Araştırma Makalesi
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İranlı ve Türk Araştırmacılar Nasıl İşbirliği Yapıyor? Bilimsel İşbirliklerinin İzlenmesi için İş Zekası Tabanlı Karar Destek Aracı

Yıl 2022, , 684 - 707, 27.08.2022
https://doi.org/10.26745/ahbvuibfd.1102805

Öz

Bilgi ve iletişim teknolojilerindeki ilerleme, her sektörde olduğu gibi yükseköğretim alanında da son teknoloji araçlarının kullanılmasını zorunlu kılmaktadır. Bu araçlar yöneticilerin yönetim fonksiyonlarını daha iyi yapmalarını sağlamakta, yürüttükleri faaliyetleri bilgiye dayanan etkin kararlar alarak sürdürmelerini sağlayabilmektedir. İş zekası teknolojisi bu araçlar arasında son yıllarda önemli bir stratejik yönetim aracı olarak karşımıza çıkmaktadır. Pek çok farklı sistemden beslenen iş zekası uygulamaları, günümüzde operasyonel, taktik ve stratejik düzeyde farklı karar seviyelerinde kullanılabilecek bir dijital araçtır. Bilimsel araştırmaların yönetimi, izlenmesi, yıllar içindeki etkinliğin gözlenmesi için kullanılabilir. Bibliyometrik veriler bu noktada önemli araçlardır. Çalışmada Web of Science üzerinden elde edilen bibliyometrik veriler aracılığı ile, 2010-2020 yılları arasındaki İran ve Türkiye’nin bilimsel üretkenliği sorgulanmaktadır. Bu sorgunun karar vericiler için daha etkin ve parametrik yapılabilmesi için bir karar destek sistemi modellenmektedir. İki ülkenin bilimsel üretkenliği ilgili bibliyometrik veri kaynağı üzerinden makro düzeyde analiz edilmekte, mikro düzeyde ise iki ülkedeki araştırmacıların ortak ürettikleri yayınlar detaylı olarak araştırma alanları, araştırmacılar, kurumlar, üretilen eserler ve alınan atıflar, birlikte yayın yapılan dergiler, fonlar vb. açısından değerlendirilmektedir. Bilimsel üretkenlik, üniversiteler, bölgesel konum, ortak işbirliği yapılan diğer ülkeler başlıkları ile değerlendirilmektedir. Yoğun çalışılan alanlarda ön plana çıkan araştırma alanlarında içerik analizi yapılmakta ve iki ülkenin yoğun işbirliği yaptığı konu başlıkları üzerinde değerlendirme sunulmaktadır. İlgili dönemde iki ülkede ortak yayın sayısı 6,723 (5,915 makale)’dır. Her İki ülke de birbiriyle komşu olmasına rağmen araştırma yoğunluğunda işbirliği yapılan ülkeler listesinde sekizinci sırada yer almaktadır. Her iki ülke için en yoğun iş birliği yapılan ülkeler arasında Amerika Birleşik Devletleri ve İngiltere vardır. Her iki ülkede en yoğun birlikte çalışan ilk üç kurum İslami Azad Üniversitesi, Orta Doğu Teknik Üniversitesi, İstanbul Teknik Üniversitesi’dir. Fizik, mühendislik, kimya, matematik ve malzeme bilimi en yoğun iş birliği yapılan araştırma alanlarıdır. Geliştirilen model, bilimsel üretkenliğin ülkeler düzeyinde değerlendirilmesi için paket yazılımlardan farklı, kullanışlı, detaylara inmeyi imkan sunan üniversite kütüphane veya bilimsel üretkenlik izleme servisleri için değerli bir araç olarak görülmektedir.

Proje Numarası

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Kaynakça

  • Abramo, G., & D’Angelo, C. A. (2020). A novel methodology to assess the scientific standing of nations at field level. Journal of Informetrics, 14(1), 1-13. https://doi.org/10.1016/j.joi.2019.100986
  • Abramo, G., D’Angelo, C. A., & Di Costa, F. (2009). Research collaboration and productivity: is there correlation?. Higher education, 57(2), 155-171. https://doi.org/10.1007/s10734-008-9139-z
  • Ardanuy, J. (2012). Scientific collaboration in Library and Information Science viewed through the Web of Knowledge: The Spanish case. Scientometrics, 90(3), 877-890. https://doi.org/10.1007/s11192-011-0552-1
  • Benckendorff, P. (2010). Exploring the limits of tourism research collaboration: A social network analysis of co-authorship patterns in Australian and New Zealand tourism research. CAUTHE 2010: Tourism and Hospitality: Challenge the Limits, 151. Hobart, Australia, 8-11 February 2010. Hobart, Australia: University of Tasmania.
  • Chen, K., Zhang, Y., & Fu, X. (2019). International research collaboration: An emerging domain of innovation studies? Research Policy, 48(1), 149-168. https://doi.org/10.1016/j.respol.2018.08.005
  • Chung, W., Chen, H., & Reid, E. (2009). Business stakeholder analyzer: An experiment of classifying stakeholders on the Web. Journal of the American Society for Information Science and Technology, 60(1), 59-74. https://doi.org/10.1002/asi.20948
  • Cox, B. L., & Jantti, M. (2012). Capturing business intelligence required for targeted marketing, demonstrating value, and driving process improvement. Library & information science research, 34(4), 308-316. http://dx.doi.org/10.1016/j.lisr.2012.06.002
  • Damar, M. (2021). Endüstri 4.0 Çağında Yükseköğretim Kurulumları İçin Tedarik Zinciri Yönetiminde Bir İş Zekâsı Karar Destek Sistemi Uygulaması. İzmir Sosyal Bilimler Dergisi, 3(2), 144-158. https://doi.org/10.47899/ijss.20213204
  • Damar, M., Özdağoğlu, G., & Özdağoğlu, A. (2018). İş zekasını ve ilgili teknolojileri konu alan araştırmalara küresel ölçekte bilimetrik bakış. Bilgi Ekonomisi ve Yönetimi Dergisi, 13(2), 197-217.
  • Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904-920. https://doi.org/10.1111/bjet.12230
  • DataWorldBank, (2022). The World Bank Data, Population Counts. Accessed Date: 17/02/2022, https://data.worldbank.org/indicator/SP.POP.TOTL?locations=IR
  • Dunning, J. (2000). Regions, Globalisation & the Knowledge-Based Economy. Oxford: Oxford University Press.
  • Guster, D., & Brown, C. G. (2012). The application of business intelligence to higher education: Technical and managerial perspectives. Journal of Information Technology Management, 23(2), 42-62.
  • Hamad, F., Al-Aamr, R., Jabbar, S. A., & Fakhuri, H. (2021). Business intelligence in academic libraries in Jordan: Opportunities and challenges. IFLA journal, 47(1), 37-50. https://doi.org/10.1177/0340035220931882
  • Hartley, K., & Seymour, L.F.(2010). Towards a framework for the adoption of business intelligence in public sector organisations: the case of South Africa. The Proceedings of the SAICSIT 11, October 3-5, 2010, Cape Town, South Africa.
  • Inzelt, A., Schubert, A., & Schubert, M. (2009). Incremental citation impact due to international co-authorship in Hungarian higher education institutions. Scientometrics,78(1), 37-43. https://doi.org/10.1007/s11192-007-1957-8
  • Lariviere, V., Gingras, Y., & Archambault, É. (2006). Canadian collaboration networks: A comparative analysis of the natural sciences, social sciences, and the humanities. Scientometrics,68(3), 519-533. https://doi.org/10.1007/s11192-006-0127-8
  • Leydesdorff, L., & Wagner, C.S. (2008). International collaboration in science and the formation of a core group. Journal of Informetrics, 2(4), 317-325. https://doi.org/10.1016/j.joi.2008.07.003
  • Miller, G. (2011). Social scientists wade into the Tweet stream. Science, 333(2011), 1814-1815. https://doi.org/10.1126/science.333.6051.1814
  • MSRT (2022). Islamic Republic of Iran, Ministry of Science Research and Technology, Statistics-2019, Erişim Tarihi: 10/02/2022, https://www.msrt.ir/en/page/20/statistics-2019#us2015
  • Nikzad, M., Jamali, H. R., & Hariri, N. (2011). Patterns of Iranian co-authorship networks in social sciences: A comparative study. Library & Information Science Research, 33(4), 313-319. http://dx.doi.org/10.1016/j.lisr.2011.01.005
  • Olmeda‐Gómez, C., Perianes‐Rodriguez, A., Ovalle‐Perandones, M. A., Guerrero‐Bote, V. P., & de Moya Anegón, F. (2009, January). Visualization of scientific co‐authorship in Spanish universities. In Aslib Proceedings, 61(1), 83-100. https://doi.org/10.1108/00012530910932302
  • Schmidt, J. (2007). Knowledge politics of interdisciplinarity. Specifying the type of interdisciplinarity in the NSF’s NBIC scenario. Innovation: The European Journal of Social Science Research, 20(4), 313-328. https://doi.org/10.1080/13511610701760721
  • Scholtz, B., Calitz, A., & Haupt, R. (2018). A business intelligence framework for sustainability information management in higher education. International Journal of Sustainability in Higher Education,19(2), 266-290. https://doi.org/10.1108/IJSHE-06-2016-0118
  • Skolnikoff, E.B. (1993). The elusive transformation: Science, technology and the evolution of international politics. Princeton, NJ: Princeton University Press.
  • Stehr, N. (2005). Knowledge politics: Governing the consequences of science and technology. New York: Routledge.
  • Tang, L., & Shapira, P. (2011). China-US scientific collaboration in nanotechnology: patterns and dynamics. Scientometrics, 88(1), 1-16. https://doi.org/10.1007/s11192-011-0376-z
  • Tešendić, D., & Krstićev, D. B. (2019). Business intelligence in the service of libraries. Information Technology and Libraries, 38(4), 98-113. http://dx.doi.org/10.6017/ital.v38i4.10599
  • 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. http://dx.doi.org/10.1504/IJTG.2005.007050
  • Webometrics (2022). Ranking Web of Universities. Countries arranged by Number of Universities in Top Ranks. Accessed Date: 17/02/2022. https://www.webometrics.info/en/distribution_by_country
  • Zeng, D., Chen, H., Castillo-Chavez, C. Lynch, W.B., & Thurmond, M. (2011). Infectious Disease Informatics and Biosurveillance. 27, Boston: Springer. https://doi.org/10.1007/978-1-4419-6892-0

A Decision Support System with Business Intelligence: Iranian and Turkish Researcher collaborate enough?

Yıl 2022, , 684 - 707, 27.08.2022
https://doi.org/10.26745/ahbvuibfd.1102805

Öz

The advancement of information and communication technologies demands the employment of cutting-edge technological tools in many sectors, including higher education. These tools assist managers in performing their management tasks more effectively and in continuing their operations by enabling them to make informed judgments. Among these tools, business intelligence technology has risen to prominence in recent years as a critical strategic management tool. Feeding from many different systems, BI is a digital tool that can be used at different decision levels at the operational, tactical and strategic level. It may be used to organize and monitor scientific research, as well as to track its efficacy over time. Bibliometric data can be an important source for this important technology at this point. The study examines the province's, Iran's, and Turkey's scientific productivity between 2010 and 2020 using bibliometric data from Web of Science. A decision support system is modeled in order to make this query more effective and parametric for decision makers. The scientific productivity of the two countries is analyzed at the macro level through the relevant bibliometric data source, and at the micro level, the publications jointly produced by the researchers in the two countries are detailed in the research areas, researchers, institutions, works produced and citations received, journals published together, funds. Scientific production is measured in terms of institutions, regional location, and collaboration with other nations. The two nations collaborated on 6.723 publications over the relevant time (5.915 articles). Although both countries are neighbors to each other, they are in the eighth place in the list of collaborating countries in terms of research intensity. Among the countries with the most intense cooperation for both countries are the USA and England. The top three institutions working together most intensively in both countries are Islamic Azad University, Middle East Technical University, and Istanbul Technical University. Physics, engineering, chemistry, mathematics, and material science are the most intensely collaborative research areas. The developed model is seen as a valuable tool for university library services or scientific productivity monitoring, which is different from packaged software, provides the opportunity to go into details, for the evaluation of scientific productivity at the level of countries.

Destekleyen Kurum

Bu çalışmada herhangi bir fon veya destekten yararlanılmamıştır.

Proje Numarası

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Teşekkür

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Kaynakça

  • Abramo, G., & D’Angelo, C. A. (2020). A novel methodology to assess the scientific standing of nations at field level. Journal of Informetrics, 14(1), 1-13. https://doi.org/10.1016/j.joi.2019.100986
  • Abramo, G., D’Angelo, C. A., & Di Costa, F. (2009). Research collaboration and productivity: is there correlation?. Higher education, 57(2), 155-171. https://doi.org/10.1007/s10734-008-9139-z
  • Ardanuy, J. (2012). Scientific collaboration in Library and Information Science viewed through the Web of Knowledge: The Spanish case. Scientometrics, 90(3), 877-890. https://doi.org/10.1007/s11192-011-0552-1
  • Benckendorff, P. (2010). Exploring the limits of tourism research collaboration: A social network analysis of co-authorship patterns in Australian and New Zealand tourism research. CAUTHE 2010: Tourism and Hospitality: Challenge the Limits, 151. Hobart, Australia, 8-11 February 2010. Hobart, Australia: University of Tasmania.
  • Chen, K., Zhang, Y., & Fu, X. (2019). International research collaboration: An emerging domain of innovation studies? Research Policy, 48(1), 149-168. https://doi.org/10.1016/j.respol.2018.08.005
  • Chung, W., Chen, H., & Reid, E. (2009). Business stakeholder analyzer: An experiment of classifying stakeholders on the Web. Journal of the American Society for Information Science and Technology, 60(1), 59-74. https://doi.org/10.1002/asi.20948
  • Cox, B. L., & Jantti, M. (2012). Capturing business intelligence required for targeted marketing, demonstrating value, and driving process improvement. Library & information science research, 34(4), 308-316. http://dx.doi.org/10.1016/j.lisr.2012.06.002
  • Damar, M. (2021). Endüstri 4.0 Çağında Yükseköğretim Kurulumları İçin Tedarik Zinciri Yönetiminde Bir İş Zekâsı Karar Destek Sistemi Uygulaması. İzmir Sosyal Bilimler Dergisi, 3(2), 144-158. https://doi.org/10.47899/ijss.20213204
  • Damar, M., Özdağoğlu, G., & Özdağoğlu, A. (2018). İş zekasını ve ilgili teknolojileri konu alan araştırmalara küresel ölçekte bilimetrik bakış. Bilgi Ekonomisi ve Yönetimi Dergisi, 13(2), 197-217.
  • Daniel, B. (2015). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5), 904-920. https://doi.org/10.1111/bjet.12230
  • DataWorldBank, (2022). The World Bank Data, Population Counts. Accessed Date: 17/02/2022, https://data.worldbank.org/indicator/SP.POP.TOTL?locations=IR
  • Dunning, J. (2000). Regions, Globalisation & the Knowledge-Based Economy. Oxford: Oxford University Press.
  • Guster, D., & Brown, C. G. (2012). The application of business intelligence to higher education: Technical and managerial perspectives. Journal of Information Technology Management, 23(2), 42-62.
  • Hamad, F., Al-Aamr, R., Jabbar, S. A., & Fakhuri, H. (2021). Business intelligence in academic libraries in Jordan: Opportunities and challenges. IFLA journal, 47(1), 37-50. https://doi.org/10.1177/0340035220931882
  • Hartley, K., & Seymour, L.F.(2010). Towards a framework for the adoption of business intelligence in public sector organisations: the case of South Africa. The Proceedings of the SAICSIT 11, October 3-5, 2010, Cape Town, South Africa.
  • Inzelt, A., Schubert, A., & Schubert, M. (2009). Incremental citation impact due to international co-authorship in Hungarian higher education institutions. Scientometrics,78(1), 37-43. https://doi.org/10.1007/s11192-007-1957-8
  • Lariviere, V., Gingras, Y., & Archambault, É. (2006). Canadian collaboration networks: A comparative analysis of the natural sciences, social sciences, and the humanities. Scientometrics,68(3), 519-533. https://doi.org/10.1007/s11192-006-0127-8
  • Leydesdorff, L., & Wagner, C.S. (2008). International collaboration in science and the formation of a core group. Journal of Informetrics, 2(4), 317-325. https://doi.org/10.1016/j.joi.2008.07.003
  • Miller, G. (2011). Social scientists wade into the Tweet stream. Science, 333(2011), 1814-1815. https://doi.org/10.1126/science.333.6051.1814
  • MSRT (2022). Islamic Republic of Iran, Ministry of Science Research and Technology, Statistics-2019, Erişim Tarihi: 10/02/2022, https://www.msrt.ir/en/page/20/statistics-2019#us2015
  • Nikzad, M., Jamali, H. R., & Hariri, N. (2011). Patterns of Iranian co-authorship networks in social sciences: A comparative study. Library & Information Science Research, 33(4), 313-319. http://dx.doi.org/10.1016/j.lisr.2011.01.005
  • Olmeda‐Gómez, C., Perianes‐Rodriguez, A., Ovalle‐Perandones, M. A., Guerrero‐Bote, V. P., & de Moya Anegón, F. (2009, January). Visualization of scientific co‐authorship in Spanish universities. In Aslib Proceedings, 61(1), 83-100. https://doi.org/10.1108/00012530910932302
  • Schmidt, J. (2007). Knowledge politics of interdisciplinarity. Specifying the type of interdisciplinarity in the NSF’s NBIC scenario. Innovation: The European Journal of Social Science Research, 20(4), 313-328. https://doi.org/10.1080/13511610701760721
  • Scholtz, B., Calitz, A., & Haupt, R. (2018). A business intelligence framework for sustainability information management in higher education. International Journal of Sustainability in Higher Education,19(2), 266-290. https://doi.org/10.1108/IJSHE-06-2016-0118
  • Skolnikoff, E.B. (1993). The elusive transformation: Science, technology and the evolution of international politics. Princeton, NJ: Princeton University Press.
  • Stehr, N. (2005). Knowledge politics: Governing the consequences of science and technology. New York: Routledge.
  • Tang, L., & Shapira, P. (2011). China-US scientific collaboration in nanotechnology: patterns and dynamics. Scientometrics, 88(1), 1-16. https://doi.org/10.1007/s11192-011-0376-z
  • Tešendić, D., & Krstićev, D. B. (2019). Business intelligence in the service of libraries. Information Technology and Libraries, 38(4), 98-113. http://dx.doi.org/10.6017/ital.v38i4.10599
  • 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. http://dx.doi.org/10.1504/IJTG.2005.007050
  • Webometrics (2022). Ranking Web of Universities. Countries arranged by Number of Universities in Top Ranks. Accessed Date: 17/02/2022. https://www.webometrics.info/en/distribution_by_country
  • Zeng, D., Chen, H., Castillo-Chavez, C. Lynch, W.B., & Thurmond, M. (2011). Infectious Disease Informatics and Biosurveillance. 27, Boston: Springer. https://doi.org/10.1007/978-1-4419-6892-0
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Ana Bölüm
Yazarlar

Muhammet Damar 0000-0002-3985-3073

Proje Numarası -
Yayımlanma Tarihi 27 Ağustos 2022
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Damar, M. (2022). A Decision Support System with Business Intelligence: Iranian and Turkish Researcher collaborate enough?. Ankara Hacı Bayram Veli Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 24(2), 684-707. https://doi.org/10.26745/ahbvuibfd.1102805