An integrated BWM–THOR II–DEMATEL–QFD framework for scrap steel reverse logistics: linking strategy desirability with implementation feasibility in the Turkish automotive sector

Abstract

Circular economy practices have elevated the role of reverse logistics in resource-intensive industries, where the recovery of high-value materials such as scrap steel is central to resource efficiency and environmental performance. This study develops an integrated multi-criteria framework addressing three questions typically treated in isolation: which reverse logistics strategy is most appropriate, which barriers shape its implementation, and which actions should be prioritised. The framework combines the Best-Worst Method (BWM) for criterion weighting, THOR II for ranking alternatives, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for distinguishing driving from dependent barriers, and Quality Function Deployment (QFD) for translating the diagnosis into prioritised solutions. The empirical application draws on five senior practitioners in the Turkish automotive industry, supported by two academic consultants during criteria validation; the same panel contributed to all four quantitative stages. THOR II is implemented with criterion-specific indifference, preference, and discordance thresholds derived from the empirical dispersion of each criterion, departing from the uniform-threshold practice shown to yield non-robust rankings. Economic and regulatory criteria carry the highest priorities, and in-house operation emerges as the leading strategy across all dominance scenarios, with outsourcing and the digital lean model as complements and public-private partnership ranking last. The informal scrap economy, the absence of a clear regulatory framework, and gaps in technology, incentives, and operational knowledge are the most influential driving barriers; prioritised actions converge on strategic embedding, regulatory clarity, and digital monitoring. The contribution is the demonstration that strategy desirability in emerging manufacturing economies cannot be separated from implementation feasibility.