過去關於集資的研究帶來了一股促進新創企業發展的趨勢，新創公司可以利用公開的管道如融資輪來吸引天使投資人或是創投公司這類潛在的投資者來投資，透過這些管道而來的投資可以使新創公司有更多資源發展自己的業務。然而新創公司仍然需要面對新創事業的高風險與不確定性，本研究回顧了過去有關創業成功的研究，發現有一些指標會影響新創公司創業的結果，因此我們關注這些因素和指標並想找出那些指標對新創公司的成功是有影響的。在回顧相關文獻後我們發現投資行為會受到社會網路的影響，以社會網路結構為基礎的一些文獻揭示出社會網絡結構之間的關係會對投資行為和經濟增長產生正面影響，因此我們在我們的模型中選擇使用社會資本理論來解釋此一現象。本研究的研究資料來源為Crunchbase.com網站，我們首先從Crunchbase.com上收集多輪企業及融資輪的相關資訊，接著利用複迴歸分析出哪些指標是重要的並且找出該指標在集資過程的運作方式及影響。我們的研究結果表明前一輪中的集資金額及投資者數量等融資輪訊息會對下一輪的集資情況產生正面影響，此外前一輪投資者的協同社會資本及關係社會資本會對下一輪的募資情況產生調節效果，這些結果告訴我們新創企業在集資的過程中若能把握初期幾輪的融資輪獲得不錯的集資金額或投資者數量的話，這些成果會在後續幾輪的融資輪帶來正面的回報。

The past researches about funding had revealed a new startup trend. Startups can use public channels like funding series to attract potential investors like an angel investor or venture capital. This kind of channel can make startup start its business more smoothly. However, startups still face high risk and uncertainty. We review the research about successful startups. We found there are some factors that affect the result of the startup. Thus, we focus on these factors and indicators to find out what indicators will affect the resource, which is crucial to startup. After reviewing related literature, we found investment behavior influenced by the social network. And base of social network structure, some literature revealed that the relationship between social network could bring positive effect on investment behavior and economic growth. Then we adopt social capital theory in our model. Our data mainly collected from Crunchbase.com, and we took multiple regression analysis to analyze which indicator is important and how it works on funding series. Our research shows that the fund condition like fund amount and investors number in funding series have a massive effect on next round fund condition. And some constructs of social capital have a moderating effect on fund condition.

論文審定書 i
摘要 ii
Abstract iii
Table of Contents iv
List of Figures vi
List of Table vii
Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Question 6
1.3 Coverage 7
1.4 Contributions 8
Chapter 2 Literature review 9
2.1 Venture capital 9
2.2 Social network 12
2.3 Social capital 14
Chapter 3 Research method 18
3.1 Research model 18
3.2 Hypothesis development – Model 1 20
3.3 Hypothesis development – Model 2 24
3.4 Data gathering 27
3.5 Proxy variable 28
3.5.1 Structural social capital 29
3.5.2 Cognitive social capital 30
3.5.3 Relational social capital 31
3.6 Data preprocessing 32
Chapter 4 Analysis Result 34
4.1 Data description 34
4.2 Correlation analysis result 37
4.3 Independent test 39
4.4 Multiple-collinearity test 40
4.5 Regression analysis result – Model 1 40
4.5.1 Main effect of fund amount 42
4.5.2 Main effect with investors’ social capital 44
4.5.3 Moderating effect 45
4.6 Regression analysis result – Model 2 56
4.6.1 Main effect of investors number 56
4.6.2 Main effect with investors’ social capital 58
4.6.3 Moderating effect 59
4.7 Analysis summary 68
4.7.1 Summary of Model 1 69
4.7.2 Summary of Model 2 70
Chapter 5 Discussion and Conclusion 73
5.1 Discussion 73
5.2 Conclusion 75
5.3 Limitation 77
Reference 79

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