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    题名: 社群網站行為與線上社會資本對社群商務之影響- 以社群網站臉書為例
    How Behaviors on Social Network Sites and Online Social Capital Influence Social Commerce: The Case of Facebook
    作者: 吳至倫
    Wu, Chih Lun
    贡献者: 李易諭
    洪叔民
    Lee, Yih Yuh
    Horng, Shwu Min
    吳至倫
    Wu, Chih Lun
    关键词: 社群網站行為
    社會資本理論
    社會交換理論
    社群商務
    給予社群商務意願
    接受社群商務意願
    SNS Behavior
    Social Capital Theory
    Social Exchange Theory
    Social Commerce
    Social Commerce Intention (Giving)
    Social Commerce Intention (Receiving)
    日期: 2015
    上传时间: 2016-01-04 16:48:38 (UTC+8)
    摘要: 隨著社群網路不斷快發展而使得上社群網站成為使用者每日生活的一部分，而社群商務也因此蓬勃發展。社群商務是社群網站使用者因社交活動而彼此交換分享產品或服務資訊的行為。根據Forrester Research在2011年的報告，預測至2015年時社群商務的產值將達300億美金。因此社群商務將隨社群網站不斷的發展，將越來越重要。
    因此，本研究文獻回顧及焦點訪談藉由社群網站行為-參與及瀏覽二種行為、社會資本-結合型社會資本(親密朋友)及橋接型社會資本(普通朋友)來預測社群網站使用者採用社群商務-給予及接受二種意願。
    本研究以社群網站臉書的使用者為研究對象，研究以紙本及線上二種方式來搜集使用者問卷。紙本問卷主要以北部某大學生為主要搜集對象，線上問卷則以在電腦教室的大學生、社群網站臉書的線上使用者及BBS-批踢踢實業坊的使用者同時也是社群網站臉書上的使用者為主。有效問卷970份。經由信度分析、效度分析及共同方法變異分析，確認本研究之信效度，並採用偏最小平方法(Partial Least Square,PLS)，來進行結構方程模式(Structural Equation Modeling, SEM)研究模型分析。
    總體研究一開始先進行分析社群網站行為、線上社會資本及採用社群商務三者主構面皆為二階構面之間的關係。結果發現社群網站行為對線上社會資本及線上社會資本對採用社群商務三個主構面皆是顯著正向的關係。接著本研究模型整體分析社群網站行為-參與及瀏覽、線上社會資本-結合型(親密朋友)及橋接型(普通朋友)對使用者採用社群商務的意願-給予及接受皆有正向顯著的影響。因此本研究並繼續在就個別研究子構面進行探討。
    參與行為和瀏覽行為皆對結合型(親密朋友)社會資本有顯著的正向影響，但瀏覽行為對於結合型(親密朋友)社會資本的正向影響程度大於參與行為對於結合型(親密朋友)社會資本的正向影響程度。參與行為和瀏覽行為皆對橋接型(普通朋友)社會資本有顯著的正向影響，但瀏覽行為對於橋接型(普通朋友)社會資本的正向影響程度大於參與行為對於橋接型(普通朋友)社會資本的正向影響程度。
    參與行為對採用社群商務意願（給予）有顯著的正向影響，但瀏覽行為對採用社群商務意願（給予）沒有影響。參與行為和瀏覽行為皆對採用社群商務意願（接受）皆有顯著的正向影響，但參與行為與瀏覽行為二種行為對於採用社群商務意願（接受）沒有顯著的不同。
    結合型(親密朋友)及橋接型(普通朋友)社會資本對採用社群商務意願（給予）皆有顯著的正向影響，且橋接型(普通朋友)社會資本對於採用社群商務意願（給予）的正向影響程度大於結合型(親密朋友)社會資本對於採用社群商務意願（給予）的正向影響程度。結合型(親密朋友)及橋接型(普通朋友)社會資本對採用社群商務意願（接受）皆有顯著的正向影響，但結合型(親密朋友)及橋接型(普通朋友)二種社會資本對於採用社群商務意願（接受）沒有顯著的不同。
    綜上所述，總體而言，瀏覽行為對於社會資本優於參與行為對於社會資本的影響。參與行為對於採用社群商務意願優於瀏覽行為對於採用社群商務意願。橋接型(普通朋友)社會資本對於採用社群商務意願優於結合型(親密朋友)社會資本對於採用社群商務意願。
    此外，在經由量化分析研究，本研究獲得全部研究假設分析的結果，接著本研究並採用事後質性分析(Post Hoc Qualitative Analysis)，利用半結構式深度訪談，對象包括大學部1-4年級的學生及上班族來做事後質性分析。事後質化分析的結果是將量化分析的所支持的假設加以驗証及探究更深一層的說明，並提供解釋量化分析所不支持假設的可能原因。
    本研究理論貢獻在於採用社群網站行為-參與及瀏覽及線上社會資本-結合型(親密朋友)及橋接型(普通朋友)來預測採用社群商務-給予及接受之意願。較少研究採用社群網站行為及社會資料理論來解釋社群商務。管理意涵在於社群網站的營運者，應思考如何藉由社群網站來增加對使用者的〞黏性〞及提昇使用者瀏覽網站的流量，並依據使用者之前瀏覽的記錄，來推測並提供使用者所喜好的内容。更進一步來說，為增加使用者的參與行為可依照使用者彼此間的互動來分析使用者社群網站上的行為以推薦使用者加入其有興趣的粉絲團及社團，以增加親密朋友及普通朋友之使用者彼此的互動，同時增加線上結合型及橋接型社會資及使用者採用社群商務的意願。此外，本研究建議社群網站經營者應努力發展線上朋友介紹功能，並藉由大數據的資料分析擴大使用者的交友範圍。對於使用者線下的朋友，希望將其成為本身結合型(親密朋友)或橋接型(普通朋友)的社會資本。對於使用者線上不認識的朋友，希望能其成為橋接型(普通朋友)的社會資本，因為他們可能加入同一粉絲團或社團，以促進社群網站的使用者採用社群商務的意願。
    Following the fast growing of social network sites (SNS) such as Twitter, LinkedIn and Facebook in the cyber world recently, the social commerce has become an important emerging issue in these SNS. According to the Forrester Research (2011) predicted the total value of output for social commerce will reach US$30 billion in 2015. Because the development of social commerce will follow the continueous growing of SNS, the social commerce will play a pivotal role in the e-commerce.
    According to the literature review and focus group discussions, the study explored and applied SNS behavior including participating and browsing, social capital theory including bonding (close friends) and bridging (ordinary friends) to predict SNS users to adopt giving and receiving social commerce intention (SCI).
    The study applied an empirical research on SNS users i.e. FB users to be research target samples. The data collection were applied by paper_based and online_based as two way to collect sample data. With regard to sample data from paper_based survey, the study adopted undergraduate students of a university located in northen Taiwan was the research main collection samples for paper_based survey. As to online_based survey, the study utilized undergraduate students, who are the same as paper_ based survey in the same university with computer lab classes, FB users of researchers’ friends and Taiwan largest Bulletin Board System-PTT who are also FB users to collect online users’ data. The total valid samples are 970 from online_based and paper_based survey. After reliability analysis, validity analysis and common method variance testing, the study confirmed that reliability and validity of study samples met the requirement of each statistical testing and were qualified for testing the study whole research model. Then, the study adopted partial least square (PLS) to proceed with structural equation modeling (SEM) research model testing.
    As to whole model research testing, in the beginning the study was testing the relationship among SNS behavior, online social capital and SCI. The three constructs are second order constructs. The testing results show the effects of SNS behavior on online social capital and the effects of online social capital on SCI are significantly positive. Hence, the research continues to proceed with the research model testing. The research findings of whole research model testing have shown SNS behavior as a second order construct of participating and browsing, online social capital-bonding and bridging are both significantly positive influence to adopt social commerce intention as a second order construct as SCI (giving and receiving). Hence, the study will continue to explore the relationships between each sub-construct in the research.
    Participating and browsing behavior are both significantly positive on bonding social capital. Moreover, browsing behavior is more significantly positive associated with bonding social capital than participating behavior is associated with bonding social capital. Participating and browsing behavior are both significantly positive on bridging social capital. Browsing behavior is more significantly positive associated with bridging social capital than participating behavior is associated with bridging social capital.
    Participating behavior is significantly positive on adopting SCI (giving). However, browsing behioavr is no significant influence on adopting SCI (giving). Participaiting behavior and browsing behavior both have significantly positive influences on SCI (receiving). However, there are no significant differences between participating behavior and browsing behavior on adopting SCI (receiving).
    Bonding and bridging social capital are both significantly positive on SCI (giving). Moreover, bridging social capital is more significantly positive associated with SCI (giving) than bonding social capital is associated with SCI (giving). Bonding and bridging social capital are both significantly positive on SCI (receiving). However, there are no significant differences between bonding and bridging social capital on adopting SCI (receiving).
    To Sum up, generally speaking, browsing behavior is better on social capital than participating behavior is on social capital. Participating behavior is more suitable on adopting SCI than browsing behavior is on social capital. Bridging social capital is more appropriate on adopting SCI than bonding social capital is on adopting SCI.
    Besides, after quantitative data analysis, the study proceeds with the post hoc qualitative analysis. Utilizing semi-structured in-depth interviews with undergraduate students and working persons to continue post hoc qualitative analysis. The aim of post hoc qualitative analysis is to validitate and provide insight for the hypotheses which are supported by quantitative analysis. Moreover, it provides the explainations for the hypotheses which ae not supported by the quantitative analysis.
    The theory contributions of the study are applying SNS behavior including participating and browsing, social capital theory including bonding and bridging to predict SNS users to adopt SCI (giving and receiving). Seldom researches SNS behavior and social capital theory to explain social commerce individually. With regard to managerial implications are for SNS operators to think how to utilize SNS to increase users stickiness and raise users’ browsing quantities - following the users’ accumulated browsing behaivors history to predict and provide the contents which users may have interest. Moreover, regarding the interacting behavior for SNS users of participating behavior is to analyze the behaviors of SNS users and to recommend uers to join the fan pages or clubs that they may be interested in. Doing so is to increase the interactions with close friends and ordinary friends to enhance online bonding and bridging social capital and the users’ intentions to adopt SCI simotenously. In addition, the study recommends SNS operators to adopt friends introducing functions thoroughly and apply big data statistical analysis to enlarge the users’ friends rang to make more SNS friends. For the SNS offline friends, the study wish to let SNS users’ offline friends to become their online bonding or bridging social capital. For the SNS online unknown friends, the study wish to let SNS users’ online unkown friends to become their online bridging social capital because they may join the same fan pages or clubs to enlarge and accelerate SNS users to adopt SCI.
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