Purpose: this paper explored the impact of market competition on the industry 4. O (I4.O) technology adoption in Indian small and medium sized enterprises (SMEs). The research seeks to explore the competitive pressure between SMEs firms always influence digital changes with different technological adoption levels. Design/methodology: This paper is based on secondary data of 142 SMEs firm for the year 2018–2024. This study employed linear and non-linear quantile regression model to understand the association between of the I4.O and competitiveness among Indian SMEs. I4.O is measured by using Data Envelopment Analysis (DEA). Finding: The result of this study revealed that competition have positive and significant effect on the I4.O at all quantile in linear model which signified that low and high adopter are enforced by the competitiveness. In non-linear model, the U-shaped relationship among I4.O and competition. This study used Porter's Five Forces framework and Resource based View (RBV) to understand the impact of external market force on improving the internal competence development. Practical implication: The finding of this study suggest that SME owner and manager have to observe that the adoption of Industry 4.O become a need for the SMEs survival in competitive environment. The policymakers have to implement digital adoption campaign, skill & training development and overall infrastructure which can bring into line the competitiveness among SMEs and enhance the transformation of I4.O among firms in more inclusive manner. Originality/value: We believe that this paper is one of the first to measure industry 4.0 through technical efficiency aspects using DEA and employ quantile regression to examine the effect of competition on the adoption of Industry 4.0 for Indian SMEs. The paper adds to theoretical contribution by incorporating Porter's and RBV frameworks within an emerging economy environment.

This study investigates whether vulnerable employment constrains GDP growth and whether its effects are linear, distributionally homogeneous, or conditioned by human capital in ten developing and emerging economies. Using a balanced panel of 10 countries from 2000 to 2023, the analysis employs Quantile Panel data analysis. The results indicate that vulnerable employment exhibits no statistically significant linear association with GDP, but a significant negative and non-linear effect exists. It indicates monotonically decreasing nonlinear relationship. Quantile estimates show that this adverse effect is concentrated at the lower (25th) quantile of the income distribution, while remaining insignificant at higher quantiles, and the interaction with tertiary education is uniformly insignificant, which surprisingly suggests that education does not significantly affect the connectivity of vulnerable employment and economic growth. The findings contribute the existing knowledge body by providing evidence that the growth implications of vulnerable employment are non-linear and have significance in countries with lower economic growth (25%ile), challenging linear employment–growth assumptions in development economics. Hence, it delivers important policy implications that employment-growth connection is crucial in lower growing economies irrespective of education.