Outcomes-based Funding and Responsibility Center Management: Combining the Best of State and Institutional Budget Models to Achieve Shared Goals

State governments serve as a key funding source for public higher education. An alternative to historically based state subsidies or enrollment-based formulas, outcomes-based funding allows states to convey goals for higher education by allocating state tax dollars based on measures of outcomes. Within higher education institutions, the Responsibility Center Management model engages deans and other mid-level managers in the responsibility and accountability for revenue generation as well as expense management. Policymakers will benefit from understanding this approach and how it could be used in concert with outcomes-based funding to support the development and delivery of new academic paradigms, expand access to underrepresented students, and, ultimately, increase educational attainment for a greater number of people. This article describes the potential alignment between incentives created by the Responsibility Center Management model and goals of outcomesbased funding. With an integration of the two models, there is a greater assurance of achieving the goals of both—fiscal sustainability and student success. By using Responsibility Center Management, college and university administrators are better able to marshal resources to help students complete their degrees and other credentials while also reaping the benefits of an outcomes-based funding system that directs public funding toward institutions that are doing just that

Spectrum sharing models in cognitive radio networks

Spectrum scarcity demands thinking new ways to manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models for organizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks and analyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoption and exploitation of cognitive radios for open civil networks.L'escassetat de demandes d'espectre fan pensar en noves formes de gestionar la distribució de les bandes de freqüència de ràdio perquè el seu ús sigui més efectiu. La tecnologia emergent que pot permetre aquest canvi de paradigma és la ràdio cognitiva. Han sorgit diferents models d'organització i gestió de les ràdios cognitives, tots amb determinats fins estratègics. En aquest article es revisen els patrons d'assignació de l'espectre de les xarxes de ràdio cognitiva i s'analitzen quals són la base comuna de cada model. S'exposen les vulnerabilitats i els desafiaments oberts que segueixen amenaçant l'adopció i l'explotació de les ràdios cognitives per obrir les xarxes civils.La escasez de demandas de espectro hacen pensar en nuevas formas de gestionar la distribución de las bandas de frecuencia de radio para que su uso sea más efectivo. La tecnología emergente que puede permitir este cambio de paradigma es la radio cognitiva. Han surgido diferentes modelos de organización y gestión de las radios cognitivas, todos con determinados fines estratégicos. En este artículo se revisan los patrones de asignación del espectro de las redes de radio cognitiva y se analizan cuales son la base común de cada modelo. Se exponen las vulnerabilidades y los desafíos abiertos que siguen amenazando la adopción y la explotación de las radios cognitivas para abrir las redes civiles