A system dynamics study on the production-price behavior of the sugar cane industry in Nigeria
A computer simulation model of the production price behavior of the Nigeria Sugar Industry is constructed using system dynamics methodology. The important factors are the interactions of land area, composite price, domestic price, refined sugar production, inventory, domestic consumption, domestic d...
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| Format: | text |
| Language: | English |
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Animo Repository
2003
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/3097 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/9935/viewcontent/CDTG003546_P.pdf |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | A computer simulation model of the production price behavior of the Nigeria Sugar Industry is constructed using system dynamics methodology. The important factors are the interactions of land area, composite price, domestic price, refined sugar production, inventory, domestic consumption, domestic demand, export, export price, sugar-cane production, expected consumption and the mill capacity. The governing dynamic equations were programmed using the Stella (dynamic models) and Simulation System software. The model reproduced the past history of the system adequately with respect to R2 the coefficient of determination which measures the degree to which two series covary. R2 for land area yielded 0.74619, for refined sugar production, 0.7631094, for composite price, 0.7767861, for domestic price, 0.78752. Indeed parameter insensitivity is an important dimension of a model that should be compared with the real system to enhance confidence in the model (Forrester and Senge 1980), (Graham, 1980). This model provides the Nigerian National Policy makers with a dynamic model to investigate the impact of their policies (formed/unformed) with respect to the total view of the Nigeria Sugar Cane Industry (N.S.C.I.) and all agricultural commodities. System boundaries were properly selected to represent the objectives, interacting variables are effectively connected, and the pertinent parameter coefficients were critically chosen. |
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