Performance Analysis of the Indian IT & ITeS Sector: An Application of Additive-DEA and G2SLS
Santanu Mukherjee et al.
What the paper says
This study uses an integrated balanced scorecard-based Additive-DEA framework to identify proxy variables for the inputs and outputs for a sample of firms in India’s information technology and information technology-enabled services sector to identify and analyse these firms’ inefficiencies. The additive-DEA model is used because it is invariant to data translation, in addition to being non-radial and nonoriented, and hence can deal with negative values of variables that are critical to analyse in(efficiency). This is the first such study in the Indian context that focuses on dealing with negative values for earnings as one of the output variables. The results show that high-performing firms, as calculated by the Additive-DEA method, have higher financial gains in terms of revenue, earnings, and return on equity. Further, the study also attempts to explain the factors influencing the firms’ performance using a regression framework for which a generalised two-stage least square method is used. The regression results show that firm characteristics like age, industry specialisation, and business type have no influence on firm performance, while factors like exports, exchange rate changes, and market focus impact its performance. These results have critical policy implications for this sector to reduce inefficiency by controlling costs and increasing spending on research and development.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.00 × 0.4 = 0.00 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.