A model to improve corn productivity and production. (5th December 2019)

• Record Type: Journal Article
• Authors: Suryani, Erma; Dewi, Lily Puspa; Junaedi, Lukman; Hendrawan, Rully Agus
• Is Part Of: Journal of modelling in management. Volume 15:Number 2(2020)
• Page Start: 589
• Page End: 621
• Publication Date: 2019-12-05
• Subjects: Modelling -- Productivity -- Simulation; Industrial management -- Mathematical models -- Periodicals; Industrial management -- Computer simulation -- Periodicals; Business -- Mathematical models -- Periodicals; Business -- Computer simulation -- Periodicals; 658.4033
• DOI: 10.1108/JM2-11-2018-0181
• Languages: English
• ISSNs: 1746-5664

Abstract

Abstract : Purpose: This paper aims to address the corn productivity and production problem under the environmental dynamics to improve the productivity and production through the use of models and scenarios. Design/methodology/approach: System dynamics simulation model is implemented to develop harvested area, productivity and production models. To improve productivity and production, several scenarios have been developed by modifying the model's structures and parameters. Findings: Some factors affecting productivity include soil nutrition, planting patterns, corn quality, irrigation, technology, climate, disease and pest attacks. Corn production after land expansion and intensification depends on the harvested area, productivity and rendement. Research limitations/implications: The data and information used in this study were obtained from East Java Agricultural Department. Practical implications: Corn productivity after land intensification would achieve 73.68 quintals/ha as the impact of structural and non-structural approaches implementation. Corn production after land intensification and expansion would achieve 10.2 M tons in 2030. Fulfillment ratio is above 100 per cent; however, the trend continues declining due to demand growth of 5 per cent and production growth of only 2.8 per cent. Originality/value: The model development provides useful directions for modelers and holistic perspective to accommodate all problem elements. The case selected in this study (East Java) can be extended to other areas. Furthermore, the practical implications can facilitate decision makers in agricultural systems to improve the land productivity and corn production.