Journals / İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi / 2017 / Cilt: 16 - Sayı: 32

SIMULATIONS OF RESEARCH PERFORMANCE IN CROSS-DISCIPLINARY CONTEXTS: A MODEL AND AN APPLICATION

DİSİPLİNLERARASI BAĞLAMLARDA ARAŞTIRMA PERFORMANSI SİMÜLASYONLARI: BİR MODEL VE BİR UYGULAMA

Pages
15–26
Publication Date
2017-12-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Contingent upon the priority-driven amount of resources devoted to research, university administrators could choose a path among different trajectories, a path that is most compatible with their institutional objectives.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The purpose of this paper is to construct a model of research performance, based on a demand-and-supply set-up, in a cross-disciplinary context and simulate the trajectory of research performances.
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Key Findings & Data:It turns out that, depending on the levels of human capital and technology, research performances could have different trajectories over time.
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Conclusion & Impact:Contingent upon the priority-driven amount of resources devoted to research, university administrators could choose a path among different trajectories, a path that is most compatible with their institutional objectives.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Araştırma performansı simülasyonları · alanlar-arası çapraz etkiler · teknoloji

Abstract

The purpose of this paper is to construct a model of research performance, based on a demand-and-supply set-up, in a cross-disciplinary context and simulate the trajectory of research performances. We take into account the effects of human capital and research technology as well as interactions among different disciplines/subjects so as to theorize about possible shapes of these trajectories. It turns out that, depending on the levels of human capital and technology, research performances could have different trajectories over time. Contingent upon the priority-driven amount of resources devoted to research, university administrators could choose a path among different trajectories, a path that is most compatible with their institutional objectives.

Özet

Bu makalenin amacı, çapraz etkileşimlerin karakterize ettiği disiplinlerarası bağlamlarda, arz ve talebe dayalı bir araştırma performansı modeli kurmak ve performansın seyrini simüle etmektir. Makalede, beşeri sermaye, araştırma teknolojisi ve disiplinlerarası etkileşimlerin dikkate alındığı bir model aracılığıyla, muhtemel performans yörüngeleri incelenmektedir. Beşeri sermayenin düzeyi ve teknolojiye bağlı olarak farklı yörüngelerin mümkün olabileceği ortaya konulmaktadır. Üniversite yönetimleri, değişik performans yörüngeleri arasında, hedeflerine uygun seçimi, araştırmaya öncelikler doğrultusunda tahsis edilmiş kaynakları kullanarak, yapabilirler.

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Cite This Article

KARA, A. (2017). SIMULATIONS OF RESEARCH PERFORMANCE IN CROSS-DISCIPLINARY CONTEXTS: A MODEL AND AN APPLICATION. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, Cilt: 16 - Sayı: 32, 15–26. https://ajindex.com/articles/123904

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References (17)

  1. Abdullah, L., Jaafar, S., Taib, I., (2013), Ranking of Human Capital Indicators using Analytic Hierarchy Process, Procedia-Social and Behavioral Sciences 107, 22-28.
  2. Abramo, G., Cicero, T., D'Angelo, C.A., (2012), Revisiting size effects in higher education research productivity,. Higher Education,3 (6), 701-717.
  3. Abramo, G., D'Angelo, C.A., Di Costa, F., (2014), Investigating returns to scope of research fields in universities. Higher Education 68 (1), 69-85.
  4. Adams, J.D., Clemmons, J.R., (2011), The role of search in university productivity: Inside, outside, and interdisciplinary dimensions. Industrial and Corporate Change, 20 (1), 215-251.
  5. Barlas, Y., Diker V., (2000),. A Dynamic Simulation Game for Strategic University Management, Simulation and Gaming, 31(3), 331-358.
  6. Barlas, Y., Diker, V. & Polat, S. (eds.), (1997), Systems Approach to Learning and Education into the 21st Century (Proceedings of 15th International System Dynamics Conference. Istanbul: Boğaziçi University Press.
  7. Dundar, H., Lewis, D.R., (1995), Departmental productivity in American universities: Economies of scale and scope. Economics of Education Review 14 (2), 119-144.
  8. Fedderke, J. W., Luiz, J. M., (2008), Does Human Capital Generate Social and Institutional Capital? Exploring Evidence from South African Time Series Data, Oxford EconomicPapers, 60 (4), 649-682.
  9. Grayson, J. P., (2004),
  10. Social Dynamics, University Experiences, and Graduates' Job Outcomes, British Journal of Sociology of Education, 25 (5), 609-627.
  11. Ivanov, V. V., Markusova, V.A., Mindeli, L. E., (2016), Government investments and the publishing activity of higher educational institutions: Bibliometric analysis, Herald of the Russian Academy of Sciences 86 4, 314-321.
  12. Jaffe, A.B., (1989),
  13. Real Effects of Academic Research, The American Economic Review, 79 (5), 957-970.
  14. Kara, A., (2011),
  15. Modeling social processes, Istanbul Commerce University, Mimeo. Kara, A., (2013a), Dynamics of Performance and Technology in Higher Education: An Applied Stochastic Model and a Case Study. Hacettepe Journal of Mathematics and Statistics 42 (1), 87-99.
  16. Kara, A., (2013b), Educational Technology and Human Capital,” Procedia – Social and Behavioral Sciences, 106, 970–979.
  17. Kara, A., (2014), A System Dynamics-Based Decision Support Model for Universities. Istanbul Commerce University, Mimeo. Kara, A., (2016), "Simulations of information technology-induced teaching performance in cross-disciplinary settings: a model and an application", The Int