Nonprofits' performance is often evaluated based, in part, on their program spending ratio (PSR). Yet, ranking nonprofits based on PSR has been criticized because it is an imprecise index of a nonprofit's actual social impact. Further, too much emphasis on PSR creates an incentive for nonprofits to increase their program spending at the expense of investing in overhead, regardless of the social value it generates. In extreme cases, excessive focus on PSR can create incentives to manipulate or even misreport financial statements. Communicating information regarding governance can potentially counterbalance the pressures created by this focus on PSR. In 2008, the U.S. Internal Revenue Service implemented significant changes in the type of information that nonprofits are required to disclose, which helps them to better display their governance quality. Studying the tax forms of 38,226 nonprofits active in social services and relief operations during 2010–2017, we find that governance quality is now an important factor in driving public donations to nonprofits, although PSR still remains a key driver. Moreover, our findings show that better governance is associated with a lower likelihood of misreporting, consistent with the argument that better governance reduces the pressure to report a high PSR. Overall, our results suggest that nonprofits should consider improving their governance quality in their strategies for securing donation income, even though that may lead to lower PSR levels.
In this paper, the problem of lot sizing for the case of a single item is considered along with supplier selection in a two-stage supply chain. The suppliers are able to offer quantity discounts, which can be either all-unit or incremental discount policies. A mathematical modeling formulation for the proposed problem is presented and a dynamic programming methodology is provided to solve it. Computational experiments are performed in order to examine the accuracy and the performance of the proposed method in terms of running time. The preliminary results indicate that the proposed algorithm is capable of providing optimal solutions within low computational times, high accuracy solutions.
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