Analyzing Supply Chain Uncertainty to Deliver Sustainable Operational Performance

The current study is based on the data collected from one single economy within one single industry. Hence, the findings may not be generalizable to other economies and industries. This study has been conducted based on an inductive approach with cross-sectional data. However, future research may consider using longitudinal data to see the changes over time. In addition, supply chain uncertainty should encourage collaborative efforts within the partners that would contribute to better operational performance, future research should incorporate the supply chain collaborative dimensions in the model. Touboulic and Walker suggested sustainable supply chain management is emerging as an applied field of knowledge and due to its' applied orientation, an action research approach would be more meaningful. By nature, the problems in the supply chain are often inter-disciplinary and concerned with the impact on society and business, at large. Also, this raises a future research question, 'to what extent can market/supply chain forces drive sustainability?' Finally, taking into consideration Schlittgen et al., PLS-IRRS, instead of PLS-SEM, should be jointly used with fsQCA. This could be useful to address issue related unobserved heterogeneity that our data may contain. For future research and taking into consideration Schlittgen et al., the iteratively reweighted regressions segmentation method for PLS (PLS-IRRS), instead of PLS-SEM, should be jointly used with fsQCA. This could be useful to address issue related unobserved heterogeneity that our data may contain.