Abstract
Since its inception, SaaS market has been one of the fastest growing segments in the software industry. It is fast becoming a serious consideration for enterprises of all types and sizes. This paper attempts to measure the productivity of SaaS firms by adopting a stochastic frontier approach. We define a two-stage empirical model to examine the catch-up effects among SaaS firms, as well as the performance differences between SaaS firms and traditional software firms. In the first stage, a stochastic frontier model is specified to derive technical efficiency scores and measure SaaS firms’ productivity. In the second stage, the efficiency scores and their growth rate are treated as dependent variables and regressed on firm-level explanatory variables to identify the source of the catch-up effects. In these two stages, traditional software firms serve as a benchmark. The findings of our study may shed light on the SaaS business model.
Recommended Citation
Ge, Chunmian and Huang, Ke-wei, "Productivity Differences and Catch-Up Effects among Software as a Service Firms: A Stochastic Frontier Approach" (2011). ICIS 2011 Proceedings. 2.
https://aisel.aisnet.org/icis2011/proceedings/economicvalueIS/2
Productivity Differences and Catch-Up Effects among Software as a Service Firms: A Stochastic Frontier Approach
Since its inception, SaaS market has been one of the fastest growing segments in the software industry. It is fast becoming a serious consideration for enterprises of all types and sizes. This paper attempts to measure the productivity of SaaS firms by adopting a stochastic frontier approach. We define a two-stage empirical model to examine the catch-up effects among SaaS firms, as well as the performance differences between SaaS firms and traditional software firms. In the first stage, a stochastic frontier model is specified to derive technical efficiency scores and measure SaaS firms’ productivity. In the second stage, the efficiency scores and their growth rate are treated as dependent variables and regressed on firm-level explanatory variables to identify the source of the catch-up effects. In these two stages, traditional software firms serve as a benchmark. The findings of our study may shed light on the SaaS business model.