ABSTRACT
This research focuses on a nonparametric approach of comparing the companies’ business performance. Since the financial ratios have become very popular in empirical research over the past couple of decades, the research implies that they can be very useful in answering specific questions of interest. Novelty of this research includes a comprehensive guidance on how to implement the Data Envelopment Analysis approach in constructing a ranking system of the selected companies, alongside robustness checking of the results via Multiple Criteria Decision-Making model. Empirical data consist of 292 companies constituting NASDAQ Computer Component Index and more than 40 financial ratios, which put the problem within the area of big data analysis. The analysis shows how to obtain relevant and meaningful results, which are also robust. The inefficient companies were identified via 9 inputs and outputs in total. The main variables found for the efficiency of a company are the P/E ratio, return on investment, earnings per share, asset turnover, dividend yield, price-to-sales ratio, price-to-cash flow, price-to-tangible book ratio, and cash per share. Thus, companies with high values of the first 5 aforementioned variables and low values of the latter mentioned variables have good business practices and performance. Research concludes with recommendations for future research and empirical applications in business as well.
