Direct and indirect influences of supply chain management practices on competitive advantage in fast fashion manufacturing industry

Purpose This study investigates supply chain management (SCM) practices in a specific fast fashion apparel (FFA) industry. The impacts of SCM practices on competitive advantage (CA) are investigated via mediating roles of supply chain agility (SCA) and partnership quality (PQ). Resource advantage (R-A) theory, in addition to resource-based view (RBV) and dynamic capability theories, is used as theoretical underpinning. Design/methodology/approach A mixed-method approach is adopted: a qualitative field study and survey research. Data from 296 apparel manufacturers in Bangladesh are analyzed using the partial least squares structural equation modeling (PLS-SEM) approach, involving reflective and formative, first- and second-order constructs and mediation tests using the Hayes PROCESS macro. Findings Both SCM practices and PQ significantly affect SCA. SCM practices are found to directly enhance CA, but, counterintuitively, only marginally. Only through mediations of SCA and PQ do SCM practices enhance CA significantly. This is a departure from past research that has postulated direct effects between SCM practices and CA. Research limitations/implications This research is confined to the FFA industry and one national setting, Bangladesh. The data analyzed is also cross-sectional, with customary limitations on the temporal dimension. Practical implications SCM practices contribute to CA, but only through the mediation of PQ and SCA. This is an important directive to practitioners. Also, the second-order reflective measures for each construct indicate the specific SCM practices needed to maximize CA. Originality/value This study contributes to the literature on SCM practices in FFA industry, specifically the mediating roles of PQ and SCA, resulting in new, more nuanced findings that are important in dynamic business settings, driven by new theoretical perspectives incorporating R-A theory, which has hardly been utilized before in SCM research.