In this study, the efficiencies of Project Management Offices (PMOs) in large-scale information system (IS) projects are addressed by using data envelopment analysis. Moreover, the potential improvement levels for each input and output factors of inefficient PMOs are examined. The effects of performance levels of PMO functions on project outcomes with respect to efficiency levels are also analyzed. A total of forty-nine PMOs are analyzed for this study. The result shows that twenty-four PMOs are found to be efficient. As a result of analyzing the impact of efficiency on project performance depending on the functional levels of PMOs, those groups with a high degree of efficiency show higher outcomes compared with the groups with a low degree of efficiency regardless of the functional levels of PMOs. Furthermore, the gap in outcome between the groups with a high degree of efficiency and the groups with a low degree of efficiency is maintained at almost the same level, regardless of the functional levels of PMOs, with the exception of the case of practice management. This indicates that even those groups with a low degree of efficiency could expect high outcomes in terms of schedule and cost compliance if their level of practice management is high.
The purpose of this study is to verify the existence of congestion in Korean hospitals, to identify the causes of congestion, and to suggest directions for efficiency improvement of hospitals. The result showed that congestion occurred in 71.90% of 1185 hospitals. In addition, it was found that hospital specialization has a negative effect on congestion. In other words, the higher the hospital specialization, the lower the overall congestion rate of the hospital. More specifically, the specialization of hospitals also showed a negative effect on congestion of nurses. On the other hand, hospital specialization was found to have a positive effect on the congestion of the number of doctors, but it does not have a significant effect on the congestion of hospital beds. It was also found that hospital size has an effect on the relationship between hospital specialization and congestion, but the location of the hospital and the type of ownership did not act as a moderator.
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