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This research aims to maximize the logistics outsourcing benefits through developing new hybrid models for evaluating and selecting Logistics Service Providers (LSPs). The growing demand for logistics outsourcing and the increase in the number and type of LSPs highlight the increasing importance of the LSP evaluation and selection process. Firms use various approaches to evaluate and select their LSP partners. Most of these approaches seem to have overlooked the strategic side of the logistics outsourcing process. Additionally, the uncertainty issue of data, the complexity of the decision and the large number of criteria involved increase the attractiveness of the Multi-Criteria Decision-Making (MCDM) approaches. A comparative literature review was used in order to identify crucial factors and methods that are used in logistics literature in fragmented ways and therefore, to establish and design a conceptual framework and models for logistics outsourcing. First, a long list of evaluation criteria was developed. Three main dimensions were identified: logistics performance, logistics resources and logistics services. Then a conceptual framework was developed using the three main dimensions with their related factors. Based on the comparative literature review outcomes, a number of integrated models have been developed and used to achieve this aim with emphasis given to FDEMATEL, FTOPSIS and FQFD techniques. Whereas the FDEMATEL technique contributed to construct influence relationships between factors under each dimension, develop impact-relationship maps and identify dependent and independent success factors (ISFs), the FTOPSIS technique used the weighted success factors to evaluate, rank and select the best LSP in three case studies. Twenty-one ISFs have been identified to be used in the final approach. These ISFs consist of eight LKPIs, seven logistics services and six logistics resources and capabilities. All of the factors were used to evaluate and select the best LSP alternative and ISFs were used to conduct the evaluation process. Different sensitivity analysis tests are used to confirm models’ robustness. Based on the outcomes of both cases, decision makers can use independent factors alone to evaluate and select the best LSP, which simplified the logistics outsourcing process in our study. The FQFD technique was used to link the LSUs strategic objectives with logistics requirements and the ISFs to develop a new strategic logistics outsourcing approach. Finally, two case studies representing the supply chain upstream and downstream are used to demonstrate the new hybrid approach effectiveness. The comparison of both cases’ findings highlighted their differences in terms of strategic objectives, logistics requirements and ISFs.