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Naresh C Saxena
Independent Researcher, Canada
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