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Thesis (Ph. D.)--Columbia University, 1930. / Vita. Published also without thesis note. Bibliography: p. 156-159.

Thesis (Ph. D.)--Columbia University, 1930. / Vita. Published also without thesis note. Bibliography: p. 156-159.

Ratio analysis is a financial analysis technique used by the corporate sector and public colleges and universities. Private colleges and universities have been largely unsuccessful utilizing this technique because of the varied accounting techniques used by the private institutions. This study attempted a different technique. The controllers of five institutions were asked to meet and agree on definitions of categories necessary for completing ratio analysis.Ratios are useful as a tool for monitoring financial changes over time within one institution, comparing similar institutions one with another and evaluating institutions in better financial condition for use as goal ratios.The resultant model consisted of a data dictionary which contained the definitions the controllers had created and iteratively refined, a data spreadsheet which contained the numbers over a five year period matching the definitions, and a ratio spreadsheet which presented the 58 ratios for each institution over a five year period. The controllers, acting as an expert panel for the study, believed the results to be reliable because of their level of involvement in setting the definitions and supplying the numbers. Average ratios were also calculated using the data from all five institutions over all five years. All resulting spreadsheets are contained in their entirety in the dissertation. / Department of Educational Leadership

Thesis (Ed.D.) -- Teachers College, Columbia University, 1991. / Typescript; issued also on microfilm. Sponsor: Gary Natriello. Dissertation Committee: Aaron Pallas. Includes bibliographical references: (leaves 190-204).

This DPhil thesis consists of three related but independent chapters discussing the question of admission and access to higher education. Chapter 1 explores the extent to which the underrepresentation of students from certain population groups at highly selective universities, can be explained by poor information and high non-monetary application costs, and how the universities' admission policies may affect outcomes. This chapter takes a positive approach and proposes a theoretical model to explore the implications of implementing alternative admission policies. Motivated by the results that arise from this exploration, Chapter 2 proceeds with a normative approach, proposing a general framework to study the optimal selection policy from a pool of applicants, taking into account that the pool of applicants is endogenous. This, it is argued, allows a characterisation of the optimal form of discrimination in university admissions. Chapter 3 studies the relationship between tuition fees and academic selectivity, by developing a different, although somewhat related model of monopolistic competition, where universities compete for students by simultaneously selecting prices and admission standards.

The subject of this study was the development of a computer-based system for the modeling of costing assumptions in an academic department. Initially, costing assumptions were defined as those assumptions made in the selection of costing sources and apportioning procedures in cost studies. The major theme of this study was that the system should allow for multiple sets of costing assumptions to be modeled, and it should allow for a very low level of cost disaggregation. This modeling system allows costs to be attached to individual course enrollments, and it also allows multiple departmental cost studies to be performed simultaneously so that any two may be compared for sensitivity analysis.

The problem of this study is to ascertain the existing relationships between enrollment size and methods of financial management in selected public institutions of higher education. The purposes set forth for this investigation are to conduct a survey of the financial management methods of a major segment of Texas higher education, to analyze the existing relationships of these financial methods with increasing enrollments ranging from 2,537 to 26,531, and to assess the implications thereof for indicators of optimum and maximum enrollments under variable methods of financial management.

An essential task of university administration is to monitor the financial position of its auxiliary enterprises. This is an ill-defined and complex task which often requires more administrative time and information than is available. In order to perform this task in an adequate manner a large amount of expertise is required to: (1) determine what constitutes reasonable performance, (2) define unacceptable levels of performance, and (3) suggest courses of action which will alleviate an unacceptable situation. Thorough analysis requires a substantial amount of an expert’s time. The purpose of this research is to explore the opportunities for the enhancement of the financial analysis of auxiliary enterprises through the use of expert systems. The research has included: (1) a comprehensive review of analytical techniques that can be used in financial position analysis, (2) a determination of the the applicability of such techniques to auxiliary enterprises, and (3) an assessment of their amenability to expert system development. As a part of the above described research, an expert system prototype was developed which addresses several of the above issues for one auxiliary enterprise at Virginia Polytechnic Institute and State University. It integrates the knowledge of an expert with both accounting data from the VPI & SU accounting system and other types of data from the auxiliary enterprise operation. The system provides a comprehensive, systematic analysis of the financial position of the Tailor Shop at VPI & SU. This analysis is performed in much less time than would be required by an expert. As a result of the research conducted, it has been concluded that building such a system is possible and it can provide significant benefits to a user. However, financial position analysis requires a substantial amount of data and numerical calculations, both of which require large amounts of computer memory and computations. Therefore, designing an expert system to efficiently perform this task requires the use of a package or a language that efficiently utilizes computer memory and CPU. / Ph. D.