消费者个体行为偏好对在线评论真实性的影响机理研究

构建理论模型,探讨了消费者的偏好、评价动机和文化因素对在线评论偏差的影响机理,并提出了纠正偏差的条件。研究发现:消费者的选择偏好、主动评价偏差以及评价行为的趋同性会导致在线评论的均值出现偏差,不能反映商品的真实质量。为了纠正偏差,让消费者购后主动撰写评论,并纠正消费者的选择偏好可以使在线评论的均值反映商品的真实质量。     

在线评论有用性影响因素实证研究——基于Tripadvisor.com酒店评论数据

随着互联网的迅速发展,消费者购物决策越来越依赖于在线评论。从信息接受模型对信息有用性影响出发,构建在线评论有用性投票增量的时间窗,建立在线评论有用性影响因素模型,研究在线评论内容和评论者对在线评论有用性的影响。基于TripAdvisor.com的4 258条酒店评论数据,运用负二项回归进行实证分析。研究发现评论内容长度、评论极端性、评论有用性投票数、评论者认可度和个人信息披露对在线评论有用性具有显著正影响,这对在线零售商和消费者具有重要的启发和建议。     

基于信息觅食理论的消费者在线评论搜索行为研究

[目的/意义]本研究旨在从信息觅食理论出发,分析点评类软件消费者在线评论搜索行为的内在机理。[方法/过程]以信息觅食理论为基础,围绕信息线索、斑块模型和菜单模型构建了消费者在线评论搜索行为模型。采用问卷调查法收集352份有效样本数据,并利用结构方程模型对理论模型进行分析与检验。[结果/结论]评论内容质量、评论丰富性、评论效价以及评论者资信度4类信息线索均会正向显著影响消费者斑块收益感知,进而正向影响消费者在线评论搜索行为。此外,评论效价也会直接正向显著影响消费者在线评论搜索行为。本研究在理论层面深入揭示了消费者在线评论搜索行为的内在机理,延伸了信息觅食理论的研究情境与边界;在实践层面为点评类软件的功能优化及引导消费者有效搜索在线评论提供了相关建议。     

基于信号传递理论的在线评论有用性影响因素研究

[目的/意义]在线评论在消费者网络购物决策过程中解决信息不对称的作用日益显著,探索在线评论有用性影响因素对消费者和商家都具有重要意义。[方法/过程]以信号传递理论为框架,从与评论内容、评论者和反馈有关的信号构建在线评论有用性影响因素模型,同时考虑商品类型的调节作用,并分析了信号环境的影响。[结果/结论]通过亚马逊中国网站获取客观数据进行实证研究,发现负面评论、评论字数越多、评论含有图片、评论者对信息有披露、评论者排名越靠前、评论回应数量越多则评论有用性越高,商品类型在评论情感倾向、评论图片对评论有用性影响中起到了显著的调节作用,并且信号影响评论有用性受到信号环境的影响。     

在线评论对消费者购买意愿影响的实证研究

以消费者感知有用性为中介变量,探讨在线评论因素对消费者购买意愿的影响,并根据"精细加工可能性模型",引入认知需求作为调节变量,研究认知需求对感知有用性的影响。研究表明,在线评论质量、效价、消费者信任倾向、评论者专业性通过正向影响感知有用性对消费者购买意愿产生影响,消费者认知需求对评论质量、评论效价与评论者专业性与感知有用性之间的关系起调节作用,而对在线评论数量与感知有用性之间的关系无调节作用。     

电子商务中在线评论有用投票数影响因素研究

在线评论对消费者购物选择具有重要的影响,但日益增加的海量信息导致了信息过载等问题。因此,判断和识别评论信息的有用性具有重要的研究意义。本文采用文本挖掘和统计分析方法,从评论信息特征和评论者信息两个角度,对在线评论获得有用投票数的影响因素进行了分析,并通过亚马逊商城的用户评论样本,具体研究了各因素的影响作用。研究发现：评论评分对在线评论的有用投票数具有负向影响,而评论信息丰富性和历史评论有用性评价对其具有正向影响。     

在线评论对消费者网络购买意愿影响的研究

为了理解在线评论对消费者网络购买意愿影响的主要动因,基于计划行为理论、技术接受模型理论和网购顾客消费体验对在线评论行为作用模型,构建在线评论对消费者网络购买决策影响的动因模型,并提出若干假设,最后通过数据采集,采用AMOS21.0软件进行数据分析,对模型和假设进行了实证研究,统计分析结果表明: 消费者——网站关系、在线评论数量、在线评论质量、在线评论接收者专业能力、在线评论接收者涉入度、在线评论接收者感知风险影响消费者网络购买意愿,在线评论者资信度和在线评论的时效性影响不显著.基于此,本文对结果进行了讨论,并对消费者和网商营销提出了建议.     

商品在线评论有用性——基于品牌的调节作用分析

商品的在线评论已经成为影响顾客进行在线购买的重要因素。本文以亚马逊（中国）网站为例,研究了在线评论、评论者的数字特征对评论有用性的影响。通过对五种在线商品的1 845条在线评论进行实证分析,研究发现：在线评论的评论长度和评论者排名对评论有用性具有正向影响,同时评论长度对有用性的影响受到品牌的调节作用。另外,评论星级对评论有用性的影响也受到品牌的调节作用,并且对于大品牌产品而言,评论的极端性与评论有用性呈"U"形关系。     

在线用户评论行为时效特征影响因素实证研究

[目的/意义]针对我国在线用户评论习惯，探索用户评论行为对评论时间的影响作用因素，对电子商务运营商探究用户评论行为规律及探索潜在用户评论时间偏好具有重要的潜在商业价值。[方法/过程]基于TAM模型抽取在线用户评论行为时间特征规律研究的影响因素并构建模型，通过抽取消费者购买行为和评论行为的时间间隔为时间序列，通过多元线性回归模型进行假设验证。[结果/结论]通过对在线评论数据的实例验证，本文所构模型能够很好地发现在线用户评论行为对评论时间的影响作用关系，对消费者评论行为的时间特征规律发现和预测具有辅助作用。     

在线评论有用性的影响因素探究 ——基于京东商城的实证研究

在线评论已经成为影响消费者做出购买决策的重要因素.以信号传递理论为框架,从评论者、评论本身和有关反馈3个方面探究其对在线评论有用性的影响,并引入产品类型作为调节变量建立模型.通过京东商城的客观数据进行实证分析,结果显示,图片数量、追评、视频、评论回复数显著影响评论的有用性.其中,评论回复数的影响最为明显;产品类型在追评对评论有用性的影响中没有起到调节作用;评论者的等级、评论的可读性对评论的有用性的影响不显著.结论既对评论有用性的研究提供了参考,也有利于企业高效地管理和应用在线评论.     

Improving aspect extraction by augmenting a frequency-based method with web-based similarity measures

Online review mining has been used to help manufacturers and service providers improve their products and services, and to provide valuable support for consumer decision making. Product aspect extraction is fundamental to online review mining. This research is aimed to improve the performance of aspect extraction from online consumer reviews. To this end, we augment a frequency-based extraction method with PMI-IR, which utilizes web search in measuring the semantic similarity between aspect candidates and target entities. In addition, we extend RCut, an algorithm originally developed for text classification, to learn the threshold for selecting candidate aspects. Experiment results with Chinese online reviews show that our proposed method not only outperforms the state of the art frequency-based method for aspect extraction but also generalizes across different product domains and various data sizes.     

在线评论研究中的主题结构：社会网络分析的视角

探索在线评论相关领域中的研究主题以及它们之间的结构关系.从Web of Science核心数据库提取2009-2013年共113篇文献,通过共词分析确定了41个关键词,然后运用社会网络分析法识别了在线评论内容分析、在线评论深度挖掘、在线评论服务响应、在线评论行为研究、在线评论系统与社交媒体、在线评论与消费者决策、在线评论质量研究7个研究主题,最后提出一个新的研究框架为当前的研究提供参考.     

不同平台在线评论消费者感知差异研究——产品类型的调节作用

本文通过实验法探索消费者对于不同平台评论的感知差异以及产品类型的调节作用。首先,在已有研究的基础上对不同平台以及不同产品类型的特征进行归纳,并提出研究假设;然后,通过3*2析因设计,即3种不同平台(卖家网站、第三方平台和消费者建立平台)*2种产品类型(搜索品和体验品)共6个实验组,并利用问卷方式在线搜集数据来进行假设检验,研究发现,消费者对第三方平台和消费者自建平台的评论的感知可信度高于商家平台,并且对于体验品,商家平台与第三方平台以及商家平台与消费者自建平台之间的消费者感知可信度存在显著差异;最后,结合研究发现展开了分析和讨论。     

Understanding the effects of physical experience and information integration on consumer use of online to offline commerce

Online to Offline (O2O) commerce commands intense attention from both academic and practical fields, but the unique features of O2O commerce and how these features affect consumer use of O2O commerce remain unclear. Based on an analysis of the features of O2O commerce, we build a research model integrating perceived value theory and the technology acceptance model to examine the influence of the features of O2O commerce on consumer use intention. The research model is tested with data collected from a field survey using structural equation modelling. Two crucial features of O2O commerce, namely, “physical experience” and “integration of online and offline information”, are shown to exert significant impacts on consumer use intention via the classic core constructs of perceived benefit, perceived usefulness, and perceived value. The findings validate the two features’ impact on consumer use of O2O commerce via both technological and economic attributes. The implications for merchants’ and platforms’ operation in O2O commerce are discussed.     

‘Arrivederci CIAO.com, Buongiorno Bing.com’—Electronic word-of-mouth (eWOM), antecedences and consequences

The Internet facilitates access to online product reviews and comments written by consumers. This paper offers new insights on the motives and antecedents of the reading behaviour of consumer reviews in online opinion platforms. This research was carried out from 2005 to 2008 using a case study approach. The case involved working with a prominent and successful online opinion platform (CIAO.com). The company was so successful it was purchased by Microsoft for $486 million in 2008 and is now incorporated into their main search engine which is still a market leader today. The research highlights four different types of motives that drive customers to read online reviews: decision-involvement, product-involvement, social-involvement and economic-involvement motives. The outcomes also demonstrated four different new types of motives: self-involvement motives, consumer-empowerment motives, new social-involvement motives and site-administration motives. Several related themes were also investigated, such as the preference for reading or writing online reviews and the reasons for choosing one over the other. The research tested the relevance of the online reading motives and their influence on consumer buying and communication behaviour. In summary, some theoretical and practical implications are highlighted and discussed.     

A framework for fake review detection in online consumer electronics retailers

The impact of online reviews on businesses has grown significantly during last years, being crucial to determine business success in a wide array of sectors, ranging from restaurants, hotels to e-commerce. Unfortunately, some users use unethical means to improve their online reputation by writing fake reviews of their businesses or competitors. Previous research has addressed fake review detection in a number of domains, such as product or business reviews in restaurants and hotels. However, in spite of its economical interest, the domain of consumer electronics businesses has not yet been thoroughly studied. This article proposes a feature framework for detecting fake reviews that has been evaluated in the consumer electronics domain. The contributions are fourfold: (i) Construction of a dataset for classifying fake reviews in the consumer electronics domain in four different cities based on scraping techniques; (ii) definition of a feature framework for fake review detection; (iii) development of a fake review classification method based on the proposed framework and (iv) evaluation and analysis of the results for each of the cities under study. We have reached an 82% F-Score on the classification task and the Ada Boost classifier has been proven to be the best one by statistical means according to the Friedman test.     

初始网络信任和持续网络信任形成与作用机制比较/FONT

网络信任的缺位是制约电子商务进一步发展的主要瓶颈,探讨消费者信任的决定要素及由此产生的行为意愿,对于指导业界制定正确的消费者信任提升策略具有重要意义。本研究认为,无网络购物经验消费者初始信任的形成和作用机制与有网络购物经验消费者的持续信任形成和作用机制存在较大差异,为此,分别建立了两类消费者的网络信任模型。基于B2C和C2C网站消费者的大样本数据,采用结构方程建模方法,实证检验了理论模型和相应的一系列假设。研究结果表明：（1）两类信任的形成机制存在明显差异。无网络购物经验的消费者,基于对卖家声誉、网站安全性和网站易用性等反映客体（卖家和网站）特征的因素的感知,判断是否应当信任卖家;有网络购物经验的消费者,则更依赖对商家响应能力和联系沟通水平等反映双方互动特征的因素的体验,判断是否应当继续信任卖家。（2）两类信任的作用机制相似。不论是网络初始信任还是网络持续信任,都决定了消费者的信息提供意愿和网上购物意愿,并且网上购物意愿与信息提供意愿正相关。     

Motivation for online impulse buying: A two-factor theory perspective

Impulse buying accounts for a large proportion of consumer shopping behavior in the bricks-and-mortar retail market. Online retailers also expect to profit from impulse buying. It is therefore interesting and beneficial to investigate the design elements of online stores and the sales promotion stimuli that e-retailers can use to either arouse consumers’ desire or decrease their self-control to evoke their purchase impulses. This study seeks to explicitly identify the factors associated with online store design and sales promotion stimuli that most affect online impulse buying behavior throughout the consumer decision-making process. Drawing on the two-factor theory, it successfully identifies the hygiene and motivation factors that trigger online impulse buying. The questionnaire responses of 239 valid respondents revealed that most of the hygiene factors are associated with the design of online stores, and all of the motivation factors are forms of sales promotion stimuli that effectively facilitate online impulse buying and present utilitarian or hedonic benefits to consumers. This study also identifies the most effective sales promotion stimuli and offers a comprehensive checklist for Web designers. Moreover, the distribution of motivation and hygiene factors for each stage of the EKB model is uneven, and some stages include only hygiene factors. The findings of this study demonstrate that the triggers of consumers’ online shopping behavior do not always apply to online impulse buying, and have important implications for impulse buying research and practice.