近年來，創業成為產業發展和轉型的重要推力。隨著創業活動的多元發展，相關的學術研究也逐年增加，再加上創業牽涉跨領域的研究，在文獻眾多且研究類別多元的情況下，卻缺乏完整及系統性的分析。本研究將探究學術文獻中創業相關領域的議題，了解知識領域的擴散和演變的情況。
使用WOS資料庫，以創業為關鍵字檢索相關文獻資料，共11206筆。運用引證和字詞關係為基礎的兩種不同研究方法，分別對文獻分群後，分析及比較兩者結果之差異。再結合tf-idf關鍵字分析，生成更進一步的關鍵字網路和分群間網路。關鍵字網路能夠更深入地了解每個分群中的議題。分群間的關係網路強調議題與議題間的連結，了解知識網路擴散的情形。
以引證關係為基礎的分群法將創業相關文獻分類為四個大議題：「創業機會的發掘與利用」、「創業導向與績效衡量」、「創業與區域發展」、「創業教育」。以文字關係為基礎的分群法將上述的四大議題更加細部的切分成六個主題，其中包含四個新議題：「創業機會、行為、績效」、「創業家人格特質」、「聯盟創業與國際化趨勢」、「新創公司與創業家財務」。綜上所述，文字關係為基礎的分群法相較於引證關係分群更能找出加細緻的議題，讓特定研究領域的分析更完整。
分群結果依研究範圍可將議題分為微觀(micro)的「創業家」層次、中觀(meso)「新創企業」層次、宏觀(macro)的「環境」層次。其中「創業導向與績效衡量」議題中的文獻包含以創業家、創業企業員工、新創公司為研究主體之研究，介於微觀與中觀之間，「新創公司與創業家財務」也有相同情況。「創業教育」的研究則是涵蓋了教育機構、教育政策、創業環境，囊括中觀與宏觀的文獻資料。
本研究的貢獻在於比較引證和字詞關係分群法之結果，提供不同角度的分析結論。此外，後續分析中分別運用質化分析與tf-idf關鍵字分析法判讀量化分群法的結果，了解議題間的關係，發現質化分析與量化分析的tf-idf關鍵字法產生了相同的結論，亦能互補性地驗證兩者結果。結合質化和量化的研究方式，不僅讓結論更加完整，也能加強研究的可信度。

Entrepreneurship has become an important driving force for industrial development and transformation in recent years. With the diversified development of entrepreneurial activities, related academic research has also increased year by year and involved cross-disciplinary issues. However, among these different researches, we need a complete and systematic analysis to explore the main themes in entrepreneurship studies. This study applies methods from different perspectives to explains how knowledge flows and changes in this field.
To observe the development, this study collects entrepreneurship relevant publications from WOS database, with a total of 11206 literature. Both citation-based and text-based methods are applied to identify the main themes of these studies. In addition, further keyword and inter-group networks are generated by combining with tf-idf keyword analysis. The keyword network provides a deeper insight of each issue, and inter-group network emphasizes the relationship among issues in order to understand the spread of the knowledge.
The results show that different methods both identify main themes belonging to macro, meso, and micro level. Entrepreneurial literature is classified into four topics by citation-based clustering method, i.e., “discovery and utilization of entrepreneurial opportunities”, “entrepreneurship orientation and performance measurement”, “entrepreneurship and regional development”, and “entrepreneurial education”. The text-based method identifies some more small but emerging themes, especially, the existence of “alliance entrepreneurship and internationalization trend”, and “entrepreneurs and startup finance”. To sum up, besides the citation-based method, the text-based clustering is complementary to show a more complete picture of the development of a research field.
The contribution of this study is to compare the results of citation-based and text-based clustering methods and provide the analysis from different perspectives. In addition, qualitative analysis and tf-idf keyword analysis are used to interpret the relationship of the clusters and provide further details for each cluster. The integration with qualitative analysis and quantitative analysis not only brings the findings a complete explanation but also enforces the credibility of research.

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