學術研究之競爭日趨激烈，學者之間透過學術合作進行研究，加快速度並解決目前所遭遇的研究瓶頸。學術合作的優點在於每位學者的觀念、背景及思考邏輯皆不盡相同，透過學術合作，學者間不僅能互相分享觀點、研究方法及經驗，也能有效的整合現有資源來產生最大效益。據此，學術合作便逐漸成為科學研究的主流趨勢。
本研究蒐集2007年至2017年臺灣經濟、管理領域學者於WOS共同發表的論文，藉由學者之間的合作關係建構出共同作者合作網絡，經過資料整理後，最終樣本數為13,913篇文獻，當中包含6,111位學者。以這些文獻為樣本，建構共同作者網絡，再利用集群分析，找出學者之間的隱性研究團隊。本研究一方面針對文獻進行分析，了解各團隊主要研究之議題及學者間的合作樣態；另一方面，也將探討影響隱形研究團隊學術影響力之重要因素。
研究結果顯示，學者因合作而形成的隱性團隊，其中經濟成長、股票收益、一般管理、庫存管理、創新與科技管理以及人力資源管理等六個領域的學者合作網絡為最大的合作群體。另外，觀察各團隊不同的網絡統計特性（如網絡密度、集中化程度等），亦發現縱使為不同的研究議題，各領域團隊的網絡特性並無太大差異，合作模式僅少數領域為分散型合作模式，如人力資源管理，而大部分領域的合作模式仍以些許學者為中心的集中型合作模式。學者的合作關係大多仍以師生、同儕或是同事為主。此外本研究藉由線性迴歸分析發現隱形研究團隊於團隊間網絡中的位置是影響隱形研究團隊長期影響力的重要因素。

The competition for academic research is becoming fierce, and scholars through academic cooperation to solve the current bottleneck of research. The advantage of academic cooperation is that each scholar's concept, background and thinking are different. Through academic collaboration, scholars can not only share ideas, research methods and experiences, but also effectively integrate existing resources to produce maximum benefits. Therefore, academic cooperation has gradually become the mainstream trend of scientific research.
This study collected papers jointly published by scholars from Taiwan’s economic and management fields from 2007 to 2017 in the WoS. The cooperative network of co-authors was constructed through the cooperation among scholars. After data collation, the final sample number was 13,913 documents, from 6,111 scholars. Using these documents as samples, this study constructed a network of co-authors and used cluster analysis to identify hidden research teams among scholars. On one hand, this study focuses on literature analysis to find out which cooperative issues form important partnerships between hidden teams and scholars; on the other hand, it also explores important factors that affect the academic influence of invisible research teams.
The research results show that the invisible college formed by scholars in cooperation include financial, commercial finance, accounting, productivity analysis, energy policy, corporate social responsibility, enterprise resource planning, etc. Among them, cooperation network of scholoars in six areas including economic growth, stock returns, general management, inventory management, innovation and technology managent, and human resource management is the largest cooperative group. In addition, by observing different network statistical characteristics (such as network density, centralization) of each group and it is also found that the different research topics, the network characteristics of various areas are not much different, only a few areas of cooperation mode for decentralized cooperation model. such as human resources management, and most of the field of cooperation model is still a few scholars-centered cooperative model. Most of the scholars ' cooperative relationships are still dominated by teachers and students, peers or colleagues. In addition, this study explores the position of the stealth research team in the network by linear regression analysis, which is an important factor influencing the long-term influence of the stealth research team.
Analyzing the cooperation patterns of the invisible academic research team, the key words statistics, the different network characteristics of each team, we can not only discover the core issues in the field, but also can understand the interaction of scholars and cooperation between scholars through the network statistical analysis. Through academic cooperation, we can not only achieve academic resource sharing, but also broaden our academic horizons and enhance the quality of research results. In addition, through the power of knowledge dissemination, we can also influence society and accelerate scientific development.

1. Beaver, D. D. (2001). Reflections on Scientific Collaboration (and its study): Past, Present, and Future. Scientometrics, 52(3), 365-377.
2. Brunn, S. D., & O'Lear, S. R. (1999). Research and communication in the “invisible college” of the Human Dimensions of Global Change. Global Environmental Change, 9(4), 285-301.
3. Burt, R. S. (1992). Structural holes: The social structure of competition: Harvard university press.
4. Casanueva, C., & Larrinaga, C. (2013). The (uncertain) invisible college of Spanish accounting scholars. Critical Perspectives on Accounting, 24(1), 19-31.
5. Crane, D. (1974) . Invisible colleges; diffusion of knowledge in scientific communities: University Of Chicago Press
6. Egghe, L., & Rousseau, R. (2003). A measure for the cohesion of weighted networks. Journal of the Association for Information Science and Technology, 54(3), 193-202.
7. Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215-239.
8. Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99(12), 7821-7826.
9. Hanneman, R. A., & Riddle, M. (2005). Introduction to Social Network Methods.
10. Ho, M., & Verspagen, B. (2006). The role of national borders and regions in knowledge flows. How Europe’s economies learn: Coordinating competing models, 50-73.
11. Katz, J. S. (1994). Geographical proximity and scientific collaboration. Scientometrics, 31(1), 31-43.
12. Lievrouw, L. (1989). The Invisible College Reconsidered Bibliometrics and the Development of Scientific Communication Theory (Vol. 16).
13. Lievrouw, L. A., Rogers, E. M., Lowe, C. U., & Nadel, E. (1987). Triangulation as a research strategy for identifying invisible colleges among biomedical scientists. Social networks, 9(3), 217-248.
14. Liu, J. S., Lu, L. Y., & Ho, M. H.-C. (2012). Total influence and mainstream measures for scientific researchers. Journal of Informetrics, 6(4), 496-504.
15. Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36(3), 363-377.
16. Palacios-Núñez, G., Vélez-Cuartas, G., & Botero, J. D. (2017). Developmental tendencies in the academic field of intellectual property through the identification of invisible colleges. Scientometrics, 1-14.
17. Persson, O., Glänzel, W., & Danell, R. (2004). Inflationary bibliometric values: The role of scientific collaboration and the need for relative indicators in evaluative studies. Scientometrics, 60(3), 421-432.
18. Pravdić, N., & Oluić-Vuković, V. (1986). Dual approach to multiple authorship in the study of collaboration/scientific output relationship. Scientometrics, 10(5-6), 259-280.
19. Price, D. J. d. S. (1986). Little science, big science: Columbia University Press New York.
20. Sparrowe, R. T., Liden, R. C., Wayne, S. J., & Kraimer, M. L. (2001). Social networks and the performance of individuals and groups. Academy of management journal, 44(2), 316-325.
21. Teixeira, A. A. C. (2011). Mapping the (in)visible college(s) in the field of entrepreneurship. Scientometrics, 89(1), 1.
22. Van Raan, A. F. J. (1998). The influence of international collaboration on the impact of research results - Some simple mathematical considerations concerning the role of self-citations. Scientometrics, 42(3), 423-428.
23. 王克君. (2001)。從科學史看無形學院對科學發展的作用。東北大學學報（社會科學版）(2001年 02)。 122-124.
24. 呂威寰（2015）。軟體工程領域國際科學合作趨勢之研究(未出版之碩士論文)。輔仁大學圖書資訊學研究所。
25. 宋麗萍、徐引篪（2007）。基於 SNA 的電子無形學院結構分析。情報學報， 26（6），頁 902-908。
26. 孫于智（2012）。臺灣英語教學領域教師對 SSCI 現象的看法及隱性學群之探討。英語教學期刊， 36（4），頁 79-121。
27. 袁大鈺、林奇秀（2009）。資訊傳播科技與非正式學術傳播: 社會取向的實證研究回顧。圖書與資訊學刊（69），頁 52-77。
28. 袁大鈺、唐牧群（2010）。跨領域學術社群之智識網絡結構初探: 以臺灣科技與社會研究為例。圖書資訊學刊， 8（2），頁 125-163。
29. 張郁蔚（2010）。臺灣與日本雙邊科學合作之探討: 2000-2009 年合著論文之書目計量研究。圖書資訊學刊， 8（2），頁 55-93。
30. 張郁蔚. (2011)。從共同作者之學科組合探討跨學科合作: 以高分子學研究為例。圖書與資訊學刊(78)，頁42-62.
31. 許秩維. (2018). 台生出國留學意願降 就業景氣可能是關鍵。取自https://www.nownews.com/news/20180408/2731533
32. 楊順涵。探討社會企業研究之發展軌跡與知識網絡(未出版之碩士論文)。臺灣科技大學科技管理研究所。
33. 趙蓉英、温芳芳 (2011) 。科研合作與知識交流。圖書情報工作，55(20)， 6-27。
34. 劉顯仲、盧文民 (2008)。科專執行單位效率評估---結合資料包絡分析與以參考網路為基礎的區分方法。科技部計畫結案報告。
35. 劉顯仲、盧煜煬 (2017) 。臺灣人文及社會科學研究樣態。科技部計畫結案報告。
36. 謝彩霞. (2008a)。國際科學合作研究狀況綜述。科研管理，29(3)，179-186。
37. 謝彩霞（2008b）。網絡分析方法用於納米科技領域科學合作狀況的研究。科研管理， 29（1），頁 130-137。
38. 蘇郁仁. (2010)。兩岸學術合作之文獻量化分析(未出版之碩士論文)。國立中央大學產業經濟研究所。
39. 蘇國賢. (2004)。社會學知識的社會生產：台灣社會學者的隱形學群。台灣社會學(8)，133-192。