Abramo, G., & D’Angelo, C. A. (2014). How do you define and measure research productivity?. Scientometrics, 101, 1129-1144. https://doi.org/10.1007/s11192-014-1269-8

Abramo, G., D'Angelo, C., & Di Costa, F. (2008). Assessment of sectoral aggregation distortion in research productivity measurements. Research Evaluation, 17(2), 111-121. https://doi.org/10.3152/095820208X280916

Aksnes, D. W., Langfeldt, L., & Wouters, P. (2019). Citations, citation indicators, and research quality: An overview of basic concepts and theories. Sage Open, 9(1), 2158244019829575. https://doi.org/10.1177/2158244019829575

Alfirevic, N., Pavicic, J., & Rendulic, D. (2023). A bibliometric analysis of public business school scientific productivity and impact in South-east Europe (2017-2021). The South East European Journal of Economics and Business, 18(1), 27-45. https://doi.org/10.2478/jeb-2023-0003

Allison, P. D., & Long, J. S. (1990). Departmental effects on scientific productivity. American sociological review, 469-478. https://doi.org/10.2307/2095801

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007

Audretsch, D. B., Lehmann, E. E., & Wright, M. (2014). Technology transfer in a global economy. The Journal of Technology Transfer, 39, 301-312. https://doi.org/10.1007/s10961-012-9283-6

Baccini, A., Barabesi, L., Cioni, M., & Pisani, C. (2014). Crossing the hurdle: the determinants of individual scientific performance. Scientometrics, 101, 2035-2062. https://doi.org/10.1007/s11192-014-1395-3

Bak, H. J., & Kim, D. H. (2019). The unintended consequences of performance-based incentives on inequality in scientists’ research performance. Science and Public Policy, 46(2), 219-231. https://doi.org/10.1093/scipol/scy052

Baker, D. R. (1991). On-line bibliometric analysis for researchers and educators. Journal of Social Work Education, 27(1), 41-47. https://doi.org/10.1080/10437797.1991.10672168

Ball, P. (2005). Index aims for fair ranking of scientists. Nature, 436(7053), 900. https://doi.org/10.1038/436900a

Batista, P. D., Campiteli, M. G., & Kinouchi, O. (2006). Is it possible to compare researchers with different scientific interests?. Scientometrics, 68(1), 179-189. http://dx.doi.org/10.1007/s11192-006-0090-4

Ben-Porath, Y. (1967). The production of human capital and the life cycle of earnings. Political economy, 75(4), 352-365. https://www.ntaccounts.org/doc/repository/Ben-Porath_paper.pdf

Bicheng, D., Adnan, N., Harji, M. B., & Ravindran, L. (2023). Evolution and hotspots of peer instruction: a visualized analysis using CiteSpace. Education and Information Technologies, 28(2), 2245-2262. https://doi.org/10.1152/advan.00110.2018

Bland, C. J., Seaquist, E., Pacala, J. T., Center, B., & Finstad, D. (2002). One school's strategy to assess and improve the vitality of its faculty. Academic Medicine, 77(5), 368-376. https://doi.org/10.1097/00001888-200205000-00004

Bornmann, L., & Daniel, H. D. (2005). Does the h-index for ranking of scientists really work?. Scientometrics, 65, 391-392. https://doi.org/10.1007/s11192-005-0281-4

Bornmann, L., & Daniel, H. D. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of documentation, 64(1), 45-80. https://doi.org/10.1108/00220410810844150

Bright, L. K. (2017). Decision theoretic model of the productivity gap. Erkenntnis, 82, 421-442. https://doi.org/10.1007/s10670-016-9826-6

Chadegani, A. A., Salehi, H., Yunus, M. M., Farhadi, H., Fooladi, M., Farhadi, M., & Ebrahim, N. A. (2013). A comparison between two main academic literature collections: Web of Science and Scopus databases. arXiv preprint arXiv:1305.0377. https://doi.org/10.48550/arXiv.1305.0377

Chen, C. (2020). The citespace manual. College of Computing and Informatics. 1(1), 1-246. https://www.researchgate.net/profile/Arsev-Aydinoglu-2/publication/274377526_Collaborative_interdisciplinary_astrobiology_research_a_bibliometric_study_of_the_NASA_Astrobiology_Institute/links/5670463b08ae0d8b0cc0e112/Collaborative-interdisciplinary-astrobiology-research-a-bibliometric-study-of-the-NASA-Astrobiology-Institute.pdf

Cole, J. R., & Zuckerman, H. (1987). Marriage, motherhood and research performance in science. Scientific American, 256(2), 119-125. https://www.jstor.org/stable/24979323

Cole, J. R., & Cole, S. (1973). Social Stratification in Science. Chicago: University of Chicago Press. https://www.journals.uchicago.edu/doi/10.1086/226571

Corallo, A., Latino, M. E., Menegoli, M., De Devitiis, B., & Viscecchia, R. (2019). Human factor in food label design to support consumer healthcare and safety: A systematic literature review. Sustainability, 11(15), 4019. https://doi.org/10.3390/su11154019

Costas, R., Zahedi, Z., & Wouters, P. (2015). Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the association for information science and technology, 66(10), 2003-2019. https://doi.org/10.1002/asi.23309

Courtial, J. (1994). A coword analysis of scientometrics. Scientometrics, 31(3), 251-260. https://doi.org/10.1007/bf02016875

Creswell, J. W. (1985). Faculty Research Performance: Lessons from the Sciences and the Social Sciences. Washington: Association for the Study of Higher Education. https://www.amazon.com/Faculty-Research-Performance-Sciences-EDUCATION/dp/0913317233

Cronin, B., & Meho, L. (2006). Using the h‐index to rank influential information scientistss. Journal of the American Society for Information Science and technology, 57(9), 1275-1278. https://doi.org/10.1002/asi.20354

Dundar, H., & Lewis, D. R. (1998). Determinants of research productivity in higher education. Research in higher education, 39(6), 607-631. https://doi.org/10.1023/A:1018705823763

Egghe, L. (2006a). An improvement of the h-index: The g-index. ISSI newsletter, 2(1), 8-9. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=bdca34b16ccefe61901c167402b9ff73e0c6629e

Egghe, L. (2006b). Theory and practise of the g-index. Scientometrics. 69(1), 131-152. https://doi.org/10.1007/s11192-006-0144-7

Fazey, I., Evely, A. C., Reed, M. S., Stringer, L. C., Kruijsen, J., White, P. C., & Trevitt, C. (2013). Knowledge exchange: a review and research agenda for environmental management. Environmental Conservation, 40(1), 19-36. https://doi.org/10.1017/S037689291200029X

Ferreira, C., Bastille‐Rousseau, G., Bennett, A. M., Ellington, E. H., Terwissen, C., Austin, C., & Murray, D. L. (2016). The evolution of peer review as a basis for scientific publication: directional selection towards a robust discipline?. Biological Reviews, 91(3), 597-610. https://doi.org/10.1111/brv.12185

Fonseca, L., Velloso, S., Wofchuk, S., & de Meis, L. (1997). The importance of human relationships in scientific productivity. Scientometrics, 39(2), 159-171. https://doi.org/10.1007/bf02457445

Fox, M. F. (1983). Publication productivity among scientists: A critical review. Social studies of science, 13(2), 285-305. https://doi.org/10.1177/030631283013002005

Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through association of ideas. Science, 122(3159), 108-111. https://doi.org/10.1126/science.122.3159.108

Garfield, E. (1972). Citation analysis as a tool in journal evaluation: Journals can be ranked by frequency and impact of citations for science policy studies. Science, 178(4060), 471-479. https://doi.org/10.1126/science.178.4060.471

Geng, Y., Zhang, N., & Zhu, R. (2023). Research progress analysis of sustainable smart grid based on CiteSpace. Energy Strategy Reviews, 48, 101111. https://doi.org/10.1016/j.esr.2023.101111

Gjerde, C. (1992). Where are articles by candidates for academic promotion published. J Fam Pract, 34(4), 449-453. https://cdn.mdedge.com/files/s3fs-public/jfp-archived-issues/1992-volume_34/April%201992/JFP_1992-04_v34_i4_where-are-articles-by-candidates-for-aca.pdf

 Glänzel, W. (2006). On the h-index-A mathematical approach to a new measure of publication activity and citation impact. Scientometrics, 67(2), 315-321. https://doi.org/10.1007/s11192-006-0102-4

Godin, B. (2009). The value of science: changing conceptions of scientific productivity, 1869 to circa 1970. Social Science Information, 48(4), 547-586. https://doi.org/10.1177/0539018409344475

Harzing, A. W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison. Scientometrics, 106, 787-804. https://doi.org/10.1007/s11192-015-1798-9

Hicks, D. (2012). Performance-based university research funding systems. Research policy, 41(2), 251-261. https://doi.org/10.1016/j.respol.2011.09.007

Hicks, D., Wouters, P., Waltman, L., De Rijcke, S., & Rafols, I. (2015). Bibliometrics: the Leiden Manifesto for research metrics. Nature, 520(7548), 429-431. https://doi.org/10.1038/520429a

Hirsch, I., Milwitt, W., & Oakes, W. J. (1958). Increasing the productivity of scientists. Harvard Business Review, 36(2), 66-76. https://doi.org/10.1007/BF02457402

Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National academy of Sciencessciences, 102(46), 16569-16572. https://doi.org/10.1073/pnas.0507655102

Holden, G., Rosenberg, G., & Barker, K. (2005). Bibliometrics: A potential decision makingdecision-making aid in hiring, reappointment, tenure and promotion decisions. Social work in health care, 41(3-4), 67-92. https://doi.org/10.1300 / J010v41n03_03

Hottenrott, H., & Thorwarth, S. (2011). Industry funding of university research and scientific productivity. Kyklos, 64(4), 534-555. https://doi.org/10.1111/j.1467-6435.2011.00519.x

Hu, A. G., Jefferson, G. H., & Jinchang, Q. (2005). R&D and technology transfer: firm-level evidence from Chinese industry. Review of Economics and Statistics, 87(4), 780-786. https://doi.org/10.1162/003465305775098143

Huang, J., Gates, A. J., Sinatra, R., & Barabási, A. L. (2020). Historical comparison of gender inequality in scientific careers across countries and disciplines. Proceedings of the National Academy of Sciences, 117(9), 4609-4616. https://doi.org/10.1073/pnas.1914221117

Isohanni, M., Isohanni, I., & Veijola, J. (2002). How should a scientific team be effectively formed and managed. Nordic Journal of Psychiatry, 56(2), 157-162. https://doi.org/10.1080/080394802753617999

Ivancheva, L. (2008). Scientometrics today: A methodological overview. Collnet Journal of Scientometrics and Information Management, 2(2), 47-56. https://doi.org/10.1080/09737766.2008.10700853

 Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research policy, 26(1), 1-18. https://doi.org/10.1016/S0048-7333(96)00917-1

Kelly, C. D., & Jennions, M. D. (2006). The h index and career assessment by numbers. Trends in Ecology & Evolution, 21(4), 167-170. https://doi.org/10.1016/j.tree.2006.01.005

Kim, M. C., & Zhu, Y. (2018). Scientometrics of scientometrics: mapping historical footprint and emerging technologies in scientometrics. Scientometrics, 1, 9-27. https://doi.org/10.5772/intechopen.77951.

Klein, W. C., & Bloom, M. (1992). Studies of scholarly productivity in social work using citation analysis. Journal of Social Work Education, 28(3), 291-299. https://doi.org/10.1080/10437797.1992.10778782

Kreuger, L. W. (1993). Should there be a moratorium on articles that rank schools of social work based on faculty publications? Yes!. Journal of Social Work Education, 29(3), 240-245. https://doi.org/10.1080/10437797.1993.10778820

Lancho-Barrantes, B. S., Ceballos, H. G., & Cantú-Ortiz, F. J. (In press). Factors that influence scientific productivity from different countries: A causal approach through multiple regression using panel data. BioRxiv. Retrieved 2019, june, 25, from https://www.biorxiv.org/content/biorxiv/early/2019/02/25/558254.full.pdf

Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015). Team size matters: Collaboration and scientific impact since 1900. Journal of the Association for Information Science and Technology, 66(7), 1323-1332. https://doi.org/10.1002/asi.23266

Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Bibliometrics: Global gender disparities in science. Nature, 504(7479), 211-213. https://doi.org/10.1038/504211a

Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social studies of science, 35(5), 673-702. https://doi.org/10.1177/0306312705052359

Lehmann, S., Jackson, A. D., & Lautrup, B. E. (2006). Measures for measures. Nature, 444(7122), 1003-1004. https://doi.org/10.1038/4441003a

Levin, S. G., & Stephan, P. E. (1991). Research productivity over the life cycle: Evidence for academic scientists. The American economic review, 114-132. https://www.jstor.org/stable/2006790

Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington academy of sciences, 16(12), 317-323. https://www.jstor.org/stable/24529203

Mahdizadeh, M. (2022). Qualitative meta-analysis of scientific articles related to faculty members' productivity in Iran. Higher Education Letter, 15(58), 31-52. https://journal.sanjesh.org/article_254274.html [In Persian].

Mairesse, J., & Turner, L. (2010). Measurement and explanation of the intensity of co-publication in scientific research: An analysis at the laboratory level [working paper]. National Bureau of Economic Research. July, 11172. https://www.nber.org/papers/w11172

Mali, F., Pustovrh, T., Platinovšek, R., Kronegger, L., & Ferligoj, A. (2017). The effects of funding and co-authorship on research performance in a small scientific community. Science and Public Policy, 44(4), 486-496. https://doi.org/10.1093/scipol/scw076

Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & López-Cózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of informetrics, 12(4), 1160-1177. https://doi.org/10.1016/j.joi.2018.09.002

Meho, L. I., & Yang, K. (2007). Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar. Journal of the american society for information science and technology, 58(13), 2105-2125. https://doi.org/10.1002/asi.20677

Merton, R. K. (1968). The Matthew effect in science: The reward and communication systems of science are considered. Science, 159(3810), 56-63.  https://www.science.org/doi/10.1126/science.159.3810.56

Milat, A. J., Bauman, A. E., & Redman, S. (2015). A narrative review of research impact assessment models and methods. Health Research Policy and Systems, 13, 1-7. https://doi.org/10.1186/s12961-015-0003-1

Miller, J. C., Coble, K. H., & Lusk, J. L. (2013). Evaluating top faculty researchers and the incentives that motivate them. Scientometrics, 97, 519-533. https://doi.org/10.1007/s11192-013-0987-7

Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106, 213-228. https://doi.org/10.1007/s11192-015-1765-5

Penfield, T., Baker, M. J., Scoble, R., & Wykes, M. C. (2014). Assessment, evaluations, and definitions of research impact: A review. Research evaluation, 23(1), 21-32. https://doi.org/10.1093/reseval/rvt021

R Core Team (2019) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. 
https://www.R-project.org/

Racherla, P., & Hu, C. (2010). A social network perspective of tourism research collaborations. Annals of Tourism Research, 37(4), 1012-1034. https://doi.org/10.1016/j.annals.2010.03.008

Ramsden, P. (1994). Describing and explaining research productivity. Higher education, 28(2), 207-226. https://doi.org/10.1007/BF01383729

Ravikumar, S., Agrahari, A., & Singh, S. N. (2015). Mapping the intellectual structure of scientometrics: A co-word analysis of the journal Scientometrics (2005–2010). Scientometrics, 102, 929-955. https://doi.org/10.1007/s11192-014-1402-8

Reskin, B. F. (1978). Scientific productivity, sex, and location in the institution of science. American Journal of Sociology, 83(5), 1235-1243. https://‌doi/abs/10.1086/226681 https://psycnet.apa.org/doi/10.1086/226681

 Schnitzler, K., Davies, N., Ross, F., & Harris, R. (2016). Using Twitter™ to drive research impact: a discussion of strategies, opportunities and challenges. International journal of nursing studies, 59, 15-26. https://doi.org/10.1016/j.ijnurstu.2016.02.004

Sedighi, M. (2014). Using Co-word Analysis Method in Mapping of the Structure of Scientific Fields (Case Study: The Field of Informetrics), Iranian Journal of Information Processing & Management, 30 (2), 373-396. https://doi.org/ 10.35050/JIPM010.2015.040 [In Persian].

Seglen, P. O. (1997). Why the impact factor of journals should not be used for evaluating research. Bmj, 314(7079), 497. https://doi.org/10.1136/bmj.314.7079.497

Shin, J., & Cummings, W. (2010). Multilevel analysis of academic publishing across disciplines: Research preference, collaboration, and time on research. Scientometrics, 85(2), 581-594. https://doi.org/10.1007/s11192-010-0236-2

Spaapen, J., & Van Drooge, L. (2011). Introducing ‘productive interactions’ in social impact assessment. Research evaluation, 20(3), 211-218. https://doi.org/10.3152/095820211X12941371876742

Tangen, S. (2005). Demystifying productivity and performance. International Journal of Productivity and performance management, 54(1), 34-46. https://doi.org/10.1108/17410400510571437

Tao, Y., & Lin, P. H. (2023). Analyses of Sustainable Development of Cultural and Creative Parks: A Pilot Study Based on the Approach of CiteSpace Knowledge Mapping. Sustainability, 15(13), 10489. https://doi.org/10.3390/su151310489

Thyer, B. A., & Bentley, K. J. (1986). Academic affiliations of social work authors: A citation analysis of six major journals. Journal of Social Work Education, 22(1), 67-73. https://doi.org/10.1080/10437797.1986.10671731

Tien, F. F., & Blackburn, R. T. (1996). Faculty rank system, research motivation, and faculty research productivity: Measure refinement and theory testing. The Journal of Higher Education, 67(1), 2-22. https://doi.org/10.1080/00221546.1996.11780246

Tootoonchi, M., Yamani, N., Changiz, T., Taleghani, F., & Mohammadzadeh, Z. (2014). Assessment of educational criteria in academic promotion: Perspectives of faculty members of medical sciences universities in Iran. Journal of education and health promotion, 3. https://doi.org/10.4103/2277-9531.131893

Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3

Van Raan, A. F. (2006). Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups. scientometrics, 67, 491-502. https://doi.org/10.1556/Scient.67.2006.3.10

Vinkler, P. (2017). The size and impact of the elite set of publications in scientometric assessments. Scientometrics, 110, 163-177. https://doi.org/10.1007/s11192-016-2165-1

Wang, X., Wang, Z., & Xu, S. (2013). Tracing scientist’s research trends realtimely. Scientometrics, 95, 717-729. https://doi.org/10.1007/s11192-012-0884-5

Xie, Y., & Shauman, K. A. (1998). Sex differences in research productivity: New evidence about an old puzzle. American sociological review, 847-870. https://psycnet.apa.org/record/1998-03313-006

Yang, W., Wang, S., Chen, C., Leung, H. H., Zeng, Q., & Su, X. (2022). Knowledge mapping of enterprise network research in China: a visual analysis using CiteSpace. Frontiers in Psychology, 13, 898538. https://doi.org/10.3389/fpsyg.2022.898538

Zerem, E. (2017). The ranking of scientists based on scientific publications assessment. Journal of Biomedical Informatics, 75, 107-109. https://doi.org/10.1016/j.jbi.2017.10.007