Decision-making is a ubiquitous and paramount issue in the modern business world. Inappropriate decisions may lead to severe consequences for companies. Considering that the evaluation of alternatives is generally affected by several criteria, decision-making should be considered a very challenging task. From the 1980s to the present day, various multi-criteria decision-making (MCDM) methods have evolved, supporting people in the decision-making process. The main aim of this paper is to propose an original MCDM method and to demonstrate its applicability in an empirical case study. To solve the electric vehicle selection problem for the last-mile delivery, we developed and applied a new MCDM method -the AROMAN (Alternative Ranking Order Method Accounting for Two-Step Normalization) method. To demonstrate the robustness of the proposed method, a comparative analysis with other state-of-the-art MCDM methods is conduct-ed. The results indicate a high level of confidence in the AROMAN method in the decision-making field. In addition, the sensitivity analysis is performed, and the results indicate a high level of stability.
Nowadays, cargo bikes play a vital role in the last-mile delivery process. Parcel distribution by cargo bikes becomes a more accessible and ecologically friendly solution. This paper addresses the investment decision on the cargo bike delivery concept selection problem. We investigated a better solution in terms of whether the company needs to perform the delivery by investing in its fleet of cargo bikes or renting cargo bikes from a third party. The third solution is to combine those two alternatives. This case considers four criteria: cargo bike procurement cost, cargo bike maintenance cost, return on investment, and financial profitability. To solve this problem, we applied the extended alternative ranking order method accounting two-step normalization (AROMAN) method. The results compared with the MARCOS and ARAS methods confirmed that delivery concept 2 (i.e. renting cargo bikes from third-party providers) represented the best solution for the e-commerce company.
Professional drivers play a crucial role in many businesses and the lives of people. They are responsible for transferring people and goods between distant points, enabling safe and efficient flows. The road traffic death rate is from 8.3 to 27.5 per 100,000 inhabitants in the countries globally. Because professional drivers spend a significant amount of time on the road, their appropriate selection may contribute to general traffic safety. In addition, an adequate selection of candidates significantly impacts the financial costs of the employing company. However, the recruitment procedure is a very complex task where multiple criteria should be considered. By its nature, this is a typical multi-criteria decision-making problem. The purpose of this paper is twofold: to contribute to the methodological, as well as to the professional field. Considering the professional, we propose a decision-making tool in the procedure of professional driver selection. There are several methodological contributions. By reviewing the literature, we identified 14 criteria for candidate selection. In the proposed model, by using expert opinion and implementing DEMATEL and Fuller’s pairwise comparisons, we ranked these criteria and determined the seven most important for further calculation procedure. Here, we introduced an original approach for measuring the reliability of obtained answers. Then, to rank the candidates, the fuzzy AROMAN approach is applied for the first time in the literature. The input data were obtained in the form of a survey, where the experts evaluated the importance of criteria and their interrelation. We used MS Excel and MATLAB for data processing. An additional methodological contribution of this study is an advancement of the AROMAN method by the proposal of an algorithm for the calculation of parameter λ used in the final ranking formula. To illustrate the applicability of the proposed model, a case study is provided. Based on the results, we can conclude that the new methodological approaches can be successfully used in the procedure of professional driver selection, as well as in solving other multi-criteria decision-making problems.
Last-mile delivery (LMD) is one of the crucial phases of the shipping process. Since e-commerce rapidly evolves, there are many issues that should be addressed in city logistics. This paper specifically tackles the issue of Third-Party Logistics (3PL) provider selection for sustainable last-mile delivery. The 3PL selection problem has been solved for the e-shop company from Belgrade, which has online sales. The management of the e-shop company has identified five possible 3PL providers. Those five 3PL providers have been evaluated according to six criteria such as distribution cost, on-time delivery, flexibility of distribution, IT capability, good cultural fit, and customer satisfaction index. To evaluate and rank the 3PL providers, two multi-criteria decision-making methods were coupled. The first one is a Best-Worst Method (BWM) used to find the criteria weights, while the second one is a Combined Compromised Solution (CoCoSo) method utilized to rank the 3PL providers from best to worst one. To check the stability as well as the robustness of the applied methods, sensitivity and comparative analyses are performed. The results show high confidence in the applied methods.
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