In fund raising management the employment of a decision support system is crucial for optimising the results of fund raising campaigns. However, the current tools based on database technology are not able to suggest suitable fund raising strategies and the support to the fund raiser is limited to give general indications in relation to specific claims. In this paper, we present a fuzzy knowledge-based decision support system, which is able to individuate promising fund raising strategies for a given campaign. The system uses a knowledge based description of the campaign features and of the donors profiles and integrates these data with two models for strategies and historical information evaluation, rules of thumb suggested by experts in the field, and recent econometric studies. The system provides a ranking of suitable strategies using fuzzy evaluations. Experimental results confirm the applicability of the proposed approach in real contexts, providing significant insight into the improvement of campaigns performances.
L. Barzanti, M. Gaspari, D. saletti (2009). Modelling decision making in fund raising management by a fuzzy knowledge system. EXPERT SYSTEMS WITH APPLICATIONS, 36, 9466-9478 [10.1016/j.eswa.2008.12.049].
Modelling decision making in fund raising management by a fuzzy knowledge system
BARZANTI, LUCA;GASPARI, MAURO;SALETTI, DAVIDE
2009
Abstract
In fund raising management the employment of a decision support system is crucial for optimising the results of fund raising campaigns. However, the current tools based on database technology are not able to suggest suitable fund raising strategies and the support to the fund raiser is limited to give general indications in relation to specific claims. In this paper, we present a fuzzy knowledge-based decision support system, which is able to individuate promising fund raising strategies for a given campaign. The system uses a knowledge based description of the campaign features and of the donors profiles and integrates these data with two models for strategies and historical information evaluation, rules of thumb suggested by experts in the field, and recent econometric studies. The system provides a ranking of suitable strategies using fuzzy evaluations. Experimental results confirm the applicability of the proposed approach in real contexts, providing significant insight into the improvement of campaigns performances.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.