社交网络下网络互动对购买意愿影响及信任保障机制研究
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摘要
社交网络的核心价值是人与人之间的关系,充分挖掘每个人的信息和联系,从而可以更好地为用户提供关系化服务。在国内,有部分社交网站在发展初期过分倚重游戏类应用,无法对用户形成持续的吸引力,导致用户粘性降低。同时,与个人用户紧密相关的电子商务在发展过程中也存在着较多问题,网上购物用户迫切需要一个真实可信,能够及时有效的进行信息沟通和分享的交流平台。
     社交网络这种基于信任的网络社交平台非常适合电子商务信息的共享与传播,以信任为纽带的传播方式,更容易引起其他用户的购买意愿。在电子商务中融入社交网络既丰富了消费者的购物渠道,又降低了卖家在交易过程中的成本。同时,对社交网站来说,与电子商务融合,不仅可以充分利用社交网络“人际关系”这一优势,增强社交用户之间的联系,把过去倚重游戏类应用的模式转变为以知识、信息、关系为核心的模式,而且能为社交网站拓展新的盈利模式,为社交网络的进一步发展带来新的生机。
     因此,深入研究社交商务网络的网络拓扑结构,探讨网络互动对网络购买意愿的影响,分析社交商务环境下的信任保障机制,既丰富并发展了网络消费行为理论,又有利于社交商务网络运营商对社交商务平台的管理和发展,进而保证我国社交网络能够平稳健康的发展,对互联网产业的发展具有重要的理论和现实意义。
     论文第一部分对社交商务网络的网络拓扑结构进行了研究。首先利用滚雪球抽样方法在美丽说社交商务分享网站中取得样本数据,随后通过社会网络分析软件UCINET对数据进行了分析,主要包括网络密度分析、中心性分析、凝聚子群分析和核心-边缘分析等。为了进一步探讨网络拓扑结构与用户购买意愿之间的影响关系,本研究对所有样本都发送了调查问题,然后把问卷统计情况与社会网络分析结果进行对比,总结出社交商务网络的网络拓扑结构特征。
     论文第二部分构建了社交商务用户网络购买意愿模型,并进行了实证分析和假设检验。基于社会互动理论、理性行为理论、技术接受模型、消费者行为理论、顾客价值理论等,从社交商务网络的互动角度,将网络互动分为互动场所、互动特性、互动方式和互动对象四个维度,随后进一步细分为自身定位、技术性、安全性、虚拟性、网络外部性、个性化、同步互动、异步互动、单人互动、多人互动、用户-用户互动、用户-平台运营商互动和用户-广告商互动等自变量,同时以信任作为中介变量,网络购买意愿为因变量,网络互动程度为控制变量,构建出社交商务用户网络购买意愿模型。之后通过SPSS15.0和AMOS7.0对样本数据进行了分析,并从网络互动程度角度把数据分为高程度互动组和低程度互动组进行对比分析验证。最终找出社交商务网络环境下网络互动对消费者购买意愿的影响因素。
     论文第三部分研究了社交商务网络环境下网络购买信任保障机制。在综述信息不对称相关理论及信任概念模型的基础上,对传统电子商务与社交商务进行了比较分析,然后根据社交商务用户在各交易阶段的侧重点不同,分别研究交易前、交易中和交易后三个阶段的信任保障机制。
     经过理论研究和实证分析,本研究主要获得以下三方面的结论:
     (1)社交商务网络的网络拓扑结构研究结论。整个样本网络呈现疏松的网络结构,派系较少,凝聚子群间的关系趋向随机分布,并且整个网络中只有核心区联系较为密切。社会网络分析结果与问卷统计结果对比发现,点度中心度低的用户,其购买意愿也相对较低;网络互动程度低的用户,绝大多数处于网络的边缘区,且未在派系之中;用户的网络互动程度与其购买意愿之间存在影响关系。
     (2)社交商务用户网络购买意愿模型的检验结论。除了自身定位、虚拟性、异步互动和多入互动以外,技术性、安全性、网络外部性、个性化、同步互动、单人互动、用户-用户互动、用户-平台运营商互动和用户-广告商互动等因素会积极影响用户对社交商务平台的信任。在高程度互动组和低程度互动组的比较分析中发现,网络互动程度会影响用户对社交商务平台的信任以及网络购买意愿。同时,在高程度互动群组中影响大小排序前三的是安全性、用户-广告商互动和同步互动,低程度互动群组中影响大小排序前三的是安全性、技术性和单人互动,其中安全性都是影响最大的因素。
     (3)社交商务网络环境下网络购买信任保障机制的结论。根据社交商务用户在社交商务交易过程中交易前、交易中和交易后三个阶段的侧重点不同,分别构建了三种不同类型的信任机制,包括基于声誉模型的信任机制、基于第三方认证机构的信任机制和基于服务质量的信任机制。
The core value of social network is the relationship between users, excavate users'information can provide them with better service. In China, however, parts of the social networking sites are over-reliance on the game-type applications in the initial stage of development, which can not form a continuous attraction to users. At the same time, there are still many problems in e-commerce market, online shopping users are urgently need an exchange platform which provides timely communication and effectively sharing.
     Social network is based on trust, which is important for the sharing and dissemination of information resources. Trust is the link of information dissemination, which is beneficial to cause the purchase intention of other users. About e-commerce, integration with social network not only can enrich the consumers'shopping channel, but also can reduce the cost of sellers in the transaction process. Meanwhile, merge e-commerce into social networking sites has two advantages:1) make the best of the social networking relationships, strengthen the connections between social users, transfer the past model which is relied on the game to the model that the cores are knowledge, information and relations;2) expand a new profit model for social networking sites and bring opportunities to the further development of social network.
     Therefore, study the network structure of social commerce network, discuss the influence of network interaction on purchase intention and analyze the trust guarantee mechanism in the social commerce environment not only enrich and develop the theory of network consumption behavior, but also do benefit to the development and management of social commerce platforms for social commerce network operators, which ensure the stable and rapid development of social network, and also have important theoretical and practical significance to the development of the internet industry in China.
     In the first part of this paper, we analyze the network structure of social commerce network. First, we use the snowball sampling method to obtain the sample data from "Meilishuo", which is a social shopping sharing website. Second, we analyze the data by UCINET, including network density analysis, centrality analysis, cohesive subgroups analysis and core/periphery analysis. Third, we sent survey questions to all samples in order to further study the impact of network structure on users' purchase intention, and then sum up the network structure characteristics of social commerce network.
     In the second part of this paper, we build the purchase intention model of social commerce users, and then conduct empirical analysis and hypothesis testing. From the perspective of the interaction of social commerce network, network interaction is classified by four dimensions: places of network interaction, characteristics of network interaction, modes of network interaction and objects of network interaction, and then further subdivided into self-localization, technology, security, virtual, network externality, personalization, synchronous interaction, asynchronous interaction, single interaction, multi-person interaction, member-member interaction, member-platform operators interaction and member-advertisers interaction. In the model, trust is the mediating variable, network purchase intention is the dependent variable, and degree of network interaction is the control variable. After that we analyze the data from random sampling by SPSS15.0and AMOS7.0, and divide the data into high degree of interaction group and low degree of interaction group from the degree of network interaction point of view. Finally identify the influence factors of network interaction on consumers' purchase intention in social commerce network.
     In the third part of this paper, we research the trust guarantee mechanism of network purchase in social commerce network environment. Base on the summary of asymmetric information and related game theory, we analyze the differences between traditional e-commerce and social commerce, and then according the different emphasis of social commerce users on each transaction phase to discuss the trust guarantee mechanism, including the stage of before transaction, the stage of during transaction and the stage of after transaction.
     The results of theoretic study and empirical analysis are as follows:
     (1) The conclusions about the network structure of social commerce network. The network structure of samples is loose, only has twelve factions, and the relationship between cohesive subgroups tend to be randomly distributed. Meanwhile, the contact in core area of network is more frequently than the contact in periphery area. Draw a comparison between social network analysis results and questionnaire statistical results, we find three points. First, the users' purchase intentions are relatively low when they have low degree centrality. Second, the vast majority of users who have low degree of interaction are in the periphery area of network, and do not pertain to any faction. Third, there is an impact relationship between users' degree of network interaction and their purchase intention.
     (2) The conclusions about the purchase intention model of social network users. Results show that except self-localization, virtual, asynchronous interaction and multi-person interaction, other influence factors have positive impact on users'trust in social commerce platform, include technology, security, network externality, personalization, synchronous interaction, single interaction, member-member interaction, member-platform operators interaction and member-advertisers interaction. Comparative analysis of the high degree of interaction group and the low degree of interaction group shows that different degree of network interaction will affect users'trust in social commerce and network purchase intention. Meanwhile, the top three influence factors of high degree of interaction group are security, member-advertisers interaction and synchronous interaction; about the low degree of interaction group, the top three influence factors are security, technology and single interaction.
     (3) The conclusions about the trust guarantee mechanism of network purchase in social network environment. According to the three stages of social commerce transaction phase, we build three trust mechanisms, including trust mechanism based on the reputation model, trust mechanism based on the third-party certification body and trust mechanism based on the quality of service.
引文
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