ESTIMATING RETURNS TO TRAINING IN THE KNOWLEDGE ECONOMY: A FIRM-LEVEL ANALYSIS OF SMALL AND MEDIUM ENTERPRISES

• 成果类型: Article
• 署名作者: Mehra, Amit; Langer, Nishtha; Bapna, Ravi; Gopal, Ram
• 署名单位: Indian School of Business (ISB); University of Minnesota System; University of Minnesota Twin Cities; University of Connecticut
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• DOI: 10.25300/MISQ/2014/38.3.06
• 发表日期: 2014
• 页码: 757-771
• 关键词: human-capital investments; information-technology; PRODUCTIVITY; COMPENSATION; professionals; ARCHIVAL; skills

摘要

The ongoing digitization of multiple industries has drastically reduced the half-life of skills and capabilities acquired by knowledge workers through formal education. Thus, firms are forced to make significant ongoing investments in training their employees to remain competitive. Existing research has not examined the role of training in improving firm-level productivity of knowledge firms. This paper provides an innovative econometric framework to estimate returns to such employee training investments made by firms. We use a panel dataset of small-to medium-sized Indian IT services firms and assess how training enhances human capital, a critical input for such firms, thereby improving firm revenues. We use econometric approaches based on optimization of the firm's profit function to eliminate the endogenous choice of inputs common in production function estimations. We find that an increase in training investments is significantly linked to an increase in revenue per employee. Further, marginal returns to training are increasing firm size. Therefore, relatively speaking, large firms benefit more from training. For the median company in our data, we find that a dollar invested in training yields a return of $4.67, and this effect approximately grows 2.5 times for the 75th percentile-sized firm. A variety of robustness checks, including the use of data envelopment analysis, are used to establish the veracity of our results.