch Behavior and the Phenomenon of Search vs. Experience Products.Journal of Family and Economic Issues. 2004, 25(4): 449~467
    118 Sen S. and D. Lerman. Why are you telling me this? An examination intonegative consumer reviews on the Web. Journal of Interactive Marketing. 2007,21(4): 76~94
    119 Qiang Ye, R Law, B Gu. The impact of online user reviews on hotel room sales.International Journal of Hospitality Management. 2009, 28: 180~182
    120 ZiQiong Zhang, Qiang Ye, Rob Law and Yijun Li. The impact ofe-word-of-mouth on the online popularity of restaurants: A comparison ofconsumer reviews and editor reviews. International Journal of HospitalityManagement. 2010.
    121 Nan Hu, Ling Liu, Jennifer Zhang. Analyst Forecast Revision and Market SalesDiscovery of Online Word of Mouth. Proceedings of the 40th Annual HawaiiInternational Conference on System Sciences (HICSS), 2007
    122 Naveen Amblee and Tung Bui. The Impact of Additional ElectronicWord-of-Mouth on Sales of Digital Micro-products Over Time: A LongitudinalAnalysis of Amazon Shorts. Proceedings of the 40th Annual HawaiiInternational Conference on System Sciences (HICSS), 2007
    123 Prag, Jay and James Casavant. An Empirical Study of the Determinants ofrevenues and Marketing Expenditures in the Motion Picture Industry. Journal ofCultural Economics. 1994, (18): 217~235
    124 Litman, B.R. and Ahn, H. Predicting Financial Success of Motion Pictures. InB.R. Litman (ed.) The Motion Picture Mega-Industry. Allyn & BaconPublishing Inc., Needham Heights, MA, 1998
    125 Reinstein, D.A. and Snyder, C.M. The Influence of Expert Reviews onConsumer Demand for Experience Goods: A Case Study of Movie Critics.Journal of Industrial Economics, 2005, 53(1): 27~51
    126 Basuroy, S., Chatterjee, S., and Ravid, S.A. How Critical are Critical Reviews?The Box Office Effects of Film Critics, Star Power and Budgets. Journal ofMarketing. Oct., 2003, 67: 103~117
    127 Ravid, S.A. Information, Blockbusters, and Stars: A Study of the Film Industry.Journal of Business. 1999, 72(4): 463~492
    128 Eliashberg, J., and Shugan, S.M. Film critics: Influencers or predictors? Journalof Marketing. 1997, 61(2): 68~78
    129 Holbrook, M. B. PopularAppeal versus Expert Judgements of Motion Pictures,”Journal of Consumer Research. 1999, 26: 144~15
    130 David Bounie, Michel Gensollen. The Effect of Online Customer Reviews onPurchasing Decisions: the Case of Video Games. Working paper, 2005
    131 RC Brooks Jr. "Word-of-Mouth" Advertising in Selling New Products. TheJournal of Marketing.1957, 22(2): 154~161
    132 Anderson E. W.,Sullivan Mary W. The antecedents and consequences ofcustomer satisfaction for firms. Marketing Seience. 1993, 12:125~143
    133 Westbrook, Robert A. Product/consumption-based Affeetive Responses andpost-purchase proeesses. Journal of Marketing Research. 1987, 24(8): 255~270
    134 Tax S. S., Brown S. W., Chandrashekaran M. Customer evaluations of serviceComplaint experiences: implications for relationship marketing. Journal ofMarketing. 1998, 62(4):60~76
    135郭会斌.营销口碑的产生路径与创造研究.经济与管理.2005, 19(l1): 44~46
    136阙克儒.网络匿名性、企业形象与关系品质对网络口碑影响之研究——以线上游戏为例.硕士学位论文,国立中兴大学, 2004
    137黄英,朱顺德.二十一世纪的口碑营销及其在中国的发展潜力.管理前沿.2003, (6): 33~36
    138 Christiansen T., Tax S. S. Measuring word of mouth: the questions of who andwhen? Journal of Marketing Communications. 2000, 6(3): 185~199
    139 Newman, P. J. An investigation of consumer reactions to negativeword-of-mouth on the Intemet. Doctor of Philosophy Dissertation,University ofIllinois atUrbana,2003
    140 Dellaroeas, C. The digitization of word of mouth: Promise and challenges ofonline feedback mechanisms.Management Science. 2003, 49(10): 1407~1424
    141 Hennig-Thurau, T., Walsh, G. E. Electronic word-of-mouth: motives for andConsequences of reading customer articulations on the Internet. InternationalJournal of Electronic Commerce. 2003, 8(2): 51~74
    142 T. Hennig-Thurau, K. P. Gwinner, G. Walsh. D. D. Gremler. Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulatethemselves on the Internet? Journal of Interactive Marketing. 2004, 18(1):38~52
    143 Datta, P. R.,Chowdhury, D. N. and Chakraborty, B. R. Viral marketing: newform of word-of-mouth through Internet. The Business Review, 2005, 3(2):69~75
    144蒋玉石.零售行业中顾客口碑传播意愿的理论研究与实证分析.西南交通大学博士论文, 2007
    145 Subramani, M. R. and B. Rajagopalan. Knowledge-Sharing and Influence inOnline Social Networks via Viral Marketing. Communications of the ACM.2003, 46(12): 300~307
    146 Weinberg, B. D. and L. Davis.Exploring the WOW in online-auction feedback.Journal of Business Research. 2005, 58(11): 1609~1621
    147 Wangenheim, F. V. and Bayon, T. The effect of word of mouth on servicesswitching: measurement and moderating variables.European Journal of Mark-eting. 2004, 38(9): 1173~1185
    148 Hovland, C. I., Janis, I. L. and Kelley, H. H. Communication and Persuasion.New haven: Yale University Press, 1953: 6~67
    149 Duncan, T. and Moriarty S. E. A communication-based marketing model formanaging relationships. Journal of Marketing. 1998, 62(2): l~13
    150 Granovetter, M. The strength of weak ties. American Journal of Sociology. 1973,78 (6): 1360-1380
    151 Forrester Research. What’s The Buzz on Word-Of-Mouth Marketing? SocialComputing and Consumer Control Put Momentum into Viral Marketing. May,2005, www.forrester.com
    152 Heider, F. The Psychology of Interpersonal Relations. John Wiley & Son Press,NewYork, USA, 1958
    153 Taylor, Shelley E., Letitia Anne Peplau and David O. Sears. Social psychology.10th edition, Prentice Hall, 2000
    154 Wikipedia: the free encyclopedia.Attributional bias. Wikimedia Foundation Inc.,2009, available at: http://en.wikipedia.org/wiki/Attributional_bias
    155智库百科. 2009.Available at:wiki.mbalib.com/wiki/%E5%89%8D%E6%99%AF%E7%90%86%E8%AE%BA#.E5.89.8D.E6.99.AF.E7.90.86.E8.AE.BA.E7.9A.84.E7.BC.BA.E9.99.B7
    156 Mitchell, V. W. Consumer perceived risk: conceptualisations and models.European Journal of Marketing. 1999, 33(1): 163~195
    157 R. A. Bauer. Consumer behavior as risk taking. Dynamic marketing for achanging world. Proceedings of the 43rd conference of the American MarketingAssociation. 1960: 389~398
    158 Zhou, L., L. Dai, and D. Zhang. OnlineShopping Acceptance Model–ACriticalSurvey of Consumer Factors in Online Shopping. Journal of ElectronicCommerce Research. 2007, (8): 41~62
    159吴韩德.网际网路消费者购物意愿之跨国比较.国立中山大学企业管理研究所硕士论文, 1992
    160 L.W. Turley, Ronald P. LeBlanc. An exploratory investigation of consumerdecision making in the service sector. Journal of Services Marketing. 1993, 7(4):11~18
    161 Nelson, P. Advertising as Information. Journal of Political Economy.1974, 82(4):729~754
    162 Mitra, K., M. C. Reiss, and L. M. Capella. An examination of perceived risk,information search and behavioral intentions in search, experience and credenceservices.Journal of Services Marketing. 1999, 13(3): 208~228
    163 Chu, K. K., and C. H. Li. A Study of the Effect of Risk-reduction Strategies onPurchase Intentions in Online Shopping. International Journal of ElectronicBusiness. 2008, 6(4): 213~226
    164 Hsieh, Y. C., H. C. Chiu, and M. Y. Chiang. Maintaining a committed onlinecustomer: a study across search-experience-credence product. Journal ofRetailing. 2005, 81(1): 75~82
    165 Murray K. B. A Test of Serviees Marketing Theory: Consumer InformationAcquisitionActivities. Journal of Marketing. 1991, 55(l): 10~25
    166 Voyer, P. A. Word-of-Mouth Process Within a Services Purchase DecisionContext. Master Dissertation, The University of New Brunswiek (Canada), 1999
    167 Adaval R. Sometimes It Just Feels Right: The Differential Weighting ofAffect-Consistent and Affect-Inconsistent Product Information. Journal ofConsumer Research. 2001, 28(1): 1~17
    168 Strahilevitz M, Myers JG. Donations to Charity as Purchase Incentives: HowWell They Work May Depend on What You Are Trying to Sell. Journal ofConsumer Research. 1998, 24(4): 434~446
    169 Mort GS, Rose T. The effect of product type on value linkages in the means-endchain: Implications for theory and method. Journal of Consumer Behaviour.2004, 3(3): 221~234
    170 Duhan, D. F., S. D. Johnson, J. B. Wilcox, and G. D. Harrell. Influences onconsumer use of word-of-mouth recommendation sources. Journal of theAcademy of Marketing Science. 1997, 25(4): 283~295
    171 Forman. C, A. Ghose, and B. Wiesenfeld. A Multi-Level Examination of theImpact of Social Identities on Economic Transactions in Electronic Markets.NYU CeDER Working Paper, 2006. From: http://dspace.nyu.edu/handle/2451/14809
    172 SAS Institute Inc. SAS/STAT Software, Changes and Enhancements. ThroughRelease 6.11. North Carolina: SAS Institute Inc, 1996: 221~230
    173 Chiang, K. P., and R. R. Dholakia. Factors Driving Consumer Intention to ShopOnline: An Empirical Investigation”, Journal of Consumer Psychology. 2003,13(): 177~183
    174 Girard, T., R. Silverblatt, and P. Korgaonkar. Influence of Product Class onPreference for Shopping on the Internet. Journal of Computer-Mediated Comm-unication. 2002, 8(1):
    175 Girard, T., P. Korgaonkar, and R. Silverblatt. Relationship of Type of Product,Shopping Orientations, and Demographics with Preference for Shopping on theInternet. Journal of Business and Psychology. 2002, 18(): 101~120
    176 Hankin, L. The effects of user reviews on online purchasing behavior acrossmultiple product categories”, Master’s final project report, UC Berkeley Schoolof Information, 2007
    177 L. S. Huang, Y. J. Chou, I. T. Lan. Effects of Perceived Risk, Message Types,and Reading Motives on the acceptance and transmission of ElectronicWord-of-Mouth Communication. Contemporary Management Research. 2007,3(4): 299~312
    178 H. Park, J. Lee, I. Han. The Effect of On-Line Consumer Reviews on ConsumerPurchasing Intention: The Moderating Role of Involvement. InternationalJournal of Electronic Commerce. 2009, 11(4): 125~148
    179 Jeon, S. Y., Park H. J. The influence of information characteristics onword-of-mouth effect. Journal Consumer Studies. 2003, 14(): 21~44
    180 China Internet Network Information Center (CNNIC). 23rd Statistical Report onthe Internet Development in China. Jan 2009, available at: http://www.cnni c.cn/uploadfiles/pdf/2009/3/23/131303.pdf
    181 J. C. Nunnally. Psychometric Theory. McGraw-Hill Companies, 2rd edition,1987.
    182 Fomell C. and D. F. Larcker. Evaluation structural equations models withunobservable variables and measurement Error. Journal of Marketing Research.1981, 18: 39~50
    183刘新燕,杨智,刘雁妮,万后芬.大型超市的顾客满意度指数模型实证研究.管理工程学报. 2004, 18(3): 96~101
    184张文彤. Spss统计分析高级教程.高等教育出版社, 2004年9月第1版
    185李河.协方差分析的正确应用.循证医学. 2004, 4(4): 224~227
    186 Pavlou, P.A. and A. Dimoka. The Nature and Role of Feedback Text Commentsin Online Marketplaces: Implications for Trust Building, Price Premiums, andSeller Differentiation. Information Systems Research. 2006, 17(12): 392~414
    187 S. Swami, J. Eliashberg, C. Weinberg. Silver screener: a modeling approach tomovie screens management. Marketing Science. 1999, 18(3): 352~372
    188高铁梅.计量经济分析方法与建模.北京:清华大学出版社. 2006
    189 T. S. Breusch and A. R. Pagan. The Lagrange Multiplier Test and itsApplications to Model Specification in Econometrics. The Review of EconomicStudies. 1980, 47(1): 239~253
    190 J. A. Hausman, P. A. Ruud. Specifying and testing econometric models forrank-ordered data. Journal of Econometrics. 1987, 34(1-2): 83~104
    191 W. H. Greene. Econometric Analysis. 5th edition. Prentice Hall, Upper SaddleRiver, New Jersey, 2003
    192易丹辉.数据分析与EVIEWS应用.中国统计出版社,第1版,2002年10月: 203~204
    193 MBA智库百科.什么是消费者购买行为. http://wiki.mbalib.com/wiki/%E6%B6%88%E8%B4%B9%E8%80%85%E7%9A%84%E8%B4%AD%E4%B9%B0%E8%A1%8C%E4%B8%BA

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