The Limits of Nonprofit Impact: A Contingency Framework for Measuring Social Performance
By Alnoor Ebrahim, V. Rangan, Kasturi P. Rangan. 2010
233 citations recorded by the source corpus.
Subfields: Finance, Public Administration, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/8afe02004ec621d5b34cc7fa89ac11d618e92ef1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Massimo Ciambotti
- Cecilia Grieco
- N. Antadze
- F. Sgrò
- Nick Bontis
- Christine L. Exley
- Gennaro Iasevoli
- Laura Michelini
In Public Administration
In Sociology and Political Science
- Massimo Ciambotti
- Cecilia Grieco
- F. Sgrò
- Nick Bontis
- Christine L. Exley
- Gennaro Iasevoli
- Laura Michelini
- Frances Westley
Citations in the corpus
- Impact Metrics for Social Innovation: Barriers or Bridges to Radical Change? (2012, background): “However, the current debate in the social sector around the measurement of social innovation outcomes and impacts mainly reflects the perspective of private social finance that is attempting to be more strategic about its capital allocation (Ebrahim and Rangan 2010).”
- Intellectual capital and financial performance in social cooperative enterprises (2018, background): “The assessment of mission-based performance has to consider the corporate inputs (tangible and intangible) used to support activities or processes for the production of goods or supply of services (Ebrahim and Rangan, 2010).”
- Excusing Selfishness in Charitable Giving (2015, result): “In a field experiment, Gneezy et al. (2014) confirm that charitable giving significantly increases in response to such assurance that donations will not be used towards overhead costs, and that this increase is even larger than a comparable matching grant or framing of this initial donation as “seed”
- Measuring Value Creation in Social Enterprises (2015, methodology): “His work is based on logic models that have been widely used to better understand the relationship between program inputs and outcomes, and also to reveal the mechanisms of change involved in moving from inputs to desired results (Ebrahim & Rangan, 2010).”