Given the growing global emphasis on sustainable transportation systems, this research presents a comprehensive approach to achieving economic, social, and environmental efficiency in transport within the waste management sector. To address the different challenges of sustainable transportation issues, this paper presents a hybrid multi-criteria decision-making (MCDM) approach that incorporates the analytic hierarchy process (AHP) along with data envelopment analysis (DEA) for sustainable route selection. By leveraging the strengths of both methods, this approach reconciles conflicting requirements and diverse perspectives, facilitating effective decision making. This paper involves identifying relevant criteria for route evaluation, engaging waste management company experts and stakeholders in pairwise comparisons using AHP. Furthermore, DEA is used to calculate route efficiency based on the inputs and outputs of the system. These evaluations enable the identification of the most effective and sustainable routes. This proposed methodology empowers decision makers and transportation policymakers to develop an effective decision-making tool for addressing waste transportation challenges in developing countries. The study contributes to the growing body of research on sustainable waste management practices and provides insights for waste management companies and decision makers on how to optimize waste transportation routes while reducing economic, social, and environmental impacts.

The rapid evolution of industrial systems demands a careful reconciliation of sustainability goals, beyond organizational success and financial profitability. While Industry 4.0 (I4.0) has driven significant advances in automation and process efficiency, its impact on the Sustainable Development Goals (SDGs) remains limited and primarily focused on economic outcomes. Responding to the need for deeper integration between digital transformation and sustainability, this study aims to map the existing literature on Lean Six Sigma (LSS) in the contexts of I4.0 and Industry 5.0 (I5.0), but also, to clarify how sustainability dimensions can be embedded into LSS practices. To achieve this, a scoping review was conducted, including all scientific research published up to submission date and sourced from reliable databases (Scopus and others). Through this comprehensive review, a notable gap in how LSS addresses the various dimensions of SDGs was identified. To address this, the present work introduces a novel conceptual framework —Lean Six Sigma 5.0 (LSS 5.0)— which repositions traditional process improvement tools within a human-centric, resilient, and sustainability-oriented manufacturing paradigm. This innovative model advances Sustainable Manufacturing (SM) by embedding sustainability at the core of quality and continuous improvement strategies, enabling organizations to respond to the evolving expectations of I5.0. Beyond its theoretical contribution, this work offers practical insights for industries seeking to align LSS initiatives with the broader goals of sustainable development. Given its theoretical nature, future research should validate this model through empirical case studies and industrial applications, supporting innovation in SM. The findings directly address the review’s objectives by mapping existing knowledge and proposing actionable pathways for integrating sustainability within LSS practices in the I5.0 era.