Logistics, Volume 5, Issue 1 (March 2021) – 18 articles

For decades, trade between Europe and China has grown consistently, which has resulted in increased container transportation volumes. Such transportation has been dominated by sea-based options. However, over the years, an air-based mode of transport was developed, while it has lately become increasingly popular to use railways utilizing the Trans-Siberian land bridge. This latter approach boomed amid the COVID-19 crisis in 2020. However, the railway container boom in Eurasia has deeper roots than just the COVID-19 era. As is illustrated in this research work, international trade containers (trade between Russia and other countries, mostly China) and transit containers (e.g., serving the Chinese–EU route) were already showing some significance as early as 2003–2004. In 2020, their volume was already measured in the millions, regardless of the railway data source being used. This is well above the starting period in the 1980s and 1990s, when total annual volumes were around 0.1 million twenty-foot equivalent units (TEU). Container capacity has developed over the years, first being used for international trade and only lately for transit. As a preliminary comparison to air freight, the growth rate was roughly double that in the two-decade observation period. Full article

The rapid growth of urbanisation and e-commerce has increased the number of home deliveries that need to be made in retail operations. Consequently, there is also an increase in unexpected incidents, such as adverse traffic, unavailability of parking space, and vehicle breakdowns. These disruptions result in delays, higher costs, and lower service levels in the last-mile delivery operation. Motivated by free, innovative, and efficient tools, such as the Google application programming interface (API) and Google OR, we built a model to measure the impact of disruptions in the last-mile delivery operation. Our model considers customers’ geographic information, speed estimation between nodes, routing optimisation, and disruption evaluation. Disruptions are considered here as external factors such as accidents and road works that imply the closure of or slow access to certain roads. Computational experiments, based on a set of real data from three different cities around the world, which contrast in size and characteristics (i.e., Boston, US; Bogotá, Colombia; and Pamplona, Spain), were conducted to validate our approach. The tests consider 50 different instances of up to 100 customers per city and analyse the impact of disruptions in terms of travelled time and distance. Our results provide managerial insights for key stakeholders (i.e., carriers, consumers, and government) to define policies and development plans that improve the resilience and capabilities of cities’ transportation systems. Full article

This study was conducted to determine the performance impact of e-procurement adoption in Indonesian manufacturing companies. This study consists of four variables: top management support, information quality, implementation of e-procurement, and company performance. Pilot testing questionnaires were used to test whether the respondents understood the questions given by the researcher. After conducting the pilot test, the final questionnaire was distributed to respondents. The pilot test results and the final questionnaire were analyzed using Statistical Package for Social Science (SPSS) version 21 and SmartPLS v3.0 software to determine the relationship between variables. The results of this study support the acceptance of three hypotheses. The results indicate that top management support has a significant effect on e-procurement implementation. Other results show that information quality has a significant effect on e-procurement implementation, while e-procurement implementation has a significant effect on company performance. From the findings of this article, recommendations from a management perspective are discussed to increase management awareness in adopting electronic procurement. Full article

The importance of considering forward and backward flows simultaneously in supply chain networks spurs an interest to develop closed-loop supply chain networks (CLSCN). Due to the expanded scope in the supply chain, designing CLSCN often faces significant uncertainties. This paper proposes a fuzzy multi-objective mixed-integer linear programming model to deal with uncertain parameters in CLSCN. The two objective functions are minimization of overall system costs and minimization of negative environmental impact. Negative environmental impacts are measured and quantified through CO₂ equivalent emission. Uncertainties include demand, return, scrap rate, manufacturing cost and negative environmental factors. The original formulation with uncertain parameters is firstly converted into a crisp model and then an aggregation function is applied to combine the objective functions. Numerical experiments have been carried out to demonstrate the effectiveness of the proposed model formulation and solution approach. Sensitivity analyses on degree of feasibility, the weighing of objective functions and coefficient of compensation have been conducted. This model can be applied to a variety of real-world situations, such as in the manufacturing production processes. Full article

In the last decade, the Industry 4.0 concept has introduced automation and cyber-physical systems as the core elements of future logistics, supported by an array of technologies, such as augmented reality (AR) providing the necessary support for the digital transformation of manufacturing and logistics and the smartification and digital refinement of traditional pre-Industry 4.0 processes. This paper studies the influence and the potential of gamification techniques in supporting innovative Industry 4.0-enhanced processes in the contemporary warehouse work ecosystem. Gamification in the workplace aims to motivate the employees and increase their involvement in an activity, while at the same time creating a sense of an everyday different experience rather than a set of repetitive and monotonous tasks. Since the design of such a system is a complex process, the most widespread design frameworks are studied, and the emphasis is on the principal game elements and their connection to mobilization mechanisms. Finally, an initial proposal of a gamification framework to support the AR-enhanced order picking process in contemporary logistics centers is provided with an emphasis on the mechanics of a fair and functional reward system. The proposed approach aims to showcase the potential alignment of business processes to human motivation, respecting the differences between tasks and the workers’ cognitive workload. Full article

Supplier risks have attracted significant attention in the supply chain risk management literature. In this article, we propose a new computational system based on the ‘Fuzzy Extended Analytic Hierarchy Process (FEAHP)’ method for supplier selection while considering the relevant risks. We sought to evaluate the opportunities and limitations of using the FEAHP method in supplier selection and analyzed the support of the system developed through the real case of a Brazilian oil and natural gas company. The computational approach based on FEAHP automates supplier selection by determining a hierarchy of criteria, sub-criteria, and alternatives. First, the criteria and sub-criteria specific to the selection problem were identified by the experts taking the relevant literature as a starting point. Next, the experts performed a pair-wise comparison of the predefined requirements using a linguistic scale. This evaluation was then quantified by calculating the priority weights of criteria, sub-criteria, and alternatives. The best decision alternative is the one with the highest final score. Sensitivity analysis was performed to verify the results of the proposed model. The FEAHP computer approach automated the supplier selection process in a rational, flexible, and agile way, as perceived by the focal company. From this, we hypothesized that using this system can provide helpful insights in choosing the best suppliers in an environment of risk and uncertainty, thereby maximizing supply chain performance. Full article

Health supply chains aim to improve access to healthcare, and this can be attained only when health commodities appropriate to the health needs of the global population are developed, manufactured, and made available when and where needed. The weak links in the health supply chains are hindering the access of essential healthcare resulting in inefficient use of scarce resources and loss of lives. A chain is only as strong as its weakest link, and demand forecasting is one of the weakest links of health supply chains. Also, many of the existing bottlenecks in supply chains and health systems impede the accurate forecasting of demand, and without the ability to forecast demand with certainty, the stakeholders cannot plan and make commitments for the future. Forecasts are an important feeder for budgeting and logistics planning. Under this backdrop, the study examines how improved forecasting can lead to better short-term and long-term access to health commodities and outlines market-related risks. It explores further how incentives are misaligned creating an uneven distribution of risks, leading to the inability to match demand and supply. For this purpose, a systematic literature review was performed, analyzing 71 articles from a descriptive and content approach. Findings indicate the emerging trends in global health and the consequences of inaccurate demand forecasting for health supply chains. The content analysis identifies key factors that can pose a varying degree of risks for the health supply chain stakeholders. The study highlights how the key factors emerge as enablers and blockers, depending on the impact on the overall health supply chains. The study also provides recommendations for actions for reducing these risks. Consequently, limitations of this work are presented, and opportunities are identified for future lines of research. Finally, the conclusion confirms that by adopting a combination of approaches, stakeholders can ensure better information sharing, identify avenues of diversifying risks, and understand the implications. Full article

The purpose of this paper is to present a rigorous and critical review of an established cost/time-distance model. The model offers a perspective on the inter-relationships between transport modes, nodes, methods and cargo volumes, types and forms. Organisations can review their door to door supply chain costs by applying the model described in the paper. The reviewed multimodal transport cost model is based on a relatively simple framework but demonstrates that other existing models of modal choice, multimodal transport and inventory location all oversimplify the transport process. The critical components of the model are the transport from origin to destination, consignment loading/unloading, intermodal transfer and performance variability. Other activities such as storage, value addition and customs clearance can be added into the model as required. Several findings emerge from the development of the model and provide much greater clarity concerning the cost-structure of door-to-door multimodal transport services along economic corridors. The model is shown to be a useful tool for identifying theoretical alternative locations for facilities such as inland terminals. The relative unit costs of operating respective freight transport modes lead to a series of classic door-to-door cost profiles stemming from the modal mix, which varies according to shipment distance, volume, cargo value-density and other variables. Full article

Loading and unloading rolling cargo in roll-on/roll-off are important and very recurrent operations in maritime logistics. In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. The objective is to teach an autonomous tug master to manage rolling cargo and perform loading and unloading operations while avoiding collisions with static and dynamic obstacles along the way. The artificial intelligence agent, representing the tug master, is trained and evaluated in a challenging environment based on the Unity3D learning framework, called the ML-Agents, and using proximal policy optimization. The agent is equipped with sensors for obstacle detection and is provided with real-time feedback from the environment thanks to its own reward function, allowing it to dynamically adapt its policies and navigation strategy. The performance evaluation shows that by choosing appropriate hyperparameters, the agents can successfully learn all required operations including lane-following, obstacle avoidance, and rolling cargo placement. This study also demonstrates the potential of intelligent autonomous systems to improve the performance and service quality of maritime transport. Full article

The main purpose of this paper is to propose solutions for overcoming the obstacles that healthcare organizations might face when implementing lean. An in-depth review of existing barriers for lean implementation in healthcare supply chain is presented and validated by experts. Although there is a widespread use of lean concepts in developed countries, little attention has been paid to implementing a lean approach by healthcare providers in developing countries. The present study’s key novelty and contribution is related to this research gap. The study is thus focused in proposing solutions for healthcare organisations in developing countries, especially in Saudi Arabia. The efficacy of these solutions is assessed through experts’ opinion. The paper enhances the body of knowledge for the successful implementation of lean in a hospital setting. Full article

The bullwhip effect is a pervasive phenomenon in all supply chains causing excessive inventory, delivery delays, deterioration of customer service, and high costs. Some researchers have studied this phenomenon from a financial perspective by shedding light on the phenomenon of cash flow bullwhip (CFB). The objective of this article is to provide the state of the art in relation to research work on CFB. Our ambition is not to make an exhaustive list, but to synthesize the main contributions, to enable us to identify other interesting research perspectives. In this regard, certain lines of research remain insufficiently explored, such as the role that supply chain digitization could play in controlling CFB, the impact of CFB on the profitability of companies, or the impacts of the omnichannel commerce on CFB. Full article

In early 2020, COVID-19 infected people throughout the world and brought world commerce to a standstill. Many believe that governments and global businesses were not as prepared as they should have been. While academics have occasionally predicted the economic problems that could result from pandemics, until 2020, there had been scant research that addresses supply chain management issues during pandemics. Eighty-four percent of all pandemic supply chain research was published in the first ten months of 2020. Since the world now finds itself operating supply chains in response to the pandemic, this literature needs to be summarized and articulated for understanding and future research. This literature review addresses that need by summarizing the research which has been generated since 1997, focusing primarily on the bulk of the research that has been published since the COVID-19 pandemic began. Research tools are used to summarize the literature citations, and the articles are coded according to some important variables to further delineate their details. This research also includes a bibliometric co-citation analysis, which clusters the pandemic supply chain literature by author, journal, and article. The findings are that pre-COVID-19 research on pandemic supply chains was primarily about influenza and the healthcare supply chain, whereas post-COVID-19 research provides more analysis of the food supply chain and uses a wider variety of research methods, including simulation, modeling, and empirical methods. Full article

The article presents the first theoretical and empirical estimation of the role of logistics in mitigating the effects of market information asymmetry in Poland. Following a review of international (Akerlof, Spencer, Stiglitz) and Polish literature (Gołembska, Gruszecki, Stradomski), a new logistic model of information asymmetry (LMAI) is presented. The article attempts an empirical verification of this model using the results of studies conducted in Polish firms in the period 2000–2018. The studies examined the efficiency and effectiveness of logistics management, with a particular focus on logistics infrastructure expenditure, balance-sheet inventories, and logistics costs. The computation of the LMAI indicator, based on averaged data provided by manufacturers, distributors and service firms, enabled the estimation of the impact of logistics management on reducing the effects of information asymmetry, and showed the differences of this impact in individual industries including the pharmaceutical, tourist, transport and food distribution industry. Full article

Globalization has led to a significant effect on today’s manufacturing sector. Manufacturers need to find new and innovative ways to increase efficiency and reduce waste in the manufacturing supply chain. Lean/six sigma tools can help companies increase production efficiency and stay in competition. Manufacturing in smaller batches can keep the supply chain lean and customizable. This leads to frequent changeovers and downtime. A changeover is usually required when a single machine produces different products based on the requirement. A large-scale industry can either install multiple individual production lines to cater to the demand (usually expensive) or make frequent machinery changes. Single Minute Exchange Die (SMED) is a system designed for reducing the changeover time for machines. It reduces the time taken to complete the activities and eliminates non-essential activities throughout the changeover. Scheduling an operating procedure within SMED in such case is a challenge. Project scheduling model with workforce constraints can be used to create a set of heuristics to provide us with an optimized list of tasks. The paper proposes to design a scheduling heuristic model to allocate tasks to the operators to get the least amount of operator idle time and reduce changeover downtime costs. The paper further illustrates the benefit of the model in a case study and proposes its integration within the existing SMED methodology. This results in a benefit-to-cost ratio of 7.5% for production scheduling compared to that of stages 4 and 5 in SMED, which is 1.2%. Full article

This paper is concerned with demand planning for internal supply chains consisting of workstations, production facilities, warehouses, and transportation links. We address the issue of how to help a supplier firmly accept orders and subsequently plan to fulfill demand. We first formulate a linear aggregate planning model for demand management that incorporates elements of order promising, recipe run constraints, and capacity limitations. Using several scenarios, we discuss the use of the model in demand planning and capacity planning to help a supplier firmly respond to requests for quotations. We extend the model to incorporate congestion effects at assembly and blending nodes using clearing functions; the resulting model is nonlinear. We develop and test two algorithms to solve the nonlinear model: one based on inner approximation and the other on outer approximation. Full article

Food Logistics 4.0 is a term derived from Industry 4.0 focusing on all the aspects of food logistics management based on cyber-physical systems. It states that real-time information and the interconnectivity of things, supplemented with novel technologies will revolutionise and improve the way food logistics is carried out. It has tremendous potential in terms of bringing transparency, swift delivery of food at reduced cost, flexibility, and capability to deliver the right quality product at the right place and at the right time. This paper discusses the vital technologies within Food Logistics 4.0 and the opportunities and challenges in this regard. It focuses primarily on food logistics, including resource planning, warehouse management, transportation management, predictive maintenance, and data security. Internet of Things, Blockchain, Robotics and Automation and artificial intelligence are some of the technologies discussed. Full article

The calculation of lashing forces on containerships is one of the most important aspects in terms of cargo safety, as well as slot utilization, especially for large containerships such as more than 10,000 TEU (Twenty-foot Equivalent Unit). It is a challenge for stowage planners when large containerships are in the last port of region because mostly the ship is full and the stacks on deck are very high. However, the lashing force calculation is highly dependent on the Classification society (Class) where the ship is certified; its formula is not published and it is different per each Class (e.g., Lloyd, DNVGL, ABS, BV, and so on). Therefore, the lashing result calculation can only be verified by the Class certified by the Onboard Stability Program (OSP). To ensure that the lashing result is compiled in the stowage plan submitted, stowage planners in office must rely on the same copy of OSP. This study introduces the model to extract the features and to predict the lashing forces with machine learning without explicit calculation of lashing force. The multimodal deep learning with the ANN, CNN and RNN, and AutoML approach is proposed for the machine learning model. The trained model is able to predict the lashing force result and its result is close to the result from its Class. Full article