Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

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Current literature merely identifies the driving factors of research productivity in higher education institutions without directly examining their interrelationships that would offer some fundamental insights into the nature of these factors. Thus, this work intends to identify those driving factor...

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Bibliographic Details
Main Authors: Lanndon Ocampo, Joerabell Lourdes Aro, Samantha Shane Evangelista, Fatima Maturan, Kafferine Yamagishi, Dave Mamhot, Dina Fe Mamhot, Dawn Iris Calibo-Senit, Edgar Tibay, Joseph Pepito, Renissa Quiñones
Format: Article
Language:English
Published: Elsevier 2022-08-01
Series:Journal of Open Innovation: Technology, Market and Complexity
Subjects:
research productivity
higher education institutions
driving factors
interpretive structural modeling
MICMAC analysis
Online Access:https://www.mdpi.com/2199-8531/8/3/148

Internet

https://www.mdpi.com/2199-8531/8/3/148

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