Investigating the determinants of successful budgeting with SVM and Binary models

Naveen Kunnathuvalappil Hariharan

No xf7ak, OSF Preprints from Center for Open Science

Abstract: Learning the determinants of successful project budgeting is crucial. This research attempts to empirically find the determinants of a successful budget. To find this, this work applied three different supervised machine learning algorithms for classification: Support Vector Machine (SVM), Logistic regression, and Probit regression with data from 470 projects. Five features have been selected: coordination, participation, budget control, communication, and motivation. The SVM analysis results showed that SVM could predict successful and failed budgets with fairly good accuracy. The results from Logistic and Probit regression showed that if managers properly focus on coordination, participation, budget control, and communication, the probability of success in project-budget increases.

Date: 2021-09-08
New Economics Papers: this item is included in nep-big, nep-cmp, nep-isf and nep-ppm
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:xf7ak

DOI: 10.31219/osf.io/xf7ak

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