Performance Evaluation of Junior Colleges of Business in Taiwan: A Data Envelopment Analysis
Date Issued
2007
Date
2007
Author(s)
Chen, Wen-Chi
DOI
zh-TW
Abstract
The increasingly large numbers of local institutions of technology and programs of study, accompanied by the decreasing local birth rate, had directly resulted in a higher school admission rate for specialized studies. As a result, students will have more choices of school in the near future. It will also be more important for the students to carefully choose the most suitable schools for themselves.
Nevertheless, there is limited public resource of information regarding business college selection. This study is conducted based on the two-year and five-year specialized studies of 26 business colleges in Taiwan. The study will explore about fresh graduates’ job performances, as well as evaluate the performance resulted from school’s ability to develop students’ diversified skills. The analysis of effects on school performance after considering the environmental variables is done by the three staged DEA (Data Envelopment Analysis). The three evaluation methods of DEA (Data Envelopment Analysis), CDEA (cross efficiency) and SDEA (Super efficiency) are adopted for school performance evaluations. Moreover, the school organization characteristics can be classified into three different kinds of authority attributions, study systems and study subjects. Further discussions will be based on the three categories of characteristics. The results of analysis are as the following:
1.It’s been found that after the wage / salary adjustment, each model’s efficiency value all increased by about 6% with less variables. In another word, there were minor differences between schools after the wage / salary adjustment due to environmental variables. This resulted in increased efficiency value for each school, meaning the job performances of the students from different schools would be much more similar after the wage / salary adjustment.
2.By viewing from the school’s ability to develop their students’ diversified skills, it’s been found that public schools performed better with less standard deviation. Also, the performances of universities of technology were better than that of institutions of technology. More business-prone schools showed superior performance on CDEA, but these schools less well performed on DEA and SDEA comparing with engineering/science-prone schools. In general, DEA expressed higher values than SDEA on the school ability to develop diversified skills of students. CDEA showed the lowest values.
3.In regards to job performances after wage / salary adjustment, public schools performed better than private schools on all models except for CDEA. The CDEA values for institutions of technology were higher than that for universities of technology. The CDEA values for business-prone schools were also higher than that for engineering-prone schools.
4.On all performances, CDEA for public schools was lower than private schools. However, the overall performances were still better for public schools. In regards to the school systems, the DEA and SDEA models of universities of technology showed better results than institutions of technology. On the other hand, institutions of technology showed superior performance on CDEA. The DEA and CDEA performances for business-prone schools were better than engineering-prone schools, which performed superior on SDEA instead.
5.From Pearson Correlation, we found little differences between the three evaluation models on the performances resulted from schools’ ability to develop students’ diversified skills. Regarding job performances before wage / salary adjustment, DEA and CDEA were highly correlated. Whereas CDEA and SDEA were not correlated and were different. Regarding job performances after wage / salary adjustment, there were major differences between DEA and CDEA. There was also only 0.527 major positive correlation between SDEA and DEA. Whereas minor negative correlation was shown between CDEA and SDEA. On comparison between job performances before and after wage / salary adjustments, the performance values of DEA and SDEA didn’t change much. However, the correlation coefficient on the part of CDEA was only 0.694, which showed there were significant differences before and after the wage / salary adjustments. There were obvious differences between all the performances values obtained from the three models. Spearman’s Correlations is basically agreeing with Pearson Correlation. Nevertheless, with Spearman’s Correlations slightly higher than Pearson Correlation, it was found that the efficiency values had changed after (wage / salary) adjustment. The ranking of these values, however, did not differ significantly before and after the adjustment.
Subjects
職場表現
績效
技職院校
Job Market
Performance
Junior Colleges
Type
thesis