In the face of the increasingly demanding of goods transportation and storage, the orchestration of cold chain logistics emerges as a critical and multifaceted endeavor. This study, addressing a notable gap in literature, establishes a comprehensive framework for temperature monitoring within cold chain logistics, focusing particularly on transportation and warehousing aspects. The complexity of managing temperature-sensitive goods is amplified by the burgeoning number of entities involved in this sector, underscoring the need for a robust monitoring approach. Recent global challenges have precipitated a series of disruptive events, further complicating the reliable transport of temperature-sensitive commodities. In light of these challenges, the necessity for meticulous temperature control during both transportation and warehousing phases is paramount; lapses in this regard could lead to grave consequences. A thorough analysis of existing cold chain delivery systems was conducted, alongside an examination of various temperature monitoring devices utilized in vehicle cargo compartments and storage facilities. The study not only scrutinizes current trends but also introduces novel solutions for effective monitoring. By exploring and evaluating these elements, the research contributes significantly to both theoretical and practical spheres, offering a solid foundation for future investigations and guidance for practitioners and decision-makers in the field. This exploration revealed the imperative for advanced sensor technologies and integrated data management systems, capable of providing real-time, accurate temperature readings throughout the entire cold chain process. The integration of smart transportation solutions, leveraging Internet of Things (IoT) technology, emerges as a pivotal factor in enhancing the reliability and efficiency of temperature monitoring. Additionally, the study underscores the importance of standardized protocols and practices across the industry to ensure consistency and reliability in temperature management. In conclusion, the framework proposed in this study not only addresses existing challenges in cold chain logistics but also paves the way for innovative approaches in temperature monitoring, fostering enhanced quality control and safety in the transportation and storage of temperature-sensitive goods.

Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study.

The selection of the appropriate distribution channel is crucial for the success of any business dealing with physical goods. When dealing with this selection, it is crucial to have an effective decision support system (DSS) that can assist with such decisions. While various DSS approaches exist in the literature, not all are suitable for real-world applications. This research aims to address this gap by developing practical DSS tools that can aid decision-makers in making optimal decisions even in situations of uncertainty. The paper explores six different distribution channels (retailer’s warehouse, wholesaler’s warehouse, manufacturer’s warehouse, cross-dock, 3PL services, and direct delivery) in order to select the optimal one based on nine established criteria (inventory costs, distribution costs, delivery speed, service level, market coverage, product availability, order consolidation capability, reverse logistics, and order tracking) by using the FUCOM (Full Consistency Method) and ADAM (Axial-Distance-Based Aggregated Measurement) methods. After applying the FUCOM method, C1 (inventory costs) had the highest value when observing criteria weights, whereas C9 (order tracking) had the lowest. The results of the ADAM method showed that A5 (3PL services) was the best-ranked alternative, whereas A4 (cross-dock) was ranked as the worst. Based on the results, a model validation, and sensitivity analysis was conducted to determine whether the final ranking of the alternatives will change. This research provides decision makers with the necessary tools for better decision making, leading to improved distribution operations and increased profitability for the business.

This study applies the FMEA-QFD approach to assess risks in the distribution process, with a focus on warehouse and transport processes, which are commonly associated with user dissatisfaction and customer loss. The methodology identifies the forms, effects, and causes of failures and determines priorities for each category. In that manner, for the warehousing process, long reception time, additional costs, and lack of experience have the highest priority. In the transportation process, time losses, generating additional costs, and longer vehicle retention time are the three failure effects with the highest priorities. Corrective and preventive measures are also defined. The proposed approach is highly applicable in practice and can be modified for use in other industries. This paper contributes both theoretically and practically to the field of logistics.

Today, e-commerce allows consumers access to a wide range of products on the global market, quick and convenient selection, purchase, ordering, and payment of products. Consumers expect to receive the products they bought online, very quickly, at favorable prices and delivery conditions. However, it is often not possible, because global supply chains are realized over large geographical distances, with a whole range of disruptions and challenges that need to be successfully overcome. With the aim of efficiently delivering products and meeting consumer expectations, retailers often leave this job to specialized and resilient logistics companies better known as fourth-party logistics (4PL) providers. On this occasion, it is necessary to conduct a very thorough evaluation of the logistics provider based on appropriate scientific approaches and models. In this paper, a new hybrid approach for the evaluation of resilient 4PLs was proposed, with the aim of providing appropriate support for the decision-making system on product delivery in e-commerce. The hybrid approach is based on the fuzzy full consistency method (FUCOM), evidence theory (ET), rule-based transformation (RBT), and weighted aggregated sum product assessment (WASPAS) methods. The proposed model was tested and applied to an example of an online retailer, which sells and delivers products originating from China and the countries of the Far East to the market of the Western Balkans and Southeastern Europe. Five 4PL providers were evaluated and ranked according to 10 criteria. According to the results, the most important criterion was IT capabilities, while the least important was cooperation. Additionally, sensitivity analysis was carried out to determine whether the final ranking will change. The obtained results showed that the proposed methodology represents a valuable decision support tool that can be used for solving not only the problem described in this paper but also similar problems.

In the logistics domain, the selection of personnel, particularly transport managers and drivers, is pivotal to operational efficacy, demanding a selection process that transcends traditional subjectivity and expertise scarcity. Addressing this, the Best Worst Method (BWM) integrated with the Combined Compromise Solution (CoCoSo) presents a novel decision-support model, employed here for the first time to refine the recruitment process within the transportation sector. Through the application of BWM, criteria weights were ascertained, a method that has shown superior performance and reliability in deriving consistent results. Concurrently, the CoCoSo method facilitated the ranking of candidates, demonstrating greater reliability and stability compared to existing methodologies. The fusion of these methods offers a distinctive approach, enhancing reliability in diverse problems and across various hierarchical strata. A meticulous compilation of evaluation criteria has been delineated, for drivers and transport managers alike, incorporating a gamut of competencies including but not limited to communication and negotiation skills, leadership skills, swift and autonomous decision-making capabilities, resilience under pressure, educational qualifications, proficiency in computer skills, and past work experience. For transport managers, additional competencies such as spatial coordination and orientation, levels of responsibility and precision, adeptness in working under pressure, operational task efficiency, comprehensive understanding of regulations, rules, and documentation, and a history of relevant work experience have been emphasized. This research marks a theoretical and practical contribution to the literature by providing a model crafted for the nuanced requisites of logistics roles. Empirical validation confirms the model's applicability and efficiency in real-world contexts, heralding its potential to refine the Human Resource Management (HRM) landscape in logistics. Consequently, this work signifies a paradigm shift in the strategic and systematic management of human resources in the logistics sector, furnishing industry decision-makers with a robust tool for personnel selection.