In social economy a great attention is devoted to non profit organizations, whose mission’s fulfillment is strongly related to the success of fund raising strategies. Then a decision support system for optimizing them is very useful. Using associations donors database a fuzzy expert system has been developed, which is able to suggest the best strategies with respect to donors profiles. This system integrates the profiles with a model for historical information evaluation and operative rules suggested by experts in the field and related literature. There are however many little and medium size organizations which don’t own or efficiently manage the donors database. In these cases another approach has been proposed, which is able to individuate the most promising raising strategies on the basis of the features of the association. The profile factors of a non profit association are widely explored and hierarchically organized in a decision tree, in order to effectively employ the Choquet integral methodology, which is recommended in these kind of multi-criteria decision problems. In the present contribution, some extensions are developed in order to enhance the first approach. In particular an integration with the second methodology is proposed, by substituting some fuzzy components with a hierarchic organization of the knowledge, that allows to use also in this context the Choquet integral, with an improvement of the tuning process and of the computational effort required. Moreover a wide analysis of donors features is performed; the donors interests evolution is managed, allowing a more precise characterization of the donors profile; an utility function approach is developed as extension of the expected gift model; new elements in the management process are modeled. The results obtained in a real operational context show the effectiveness of the proposed improvements.

L. Barzanti, M. Mastroleo (2013). An enhanced approach for developing an expert system for fund raising management. NYC : Nova Science Publishers.

An enhanced approach for developing an expert system for fund raising management

BARZANTI, LUCA;
2013

Abstract

In social economy a great attention is devoted to non profit organizations, whose mission’s fulfillment is strongly related to the success of fund raising strategies. Then a decision support system for optimizing them is very useful. Using associations donors database a fuzzy expert system has been developed, which is able to suggest the best strategies with respect to donors profiles. This system integrates the profiles with a model for historical information evaluation and operative rules suggested by experts in the field and related literature. There are however many little and medium size organizations which don’t own or efficiently manage the donors database. In these cases another approach has been proposed, which is able to individuate the most promising raising strategies on the basis of the features of the association. The profile factors of a non profit association are widely explored and hierarchically organized in a decision tree, in order to effectively employ the Choquet integral methodology, which is recommended in these kind of multi-criteria decision problems. In the present contribution, some extensions are developed in order to enhance the first approach. In particular an integration with the second methodology is proposed, by substituting some fuzzy components with a hierarchic organization of the knowledge, that allows to use also in this context the Choquet integral, with an improvement of the tuning process and of the computational effort required. Moreover a wide analysis of donors features is performed; the donors interests evolution is managed, allowing a more precise characterization of the donors profile; an utility function approach is developed as extension of the expected gift model; new elements in the management process are modeled. The results obtained in a real operational context show the effectiveness of the proposed improvements.
2013
Expert System Software
131
156
L. Barzanti, M. Mastroleo (2013). An enhanced approach for developing an expert system for fund raising management. NYC : Nova Science Publishers.
L. Barzanti; M. Mastroleo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/127226
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