Third-party logistics outsourcing: A review of two decades of advancing decision-making approaches with an up-to-date three-layer criteria framework integrating environmental, social, and governance metrics

Abstract

Selecting third-party logistics (3PL) providers is a crucial strategic decision for organizations seeking to enhance supply chain performance in today's dynamic business environment. This study explores the advancement of decision-making approaches for 3PL outsourcing, analysing 121 research articles published from 2002 to 2024. Through a comprehensive systematic literature review supported by descriptive and keyword co-occurrence analyses, the study identifies three primary methodological approaches: Multi-Criteria Decision Making (MCDM), Mathematical Programming (MP), and Artificial Intelligence (AI), with MCDM emerging as the most preferred approach. These methodologies show promising advancements in addressing traditional limitations, adopting data-driven approaches, integrating hybrid methods, managing uncertainty, and refining criteria development processes. Based on an analysis of 1662 selection criteria from the literature, the study proposes an up-to-date and universally applicable three-layer criteria framework focusing on five key aspects: Business Strength and Prestige, Service Excellence, Cost and Pricing, Technology Capabilities, and Sustainability (measured by Environmental, Social, and Governance metrics). This framework, enhanced by insights from industry experts and top 3PL companies, reflects a shift toward more holistic 3PL evaluation and selection. The study contributes to decision science and management literature while providing valuable insights for supply chain professionals, concluding with suggestions for future research directions.