臺灣博碩士論文加值系統

科學遷移影響國家整體科研發展，長久以來備受重視。本研究以遷移至臺灣、中國、日本、南韓之929位商管領域學者為研究對象，探討學者的科學遷移特性（包含發表文章特性、合著特性與機構類型變化）、科學遷移結果（包含遷移次數與遷移距離）及科學遷移影響因素（包含學術聲望與經濟資源）等三面向情形，並對臺中日韓在國與國之間人才流動情形做整體的檢視，評估各國的人才得失。本研究自Web of Science資料庫蒐集遷移學者至2019年為止所有的書目紀錄，再以自動化方式將Scopus作者 ID對應至Web of Science書目資料，進行跨資料庫的作者姓名識別。最後，用哈密頓路徑演算法來計算學者的遷移次數，建構出學者的遷移軌跡。
研究結果發現，在科學遷移特性上，四國商管領域學者的相對論文發表比值平均為2.01。臺灣學者發表文章的平均被引次數最多，可知臺灣作者發表論文有一定的水準。發表文章領域主要集中在「商業與經濟」領域，符合樣本領域背景。國際合作情形可看出，臺灣、日本及南韓以美國為首要合作對象，中國則與香港合作較為緊密。機構類型變化的分析結果則顯示四國學者都以大學之間的遷移為主，大學與產業、大學與政府之間的跨機構遷移比例少。
在科學遷移結果面向上，研究結果顯示科學遷移趨勢以學術年齡3至13歲時期為高峰，超過學術年齡14歲之後遷移率便往下降。遷移次數部分，研究分析三種科學屬性，以資深學者、國際遷移者及臺灣的遷移機率最高。而遷移距離的分析結果發現，資深、中堅、年輕學者的「初次遷移距離」無顯著差異，說明學者在職涯初期的遷移距離沒有世代差異。另外，研究更發現四國的國內遷移者以同區遷移為主，跨區遷移比例較低，顯示學者傾向遷移至鄰近地區。
科學遷移影響因素的分析結果顯示，國際遷移者多為學術聲望及經濟資源皆向下的遷移軌跡，國內遷移者亦多半往學術聲望較低的機構遷移，但卻有較高比例會遷移至經濟發展較好的地區或城市。而分析學者的初次遷移的軌跡則發現，向下遷移的比例隨著學術年齡越輕越高，代表多數年輕學者遷移後的學校比母機構的學術聲望要低。綜合學術聲望與經濟資源的象限圖分析結果顯示，本研究樣本學者的遷移主要分布於第三象限與第一象限，也就是若遷移到學術聲望較好的學校則該地區的經濟條件亦較佳，反之亦然。
觀察臺中日韓四國的人才流動情形發現，遷移至中國的學者比例從1979年至2009年區間的9%提升至2010年至2019年區間的41%，顯示中國在2010年至2019年區間為人才獲得大國。另一方面，臺灣遷入的學者從1979年至2009年區間的28%，下降至2010年至2019年區間的12%。由於日本及南韓在兩段時期的學者遷入比例並無太大變化，推論中國在2010年至2019年期間吸納了許多臺灣與世界其他各國的人才。
本研究結果證實書目計量方法可以有效分析科學遷移與人才流動。由於科學遷移與分析資料集、國際情勢及各國教育制度有關，建議進行多國家科學遷移研究時可採用多種引文資料庫之書目資料，建構細密的科學遷移軌跡，並同步蒐集各國教育制度規範與各項國際事件等質性資料，分析與詮釋學者的科學遷移與研究表現將會更加精確。

Scientific migration has long been highly valued since it is related to a country’s general development of scientific research. This study focuses on 929 migrant scholars in the field of business/management who have migrated to China, Japan, South Korea, and Taiwan (CJKT). It explores three aspects of scientific migration: the publication characteristics and movement of migrant scholars (including research performance, research collaboration, and changes in institution types), the scientific migration outcomes of migrant scholars (including the number of moves and migration distance), and the factors affecting scientific migration (including academic reputation and economic resources). Furthermore, this study observed the overall flow of migrant scholars between other countries and CJKT, assessing the brain gain and brain drain of the four countries. The bibliographic data of 929 migrant scholars were collected from the Web of Science; Scopus author IDs were used to disambiguate the cross-database data. The Hamiltonian path algorithm was used to process the bibliographic data, construct the migration trajectories of individual authors across publications, and identify their locations.
The result of research performance reveal that, the average relative publication rate of migrant scholars is 2.01. Scholars in Taiwan have the highest citations per paper among the four countries. The published papers are mainly concentrated in the field of business & economics, which is in line with the background of the sample. In terms of research collaboration, the results show that the U.S. is the main collaborative partner for migrant scholars from Japan, South Korea and Taiwan; China, by contrast, has primarily formed partnerships with Hong Kong. Regarding the changes of institution types, more than 90% of the institutional changes for migrant scholars are university-to-university migration, and the number of moves to non-universities are rare, accounting for less than 5% of all institutional changes.
For the analysis of scientific migration outcomes, the results reveal that, the main migration period for migrant scholars are between the academic age of 3 and 13 years, after which the migration rates decrease. In terms of the number of moves, three variables (academic age, migrant type, and country) have significant effects on migration moves, with senior scholars, international migrants and Taiwanese scholars having the highest migration rates. The migration distance of migrant scholars is similar across academic age groups regarding their “first-move distance”, indicating that the various generations of migrant scholars share similar career trajectories during the early stage of their careers. Furthermore, the research results also reveal that cross-regional migration rates are low, indicating that domestic migrants are less likely to undertake long-distance migrations.
For the factors affecting scientific migration, the overall results show that international migrants primarily migrate to institutions with lower academic reputation and economic resource scores. Domestic migrants also tend to migrate to institutions with lower academic reputation scores, however, a higher proportion of them migrate to regions or cities with better economic development. This study further analyzes the first migration of scholars, and the results show that the proportion of downward migration increases with younger academic age, indicating that most junior scholars migrate to institutions with lower academic reputation scores than their original institutions. The quadrant analysis results show that the migration trajectory of migrant scholars in this study are primarily found in the third quadrant (downward migration of academic reputation and economic resources) and the first quadrant (upward migration of academic reputation and economic resources), that is, if scholars migrate to institutions with better academic reputation, the economic conditions in that region are also generally better, and vice versa.
Observing the flow of international migrants in China, Japan, South Korea and Taiwan, it is found that the proportion of scholars who migrate to China increased from 9% during 1979–2009 to 41% in 2010–2019, indicating that China is a “brain gain” country during 2010–2019. On the other hand, scholars who migrate to Taiwan decreased from 28% during 1979–2009 to 12% in 2010–2019. Since there was no significant change in the proportion of migrant scholars in Japan and South Korea over the two periods, it can be inferred that China has attracted many scholars from Taiwan and other countries around the world during the 2010–2019 period.
The results of this study confirm that bibliometric methods can effectively analyze scientific migration and talent flow. Since scientific migration is related to the analyzed datasets, international events and national education systems, it is recommended to capture bibliographic data from multiple citation index databases when conducting scientific migration studies across multiple countries, which can then be used to construct detailed migration trajectories of migrant scholars. In addition, collecting qualitative data such as major international events and the educational system in different countries will enable a more accurate analysis and interpretation of the scientific migration and research performance of scholars.

摘要 I
Abstract III
目次 VII
圖目次 IX
表目次 XI
第一章 緒論 1
第一節 問題陳述 1
第二節 研究目的與問題 7
第三節 研究範圍與限制 9
第四節 名詞解釋 11
第二章 文獻探討 15
第一節 科學遷移 15
第二節 科學人才遷移與合作 27
第三節 科學遷移的影響因素 37
第四節 臺中日韓的科學人才遷移 47
第三章 研究設計 55
第一節 研究方法與對象 55
第二節 研究架構與設計 63
第三節 研究步驟與流程 73
第四節 資料處理與分析 77
第四章 研究結果 91
第一節 發表特性與機構類型變化 91
第二節 不同遷移屬性之遷移結果分析 108
第三節 學術聲望及經濟資源與遷移之關係 123
第四節 臺中日韓學術人才流動之綜合討論 149
第五章 結論與建議 160
第一節 結論 160
第二節 建議 164
第三節 研究貢獻 167
第四節 進一步研究之建議 169
參考文獻 172

BBC NEWS（2019年8月21日）。中美貿易戰讓大批中國留學生棄美留英。BBC NEWS中文。https://www.bbc.com/zhongwen/trad/world–49420707
行政院主計總處（2010）。中華民國職業標準分類（第6次修訂）。https://www.dgbas.gov.tw/ct.asp?xItem=26132&ctNode=3112&mp=1
行政院主計總處（2016）。中央政府各機關派赴大陸地區、香港及澳門出差人員生活費日支數額表。https://law.dgbas.gov.tw/NewsContent.aspx?id=800
行政院主計總處（2019）。中央政府各機關派赴國外各地區出差人員生活費日支數額表。https://law.dgbas.gov.tw/NewsContent.aspx?id=1124
吳文星（2000）。日治時期的台灣教育與社會流動。臺灣文獻，51（2），163–174。
李幸珍、張錦特（2015）。台灣商管學院在國際頂尖期刊發表狀況之研究。中山管理評論，23（4），1057–1083。
周祝瑛（1999）。大陸高等教育問題研究: 兼論台灣相關課題。臺北市：師大書苑。
彼得‧史托克（2002）。國際遷徙與移民：解讀「離國出走」。（蔡繼光譯）。臺北市：書林。（原著出版於2001）。
姜蘭虹、黃子健（2016）。全球城市的生活挑戰與機遇：以臺灣青年人才遷移香港為例。中國地理學會會刊，（56），45–66。
泉三郎（2019）。岩倉使節團：環遊世界，探索日本現代化的方向。走進日本。https://www.nippon.com/hk/japan–topics/g00680/
胡建華（2001）。戰後日本大學史。南京：南京大學出版社。
祖父江孝男（2018）。日本縣民性學問大：文化人類學家的47都道府縣性格大調查。（陳亦苓譯）。臺北市：遠足文化。（原著出版年：2000）。
高崑銘、吳信宏（2009）。馬可夫鏈模式於服務品質之應用。科技管理學刊，14（4），57–81。
張妍、丁昱（2020年6月18日）。重磅：實驗室裏的政治陰影，被FBI瞄準的中國「千人計劃」。端傳媒。https://theinitium.com/article/20200618–international–fbi–ten–thousand–plan–china–united–states/
張建中（2022年2月15日）。台積電招募政經博士人才因應地緣政治分析。中央通訊社。https://www.cna.com.tw/news/afe/202202150206.aspx
張郁蔚（2009）。以直接引用、書目耦合及共同作者探討圖書資訊跨學科之變遷。未出版之博士論文，國立臺灣大學圖書資訊學研究所，臺北市。
陳光華、陳雅琦（2015）。探索人文社會學者研究產出之總合軌跡：以臺灣大學人文社會高等研究院為例。圖書資訊學刊，12（2），81–116。
陳明俐（2019）。推動ORCID對學術傳播的重要性。科技政策觀點。doi:10.6916/STPIRP.2019–08–08
陳金龍（2014）。十二五規劃下中國大陸高等教育的發展與挑戰：兼論其對我國教育政策之意涵。學校行政，（91），181–198。
陳信宏主持（2007）。主要國家吸引人才政策之研究。（行政院經濟建設委員會委託研究計畫成果報告，（96）005.802）。臺北市：行政院經濟建設委員會。
陳雅雯（2018）。強化延攬外籍人才策略之國際做法研究。在國家發展委員會人力發展處編，人力規劃及發展研究報告第18輯（頁199–230）。臺北市：國發會。
馮昭、林克倫（2018年10月14日）。中國千人計畫一次看懂。中央通訊社。 https://www.cna.com.tw/news/acn/201810140176.aspx
黃意丹、詹德譯、殷正華、高敏雅（2019）。歸國博士級人才在地連結相關計畫之研究。臺北市：財團法人國家實驗研究院科技政策研究與資訊中心。
黃意植（2016）。韓國人才政策初探。科技政策觀點。doi:10.6916/STPIRP.2016–04–11.0001
黃慕萱（2011）。世界大學科研論文質量評比與其他排名系統比較。評鑑雙月刊，（29），53–59。
黃慕萱、張郁蔚（2005）。從研究產出探討人文社會學者學術評鑑之特性。圖書資訊學刊，2（3/4），1–19。
葛劍雄（2005）。中國移民史。臺北市：五南。
詹盛如（2017）。亞洲跨境學生流動：哪些品質重要呢？。評鑑雙月刊，（70），19–21。
劉郁昇、徐健進、楊君琦、鄒幼涵、鄭宇庭（2008）。專業人才之培養、延攬與流動：華人地區跨國比較研究。數據分析，3（6），127–148。
魯曙明、田憲生（2014）。旅美學者看臺灣：二十一世紀臺灣社會考察與分析。臺北市：秀威資訊。
盧倩儀（2006）。政治學與移民理論。台灣政治學刊，12（2），209–261。
饒高琦、夏恩賞、李琪（2020）。近10年國際學術論文中的語言選擇和中文使用情況分析研究。語言文字應用，（2），37–50。
顧祐瑞（2019）。圖解生態學。臺北市：五南。
鹽崎正晴（2018）。日本留學生政策概略。教育部電子報，（844）。
Abramo, G., D’Angelo, C. A., & Solazzi, M. (2011). The relationship between scientists’ research performance and the degree of internationalization of their research. Scientometrics, 86(3), 629–643.
Ackers, L. (2004). Managing relationships in peripatetic careers: Scientific mobility in the european union. Women’s Studies International Forum, 27(3), 189–201.
Ackers, L. (2005). Moving people and knowledge: Scientific mobility in the European Union. International Migration, 43(5), 99–131.
Ackers, L. (2008). Internationalisation, mobility and metrics: A new form of indirect discrimination? Minerva, 46(4), 411–435.
Ackers, L., & Gill, B. (2009). Moving people and knowledge: Scientific mobility in an enlarging European Union. Edward Elgar Publishing.
Aksnes, D. W., Rørstad, K., Piro, F. N., & Sivertsen, G. (2013). Are mobile researchers more productive and cited than non–mobile researchers? A large–scale study of Norwegian scientists. Research Evaluation, 22(4), 215–223.
Albarrán, P., Carrasco, R., & Ruiz–Castillo, J. (2017). Geographic mobility and research productivity in a selection of top world economics departments. Scientometrics, 111(1), 241–265.
Allison, P. D., & Long, J. S. (1990). Departmental effects on scientific productivity. American Sociological Review, 55(4), 469–478.
Altbach, P. G. (2004). Higher education crosses borders: Can the United States remain the top destination for foreign students? Change, 36(2), 18.
Altbach, P. G., Reisberg, L., Yudkevich, M., Androushchak, G., & Pacheco, I. F. (Eds.). (2012). Paying the professoriate: A global comparison of compensation and contract. Taylor & Francis.
Alwin, D.F., McCammon, R.J. (2003). Generations, cohorts, and social change. In Mortimer, J.T., Shanahan, M.J. (Eds.), Handbook of the Life Course. (pp. 23–49). Springer, Boston, MA.
Aman, V. (2018a). A new bibliometric approach to measure knowledge transfer of internationally mobile scientists. Scientometrics, 117, 227–247.
Aman, V. (2018b). Does the Scopus author ID suffice to track scientific international mobility? A case study based on Leibniz laureates. Scientometrics, 117, 705–720.
Appelt, S., van Beuzekom, B., Galindo–Rueda, F., & de Pinho, R. (2015). Which factors influence the international mobility of research scientists? In Global mobility of research scientists: The economics of who goes where and why (pp. 177–213). Academic Press.
Archambault, É., Campbell, D., Gingras, Y., & Larivière, V. (2009). Comparing bibliometric statistics obtained from the Web of Science and Scopus. Journal of the American Society for Information Science and Technology, 60(7), 1320–1326.
Aref, S., Zagheni, E., & West, J. (2019). The demography of the peripatetic researcher: Evidence on highly mobile scholars from the Web of Science. In International conference on social informatics (pp. 50–65). Springer, Cham.
Asian American Scholar Forum. (2022, September 23). The chilling effect & fears of Chinese-American scientists and the implications to U.S. science and technology: A nationwide study. https://www.aasforum.org/upcoming-webinar-the-chilling-effect-fears-of-chinese-american-scientists-and-the-implications-to-u-s-science-and-technology-a-national-study/
Ault, D. E., Rutman, G. L., & Stevenson, T. (1982). Some factors affecting mobility in the labor market for academic economists. Economic Inquiry, 20(1), 104–132.
Azoulay, P., Ganguli, I., & Graff Zivin, J. (2017). The mobility of elite life scientists: Professional and personal determinants. Research Policy, 46(3), 573–590.
Bäker, A., Breuninger, S., Muschallik, J., Pull, K., & Backes–Gellner, U. (2016). Time to go? (Inter)National mobility and appointment success of young academics. Schmalenbach Business Review, 17(3), 401–421.
Baldwin, G. B. (1970). Brain drain or overflow? Foreign Affairs, 48(2), 358–372.
Barbezat, D. A., & Hughes, J. W. (2001). The effect of job mobility on academic salaries. Contemporary Economic Policy, 19(4), 409–423.
Baruffaldi, S. H., & Landoni, P. (2012). Return mobility and scientific productivity of researchers working abroad: The role of home country linkages. Research Policy, 41(9), 1655–1665.
Baruffaldi, S. H., Marino, M., & Visentin, F. (2020). Money to move: The effect on researchers of an international mobility grant. Research Policy, 49(8), 104077.
Bauder, H. (2015). The international mobility of academics: A labour market perspective. International Migration, 53(1), 83–96.
Beine, M., Docquier, F., & Rapoport, H. (2008). Brain drain and human capital formation in developing countries: Winners and losers. The Economic Journal, 118(528), 631–652.
Bogue, D. J. (1969). Principles of demography. Wiley.
Bogue, D. J. (1977). A migrant’s–eye view of the costs and benefits of migration to a metropolis. In A. A. Brown & E. Neuberger (Eds.), Internal migration: Chapter 11 (pp. 167–182). Academic Press.
Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual Review of Information Science and Technology, 36, 3–72.
Brettell, C., & Hollifield, J. F. (2000). Migration theory: Talking across disciplines. Psychology Press.
Butler, D. (2019, January 23). Number of EU research students in Britain drops from pre–referendum high. Nature News. https://doi.org/10.1038/d41586-019-00240-8
Callie, T. M., & Cheslock, J. J. (2008). The hiring and compensation practices of business school deans. The Review of Higher Education, 32(1), 25–49.
Cañibano, C., & Woolley, R. (2015). Towards a socio‐economics of the brain drain and distributed human capital. International Migration, 53(1), 115–130.
Carlson, T., & Martin–Rovet, D. (1995). The implications of scientific mobility between France and the United States. Minerva, 33(3), 211–250.
Caron, E., & van Eck, N. J. (2014). Large scale author name disambiguation using rule–based scoring and clustering. In Proceedings of the 19th international conference on science and technology indicators (pp. 79–86). Leiden: CWTS–Leiden University.
Chang, P., & Deng, Z. (1992). The chinese brain drain and policy options. Studies in Comparative International Development, 27(1), 44–60.
Chang, S. L. (1992). Causes of brain drain and solutions: The Taiwan experience. Studies in Comparative International Development, 27(1), 27–43.
Chiang, L. H. N. (2011). Return migration: The case of the 1.5 generation of Taiwanese in Canada and New Zealand. China Review, 11(2), 91–123.
Chinchilla–Rodríguez, Z., Miao, L., Murray, D., Robinson–García, N., Costas, R., & Sugimoto, C. R. (2018). A global comparison of scientific mobility and collaboration according to national scientific capacities. Frontiers in Research Metrics and Analytics, 3.
Cohen, R. (1996). Theories of migration. Edward Elgar Publishing.
Conchi, S., & Michels, C. (2014). Scientific mobility: An analysis of Germany, Austria, France and Great Britain (No. 41; Discussion Papers “Innovation Systems and Policy Analysis”). Fraunhofer Institute for Systems and Innovation Research (ISI). https://ideas.repec.org/p/zbw/fisidp/41.html
Cruz–Castro, L., & Sanz–Menéndez, L. (2010). Mobility versus job stability: Assessing tenure and productivity outcomes. Research Policy, 39(1), 27–38.
Czaika, M., & Orazbayev, S. (2018). The globalisation of scientific mobility, 1970–2014. Applied Geography, 96, 1–10.
Davies, S. R. (2020). Epistemic living spaces, international mobility, and local variation in scientific practice. Minerva, 58(1), 97–114.
de Solla Price, D. J. (1986). Little science, big science—and beyond. Columbia University Press.
Dennis, M. J. (2016). Consider implications of Brexit for international student mobility. Enrollment Management Report, 20(6), 3–3.
Dietz, J. S., Chompalov, I., Bozeman, B., Lane, E. O., & Park, J. (2000). Using the curriculum vita to study the career paths of scientists and engineers: An exploratory assessment. Scientometrics, 49(3), 419–442.
Edler, J., Fier, H., & Grimpe, C. (2011). International scientist mobility and the locus of knowledge and technology transfer. Research Policy, 40(6), 791–805.
Ejermo, O., Fassio, C., & Källström, J. (2020). Does mobility across universities raise scientific productivity?. Oxford Bulletin of Economics and Statistics, 82(3), 603–624.
Faggian, A., Rajbhandari, I., & Dotzel, K. R. (2017). The interregional migration of human capital and its regional consequences: A review. Regional Studies, 51(1), 128–143.
Fernández–Zubieta, A., Geuna, A., & Lawson, C. (2015). Mobility and productivity of research scientists. In A. Geuna (Ed.), Global mobility of research scientists (pp. 105–131). Academic Press.
Fernández–Zubieta, A., Geuna, A., & Lawson, C. (2016). Productivity pay–offs from academic mobility: Should I stay or should I go? Industrial and Corporate Change, 25(1), 91–114.
Ferro, A. (2006). Desired mobility or satisfied immobility? Migratory aspirations among knowledge workers. Journal of Education and Work, 19(2), 171–200.
Flowerdew, J., & Li, Y. (2009). English or Chinese? The trade–off between local and international publication among Chinese academics in the humanities and social sciences. Journal of Second Language Writing, 18(1), 1–16.
Fontes, M. (2007). Scientific mobility policies: How Portuguese scientists envisage the return home. Science and Public Policy, 34(4), 284–298.
Fontes, M., Videira, P., & Calapez, T. (2013). The impact of long–term scientific mobility on the creation of persistent knowledge networks. Mobilities, 8(3), 440–465.
Franceschet, M., & Costantini, A. (2010). The effect of scholar collaboration on impact and quality of academic papers. Journal of Informetrics, 4(4), 540–553.
Furukawa, T., Shirakawa, N., & Okuwada, K. (2011). Quantitative analysis of collaborative and mobility networks. Scientometrics, 87(3), 451–466.
Gaillard, J., & Gaillard, A. M. (1997). Introduction: The international mobility of brains: Exodus or circulation? Science, Technology and Society, 2(2), 195–228.
Garcia-Rodriguez, Y., Mihi-Ramirez, A., & Navarro-Pabsdorf, M. (2015). Highly-skilled migration, migrant networks and the prestige of academic institutions. Engineering Economics, 26(5), 500-506.
Gaulé, P. (2014). Who comes back and when? Return migration decisions of academic scientists. Economics Letters, 124(3), 461-464.
Gilpin, R. (1968). France in the age of the scientific state. Princeton University Press.
Glaser, W. A. (1978). The brain drain: Emigration and return. Pergamon Press.
Global Commission on International Migration (2005). Migration in an interconnected world: New directions for action. The Commission, [Geneva, Switzerland].
Gmelch, G. (1980). Return migration. Annual Review of Anthropology, 9, 135–159.
Gomez, C. J., Herman, A. C., & Parigi, P. (2020). Moving more, but closer: Mapping the growing regionalization of global scientific mobility using ORCID. Journal of Informetrics, 14(3), 101044.
Grigg, D. B. (1977). E. G. Ravenstein and the “laws of migration.” Journal of Historical Geography, 3(1), 41–54.
Grubel, H. G. (1987). The economics of the brain drain. In G. Psacharopoulos (Ed.), Economics of education (pp. 201–206). Pergamon.
Guo, S., & Lei, L. (2019). Toward transnational communities of practice: An inquiry into the experiences of transnational academic mobility. Adult Education Quarterly, 70(1), 26–43.
Gureyev, V. N., Mazov, N. A., Kosyakov, D. V., & Guskov, A. E. (2020). Review and analysis of publications on scientific mobility: Assessment of influence, motivation, and trends. Scientometrics, 124(2), 1599–1630.
Guth, J., & Gill, B. (2008). Motivations in East–West doctoral mobility: Revisiting the question of brain drain. Journal of Ethnic and Migration Studies, 34(5), 825–841.
Haggard, S. (2004). Institutions and growth in East Asia. Studies in Comparative International Development, 38(4), 53–81.
Halevi, G., Moed, H. F., & Bar–Ilan, J. (2016). Researchers’ mobility, productivity and impact: Case of top producing suthors in seven disciplines. Publishing Research Quarterly, 32(1), 22–37.
Haustein, S., Tunger, D., Heinrichs, G., & Baelz, G. (2011). Reasons for and developments in international scientific collaboration: Does an Asia–Pacific research area exist from a bibliometric point of view? Scientometrics, 86, 727–746.
He, Z., Zhen, N., & Wu, C. (2019). Measuring and exploring the geographic mobility of American professors from graduating institutions: Differences across disciplines, academic ranks, and genders. Journal of Informetrics, 13(3), 771–784.
Heffernan, M., & Jöns, H. (2013). Research travel and disciplinary identities in the University of Cambridge, 1885–1955. The British Journal for the History of Science, 46(2), 255–286.
Hua, S., & Hao, K. (2022, September 22). U.S.-China tensions fuel outflow of Chinese scientists from U.S. universities. The Wall Street Journal. https://www.wsj.com/articles/u-s-china-tensions-fuel-outflow-of-chinese-scientists-from-u-s-universities-11663866938
Huang, M. H., Lin, C. S., & Chen, D. Z. (2011). Counting methods, country rank changes, and counting inflation in the assessment of national research productivity and impact. Journal of the American Society for Information Science and Technology, 62(12), 2427–2436.
Huang, W. C. (1988). An empirical analysis of foreign student brain drain to the United States. Economics of Education Review, 7(2), 231–243.
IMD World Competitiveness Center. (2022). IMD world talent ranking 2021. https://www.imd.org/centers/world-competitiveness-center/rankings/world-talent-competitiveness/
Inglis, C., Li, W., & Khadria, B. (2019). The SAGE handbook of international migration. SAGE.
Johnson, H. G. (1965). The economics of the" brain drain": The Canadian case. Minerva, 3(3), 299–311.
Johnson, J. M. (2002). The reverse brain drain and the global diffusion of knowledge. Georgetown Journal of International Affairs, 3(2), 125–131.
Jonkers, K. (2010). Mobility, migration and the Chinese scientific research system. Routledge.
Jonkers, K., & Cruz–Castro, L. (2013). Research upon return: The effect of international mobility on scientific ties, production and impact. Research Policy, 42(8), 1366–1377.
Jonkers, K., & Tijssen, R. (2008). Chinese researchers returning home: Impacts of international mobility on research collaboration and scientific productivity. Scientometrics, 77(2), 309–333.
Jöns, H. (2009). ‘Brain circulation’ and transnational knowledge networks: Studying long–term effects of academic mobility to Germany, 1954–2000. Global Networks, 9(3), 315–338.
Kato, M., & Ando, A. (2017). National ties of international scientific collaboration and researcher mobility found in Nature and Science. Scientometrics, 110(2), 673–694.
Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26(1), 1–18.
Kawashima, H., & Tomizawa, H. (2015). Accuracy evaluation of Scopus Author ID based on the largest funding database in Japan. Scientometrics, 103, 1061–1071.
Keely, C. B. (1986). Return of talent programs: Rationale and evaluation criteria for programs to ameliorate a ‘brain drain.’ International Migration, 24(1), 179–189.
Keith, B. (1994). The institutional structure of eminence: Alignment of prestige among intra–university academic departments. Sociological Focus, 27(4), 363–380.
Kidd, C. V. (1983). The movement of younger scientists into and out of the United States from 1967 to 1980: Some aspects of the international movement of scientific knowledge. Minerva, 21(4), 387–409.
Kiessling, A. R. (2020). Brexit in the channel: Europe cut off: A young German scientist’s perspective. Medical Microbiology and Immunology, 209(3), 229–231.
Kim, J. (2011). Foreign aid and economic development: The success story of South Korea. Pacific Focus, 26(2), 260–286.
Kim, T. (2009). Shifting patterns of transnational academic mobility: A comparative and historical approach. Comparative Education, 45(3), 387–403.
King, R. (2002). Towards a new map of European migration. International Journal of Population Geography, 8(2), 89–106.
King, R. (2012). Geography and migration studies: Retrospect and prospect. Population, Space and Place, 18(2), 134–153.
King, R., & Skeldon, R. (2010). ‘Mind the gap!’ integrating approaches to internal and international migration. Journal Journal of Ethnic and Migration Studies, 36(10), 1619–1646.
Kinoshita, J. (1996). Leaving home: Many Japanese say West is still to their liking. Science, 274(5284), 55–56.
Kofman, E. (2000). The invisibility of skilled female migrants and gender relations in studies of skilled migration in Europe. International Journal of Population Geography, 6(1), 45–59.
Kotsemir, M., Dyachenko, E., & Nefedova, A. (2021). Publish more or publish differently? New aspects of relationship between scientific mobility and performance of young researchers. In 18th International Conference on Scientometrics and Informetrics, ISSI 2021 (pp. 585–596).
Krishna, V. V., & Khadria, B. (1997). Phasing scientific migration in the context of brain gain and brain drain in India. Science, Technology and Society, 2(2), 347–385.
Ku, S. C. Y., & Kristina, K. (2016). Migration in East and Southeast Asia. World Scientific.
Kwiek, M. (2015). Academic generations and academic work: Patterns of attitudes, behaviors, and research productivity of Polish academics after 1989. Studies in Higher Education, 40(8), 1354–1376.
Laudel, G. (2003). Studying the brain drain: Can bibliometric methods help? Scientometrics, 57(2), 215–237.
Lee, E. S. (1966). A theory of migration. Demography, 3(1), 47–57.
Leeuwen, T. van. (2004). Descriptive versus evaluative bibliometrics. In Handbook of quantitative science and technology research (pp. 373–388). Springer, Dordrecht.
Lian, K. F. (2019). International migration and the politics of multiculturalism in Japan, South Korea and Singapore. In International Labour Migration in the Middle East and Asia (pp. 157-175). Springer, Singapore.
Liu, J., Wang, R., & Xu, S. (2021). What academic mobility configurations contribute to high performance: An fsQCA analysis of CSC-funded visiting scholars. Scientometrics, 126(2), 1079-1100.
Liu, J., Yin, Z., Lyu, W., & Lin, S. (2019). Does money accelerate faculty mobility? survey findings from 11 research universities in China. Sustainability, 11(24), 6925.
Liu, M., & Hu, X. (2021). Will collaborators make scientists move? A generalized propensity score analysis. Journal of Informetrics, 15(1), 101113.
Liu, X. (1997). Refugee flow or brain‐drain? The humanitarian policy and post‐tiananmen Mainland Chinese immigration to Canada. International Journal of Population Geography, 3(1), 15–29.
Mahroum, S. (2000a). Highly skilled globetrotters: Mapping the international migration of human capital. R&D Management, 30(1), 23–32.
Mahroum, S. (2000b). Scientific mobility: An agent of scientific expansion and institutional empowerment. Science Communication, 21(4), 367–378.
Mahroum, S. (2000c). Scientists and global spaces. Technology in Society, 22(4), 513–523.
Mahroum, S. (2005). The international policies of brain gain: A review. Technology Analysis & Strategic Management, 17(2), 219–230.
McKenna, J. F., & Sikula, A. F. (1981). On the move through the groves of academe: Mobility among business professors. Business Horizons, 24(6), 70–75.
Mendoza, C., Staniscia, B., & Ortiz, A. (2020). “Knowledge migrants” or “economic migrants”? Patterns of academic mobility and migration from Southern Europe to Mexico. Population, Space and Place, 26(2), e2282.
Meyer, J.–B. (2001). Network approach versus brain drain: Lessons from the diaspora. International Migration, 39(5), 91–110.
Milojević, S. (2012). How are academic age, productivity and collaboration related to citing behavior of researchers? PLOS ONE, 7(11), e49176.
Moed, H. F., & Halevi, G. (2014). A bibliometric approach to tracking international scientific migration. Scientometrics, 101(3), 1987–2001.
Moed, H. F., Aisati, M., & Plume, A. (2013). Studying scientific migration in Scopus. Scientometrics, 94, 929–942.
Moon, R. J. (2019). International students as skilled labor migrants for Korean SMEs. Asian Survey, 59(4), 607–629.
Morano‐Foadi, S. (2005). Scientific mobility, career progression, and excellence in the European research area. International Migration, 43(5), 133–162.
Morley, L., Alexiadou, N., Garaz, S., González–Monteagudo, J., & Taba, M. (2018). Internationalisation and migrant academics: The hidden narratives of mobility. Higher Education, 76(3), 537–554.
Murakami, Y. (2009). Incentives for International migration of scientists and engineers to Japan. International Migration, 47(4), 67–91.
Murakami, Y. (2010). Japan’s brain drain: An analysis of Japanese researchers living in the United States. Japanese Economy, 37(2), 23–57.
Nane, G. F., Larivière, V., & Costas, R. (2017). Predicting the age of researchers using bibliometric data. Journal of Informetrics, 11(3), 713–729.
Pisarevskaya, A., Levy, N., Scholten, P., & Jansen, J. (2020). Mapping migration studies: An empirical analysis of the coming of age of a research field. Migration Studies, 8(3), 455–481.
Ravenstein, E. G. (1876). The birthplaces of the people and the laws of migration. Trübner.
Ravenstein, E. G. (1885). The laws of migration. Journal of the Statistical Society of London, 48(2), 167–235.
Ravenstein, E. G. (1889). The laws of migration. Journal of the Royal Statistical Society, 52(2), 241–305.
Robinson–Garcia, N., Sugimoto, C. R., Murray, D., Yegros–Yegros, A., Larivière, V., & Costas, R. (2019). The many faces of mobility: Using bibliometric data to measure the movement of scientists. Journal of Informetrics, 13(1), 50–63.
Ryazanova, O., & McNamara, P. (2019). Choices and consequences: Impact of mobility on research–career capital and promotion in business schools. Academy of Management Learning & Education, 18(2), 186–212.
Sandström, U. (2009). Combining curriculum vitae and bibliometric analysis: Mobility, gender and research performance. Research Evaluation, 18(2), 135–142.
Savolainen, R. (1993). The sense–making theory: Reviewing the interests of a user–centered approach to information seeking and use. Information Processing and Management, 29(1), 13–28.
Saxenian, A. (2005). From brain drain to brain circulation: Transnational communities and regional upgrading in India and China. Studies in Comparative International Development, 40(2), 35–61.
Scellato, G., Franzoni, C., & Stephan, P. (2015). Migrant scientists and international networks. Research Policy, 44(1), 108–120.
Shuster, L. J. (1970). Mobility among business faculty. Academy of Management Journal, 13(3), 325–335.
Solimano, A. (2008). The international mobility of talent: Types, causes, and development impact. Oxford University Press.
Song, H. (1997). From brain drain to reverse brain drain: Three decades of Korean experience. Science, Technology and Society, 2(2), 317–345.
Sonnenwald, D. H. (1999). Evolving perspectives of human information behavior: Contexts, situations, social networks and information horizons. In Exploring the contexts of information behavior: Proceedings of the second international conference in information needs (pp. 176–190). Taylor Graham.
Sonnenwald, D. H. (2008). Scientific collaboration. Annual Review of Information Science and Technology, 41(1), 643–681.
Stark, O., Helmenstein, C., & Prskawetz, A. (1997). A brain gain with a brain drain. Economics Letters, 55(2), 227–234.
Subramanyam, K. (1982). Bibliometric studies of research collaboration: A review. Journal of Information Science, 6, 33–38.
Sugimoto, C. R., Sugimoto, T. J., Tsou, A., Milojević, S., & Larivière, V. (2016). Age stratification and cohort effects in scholarly communication: A study of social sciences. Scientometrics, 109(2), 997–1016.
Tang, L., & Walsh, J. (2010). Bibliometric fingerprints: Name disambiguation based on approximate structure equivalence of cognitive maps. Scientometrics, 84(3), 763–784.
Tartari, V., Di Lorenzo, F., & Campbell, B. A. (2020). “Another roof, another proof”: The impact of mobility on individual productivity in science. The Journal of Technology Transfer, 45(1), 276–303.
Teferra, D. (2005). Brain circulation: Unparalleled opportunities, underlying challenges, and outmoded presumptions. Journal of Studies in International Education, 9(3), 229–250.
Teichler, U. (2015). Academic mobility and migration: What we know and what we do not know. European review, 23(S1), S6–S37.
Tekles, A., & Bornmann, L. (2020). Author name disambiguation of bibliometric data: A comparison of several unsupervised approaches. Quantitative Science Studies, 1(4), 1510–1528
Trippl, M. (2013). Scientific mobility and knowledge transfer at the interregional and intraregional level. Regional Studies, 47(10), 1653–1667.
Tsai, H. C. (1988). A study on the migration of students from Taiwan to the United States: A summary report. Ren Kou Xue Kan (Taipei), 12, 91–120.
Velema, T. A. (2012). The contingent nature of brain gain and brain circulation: Their foreign context and the impact of return scientists on the scientific community in their country of origin. Scientometrics, 93(3), 893–913.
Verginer, L., & Riccaboni, M. (2021). Talent goes to global cities: The world network of scientists’ mobility. Research Policy, 50(1), 104127.
Wagner, C. S., & Jonkers, K. (2017). Open countries have strong science. Nature, 550, 32–33.
Wagner, C. S., & Leydesdorff, L. (2005). Mapping the network of global science: Comparing international co–authorships from 1990 to 2000. International Journal of Technology and Globalisation, 1(2), 185–208.
Wang, W., Yu, S., Bekele, T. M., Kong, X., & Xia, F. (2017). Scientific collaboration patterns vary with scholars’ academic ages. Scientometrics, 112(1), 329–343.
Wang, X., Xu, S., Wang, Z., Peng, L., & Wang, C. (2013). International scientific collaboration of China: Collaborating countries, institutions and individuals. Scientometrics, 95(3), 885–894.
Wapman, K. H., Zhang, S., Clauset, A., & Larremore, D. B. (2022). Quantifying hierarchy and dynamics in US faculty hiring and retention. Nature, 610, 120–127.
Woolley, R., & Turpin, T. (2009). CV analysis as a complementary methodological approach: Investigating the mobility of Australian scientists. Research Evaluation, 18(2), 143–151.
Wright, M., Tartari, V., Huang, K. G., Lorenzo, F. D., & Bercovitz, J. (2018). Knowledge worker mobility in context: Pushing the boundaries of theory and methods. Journal of Management Studies, 55(1), 1–26.
Xie, Y., Lin, X., Li, J., He, Q., & Huang, J. (2022). Caught in the crossfire: Fears of Chinese-American scientists. arXiv preprint. arXiv:2209.10642v2
Yamashita, Y., & Yoshinaga, D. (2014). Influence of researchers’ international mobilities on publication: A comparison of highly cited and uncited papers. Scientometrics, 101, 1475–1489.
Youtie, J., Carley, S., Porter, A. L., & Shapira, P. (2017). Tracking researchers and their outputs: New insights from ORCIDs. Scientometrics, 113(1), 437–453.
Zhao, Z., Bu, Y., Kang, L., Min, C., Bian, Y., Tang, L., & Li, J. (2020). An investigation of the relationship between scientists’ mobility to/from China and their research performance. Journal of Informetrics, 14(2), 101037.
Zweig, D. (1997). To return or not to return? Politics vs. economics in China’s brain drain. Studies in Comparative International Development, 32(1), 92–125.
Zweig, D., Chung, S. F., & Han, D. (2008). Redefining the brain drain: China’s ‘diaspora option.’ Science, Technology and Society, 13(1), 1–33.