Article2021

Measuring financial performance of Indian manufacturing firms: application of decision tree algorithms

44 citations0/0 files storedMeasuring Business Excellence

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Financial Analysis and Corporate Governance Working Capital and Financial Performance Financial Distress and Bankruptcy Prediction

Abstract

Purpose Determining the relevant information using financial measures is of great interest for various stakeholders to analyze the performance of the firm. This paper aims at identifying these financial measures (ratios) which critically affect the firm performance. The authors specifically focus on discovering the most prominent ratios using a two-step process. First, the authors use an exploratory factor analysis to identify the underlying dimensions of these ratios, followed by predictive modeling techniques to identify the potential relationship between measures and performance. Design/methodology/approach The study uses data of 25 financial variables for a sample of 1923 Indian manufacturing firms which exist continuously between 2011 and 2018. For prediction models, four popular decision tree algorithms [Chi-squared automatic interaction detector (CHAID), classification and regression trees (C&RT), C5.0 and quick, unbiased, efficient statistical tree (QUEST)] were investigated, and the information fusion-based sensitivity analyses were performed to identify the relative importance of these input measures. Findings Results show that C5.0 and CHAID algorithms produced the best predictive results. The fusion sensitivity results find that net profit margin and total assets turnover rate are the most critical factors determining the firm performance in an Indian manufacturing context. These findings may enable managers in their decision-making process and also have vital implications for investors in assessing the performance of the firm. Originality/value To the best of the authors’ knowledge, the current paper is the first to address the application of decision tree algorithms to predict the performance of manufacturing firms in an emerging economy such as India, with the latest data. This practical perspective helps the organizations in managing the critical parameters for the firm’s growth.

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1974An Index of Factorial Simplicity 1966Financial Ratios As Predictors of Failure 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 1994Bankruptcy prediction using neural networks 1987Multinationality and Performance among British Manufacturing Companies 2013Measuring firm performance using financial ratios: A decision tree approach 2011Comparative analysis of data mining methods for bankruptcy prediction

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