When solving a Multi-Criteria Decision-Making problem of any degree of complexity, many researchers rely on the analytic hierarchy process (AHP). To consider mutual connections between criteria and clusters at the same level and not only the hierarchical structure between criteria and subcriteria, researchers often upgrade from AHP to the Analytic Network Process (ANP), which also examines the interdependency of criteria. However, the ANP method requires a large number of pairwise comparisons. In the case of a complex decision-making problem, the authors of this paper suggest upgrading the AHP method with the graph theory and matrix approach (GTMA) for several reasons: (1) The new method is based on digraphs and permanent value computation, which does not require a hypothesis about interdependency; (2) in case of similar alternatives, the distinguishable coefficient of the new method is higher than those computed for AHP and ANP; (3) the new method allows decision makers to rank comparable alternatives and to combine structurally similar methods without increasing the number of comparisons and the understanding of the results. The developed method (AH-GTMA) is validated by a numerical example of a complex decision-making problem based on a symmetrical set of similar alternatives, a third party logistic provider (3PLP) selection problem.

Sustainable concerns are reputed to be of the utmost priority among governments. Consequently, they have become more and more of a concern among supply chain partners. Logistics service providers (LPs), as significant contributors to supply chain success but also one of the greatest generator of emissions, play a significant role in reducing the negative environmental impact. Thus, the performance evaluations of LPs should necessarily involve such a measure which, firstly, represents a balance between all three pillars of sustainability and, secondly, consider the desirable and undesirable performance criteria. This paper proposes an integrated analytic hierarchy process (AHP) and slack-based measure (SBM) data envelopment analysis (DEA) model, based on the assumption of a variable return to scale (VRS). An AHP pairwise comparison enables selecting the most influential input/output variables. Output-oriented SBM DEA provides simultaneously evaluation of both the undesirable and desirable outputs. The proposed model was tested on a numerical example of 18 LPs. The comparison of output Charnes, Cooper and Rhodes (CCR) and SBM DEA models resulted in a higher number of inefficient LPs when the SBM DEA model was applied. Moreover, efficiency scores of inefficient LPs were lower in SBM DEA model. The proposed model is fair to those LPs that are environmentally friendly.

Notwithstanding the fact that maritime shipping is the most energy efficient mode of transportation for large quantities of freight, there are continues efforts to improve its performance. These efforts have become even more intensive since the beginning of global economic crisis.Slow steaming is one of the attempts to improve both environmental and economic performance of maritime shipping.The paper gives an overview of existing studies on slow steaming and lists other available and already applicable solutions. KEY WORDS:~Slow steaming ~Operating costs ~Environmental efficiency ~Maritime transport efficiency

Green environmental performance increases the competitiveness of the supply chain. However, the greening of the supply chain depends on the manufacturer who drives the green initiative, as well as on all the members of the supply chain who take part in the process. The manufacturer's attention has been largely focused on the environmental performance of the supplier and retailer, whereas logistics service providers have been somehow neglected. It is, in fact, the case is that logistics service providers have begun to play a critical role in supply chain management and could therefore significantly improve environmental sustainability. They have already undertaken a green initiative that unfortunately has rarely, if at all, been required by the manufacturer. The lack of requirements for logistics providers hinders the progress of a green initiative. To take a step forward towards green supply chain management, this chapter aims to introduce all the necessary criteria for the selection of a logistics service provider (LP), with an emphasis on environmental criteria. The environmental selection criteria, with all related subcriteria, were achieved on the basis of a systematic literature review. It has been found that buyers of logistics services still strive to minimize costs, expect quality logistics services, a wellpositioned LP, all the while overlooking environmental issues. The most frequently applied environmental selection criteria are value-added reverse logistics services, followed by environmental expenditures, pollutants released, energy consumption, clean materials and energy use. The findings presented here are useful particularly for researchers, as issues regarding sustainable LP selection and its limitations are highlighted, related to selection criteria identification. These findings may be of less use to managers. However, future phases of this study, richer for the evaluation of logistics experts, will be much more applicable to buyers and providers of logistics services.

Existing research on electric bike sharing systems (e-BSS) emphasises the importance of the sustainability of the systems and the need to respect the views of all stakeholders when planning e-BSS. However, this research overlooks the fact that the sustainability of e-BSS depends to a large extent on the skills and knowledge of the parties who select an electric bike provider, which in most cases is the investor in the e-BSS. There is no previous paper that provides support for investors in (1) defining a set of criteria for selecting a provider that takes into account all of the three domains of sustainability (economic, social, and environmental) and (2) developing a tool that best meets sustainability standards on the one hand and the needs and requirements of all stakeholders (including e-bike users and investors) on the other hand. A distance-based analytic hierarchy process/data envelopment analysis (AHP-DEA) super-efficiency approach was proposed and applied to adapt DEA to the needs of predefined groups by using slack variables. The approach takes into account the fact that not all outputs have a positive impact on the final outcome; the approach also allows decision-makers to define the hierarchical structure of the importance of the criteria directly based on the responses of the selected group. A case study in Slovenia illustrated the application of the approach.