Revisiting Measuring Performance In Not-For-Profit organizations

Measuring performance is important both in the private sector and in the not-for-profit sector. Private sector performance has been measured by the changes in variables such as earnings per share, stock price, or income tax liability. Performance in the not-for-profit sector is more difficult to measure. A model that combines data envelopment analysis and regression analysis will be used to measure management performance. Data envelopment analysis will measure the organization’s efficiency, the dependent variable, and regression analysis will determine the predictability of not-for-profit financial ratios. In this paper, the Texas arts community is sampled and data is taken from the Federal Form 990s. The input variables will be the total expenses and the total of beginning assets, while the output variables will be the percentage of tickets sold and the percentage of contribution revenue received. This score is the dependent variable in the regression model. In the regression model, financial ratios developed by Greenlee and Bukovinsky (1997) will be used as the independent variables. The results show that the “program expenses to total assets” ratio is the most statistically significant ratio. The remaining ratios do not significantly increase the adjusted R2(squared). From a practical viewpoint, the results show that measuring performance requires more than quantitative measures, even in the not-for profit sector.