Efficiency determinants in Industry 4.0: a two-stage DEA approach in the Brazilian 3PL industry

Abstract

Paper aims: The main objective is to determine which Industry 4.0 (I4.0) technologies significantly impact the scale efficiency of 3PLs’ (Third Party Logistics). Originality: This paper provides a significant academic contribution given that it is the first quantitative research endeavor to evaluate the influence of I4.0 applications on productivity within the Brazilian 3PL industry. Research method: A two-stage Data Envelopment Analysis (DEA) model was adopted. The first stage of the DEA enabled the measurement of 3PL efficiency, and the second stage (Bootstrap Truncated Regression) allowed us to explore the relationship between efficiency and the I4.0 technologies. Secondary data from Revista Tecnologística provided the inputs, outputs, and contextual variables for this analysis. Main findings: In the first stage of the analysis, a high average technical inefficiency was identified, suggesting managerial failures to efficiently use available resources. However, 3PLs demonstrated low-scale inefficiency, operating close to the optimal production scale. In the second stage, the contextual variables Drones, Big Data, and Business Intelligence were positively significant, while Internet of Things technology was negatively significant. Implications for theory and practice: Our study enhances 3PL efficiency literature by applying DEA, considering contextual aspects, and exploring the adoption challenges of I4.0 technologies in emerging economies.