Supply Chain Cost Research Articles

Digital Transformation Management of Supply Chain Firms Based on Big Data from DeFi Social Media Profiles

Emerging technologies in the digital context can favor industrial sector firms in their aim to improve their performance. Digitalization is mainly expressed through the utilization of big data that originate from various sources. Blockchain technology has led to the extended adoption of capitalization of Decentralized Finance (DeFi) services, such as cryptocurrency trade platforms. Supply chain firms, in their quest to exploit any means and collaborations available to promote their services, could place advertisements on DeFi’s social media profiles to boost their financial performance. Social media analytics, as a part of the big data family, are an emerging tool for promoting a firm’s digital transformation, based on the plethora of customer behavioral data they provide. This study aims to examine whether the social media analytics of DeFi platforms are capable of affecting their website visibility, as well as the financial performance of supply chain firms. To do so, the authors collected data from the social media profiles of the most-known DeFi platforms and web analytics from the most significant supply chain firms’ websites. For this purpose, proper statistical analysis, Fuzzy Cognitive Mapping, Hybrid Modeling, and Cognitive Neuromarketing models were adopted. Throughout the present research, it has been discerned that from an increase in the social media analytics of DeFi platforms, their website visibility increases, while the organic and paid traffic costs of supply chain firms decrease. Supply chain firms’ website customers tend to increase at the same time.

Robust Optimization Model for Sustainable Supply Chain Design Integrating LCA

Supply chain management is the basis for the operations in an organization. The development of realistic supply chain designs that work effectively in the presence of disturbances in a stochastic environment and incorporate sustainability factors, is a complex challenge being investigated in recent years. However, the inclusion of a methodological structured framework to evaluate environmental impacts constitutes a knowledge gap in the literature on supply chain design. This study developed a model for sustainable supply chain design, integrating Life Cycle Assessment and based on a robust optimization approach. The study follows a 4-stage methodology beginning with data collection and the execution of a Life Cycle Assessment. Then, the deterministic modeling is proposed, concluding with a robust model. A bi-objective model is proposed to maximize utility and minimize environmental impact based on demand scenarios. The model was validated with real data from a medium-sized enterprise that produces antibacterial gel, generating as a result, different configuration alternatives for the supply chain to transport the products and raw materials between its elements. The conclusions of this work highlight the importance of including sustainability factors during supply chain design, the consequences and costs of its inclusion, as well as the priority actions that promote sustainable designs.

Research on the Supply Chain Strategy of Freshippo in the Context of Epidemic

Since the end of 2019, the outbreak of COVID-19 has had a severe impact on the economy and peoples lives. In this paper, Freshippo was selected as the research object to discuss the problems and optimization strategies of its supply chain in the context of the epidemic, to provide reference for supply chain management of fresh food e-commerce enterprises. The research methods used in this paper are literature review and field research. The epidemic has brought historic opportunities to the whole fresh food e-commerce industry represented by Freshippo, but also put forward higher requirements for the efficiency and flexibility of the supply chain. The fresh food e-commerce industry should optimize supply chain management for improving response efficiency and coping with epidemic risk, improve emergency support capacity, ensure freshness of goods and reduce wastage, and share supply chain costs.

Analysis of variables influencing the cost of wood freight: the case of southeastern Brazil

ABSTRACT This study aimed to analyze the variables that influence freight cost in the forest supply chain and to fit nonlinear regression models to estimate the freight cost of wood transportation from the production areas to the processing units. The data used for cost analysis considered the following variables: volume of wood (m3); average fuel consumption (km/l) and average speed of the complete journey (km/h) per round trip. The results showed that there is a strong positive correlation between the variables transport distance and the freight cost of the wood, as well as between the moisture content of the wood and the freight cost of the wood. The load capacity of the vehicle combinations showed a mean negative correlation with the freight cost of the wood, and the length of the wood did not show a correlation with the cost of the transported wood. The fitted models for estimating the value of wood freight showed a high degree of adjustment of the dependent variable, indicating a good capacity for extrapolating the results from these variables. Such results emphasize the importance of optimizing transport routes, controlling wood moisture, maximizing vehicle volumetric load capacity, and using cost forecast models in order to make correct and efficient decisions in the forest supply chain context.

Robust optimization and strategic analysis for agri-food supply chain under pandemic crisis: Case study from an emerging economy

Pandemic crises like the coronavirus disease 2019 (COVID-19) have severely influenced companies working in the Agri-food industry in different countries. Some companies could overcome this crisis by their elite managers, while many experienced massive financial losses due to a lack of the appropriate strategic planning. On the other hand, governments sought to provide food security to the people during the pandemic crisis, putting extreme pressure on companies operating in this field. Therefore, the aim of this study is to develop a model of the canned food supply chain under uncertain conditions in order to analyze it strategically during the COVID-19 pandemic. The problem uncertainty is addressed using robust optimization, and also the necessity of using a robust optimization approach compared to the nominal approach to the problem is indicated. Finally, to face the COVID-19 pandemic, after determining the strategies for the canned food supply chain, by solving a multi-criteria decision-making (MCDM) problem, the best strategy is specified considering the criteria of the company under study and its equivalent values are presented ​​as optimal values of a mathematical model of canned food supply chain network. The results demonstrated that "expanding the export of canned food to neighboring countries with economic justification" was the best strategy for the company under study during the COVID-19 pandemic. According to the quantitative results, implementing this strategy reduced by 8.03% supply chain costs and increased by 3.65% the human resources employed. Finally, the utilization of available vehicle capacity was 96%, and the utilization of available production throughput was 75.8% when using this strategy.

The Fourth Channel: Automatic Home Replenishment and Its Implications for Supply Chain Cost and Customer Convenience

Stanley Lim and David Pyke present recent developments in grocery shopping and delivery models and explore subscription and automatic replenishment services. They introduce a model for auto replenishment that could give customers what they are looking for without bringing unsustainable costs to the supply chain.

Research on carbon footprint measurement and emissions reduction optimization of the beer supply chain in China.

The carbon emissions of the beer industry have always been a concern. To reduce environmental pollution, this paper systematically calculates the carbon emissions of the beer supply chain and studies the optimization of carbon emissions reduction through scenario simulation. In this study, the boundary of the beer supply chain carbon emissions system is constructed. The scenario simulation and simulation analysis are carried out based on five factors: water recycling utilization rate, power generation mode, weight-volume ratio, recovery ratio, and transportation mode. To obtain the optimal scheme of economic cost and emissions reduction, the cost of the beer supply chain is analyzed under the condition of carbon trading. The results show that the proportion of carbon emissions in each link of the beer supply chain is production, packaging, transportation, and storage, which are 59.58%, 22.27%, 17.67%, and 0.5%, respectively. The improvement of the water recycling utilization rate of manufacturing enterprises can reduce the overall carbon emissions of the supply chain, and the effect is obvious. The highest proportion of carbon emissions in the packaging link is the bottle consumption stage (22.43%). Raw materials transportation accounts for the highest proportion of total carbon emissions in transportation (63.73%). The waterway/railway ratio will be increased to 0.6/0.4, and the carbon emissions in the supply chain will be reduced by 5.7%. In the context of carbon trading, when the carbon trading price is higher than 49.16 yuan/ton, enterprises can achieve a win-win situation in reducing emissions and maintaining positive economic growth by the measures given in the paper.

Progress Towards the Development and Understanding of Energy Dense Rechargeable Batteries Utilizing Zn and Cu

Batteries are easy to use, remotely monitorable, not fuel dependent, easily permitted and installed, and start automatically and reliably during an electrical outage. This makes them optimal for stationary storage and power assurance applications. Within battery-based grid storage, as of mid-2017, lithium-ion, sodium-ion, and lead-acid systems are the leaders, comprising 59% (~1.1 GW), 8% (0.15 GW), and 3% (0.06 GW) of global operational electrochemical storage, respectively.However, these batteries suffer from low energy density, high cost, poor safety, environmental concerns, and/or cycle life. Existing battery options on the market also do not meet the required market needs for long-duration backup power. For example, lead-acid batteries require too much space, are heavy, and contain toxic materials. Lithium-ion batteries, while compact and capable of excellent cycle life, are too expensive to serve long outages and have notable flammability and environmental risks.Alkaline Zn batteries are a strong candidate for electrical grid storage applications due to Zn’s high capacity (820 mAh/g), established materials supply chain and low cost. To realize the highest energy dense batteries, Zn needs to be coupled with a similarly low cost, abundant and high-capacity cathode. CuO (674 mAh/g) is an intriguing high-capacity cathode when paired with Zn in alkaline electrolyte, a battery that until recently has been relegated to the history books as a primary system. In 2021 Schorr et al. reported a rechargeable Zn/CuO battery that utilized a Bi additive to help facilitate the electrochemical reversibility of the Cu conversion electrode. Bi2O3, a species with comparable redox potentials to Cu2O, promoted reversibility and minimized passivation in the historically non-reversible system. The battery cycled without any observable Cu and Bi mixed oxide phases, cycling between metallic Cu and Bi and Cu2O/Cu(OH)2 and Bi2O3, respectively. Although the Bi additive did not eliminate capacity fade completely, limiting the cells to a 30% depth of discharge (relative to CuO) enabled 250 cycles at > 124 Wh/L. Alternatively, compensating for capacity loss with additional Cu metal provided for very high areal capacities (∼40 mA h/cm2) and energy densities (∼260 W h/L), despite only 65% active material cathode loadings and ∼10% Zn anode utilization; preliminary tests indicated these batteries were prone to shorting.Seeking to improve performance and minimize the spatial segregation of Cu- and Bi-phases observed upon cycling in the prior system, D. Arnot et al. prepared nanoscale carbon coated (Cu/Bi) particles, where the coating partially minimized dissolution and diffusion of soluble cuprate and bismuthate complexes, where ~ 200 cycles at 300 mAh/g was demonstrated (@ ~ 100 Wh/L). CuBi2O4 and CuO phases were formed upon oxidation, indicating carbon coatings can affect the battery cycling mechanism and may have future roles increasing performance. Data collected from a variety of experimental techniques, including cyclic voltammetry, rotating ring-disk electrode voltammetry, electrochemical impedance spectroscopy, electron microscopy, transmission electron microscopy, Raman spectroscopy, operando energy-dispersive X-ray diffraction measurements, battery cycling along with recent DFT modeling will be presented to help elucidate the role of additives, carbon coatings, and ion selective polymers in enabling reversible Zn/Cu based batteries. In addition, the general challenges of achieving a highly reversible energy dense battery based on two conversion electrodes operating in highly alkaline environment will be discussed.The goal is to demonstrate a Zn/CuO battery with long lifetime, at appreciable energy densities (> 200 Wh/L), with excellent safety, lower toxicity and sufficiently low cost to be manufactured and installed on the grid. While the laboratory scale Zn/CuO battery builds have very promising characteristics to date they have not been optimized or adapted for consumer or market-based needs in terms of power performance, energy density, cycle life or stability in terms of shelf life and the ability to tolerate partial state of charge. Progress towards these goals may also be discussed.N. B. Schorr et al. Rechargeable Alkaline Zinc/Copper Oxide Batteries. ACS Applied Energy Mater. 2021, 4, 7, 7073–7082. https://doi.org/10.1021/acsaem.1c01133.D. J. Arnot et al. Rechargeable Alkaline Zn-Cu Batteries Enabled by Carbon Coated Cu/Bi Particles. J. Power Sources 2022, 529, 231168. https://doi.org/10.1016/j.jpowsour.2022.231168.This work was supported by the U.S. Department of Energy, Office of Electricity, and the Laboratory Directed Research and Development program at Sandia National Laboratories. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

Blockchain-enabled supply chain coordination for off-site construction using Bayesian theory for plan reliability

The potential of blockchain is being widely explored within the construction industry, particularly for transparent communication and information sharing. However, only limited research has focused on implementing blockchain to address the challenge of aligning conflicting interests among independent agents, specifically, supply chain coordination. This paper develops a blockchain-enabled supply chain coordination system that facilitates the alignment of diverse decisions made by stakeholders in an off-site construction supply chain. To achieve this goal, Bayesian updating is employed to estimate the probabilistic distribution of plan reliability, enabling the calculation of a supplier rebate that incentivizes the contractor to schedule deliveries aimed at minimizing joint supply chain costs. Additionally, the paper describes a blockchain-enabled system that allows practitioners to measure plan reliability. The research findings demonstrate that the blockchain-enabled supply chain coordination system fosters shared common knowledge among project stakeholders and facilitates real-time updates of changes in the contractor's plan reliability, aligning the interests of both the supplier and contractor.

Dynamic supply chain risk management plans for mitigating the impacts of the COVID-19 pandemic

COVID-19 pandemic prompted supply chain (SC) disruptions and heightened demand for crucial items like facemasks and ventilators. Lockdowns and border closures hindered raw material supply and manufacturing capacity expansion. Consequently, manufacturers faced challenges in inventory, transport, and delivery, resulting in higher shortage costs, elevated SC expenses, and reduced SC efficacy. Using an integrated agent-based model (ABM) and optimisation, this paper examines COVID-19's multifaceted impacts on facemask SCs. It assesses four primary resilience strategies: enhancing manufacturing capacity, improving raw material supply, increasing transportation and distribution facilities, and maintaining dynamic inventory policy. Moreover, the model tested the proposed strategies under different scenarios by optimising the inventory policy and transportation strategies, leading to improved facemask production and delivery during extreme events. Our study found that increased production capacity through an optimal inventory and transportation strategy for a long period reduced the multiple impacts of the pandemic on facemask SCs, resulting in diminished total SC costs and increased consumer access to finished products. Based on demand forecasts, maintaining dynamically optimal reordering points and order up to levels can help maximise raw material supply and inventory levels, thereby minimising risks. Using these findings, future risks related to outbreaks and pandemics can be more effectively planned.

A Stochastically Optimized Two-Echelon Supply Chain Model: An Entropy Approach for Operational Risk Assessment.

Minimizing a company's operational risk by optimizing the performance of the manufacturing and distribution supply chain is a complex task that involves multiple elements, each with their own supply line constraints. Traditional approaches to optimization often assume determinism as the underlying principle. However, this paper, adopting an entropy approach, emphasizes the significance of subjective and objective uncertainty in achieving optimized decisions by incorporating stochastic fluctuations into the supply chain structure. Stochasticity, representing randomness, quantifies the level of uncertainty or risk involved. In this study, we focus on a processing production plant as a model for a chain of operations and supply chain actions. We consider the stochastically varying production and transportation costs from the site to the plant, as well as from the plant to the customer base. Through stochastic optimization, we demonstrate that the plant producer can benefit from improved financial outcomes by setting higher sale prices while simultaneously lowering optimized production costs. This can be accomplished by selectively choosing producers whose production cost probability density function follows a Pareto distribution. Notably, a lower Pareto exponent yields better supply chain cost optimization predictions. Alternatively, a Gaussian stochastic fluctuation may be proposed as a more suitable choice when trading off optimization and simplicity. Although this may result in slightly less optimal performance, it offers advantages in terms of ease of implementation and computational efficiency.

Rotavirus vaccine product switch in Ghana: An assessment of service delivery costs, switching costs, and cost-effectiveness.

Ghana introduced rotavirus vaccine (ROTARIX 1-dose presentation) into the routine national immunization program in 2012 and switched to a different product (ROTAVAC 5-dose presentation) in 2020. ROTAVAC has a lower price per dose (US$0.85 versus US$2.15 for ROTARIX) and smaller cold chain footprint but requires more doses per regimen (three versus two). This study estimates the supply chain and service delivery costs associated with each product, the costs involved in switching products, and compares the cost-effectiveness of both products over the next ten years. We estimated the supply chain and service delivery costs associated with ROTARIX and ROTAVAC (evaluating both the 5-dose and 10-dose presentations) using primary data collected from health facilities in six of the 14 regions in the country. We estimated the costs of switching from ROTARIX to ROTAVAC using information collected from key informant interviews and financial records provided by the government. All costs were reported in 2020 US$. We used the UNIVAC decision-support model to evaluate the cost-effectiveness (US$ per disability-adjusted life-year (DALY) averted from government and societal perspectives) of ROTARIX and ROTAVAC (5-dose or 10-dose presentations) compared to no vaccination, and to each other, over a ten-year period (2020 to 2029). We ran probabilistic sensitivity analyses and other threshold analyses. The supply chain and service delivery economic cost per dose was $2.40 for ROTARIX, $1.81 for ROTAVAC 5-dose, and $1.76 for ROTAVAC 10-dose. The financial and economic cost of switching from ROTARIX to ROTAVAC 5-dose was $453,070 and $883,626, respectively. Compared to no vaccination, the cost per DALY averted was $360 for ROTARIX, $298 for ROTAVAC 5-dose, and $273 for ROTAVAC 10-dose. ROTAVAC 10-dose was the most cost-effective option and would be cost-effective at willingness-to-pay thresholds exceeding 0.12 times the national GDP per capita ($2,206 in the year 2020). The switch from ROTARIX to ROTAVAC 5-dose in 2020 was cost-saving. Rotavirus vaccination is highly cost-effective in Ghana. A switch from ROTAVAC 5-dose to ROTAVAC 10-dose would be cost-saving and should be considered.

Telangana Kanti Velugu 2023: Universal Access for Eye Screening and Provision of Quality Spectacles for Millions - A Case Study in Effective Supply Chain Management, Operations, and Cost Effectiveness by TSMSIDC & CHFW, DoHMFW, Govt. of Telangana India

Telangana Kanti Velugu 2023: Universal Access for Eye Screening and Provision of Quality Spectacles for Millions - A Case Study in Effective Supply Chain Management, Operations, and Cost Effectiveness by TSMSIDC & CHFW, DoHMFW, Govt. of Telangana India

The impact of adopting customization policy and sustainability for improving consumer service in a dual-channel retailing

In recent decades sustainability and dual-route retailing have been adopted by many big industries. Companies are now bound to maintain such strategies that fulfill the sustainable goals developed by the United Nations. Industries face a huge penalty if carbon emissions exceed a certain boundary. Moreover, factories should maintain sufficient flow in retail chains and product quality. This paper demonstrates 3-pillar sustainability in dual channel retailing, empowering firms to integrate the financial-economic pillar with the non-financial (environmental, social, and ethical) pillar. The core product is made available through the traditional channel and customized products are through online channels. The model is enabling the customers with customization provisions where they can influence the products. Thus, as a novel approach, the article incorporates a presumed threshold limit on the product's (standard and customized) selling price difference. Due to customization, a new product is developed which needs extensive quality checks. The study introduces an investment in checking the quality of the customized product which reduces the probability of customization defects exponentially. Additionally, current research adapts the carbon emission cost, penalties charged to a firm for overshooting the limit, and social costs in a smart supply chain. It also exemplifies that production is directly proportional to financial investments in meeting sustainability objectives. The numerical analysis reflects that as production increases, penalty costs decrease at a significant rate but after reaching optimal production penalty cost again starts to increase. It is observed that the downfall of penalty is 20% more for the single-channel than dual. Adaptation of the customization policy makes the retailing strategy more cost-effective. The model exemplifies that it is more economical to adopt dual-channel retailing compared to single-channel as there is approximately a 14.0625% reduction in total cost in dual-channel retailing. Moreover, an 80% improved quality is observed with a financial investment, which improves consumer satisfaction.

Supply chain preparedness: How operational settings, product and disaster characteristics affect humanitarian responses

Supply chains are dynamic and complex systems. This holds particularly true for humanitarian supply chains that operate under strong uncertainty. In view of an ever‐growing gap of unmet humanitarian needs, it is essential to gain a better understanding of the behavior of humanitarian supply chain systems. Despite a growing academic output in this field, there is a lack of empirical studies that take an integrated view on humanitarian supply chains and support decision makers with fact‐based evidence. Based on four extensive case studies and existing literature, we developed a system dynamics model that reflects the operational reality of humanitarian organizations in form of their centralized, hybrid and decentralized settings. The model provides a holistic supply chain view and measures the operational performance with regard to response cost, delivery lead time and impact on the local economy. Furthermore, we studied the impact of preparedness investments to enhance operational performance in the supply chain and deliver more humanitarian assistance with the limited resources available. Finally, we used our model to analyze the impact of major shocks such as the COVID‐19 pandemic to assess the vulnerability of humanitarian supply chains. The results indicate that operational settings, product and disaster characteristics have a major influence on the supply chain performance both in the noninvestment case as well as in the case where preparedness investments have been made. Specifically, for low‐value items, we find that decentralized settings have the lowest supply chain costs while for high‐value items the price difference between local and international procurement determines which setting is the most cost‐effective one. The preferability of the supply chain setting strongly depends on the indicator chosen. Hence, ultimately, the findings emphasize the need to apply appropriate indicators and identify their trade‐offs to comprehensively analyze the performance of humanitarian supply chain settings. The newly introduced Humanitarian Return‐on‐Investment concept can play an important role in this context.

Supply chain concentration and cost of capital

AbstractThis study examines the impact of supply chain concentration on a firm's financing costs. We show purchasing firms with multiple supplier relationships are subject to higher information asymmetry and cost of equity. This effect is more pronounced when the supplier's financial performance deteriorates. We also find that lower supply chain concentration increases a firm's cost of debt. We believe that the purchaser's supply chain represents a source of material private information and that investors require a higher rate of return as compensation for increased information asymmetry. Our results are robust to combining the suppliers producing similar output and endogeneity issues.

Sustainable Performance Assessment towards Sustainable Consumption and Production: Evidence from the Indian Dairy Industry

The current global economic status quo is widely seen as unsustainable in the food sector. The field of sustainability science is still rather fragmented, covering a wide range of techniques and issues, despite the large number of publications in this area. Due to population growth, the food supply chain (FSC) and farmers have to produce more food. The UN estimates that one-third of edible food is wasted, producing greenhouse gases. A balance must be struck between company operations and social, environmental, and economic activities for sustainable development of the FSC. To assist FSC organizations in managing sustainable advancement, this study created a methodology for the assessment of sustainable performance. We provide a sustainable assessment system using a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS. Our research framework evaluated the sustainability of three cooperative-society-run Indian dairy firms. Our study gives environmental criteria the highest weight (0.33) and social criteria the lowest (0.16), with economic reasons (0.306) and business operations (0.204) falling in the middle. Supply chain costs, on average, are given the highest weight, and capacity utilization, the lowest weight. Three dairy industries are ranked (DPI3, DPI1, and DPI2) based on sustainable performance. By modifying the maximum set utility value and validating VIKOR results with TOPSIS, we have checked the robustness of this performance assessment tool. This research aids dairy businesses in achieving several Sustainable Development Goals, including sustainable production and consumption, through the regular assessment of their sustainable performance.

A robust vaccine supply chain model in pandemics: Case of Covid-19 in Iran

Healthcare supply chains face a couple of challenges in keeping vaccines safe from the phase of production to the injection. Therefore, it is necessary to create a robust vaccine supply network composed of people and suitable equipments in every place that helps deliver the vaccine safely and effectively to the consumer. The main contribution of this research, comparing the existing literature, is to propose a three-objective optimization model for the robust vaccine supply chain network to allocate mobile and fixed vaccine injection centers. The first objective function minimizes the costs of the entire supply chain, the second objective maximizes the selected routes' reliability, and the third objective minimizes the unmet demand. The vaccine supply chain network considered in this research includes several levels: vaccine injection centers, vaccine suppliers, vaccine storage centers, distributors, and vehicles. The results obtained from solving the model optimized the allocation of the mobile and the fixed vaccine injection centers to the areas of a big city (Tehran). That means the costs are minimized, and maximum reliability is achieved. In addition, according to the results, it can be seen that the robust probability model is much more stable than the fuzzy probability model and is more robust than the changes in uncertain parameters.

RESILIENCE OF FRANCHISE SYSTEMS IN THE UNITED STATES AND POLAND TO SHOCKS ON THE EXAMPLE OF THE COVID-19 PERIOD

The article deals with the issue of franchise as a distribution system. Participation in such systems brings many benefits, both for franchisors and franchisees. Still, the uneven bargaining power of the parties is significant, and effective actions require mutual trust and a certain autonomy of the parties. The work aims to determine how franchise systems reacted to the crisis caused by, among others, COVID-19 and whether food industry systems were characterized by higher resistance to shocks. The assessment was made based on data from the USA and Poland on the franchise according to the International Franchise Association and Profit System Sp. z o.o. for the years 2007-2021, and subject to availability for a longer period. It found that the franchise sector shrank by around 10% during the pandemic, but after two years, the level of turnover and employment returned to pre-crisis levels. In the USA, food distribution and restaurant systems were more resilient to the lockdown crisis and quickly recovered to their previous turnover and employment levels. In Poland, the gastronomy brand industries accounted for as much as 35% of the systems, and grocery and industrial stores accounted for another 29%. The franchise industry turned out to be resistant to crises, and the high share of food distribution indicates that franchise systems are an effective solution in the food trade, mainly due to an efficiently organized supply chain and lower distribution costs.

The hydrogen storage challenge: Does storage method and size affect the cost and operational flexibility of hydrogen supply chains?

Hydrogen is seen as a key energy vector in future energy systems due to its ability to be stored in large volumes for long periods, providing energy flexibility and security. Despite the importance of storage in hydrogen's potential role in a zero-carbon energy system, many techno-economic analyses fail to adequately model different storage methods in hydrogen supply chains, often ignoring storage requirements altogether. Therefore, this paper uses a data-driven techno-economic analysis (TEA) tool to examine the effect of storage size and cost on three different 2030 hydrogen supply chain scenarios: wind-based, solar-based, and mixed-source grid electrolysis. For varying storage sizes and specific capital costs, the overall levelised cost of hydrogen (LCOH), including production, storage, and delivery to a constant demand, varies significantly. The LCOH ranges from €3.90–12.40/kgH2, €5.50–12.75/kgH2, and €2.80–15.65/kgH2 for the wind-based, solar-based, and mixed-source grid scenarios respectively, with lower values for scenarios with low-cost storage. This highlights the critical role of low-cost hydrogen storage in realising the energy flexibility and security electrolytic hydrogen can provide.