Assessing the entrepreneurship process: an application of the data envelopment analysis

A Global Entrepreneurship Efficiency Benchmarking and Comparison Study based on National Systems of Entrepreneurship and Early-Stage Business: A Data Envelopment Analysis Approach

“…Also, Lafuente et al (2021) conducted an efficiency analysis using the non-parametric technique to figure out how country-level entrepreneurship relates to total factor productivity using global entrepreneurship data from 2002 to 2013. Faghih et al (2021) investigated entrepreneurship “overall efficiency,” assessing national entrepreneurship attitude toward the entrepreneurship system, based on GEM 2018 data. Inacio Junior et al (2021) conducted an efficiency analysis of the GEI data to demonstrate that the global entrepreneurial rankings may misinterpret NSE dynamics with the impression that countries showing higher national framework indicators are more productive in generating actual entrepreneurial activity.…”

“…The previous studies can be divided into three streams; (a) Research that dealt with the level of NSEs without efficiency analysis among countries (i.e., Ács et al, 2014), (b) Research that compared efficiency among countries without longitudinal or time-series consideration (e.g., Inacio Junior et al, 2021; Tasnim & Afzal, 2018), and (c) Research that needs further probe in setting input-output relationship (i.e., Faghih et al, 2021). In Faghih et al’s efficiency study (2021), GDP is defined as the output of the overall entrepreneurial activity.…”

“…To date, global entrepreneurship research investigating entrepreneurial efficiency frontiers based on the institutional factors and early-stage entrepreneurs for the multi-faceted efficiency and longitudinal analyses as in this paper are somewhat limited. Some previous studies suggesting NSE constructs (regional framework conditions) such as output measures, attitude measures, and framework measures but without efficiency comparison (i.e., Ács et al, 2014) failed to examine longitudinal dynamics (e.g., Das & Kundu, 2019; Inacio Junior et al, 2021; Tasnim & Afzal, 2018) or set misleading causal relationships between inputs and outputs for efficiency analysis (i.e., Faghih et al, 2021). Overall, it is understood that global entrepreneurship literature further requires; (a) an efficiency study based on NSE, (b) empirical evidence for benchmarking, and (c) integrated efficiency measures that would advance future studies.…”