Green supply chain practices and competitive advantage: The roles of integration and environmental uncertainty

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Type of the article: Research Article

Abstract
In highly dynamic markets with regulatory, market, and technological pressures, especially in emerging economies, manufacturing companies are increasingly striving to become environmentally sustainable, mitigate environmental liabilities, and enhance their competitive advantage. This study investigates the relationship between green supply chain practices and competitive advantage in Jordanian manufacturing companies through the lens of supply chain integration as a mediator and environmental uncertainty as a moderator. From March to June 2025, a quantitative, cross-sectional survey was conducted among managers whose direct responsibilities include supply chain management, procurement, operations, environmental management, and strategic decision-making. After data screening, 254 responses eligible for analysis were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4. Green supply chain practice was found to have a positive relationship with supply chain integration (β = 0.676, p < 0.001) and competitive advantage (β = 0.298, p = 0.012) among respondents. Supply chain integration was also positively associated with competitive advantage (β = 0.527, p < 0.001), and the estimated indirect effect of SC integration was statistically significant (β = 0.356, p < 0.001). The interaction between green supply chain practices and environmental uncertainty was positive and statistically significant in predicting competitive advantage (β = 0.172, p = 0.021), indicating that it might be stronger in a more uncertain environment. Overall, the results suggest that supply chain integration could be a strategy to achieve competitive results from the environment. But the findings should be viewed as statistical relationships, not causal relationships, given a cross-sectional, self-reported, single-informant, non-random sample in one national manufacturing context.

Acknowledgments
The authors would like to address the gratitude to all the respondents who took part in this research. The authors also mention the assistance of the colleagues and institutions that helped in the process of data collection.

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    • Figure 1. Research model
    • Table 1. Survey procedure and primary data
    • Table 2. Profile of respondents and the 254 participating firms
    • Table 3. Descriptive statistics, factor loadings, and collinearity
    • Table 4. Measurement model assessment
    • Table 5. Discriminant validity
    • Table 6. Hypotheses testing
    • Table 7. Mediation results
    • Table 8. Moderation results
    • Table 9. Simple slope analysis of environmental uncertainty
    • Table A1. All items were measured using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree
    • Conceptualization
      Ahmad Ali
    • Data curation
      Ahmad Ali
    • Formal Analysis
      Ahmad Ali
    • Investigation
      Ahmad Ali, Rany Abu Eitah
    • Methodology
      Ahmad Ali, Rany Abu Eitah
    • Supervision
      Ahmad Ali
    • Validation
      Ahmad Ali, Rany Abu Eitah
    • Visualization
      Ahmad Ali
    • Writing – original draft
      Ahmad Ali
    • Writing – review & editing
      Ahmad Ali, Rany Abu Eitah