Important Cost Research Articles

A Life Cycle Cost Analysis—Relevant Method Supporting the Decision to Establish an Apple Orchard in an Organic System

The life-cycle cost analysis is a method used to assess long-term economic efficiency among equivalent competing processes or products. The purpose of this paper is to investigate the nature and level of costs for an organic orchard located in Southern Romania, using a complex approach covering the entire chain of production, through its life span. The research results, based on a dynamic analysis and an integrated evaluation of the orchard’s performance, were ranked on investment and operational costs and broken down into three categories (establishment, production, post-harvest, transport costs). The highest costs, representing 151,726 EUR/ha/20 years, about 52.72% of the total operational costs and 50.4% of the total farm costs/ha/20 years, were recorded in the exploitation stage. The scenarios for the sensitivity analysis considered different levels of average yields (40 and 60 tons/ha, respectively) with different rates of sold productions (85%, optimistic scenario; 70%, pessimistic scenario). The hot points identified at the production stage were the use of agricultural machinery, several pesticides, the costs of seedlings, anti-hail nets, plastic boxes, and labor costs, while at the post-harvest stage, there were those related to labor and energy consumption. The transport stage had important costs with respect to tractor operations and the track.

Large-scale integration of renewable energies by 2050 through demand prediction with ANFIS, Ecuador case study

The growing reliance on hydroelectric power and the risk of future droughts pose significant challenges for power systems, especially in developing countries. To address these challenges, comprehensive long-term energy planning is essential. This paper proposes an optimized electrical system for 2050, using Ecuador as a case study. For forecasting electricity demand, a Neuro-Fuzzy Adaptive Inference System is employed, utilizing real historical data. Subsequently, the EnergyPlan software constructs a long-term energy consumption model, exploring three scenarios based on Ecuador's energy potential. The first scenario represents a 'business as usual’ approach, mirroring the current trend in the Ecuadorian electricity system. In contrast to the second scenario, it encompasses a broader range of renewable sources, including offshore wind, pumped storage, biomass, and geothermal energy. The third scenario extends the second one by incorporating demand response systems, such as vehicle-to-grid and hydrogen-to-grid technologies. In terms of novelty, this study highlights the innovative use of the Neuro-Fuzzy Adaptive Inference System for demand forecasting, along with a comprehensive exploration of multiple scenarios to optimize the electrical system. Research findings indicate that the integration of these new renewable energy sources not only reduces electricity import costs but also ensures surplus electricity production. Consequently, it is anticipated that the 2050 electricity system will reduce its dependence on hydroelectric energy while adopting photovoltaic and wind energy with penetration rates of 65 %, 11.2 %, and 9 %, respectively. This transition will be facilitated by a pumped storage system with a 28 % penetration rate and enhanced connectivity with neighboring countries, enabling the seamless integration of electric and hydrogen vehicles.

The Role of Diffusion on Reservoir Performance in Underground Hydrogen Storage

Summary Underground hydrogen storage (UHS) has the potential to balance fluctuating sustainable energy generation and energy demand by offering large-scale seasonal energy storage. Depleted natural gas fields or underground gas storage fields are attractive for UHS as they might allow for cost-efficient hydrogen storage. The amount of cushion gas required and the purity of the backproduced hydrogen are important cost factors in UHS. This study focuses on the role of molecular diffusion within the reservoir during UHS. Although previous research has investigated various topics of UHS such as microbial activity, UHS operations, and gas mixing, the effects of diffusion within the reservoir have not been studied in detail. To evaluate the composition of the gas produced during UHS, numerical simulation was used here. The hydrogen recovery factor and methane-to-hydrogen production ratio for cases with and without diffusive mass flux were compared. A sensitivity analysis was carried out to identify important factors for UHS, including permeability contrast, vertical-to-horizontal permeability ratio, reservoir heterogeneity, binary diffusion coefficient, and pressure-dependent diffusion. Additionally, the effect of numerical dispersion on the results was evaluated. The simulations demonstrate that diffusion plays an important role in hydrogen storage in depleted gas reservoirs or underground gas storage fields. Ignoring molecular diffusion can lead to the overestimation of the hydrogen recovery factor by up to 9% during the first production cycle and underestimation of the onset of methane contamination by half of the back production cycle. For UHS operations, both the composition and amount of hydrogen are important to design facilities and determine the economics of UHS, and hence diffusion should be evaluated in UHS simulation studies.

A cost calculation model for urban delivery of parcels by river

Public and private actors in cities have embarked on a race to achieve net-zero carbon emissions. However, parcel delivery in urban areas is booming, especially due to e-commerce. This context necessitates the study of sustainable transportation use. Among the various city-center parcel delivery modes, delivery by river is largely understudied. This study proposes a cost calculation model for delivery by inland waterways. This model considers fixed and variable costs for pre-carriage, transshipment, and last-mile delivery using a two-echelon last-mile delivery network framework. The model is tested using a real-life French case study and worldwide academic investigation. The results show that load optimization is key for profitability and that the most important costs are personnel and investment costs.

Sustainable Production Insight Through LCA and LCC Analysis of Injection Overmolded Structural Electronics Manufactured through Roll-to-Roll Processes.

Printed electronics (PE) have provided new material and application opportunities for devices and systems as well as new manufacturing routes that all need to be considered for commercialization. This paper introduces a case study with universally relevant manufacturing processes and applications in the PE area, focusing on the Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) of the Personal Activity Monitor (PAM) device. In the study, the PAM device's most important costs and environmental impacts during the prototype pilot production and device use phases are identified and assessed. Additionally, the potential environmental impacts of post-consumption scenarios are considered. The LCA results indicate that the roll-to-roll (R2R) assembly of electronics and the R2R injection over-molding are generally the most prominent production process steps affecting the results. From the LCC perspective, the capitial expenditure (CAPEX) contributor is the R2R assembly pilot line, due to its high investment cost and long operating time compare to other production assets. The traditional electronic components are the major operating expenditures (OPEX), especially the microcontroller units (MCUs) and accelerometers, in contrast to the low impact from the printed electronics. There are several advantages to applying LCA and LCC since they provide explanations of the relationships between cost, environmental, design, and manufacturing characteristics.

Outbreak economic analysis of six imported hemorrhagic fevers following detection at 24 hours

Abstract A ten-language search found no economic analysis of symptomatic hemorrhagic fever importation for Crimean Congo (CCHF), Hantavirus (HV), Lassa (LV), Marburg (MARV), Middle East Respiratory Syndrome (MERS) or Nipah (NV) into the USA/EU/UK. This study used available literature to calculate the cost of importation of the six selected fevers with each outbreak detected at 24 hours. A PRISMA search of Pubmed and grey literature was undertaken to uncover respective R0, case fatality ratios, average hospital stay, time to death, frontline casualty frequency and contact histories. A simulated breakout, t24 intervention, Borel distribution contact model, with R0 determined infection (0-1.59) and death rate (CFR: 0.01-0.5) was formed. Treatment inc. plasma therapy, and PPE best prices were determined. ICU median operational costs were factored with contact tracing. Indirect admin costs, based on national mean values, frontline replacement, GNI per capita productivity losses through isolation (21 days as standard), hospitalisation and death were factored. Mean patient discharge ranged 4.4 - 28 days (CCHF to MERS). Time to death ranged 2 - 15 days (HV, NV). The number infected at t48 ranged 1 - 9.59 (CCHF/HV to MARV). Contacts ranged 27 - 169 (CCHF to MARV/NV/MERS). Direct costs of outbreak care, labour, and tracing ranged €424707 - €2850083.07 (CCHF - MARV). Indirect costs, attributed to administrative burdens ranged €5264 -€32800.02 (CCHF to MARV). Productivity losses, attributed separately to the isolated, treated, and dead totaled €2042613 - €26198606 (CCHF - MARV). The total outbreak cost ranged €2488512.78 - €29081489.72 (EU, CCHF - MARV). Significant direct, indirect and productivity costs were attributed to the importation of a single case of six hemorrhagic fevers when detected at t24. The significant societal cost of MARV in particular highlights the importance of continued hemorrhagic fever research and preparedness to healthcare systems in protecting future budgets. Key messages • The importation of hemorrhagic fevers has significant direct and indirect budgetary, and productivity, impacts. • Besides human cost, financial costs demand public health enhanced surveillance and response plans for hemorrhagic fever importation.

Revisiting India’s Export Potential: Modern Gravity Model Approach

The high contribution of India’s exports to its gross domestic product underscores the vulnerability of macroeconomic shocks like the COVID-19 in terms of losses in export revenues, increased cost of import and slowdown in growth. The scale of impact also depends on the degree of trade concentration, geographical expansion, export potential and strategic relationship of a country with its trading partners. This article aims to examine these factors using the modern gravity model approach. It also intends to analyse the export intensity and export potential of India with its 25 major trading partners. The results are estimated by using the Poisson pseudo-maximum likelihood method for the period 1991–2020. The results show that the exports between two nations are remarkably impacted by the trade cost and combined economic size. Furthermore, variables like population and islands are introduced in the extended gravity model, which positively impacts India’s exports. The direction of India’s exports witnessed a reversal in trend towards the traditional export destinations in 2020 compared to emerging countries from 2010 onwards. The export potential index also explains that India has the scope to enhance the export potential with developed nations as advocated by the Heckscher–Ohlin model. JEL Codes: F14, F49

Feasibility of green ammonia trading via pipelines and shipping: Cases of Europe, North Africa, and South America

Ammonia is a key chemical for the agriculture and chemical industries, and a potential future marine fuel. Potential growth in ammonia demand further highlights the importance of ammonia production defossilisation to comply with climate goals. Widely available renewable resources and declining costs of solar photovoltaics and wind power enable the production of green e-ammonia at many locations and potential exports to countries with less optimal resources and other restrictions. This paper aims to compare the cost of imported e-ammonia to Germany, Finland, and Spain from regions with excellent renewable resources, Morocco and Chile, to the cost of local production, and to quantify potential economic savings due to trading. Transportation costs are calculated in this study with techno-economic parameters reported in detail to assess their impact on final import costs, and to allow comparison of shipping costs to pipeline transmission costs over various distances. Pipeline imports from Morocco were found to be significantly higher in cost compared to imports by sea from Chile and Morocco or local production. Imports from Chile were found to be economically feasible for Germany and Finland, with import costs 10–33% lower than domestic e-ammonia production in 2030–2050. Imports to Spain may be attractive in 2030s, but, after 2040, local solar resources enable local e-ammonia production costs at the same or lower cost as imported e-ammonia. Ammonia trading in the future may depend on access to the sea. Other factors such as creation of jobs, additional revenues, and energy security concerns may also impact e-ammonia trade.

FORECASTING QUARTERLY RICE AND CORN PRODUCTION IN THE PHILIPPINES: A COMPARATIVE STUDY OF SEASONAL ARIMA AND HOLT-WINTERS MODELS

Rice and corn are essential crops for the Philippines, playing a critical role in the nation’s economy and food security. However, the agricultural sector faces challenges, including climate variability, land constraints, and the need for imports to meet growing demand. Accurate forecasting of rice and corn production is crucial for informed decision-making and resource allocation. This research applied Seasonal Autoregressive Integrated Moving Average (SARIMA) and Holt-Winters exponential smoothing models to forecast rice and corn production. The study used quarterly production data from 1987 to 2023 obtained from the Philippine Statistics Authority. The Holt-Winters model with additive seasonality outperformed the SARIMA model for both rice and corn production, achieving lower Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) values. The findings have significant implications for policymakers, agricultural stakeholders, and commodity traders, guiding them in making informed decisions regarding import requirements. The volatility of global food prices and exchange rates can significantly impact the cost of imports, putting a strain on the country’s financial resources. Accurate forecasting models are essential for ensuring food sufficiency and making informed decisions on the amount of imports required. By adopting the Holt-Winters model and continuously improving forecasting methodologies, the Philippines can enhance food sufficiency and promote rural economic growth. The study highlighted the importance of accurate forecasting models in ensuring stable and sufficient rice and corn supplies to meet the nation’s growing demands, contributing to sustainable agricultural development and food security. Continuous research in agricultural forecasting methodologies is necessary to address the challenges posed by evolving agricultural dynamics and further enhance predictive accuracy.

Game-theoretic analysis of the impact of crew overnight hotel cost on airlines’ fleet assignment and crew pairing

Crew costs account for a high proportion of the total operational costs of an airline. The cost of overnight stay for the crew at a hotel is an important additional cost. To address this problem, this study establishes an integrated model to depict the interaction between the fleet assignment problem and the crew pairing problem. Because this cost is largely determined by the price agreed by the agreement hotel group, we further present a Stackelberg price game model to capture the interdependence between the integrated fleet assignment and crew pairing of airlines and the price game among hotel groups that provide accommodation services for airlines. We combine the idle time re-allocation with a spatio-temporal graph convolutional network to ensure the robustness of crew pairing. The solvability of the model is improved using the Reformulation-Linearization Technique. To obtain the overall Nash equilibrium of the Stackelberg price game model, we design a heuristic algorithm based on a decomposition algorithm and a proximity search algorithm. A case study is made to demonstrate that our robust model is cost-saving for the airline.

Prevalence and cost of sickle cell disease in France: real-world analysis using data from the Echantillon Généraliste des Bénéficiaires.

Sickle cell disease (SCD) is a genetic disorder of the hemoglobin resulting in chronic anemia, hemolysis, and vaso-occlusions. Its treatment mostly relies on hydroxycarbamide, transfusions, and stem cell transplantation. This study aimed at describing the epidemiology and management of SCD in adolescent and adult patients in France. This was a retrospective study performed among SCD patients aged ≥12 years between 2016 and 2018 and controls. SCD patients were matched on a 1:3 ratio with a group of individuals with no diagnosis of SCD, referred as control group. The matching of SCD patients and controls was a direct matching based on age, sex, CMU-c status (which corresponds to free-of-charge complementary coverage for people with low resources) and geographical region of residence. SCD patients and their matched controls were followed-up for the same amount of time by adjusting controls' follow-up period to that of the associated patients. This study used claims data from the French representative 1/97th sample of health data system. The main outcomes were the patients' characteristics and treatments received, healthcare consumptions and related costs among SCD cases and controls. Between 2016 and 2018, 151 patients with ≥6 months of follow-up were identified out of the total population of 732,164 individuals. SCD prevalence extrapolated to the entire population [95% CI] was 19,502 [19,230, 19,778] in 2018. The median (Q1-Q3) age at inclusion date was 37.0 (25.0-48.0) years, with 69.5% of patients being female. The mean (SD) reimbursed cost over follow-up was €24,310 (89,167), mostly represented by hospitalization costs accounting for €21,156 (86,402). A switch in SCD management was observed with age, as younger patients presented more frequent hospitalizations and acute procedures, while older ones had more frequent medical visits and paramedical care. Mean (SD) annual costs were €25,680 (91,843) and vs. €3,227 (23,372) for patients and controls, respectively (p < 0.001), representing an extra cost of almost €150 million over the entire SCD population. This study highlighted the important costs related to SCD and the related medical need with treatment alternatives, which could be filled by the emergence of new therapies.

A novel deep learning-driven approach for predicting the pelvis soft-tissue deformations toward a real-time interactive childbirth simulation

Background and objectiveSoft-tissue dynamics plays an essential role in the mechanical functions of the human body. Numerical approaches using finite element modeling and mass-spring framework have been currently used to estimate the biological soft tissue dynamics. However, these approaches still have important computational cost due to the use of a mesh configuration in the formulation of the dynamic equilibrium equation and unstable convergence issue. MethodsWe present in this study a novel approach based on the deep learning framework to predict the deformation of soft-tissues. In particular, the Long Short-term Memory (LSTM) neural network and deep neural network (DNN) were used to deal with high-frequency oscillation signals. Different learning strategies (with and without data dimension reduction) were also applied. A simulation-based database was generated using our HyperMSM model for training and testing purposes. The application of the proposed approach on the childbirth simulation was addressed. ResultsUsing the root mean square error, the LSTM- and DNN-derived deformation deviation range from 0.139 mm to 1.062 mm (0.266%–2.028%) for both training and testing processes. The Pearson correlation coefficient of 0.994–0.999 demonstrates the strong similarity between predicted outputs and ground truth data. ConclusionsThis present work showed the capacity of the deep learning neural networks to predict complex physiological signals of the human body functions. As a perspective, this approach will be coupled with the Hololens device toward a novel interactive childbirth training tool with real-time feedback on the soft tissue deformations.

Guidelines for Inventory Cost Reduction in Finished Goods for Competitive Advantage

Inventory cost is an important cost included in the total cost of logistics in Thailand, which tends to increase continuously, whereas entrepreneurs still encountered difficulty in draining existing inventory into the market thus affecting their performance in inventory management. The purpose of this study was to investigate inventory management and define guidelines to reduce inventory costs in finished goods to create competitive advantages in the industrial business sector. The finding, then, was used to develop a structural equation model. This study was conducted both qualitatively and quantitatively. Questionnaires were used to interview 500 executives of industrial business organizations. Descriptive, referential, and multiple statistics were employed to analyze the data. The study revealed that 4 major guideline areas for reducing inventory costs for the finished goods were found, prioritized as follows: data insight (X̅ = 4.33), alliance-centric (X̅ = 4.22), resource management (X̅ = 4.22), and innovation technology (X̅ = 4.19). As for the hypothesis test, it was found that small and medium-sized businesses, and large businesses differently prioritized guidelines to reduce inventory costs in the finished goods at the statistical significance level of 0.05. The analysis of the developed structural equation model revealed that the evaluation criteria were consistent with the empirical data with its Chi-square Probability, the Relative Chi-square, Goodness of Fit Index, and the Root Mean Square Error of Approximation of 0.055, 1.172, 0.959, and 0.019, respectively.

Rabies post-exposure prophylaxis delivery to ensure treatment efficacy and increase compliance

ObjectivesSince rabies is lethal once symptoms appear, its prevention including community awareness, mass dog vaccination and post-exposure prophylaxis (PEP) is crucial. Although safe and potent rabies vaccines have long been available, the global rabies burden is still high and access to adequately-delivered PEP remains challenging. Here we offer healthcare providers up-to-date, simple, exhaustive, visual guidance on how to perform PEP steps correctly. ProtocolPEP consists of 1) washing the wound with water and soap for 15 min, 2) assessing the need for rabies biologicals based on specific criteria; 3) administering, if required, rabies immunoglobulin or monoclonal antibodies deep in and around all wounds; 4) starting, if necessary, the WHO-recommended intradermal 1-week vaccination regimen; 5) informing patients adequately throughout the PEP process to increase compliance and avoid dangerous misconceptions about animal bite treatment and rabies risk. DiscussionThe intradermal 1-week vaccination regimen recommended by WHO is as safe as other regimens but carries important cost-, dose- and time-sparing benefits. As fundamental as the correct administration of rabies biologicals is clear doctor-patient communication and sharing of up-to-date knowledge among healthcare professionals. ConclusionsThis resource will help ensuring that no life is lost to rabies, an incurable yet preventable disease.

Quantitative techno-economic comparison of a photovoltaic/wind hybrid power system with different energy storage technologies for electrification of three remote areas in Cameroon using Cuckoo search algorithm

This research work presents a techno-economic comparisons and optimal design of a photovoltaic/wind hybrid systems with different energy storage technologies for rural electrification of three different locations in Cameroon. The determination of the optimal, cost-effective, and reliable configuration is performed for the locations of Fotokol, Figuil and Idabato which describe the weather conditions diversity in Cameroon with different solar and wind energy potentials. The sizing-optimisation problem is founded on real data of wind speed and solar radiation, with the principal goal of minimizing the hybrid system net present cost (NPC) while taking into consideration the load deficit probability (LDP) as the reliability constraint. The cuckoo search algorithm with a high convergence rate is utilised to find the optimal combination of the hybrid system with the lowest cost of energy (COE) and NPC which satisfies the LDP of the considered locations. At each location, six different configurations namely photovoltaic/wind/battery, photovoltaic/battery, wind/battery, photovoltaic/wind/fuel-cell, photovoltaic/fuel-cell and wind/fuel-cell are optimised and compared in view of satisfying the heavy, medium and small activities electrical loads demand of non-domestic subscribers. The optimal configuration is obtained for each activity and location in connection with the minimum cost and best reliability. The results revealed that the optimal, cost-effective, and reliable configuration for all activities and locations is a battery-based photovoltaic/wind hybrid system. The results showed that integration of 20 photovoltaic arrays, 1 wind turbine and 27 batteries with LDP value of 0.0486 is the most appropriate configuration which leads to the lowest NPC and COE of 23,024$ and 0.1570 $/kWh, respectively for satisfying the heavy activity load demand at Fotokol. The best hybrid system configuration needed for covering loads demand for medium and small activities at Fotokol were found to be 8 photovoltaic arrays, 1 wind turbine and 19 batteries with LDP, NPC and COE values of 0.0497, 16,640$ and 0.1942 $/kWh, respectively for medium activity; and 5 photovoltaic arrays, 1 wind turbine and 10 batteries with NPC, COE and LDP values of 12,860$, 0.2120 $/kWh and 0.0494, respectively for small activity. The optimisations studies performed at the site of Figuil considering the heavy activity load demand revealed that the cost-effective configuration which leads to the minimum NPC and COE of 28,400$ and 0.1937 $/kWh, respectively consists of 26 photovoltaic panels, 1 wind turbine and 38 batteries with the LDP equal to 0.0499. The obtained results also indicated that substituting the battery banks with a chemical storage which consist of a combination of an electrolyser, hydrogen reservoir and fuel cell is possible, though the cost increases because of the important investment cost of the system constituents. Integrating photovoltaic/wind/fuel-cell at the site of Idabato gives the lowest NPC and COE values of 48,864$ and 0.8056 $/kWh, respectively with a LDP of 0.0491. The optimum sizing of this configuration has 9 photovoltaic arrays, 1 wind turbine and 15 hydrogen tanks.

Impacto del Ajuste de valor aduanero en el costo de importación de la empresa GRUPO NESBUSI SAC

In recent years, imports into Peru have been subject to regular value adjustment notifications according to the portal of the National Superintendence of Customs and Tax Administration (SUNAT). This has generated the need to understand the reason and the impact of these customs adjustments on import costs, especially in determining the cost of import projects. The present research looks to determine the impact of the customs value adjustment on the import costs of the company Grupo Nesbusi S.A.C. during the year 2021. A quantitative approach was used, with a non-experimental cross-sectional design and a descriptive level. A quantitative approach was used, with a non-experimental cross-sectional design anda descriptive level. The sample consisted of import documents related to DUA 013498 - 2021, which represents the condition of "customs value adjustment". These documents included notices of reasonable doubt, commercial invoices, notice of arrival, and other documents related to the transaction. The results revealed that the customs value adjustment had a negative impact on the import costs of the company Grupo Nesbusi S.A.C. in 2021, with an increase of 3.32% in indirect costs. It was concluded that the nature of the customs value adjustment was mainly due to the difference between the declared price and the price indicators registered in the SUNAT price verification system, and not to errors on the part of the importer. This negative impact was reflected in the indirect import costs of the company Grupo Nesbusi S.A.C. during the year 2021, including additional logistics expenses and an increase of 11.57% in paying taxes.

Dinamik yüklerin etkisi altında abrasiv aşınma gösteren bekoloder kova tırnaklarının çalışma ömürlerinin belirlenmesi

Especially in developing countries, the rise of infrastructure works increases the demand for heavy machines. Backhoe loaders: These are small tonnage work machines consisting of a bucket group at the front and a bucket set at the back, which are used in many areas such as infrastructure, road construction, maintenance, and repair in the construction industry. The teeth, which are bolted or welded to the front of the buckets, protect the bucket against the abrasive effects of soil and rocks. The rapid wear of the teeth under great loads is an important cost item in construction equipment. In this study, the stresses under the effect of dynamic loads were tried to be determined in the teeth in the backhoe loader buckets. In this context, it is aimed to determine the wear conditions of two different models of teeth, which are frequently used in the sector, with the help of the discrete element and finite element methods.

Competitiveness throughout the seaport-hinterland: a container shipping analysis

ABSTRACT With customers looking for the highest level of services and reduction of cost on international trade of goods, shippers have recently begun to focus on the inland leg of containerized import/export, making the competition advance between ‘seaport against seaport’ to ‘seaport-hinterland against seaport-hinterland’. Bearing this in mind, this paper seeks to assess the logistic costs and the import process time in order to identify how these factors influence seaport-hinterland customer’s choice and what is the effect of these factors on the main actors’ competitiveness. In terms of time, the findings indicate that dry ports have been operationally more efficient, with customs and delivery process faster than in seaports and extended gates. In terms of cost we have applied Monte-Carlo simulation in a case study in Brazil to assess stochastically the import cost considering multiple actors as options. The study makes practical contributions, showing the cost-efficient zone for each macro region in the studied area and simulating a hypothetical scenario, where multimodal transportation is a delivery option. Lastly, the study makes theoretical contributions, discussing the competitiveness environment in light of the literature, bringing relevant insights to aid customers’ and practitioners decision-making.

An Intelligent Grazing Development Strategy for Unmanned Animal Husbandry in China

Grazing is the most important and lowest cost means of livestock breeding. Because of the sharp contradiction between the grassland ecosystem and livestock, the grassland ecosystem has tended to degrade in past decades in China; therefore, the ecological balance of the grassland has been seriously damaged. The implementation of grazing prohibition, rotational grazing and the development of a large-scale breeding industry have not only ensured the supply of animal husbandry products, but also promoted the restoration of the grassland ecosystem. For the large-scale breeding industry, the animal welfare of livestock cannot be guaranteed due to the narrow and crowded space, thus, the production of the breeding industry usually has lower competitiveness than grazing. Disorderly grazing leads to grassland ecological crises; however, intelligent grazing can not only ensure animal welfare, but also fully improve the competitiveness of livestock husbandry products. Under the development of urbanization, the workforce engaged in grazing and breeding in pastoral areas is gradually lost. Intelligent grazing breeding methods need to be developed and popularized. This paper focuses on intelligent grazing, reviews grass remote sensing and aerial seeding, wearable monitoring equipment of livestock, UAV monitoring and intelligent grazing robots, and summarizes the development of intelligent grazing elements, exploring the new development direction of automatic grazing management with the grazing robot at this stage.

Social supermarkets, nutritional implications and healthy eating: exploration of members and their views.

The Covid-19 pandemic has increased the need for food support but simultaneously enabled substantial innovation in food support provision, including the evolution of social supermarkets (SSM). These allow consumers to choose from a range of low-cost products, minimise stigma and reduce food waste. Data from members of two Sussex SSM were gathered for their perspectives and experiences, as well as potential nutritional implications of the SSM. Questionnaires administered face-to-face during site visits and optional telephone interviews were used. Data were collected during three site visits; 111 participants completed questionnaires, and an additional 25 detailed interviews with members of the SSM were completed. All data were gathered between December 2021 and May 2022. Overall, the SSMs were valued by their members. Social, economic and nutritional benefits were identified. SSM increased consumer choice and reduced stigma. Most members visited regularly, using SSM to supplement other food purchases. They valued the opportunity to choose their own foods and opportunities to socialise, in addition to the range of food and household items offered. The majority agreed that healthy eating was important but time and cost were barriers especially for younger members. SSM introduced members to novel foods and dishes, potentially diversifying dietary intakes. Challenges included restrictions on the amounts of food available, depending on the timing of visits. This was a greater challenge for those more reliant on SSM for household needs. SSM represent an innovative and less stigmatising model of food support. Greater variety of food offered suggests their potential to diversify and improve dietary intakes. Challenges include ensuring stability of food supply and reducing stigma further.