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A cost analysis model for universiti...

Tantanadaecha, Suchart.

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A cost analysis model for universities in Thailand: A case study of Chulalongkorn University.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A cost analysis model for universities in Thailand: A case study of Chulalongkorn University./
作者:	Tantanadaecha, Suchart.
面頁冊數:	193 p.
附註:	Adviser: Austin D. Swanson.
Contained By:	Dissertation Abstracts International54-07A.
標題:	Education, Administration. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9330119

A cost analysis model for universities in Thailand: A case study of Chulalongkorn University.
Tantanadaecha, Suchart.

A cost analysis model for universities in Thailand: A case study of Chulalongkorn University. - 193 p.

Adviser: Austin D. Swanson.

Thesis (Ph.D.)--State University of New York at Buffalo, 1992.

The purpose of this study was to examine and analyze Chulalongkorn University's (Chula's) budget in light of different policy climates, to see how budgets have responded to past policy developments and to estimate the budget implications of future policy ideas. The analyses consisted of three parts: (1) Historical Description; (2) Cost Modeling; and (3) Hypothetical Estimation.Subjects--Topical Terms:

626645
Education, Administration.

A cost analysis model for universities in Thailand: A case study of Chulalongkorn University.
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245 1 2 $a A cost analysis model for universities in Thailand: A case study of Chulalongkorn University.
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500 $a Adviser: Austin D. Swanson.
500 $a Source: Dissertation Abstracts International, Volume: 54-07, Section: A, page: 2423.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 1992.
520 $a The purpose of this study was to examine and analyze Chulalongkorn University's (Chula's) budget in light of different policy climates, to see how budgets have responded to past policy developments and to estimate the budget implications of future policy ideas. The analyses consisted of three parts: (1) Historical Description; (2) Cost Modeling; and (3) Hypothetical Estimation.
520 $a The results of analyses indicated that, to some extent, Chula's government budgets in the past were consistent with policy development periods. During the expansion period, there was extensive construction, the number of students and faculty was growing dramatically, salary was the largest single expenditure and was increasing substantially. During the consolidation period, Chula invested more on equipment than on buildings. Number of faculty was almost constant, total number of students was maintained at the same level as in the expansion period. However, student enrollment increased in hard sciences during the consolidation period, partly due to demands of a rapidly growing economy.
520 $a The cost models, across the three different data periods, showed similar patterns of relationships between outcome costs (salary, wages, maintenance and services) and some policy relevant variables such as number of faculty, students, type of program, capital cost, age of program, and faculty education. Number of faculty was consistently the most significant policy variable accounting for the biggest explained variance in all outcome costs. Number of students, type of program, and age of program were not strong policy variables and did not contribute statistically to the explained variance of any outcome costs. Nevertheless, there was evidence that the models in this study fitted the data well and accounted for considerable amount of variance in costs.
520 $a The hypothetical estimation analysis provided a useful tool to estimate and predict the monetary effect of implementing the new market-based faculty salary policy and reducing faculty positions. Moreover, the hypothetical model allowed testing policy alternatives for implementing the new market-based faculty salaries in the future.
520 $a This study was the first comprehensive cost analysis model for a university in Thailand which could provide relevant information about patterns of government budgets, the relationship between significant policy variables and costs, and which could also be used to predict the potential budget consequences of changes in policy variables and to explore policy alternatives of improving quality of education.
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