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Naresh C Saxena
Independent Researcher, Canada
https://doi.org/10.21571/pehyj.2022.2601.02
Across the world, the governments are seeking to enhance the performance their public enterprises This process involves changing the mindset of public enterprise executives from that of a government bureaucrat to that of a business leader. This includes running public sector enterprises profitably. As agriculture transforms itself from a subsistence activity to agribusiness across the world, the importance of agribusiness construction is increasing. Commercial managers employed by public sector enterprises are asked to estimate the expected profit on a prospective contract to either decide whether to proceed with the project or to aid in financial forecasting for the company. The estimation of a prospective contract’s profitability is generally done by intuition. A mathematical model to aid in predicting the profitability of a prospective contract would be of immense use to public sector enterprises and can be used as a tool to ward off political interference. Furthermore, it would of considerable interest to commercial managers to know the effect on predicted profitability of a contract should they change the value of an attribute of a prospective contract. The application will, however, require close interaction between IT professionals and public enterprise executives.
Construction, Agribusiness, Profitability, Machine Learning
Reference to this paper should be made as follows: Saxena, N.C. (2022). Profitability prediction in Public Enterprise contracts. Public Enterprise, 26(1), 25-42. https://doi.org/10.21571/pehyj.2022.2601.02
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