Strategy formation for higher education institutions using system dynamics modelling

Mridula Sahay, Kuldeep Kumar

Research output: Contribution to journalArticleResearchpeer-review

Abstract

System Dynamics is the modeling technique used to understand the behavior of a complex system over time. It is particularly useful in long-term forecasting when several variables are interrelated with each other. System dynamics models are different from statistical models in the sense they not only provide forecast and control, but they also offer explanations and an understanding of the relationships between the dependent variable and numerous exogenous and endogenous variables. This research paper focuses on the strategy formation for quality improvement in Higher Education Institutions (HEI's) using system dynamics models. Most HEI's in developing countries are taking a strong interest to the extent that they are adopting new educational strategies for enrichment of quality in higher education. The impetus for this development is coming from internal pressure and also considerably from the outside stakeholders. This paper also provides a dynamic model that can accommodate changing economic and environmental conditions, and hence has the capability to provide various 'what-if' analyses to facilitate the adoption of appropriate strategy.
Original languageEnglish
Pages (from-to)207-227
Number of pages21
JournalInternational Journal of Intelligent Technologies & Applied Statistics
Volume7
Issue number3
DOIs
Publication statusPublished - 1 Sep 2014

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Strategy formation
System dynamics model
System dynamics modeling
Higher education institutions
Long-term forecasting
Environmental conditions
Developing countries
Modeling
Complex systems
Economic conditions
Exogenous variables
Education
Statistical model
System dynamics
Endogenous variables
Quality improvement
Stakeholders

Cite this

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Strategy formation for higher education institutions using system dynamics modelling. / Sahay, Mridula; Kumar, Kuldeep.

In: International Journal of Intelligent Technologies & Applied Statistics, Vol. 7, No. 3, 01.09.2014, p. 207-227.

Research output: Contribution to journalArticleResearchpeer-review

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