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On the logistics of cocoa supply chain in Côte d’Ivoire: Simulation-based analysis

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On the logistics of cocoa supply chain in Côte d’Ivoire: Simulation-based analysis

Closed access

Samenvatting

Côte d’Ivoire produces about 42 percent of the world’s total Cocoa but processes only 30 percent of the total production. A large part of the country depends on the commercial benefits of the Cocoa production and supply chain of it. In this paper, we develop a simulation model that assess the performance of the logistics of the Cocoa supply chain in Côte d’Ivoire. The simulation model shed light on the potential of improvements in the logistics of the Cocoa supply chain by identifying inefficiencies, bottlenecks, and blockers that hinder the productivity and performance of the Cocoa supply chain. Results from simulations show that reduction of checkpoints along the roads will increase productivity by 30 percent, while the value of beans in the Port will increase 3 percent and of butter 5 percent. Investing in improving secondary and tertiary roads will increase the productivity by 9 percent and value by 1 percent while investing in improving road infrastructure and checkpoints will raise the productivity by 27 percent and the value by 3 percent. The results suggest that a combination of reducing the checkpoints with the investment in secondary and tertiary roads will increase productivity while at the same time the pollution will be reduced importantly. The results also suggest that the switching from only producing beans to butter should be accompanied with the increase in productivity otherwise the value at the market would not be sensitive. Other important results are also presented in this paper, together with suggestions for improvement in order to optimize the logistics of Cocoa supply chain, and increase the profitability of the Cocoa sector, and hence the living conditions and wellbeing of the farmers in the country.

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OrganisatieHogeschool van Amsterdam
Datum2019-11-01
TypeArtikel
DOI10.1016/j.cie.2019.106034
TaalEngels

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