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further studies and practices, it’s necessary to build more scientific evaluation


indicator system on a solid theoretical framework, which could reflect the substance


of research activities.


Forth, most of literature uses cross-sectional data to analyze university research


efficiency and productivity, and only a few utilize longitudinal data or panel data to


reveal the change or the trend of university research efficiency. Whereas, trend


analysis is much more valuable to administrators and policymakers.


Fifth, most of literature is restricted to evaluating the status of efficiency, while


short of exploiting the underlying factors impacting on efficiency and productivity,


which makes the policy implications obtained from these studies be not


well-supported by the empirical evidences.


To China, due to limited data accessibility, most studies have no choice but to


use the administrative data published of universities administered by Ministry of


Education (MOE) or other top universities, leaving no touch on the evaluation and


examination on the research efficiency of other types. For instance, to date, there is


no study evaluating the research efficiency of 211Us. Besides, there lacks classified


evaluations university research efficiency subject to their different types. These


points not only violate the principle of sample homogeneity required by DEA


method, but also leaves no space for providing helpful suggestions to manage


universities according to their specific type.
Above all, the existing studies concerning university research efficiency and


productivity still have much room for extension and exploration, in aspects of


indicator selection, estimation technique, as well as time-trend analysis, which all


need to be overcome and challenge in the further studies. Besides, researchers


should also pay more attention to the micro-mechanism on allocation process of


university research resources, such as human resource structure of research staff


(human resource allocation), the trade-off of a faculty’s time between teaching and


research (time allocation), funds for teaching and R&D activities (financial allo-


cation), faculty’s individual choice and research incentive institutions (institutional


allocation). Only through sophisticated exploitation into internal resource allocation


process can we discover the inner mechanism of university efficiency and


productivity.


2.5.2 Limitations on Quantitative Approach.................


It’s well recognized that quantitative approach like DEA, SFA and other econo-


metric models have enriched the empirical studies in evaluating efficiency and


productivity of university research production, and have shown its advantages in


aspects such as the evaluation accuracy, broadness of evaluation scope, and eval-


uation equity over non-quantitative approach. However, it’s worth notifying that


there are certain limitations to employ quantitative approach.


First, there is no quantitative approach that has no restrictions andflaws. As we
mentioned before, both parametric and non-parametric methods in measuring


2.5 Comments on Empirical Literature and Quantitative Approach 25

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