Cavanaugh, Gesulla

The purpose of this study was first to determine factors associated with intellectual
reputation. Second, the study aimed to examine intellectual reputation in relationship to doctoral
graduates’ productivity in the biomedical sciences and in relationship to organizational
biomedical advancement and productivity. Third, the study aimed to visualize a spatial
relationship between intellectual reputation and local organizational biomedical advancement
and productivity. Finally, a simulated research-based model was proposed for understanding
hospital productivity.
The study used quantitative analysis and The Geographic Information System GIS. The findings
from this study suggest that university’s research intensity, having a Nobel Laureate on staff,
Hirsch Index of the most prominent researcher on staff, scientific patent, scientific publications,
and affiliation with multiple countries are good predictors of intellectual reputation. Correlation
analysis suggests that university intellectual reputation is associated with doctoral graduates’
productivity. When examining the relationship between the university and hospitals, university
intellectual reputation was positively correlated with hospital biomedical advancement. Hospital
productivity was significantly correlated with university intellectual reputation. University
intellectual reputation was significantly correlated with hospital capacity to absorb knowledge
and knowledge spillover. Regression analysis also reveals that hospital capacity to absorb
knowledge and knowledge spillover are good predictors of hospital biomedical advancement, F
2, 176 62.637, p 0.001.Visual examination of the hospitals suggests that when universities
publish at a large quantity, this influences hospitals within the area to publish as well.
Additionally, hospitals that are more productive tend to cluster around universities with higher
intellectual reputation.

The purpose of this study was first to determine factors associated with
intellectual reputation, specifically among selected biomedical departments worldwide
within the university setting. Second, the study aimed to examine intellectual reputation
in relationship to doctoral graduates’ productivity in the biomedical sciences and in
relationship to organizational biomedical advancement and productivity. Third, the study
aimed to visualize a spatial relationship between intellectual reputation and local
organizational biomedical advancement and productivity in the United States and the
United Kingdom. Finally, a simulated research-based model was proposed for
understanding hospital productivity. The study used quantitative analysis in order to achieve these goals. The Geographic Information System (GIS) and Geocommons were used to visualize possible relationship between universities and hospitals in different regions. The findings from
this study suggest that the university’s research intensity, having a Nobel Laureate on
staff, Hirsch Index of the most prominent researcher on staff, scientific patent, scientific
publications, and affiliation with multiple countries are good predictors of intellectual
reputation. Correlation analysis suggests that university intellectual reputation is
associated with doctoral graduates’ productivity. When examining the relationship
between the university and hospitals, university intellectual reputation was positively
correlated with hospital biomedical advancement, r= .445, p =0.001. Hospital
productivity was significantly correlated with university intellectual reputation, r= .322,
p =0.001. University intellectual reputation was significantly correlated with hospital
capacity to absorb knowledge (r= 0.211, p =0.005) and knowledge spillover (r=.242,
p =0.001). Regression analysis reveals that hospital capacity to absorb knowledge and
knowledge spillover are good predictors of hospital biomedical advancement, F (2, 176)
= 52.637, p = 0.001. Hospital capacity to absorb knowledge, affiliation with a university,
intellectual reputation of the affiliated university, and distance between the hospital and
the affiliated university were shown to be good predictors to hospital productivity, F (4,
106) = 11.115, p = 0.001. Visual examination of the hospitals suggests that when the universities publish at a large quantity, this tends to influence the hospitals within the area to publish a large
quantity as well. Additionally, hospitals that are more productive tend to cluster around
universities with higher intellectual reputation.