Important Cost Research Articles

Trade policy reform, retail food prices and access to healthy diets worldwide

Recent use of least-cost diets as a measure of global food security revealed that over 3 billion people are unable to afford sufficient nutritious food for an active and healthy life, driving demand for policy changes to improve access and affordability. This study quantifies the role of imports in consumer prices, matching retail prices in 144 countries to imports by origin of the item or its main ingredient, resulting in a total of 13,846 pairs of a retail price and its import cost in 2017. We find that 55% of retail items had some active imports supplementing domestic production, and of those around 48% have nonzero tariffs whose average effective rate is around 6.7% of the imported commodity price. Over all countries for which data are available, the share of consumer prices for least-cost healthy diets that is attributable to tariffs and non-tariff measures averages 0.67% and 2.45% globally. The highest restrictions are on nutrient-rich vegetables, fruits and animal-sourced foods. Access to bulk commodities from diverse origins is essential for food and nutrition security, providing a greater diversity of foods and food ingredients at lower and more stable prices than can be grown at any one location. On average over all food products that are imported, 83% of the retail price is domestic value added after arrival. We conclude that food imports are best understood as inputs to the domestic production and distribution of retail items, with consumer prices and growth of the food sector dependent on the cost levels, infrastructure and institutions underlying each product’s entire value chain.

PENGENALAN PENGUKURAN KELAYAKAN FINANCIAL PADA UMKM PD PUTRI DI PGC JAKARTA TIMUR

The financial feasibility measurement introduction training conducted by the Community Service team had the main objective of providing assistance to PD PUTRI's Small and Medium Enterprises (SMEs) in conducting a comprehensive evaluation of the financial feasibility of their development business. The training process covered several important aspects, including investment and production cost analysis, cost of goods sold, and business feasibility criteria such as Break Even Point (BEP), Net Present Value (NPV), Payback Period (PP), Internal Rate of Return (IRR), and Profitability Index (PI). In addition, in the context of SME development, careful planning requires serious consideration regarding the addition of working capital. The allocation of working capital by SMEs is crucial in providing the technology, equipment, and facilities and infrastructure needed to run the business optimally. Financial feasibility analysis is a key instrument in assessing whether the planned business can provide adequate profits and whether it is economically viable. Within the framework of raising working capital, aspects such as capital utilization efficiency, investment strategy, and risk management are also a key focus. This training aims to equip PD PUTRI's SME team with the knowledge and skills needed to design and evaluate a development strategy based on an in-depth financial feasibility analysis. As a result of the training, PD PUTRI SMEs are expected to make more informed decisions and optimize their working capital management. In addition, it is also expected to improve business competitiveness through a better understanding of the financial factors that influence business viability and sustainability

Economic burden of chronic obstructive pulmonary disease in Morocco: a cost of illness study.

Chronic obstructive pulmonary disease (COPD) carries an important economic burden worldwide. However, the cost of this disease in Morocco is not well explored. This study aimed to estimate the economic cost associated with COPD in Morocco and identify its determinants. A cost of illness, prevalence-based study using a bottom-up approach method, including COPD patients, was carried out in 2021-2022. The cost was estimated from a societal perspective, and the time horizon was 1 year. Data collection was performed using a questionnaire including socio-demographic, clinical data, and utilization of health care resources in 2019: hospitalization, medical tests, medications, and medical visits. Direct health cost (DHC) was estimated by multiplying the use of health services by the official prices (unit costs) published by the National Agency for Health Insurance. The indirect cost (IC) represented by labor productivity losses was calculated using the human capital method. Costs were compared according to different socio-demographic and clinical factors. We included 159 patients; 82.4% were men, 80.4% were current or former smokers, and 78.7% were categorized as "high-risk" groups (grades C-D). The DHC was estimated at $1816.6 per patient per year. Pharmaceutical and hospitalization costs represented the highest part of the total DHC (42.5% and 22.1%, respectively). The IC was estimated at $709.5±1081.3 per patient per year. DHC increased with increasing disease severity and with the number of severe exacerbations (p<0.001). Current and former smokers were more costly to the healthcare system than nonsmokers (p=0.029). IC also increased with the number of severe exacerbations (p=0.003). In this study, we showed that COPD in Morocco generates important costs for the health system, mainly related to smoking and the severity of the disease. It is therefore important to strengthen tobacco control measures in our country.

Network Usage Tariff (NUT) structure and vision in Hungary in consideration of renewable generation trends

The consumption behaviour focus points are changing nowadays: in certain areas start industrial developments where entirely different needs were common, creation the new consumer design of multi-directional connections generate pressure to loosen regulations; climate change is changing malfunctions impact; widespread use of renewable energy sources; etc. Beyond the global trends there are huge facilitators in Hungary which can basically act to regulation, pay-off and supplying methods. In the paper one really important and sensitive cost element will be investigated – the Network Usage Tariff (NUT) – and its influential elements: governmental overhead reduction, increasing renewable penetration, changing subsidy systems. After introducing the existing business case and the possible trends, affecting regulation and market changes, the scenarios will be analysed and results summarized. At the end as an outcome a proposal will be presented.

Applied denitrifying bioreactor cost efficiencies based on empirical construction costs and nitrate removal

Adoption of edge-of-field conservation practices, such as denitrifying bioreactors, may be intrinsically linked to barriers associated with cost. However, most previous bioreactor cost efficiency assessments assumed values for either costs and/or nitrate removal. The objective of this work was to use actual construction costs as well as monitored nitrate removal to develop empirical cost efficiencies for eight full-size bioreactors in Illinois, USA. Capital construction costs were obtained via invoices or personal communications. A cash-flow discounting procedure was used to develop an equal annualized cost for each bioreactor assuming two media recharges over a 24-y planning horizon. These costs were combined with monitored nitrate removal based on one to six years of monitoring per site. Construction costs averaged $12,250 ± $7520 across the eight sites (or, $16,020 ± $9960 in 2023 price levels) but considering one of the sites was a paired bioreactor system, costs averaged $10,890 per bioreactor unit. Drainage treatment area-based cost averaged $132/ha-y and treatment area was strongly correlated with capital costs (R2 = 0.90; p = 0.001). The bioreactors averaged $108/m3 of woodchips and available federal government conservation programs could have offset an average of 70% of this cost. Monitored nitrate removal across 27 site-years resulted in a median of $33/kg N-y removed. This mass-based cost efficiency was higher than most previous assessments because the monitored nitrate removal for the study sites was lower than has been previously assumed or modeled. Future reporting about bioreactor recharge timing and cost will help guide assessment and planning. Water quality planning efforts should also consider the increasingly important engineering design costs, which were not included here. Suggested research and outreach to improve bioreactor cost efficiencies involves scaling the physical capacity of this technology for larger treatment areas, revisiting the use of low-cost non-standard fill media, and providing practical construction training.

In-house or outsourcing? The impact of remanufacturing strategies on the dynamics of component remanufacturing systems under lifecycle demand and returns

We consider a component manufacturing and remanufacturing system where, due to the end-of-life warranty, new and after-sales demand must be satisfied. Two kinds of demand exhibit different lifecycle patterns with different scales and a time lag, while a third correlated component return lifecycle with again a different lag and scale, driven by adoption of remanufacturing, is also presented. To achieve supply and demand balance during demand lifecycles, companies need a strategic decision on their remanufacturing: remanufacturing outsourcing strategy (ROS) or remanufacturing in-house strategy (RIS), yet inadequately studied from system dynamics perspective. We developed base-stock system dynamics models and analytically explored the dynamic implications of RIS and ROS remanufacturing strategies under correlated lifecycle demand and returns. Applying z-transform and discrete time simulation, we found that RIS outperforms ROS system including less peak capacity cost, less inventory holding cost and less backlog cost. Also, the bullwhip of the RIS is always less than the ROS system. However, the adoption of the RIS may result longer-lasting manufacturing production and thus lead to a higher cost: an important cost needs to be strategically considered. Thereby, from system dynamics perspective, the component manufacturer needs carefully consider trade-offs between production and inventory costs, as well as their demand lifecycle characteristics to choose the right remanufacturing strategy.

The Impact of Currency Fluctuations on Import Cost and Export Revenue of Tolar Ocean Products

This study examines the impact of currency fluctuations on Tolar Ocean Products, a seafood exporter and importer. The research finds that exchange rate volatility significantly affects both import costs and export revenues for the company. To mitigate these risks, Tolar Ocean Productsshould implement hedging strategies, diversify its markets, and closely monitor exchange rate movements. Effective risk management is crucial for the company's long-term success in the global seafood market.

Fertilizer Production in Africa as a Way to Minimise Fertilizer Importation Cost

Fertilizer Production in Africa as a Way to Minimise Fertilizer Importation Cost

Импортоемкость регионов российской экономики

In the pre-sanction period, foreign economic relations in Russia were growing in importance. While the country’s gross domestic product increased by 1.75 times in 2013 compared to 2000, imports increased by 5.7 times in comparable prices during this period. Despite actual and potential effects of comparative advantages, the growing dependence on foreign markets also had negative consequences. The study assesses the demand for imported goods, considering the existing interindustry relations in the Russian economy. The paper describes the first stage of comparison of direct and total costs for the Russian economy and presents mathematical tools used to calculate indicators of its import dependence. In the future, we are planning to extend this approach to examine the spatial economy of two macrozones, namely, the European and Asian parts of Russia. Statistics show that the direct import intensity of the Russian economy is approximately 6 %, which is less than the global average. The vertical specialisation index of about 11 % indicates a relatively low dependence of the export of domestic goods on imports. In 2014–2020, total import costs reduced the most in the pulp and paper industry (-5 %) and vehicle manufacturing industry (-3 %) mainly due to a decline in their import intensity. In general, the impact of forced import substitution turned out to be negative for most regions after 2013. The proposed methods can be used to forecast the trade balance and consequences of implementing various import substitution policies. Since that intermediate consumption flows are included in indirect and total costs, it is advisable to develop a methodology accounting for investment goods.

The Influence of the Cost of Services on the Selling Price of Air Export Services Destination to Incheon City, Kr (ICN) at PT. NCS Line World Wide

A company is a business entity that strives to always optimize the profits that can be generated from its operational activities. Optimizing profits requires adequate cost information to be used as a basis for determining planning and decision making. One of the important cost information for companies to pay attention to is information regarding the cost price. Cost price is an important factor in determining the selling price of a product, with the hope that if the product is sold the company will make a profit. This research aims to determine the effect of calculating the cost of services on determining selling prices in an effort to increase profits at PT NCS Line World Wide. The subject of this research is air export service activities to Incheon City. The results of this research reveal that the cost of services has a significant positive effect on selling prices.&#x0D; &#x0D; Keywords: selling price, cost price, profit

Economic Burden of Tuberculosis for Patients and their Households in Cochabamba, Bolivia

Background: Patients with tuberculosis usually incur large costs directly related to their disease. Additional indirect costs also increase the economic burden of households creating barriers of access and adherence. Because TB affects the poorest segment of society the effects can be more serious for poor people. Indirect costs are poorly documented in Bolivia. We therefore conducted a study to determine the socioeconomic impact of TB on patients and their households.&#x0D; Methods: A cross-sectional survey was carried out on 2017 in Cochabamba, Bolivia, included all patients who were on TB treatment within the health network. The generic survey instrument proposed by WHO for tuberculosis patients cost surveys was used. The most important direct medical and direct non-medical payments were calculated in a disaggregated manner. The calculation of indirect costs was carried out through the results-based approach where the loss of income was calculated from the report of household income. Catastrophic cost was determined and multivariable logistic regression was run to assess which factors were independently associated.&#x0D; Results: The indirect costs during an entire illness episode had a median of USD 768.1 corresponding to 63.4% of the total cost for all patients. In the case of multidrug-resistant TB (MDR TB) patients, the median cost was USD 6454.8 corresponding to 54.3% of their total costs. Direct non-medical costs had a median for all patients of USD 408.7 (33.7%), and of USD 5399.6 (45.4%) for MDR TB patients. The most important non-medical costs were those linked to directly observed treatment (DOT) with a median of USD 419.8 during intensive phase and of USD 108.6 during continuation phase for transport costs. Food and drinks costs had a median of USD 94.5 during intensive phase and of USD 54.8 during continuation phase; consumption of nutritional supplements had a median cost of USD 249.1 and additional food outside the regular diet had a median cost of USD 519 for all patients. Catastrophic costs were incurred by 43.9% of TB patients. These catastrophic costs were observed in 50% of the population aged over 55 years, in 60% of MDR-TB patients, and in 63% of poor patients. Using logistic regression, factors associated with a higher risk of catastrophic costs were to live in an urban province (OR = 1.82 1.11 to 2.98, P = 0.002), to be older than 55 years (OR = 1.21 1.07 to 1.38, P = 0.005), and to have a low economic income (OR = 0.83 0.69 to 0.99, P = 0.049).&#x0D; Conclusions: Patients with TB treated in health services face a great financial burden. Indirect cost was higher than direct costs in a complete TB episode, especially in MDR-TB patients. During the treatment, the most important costs were those related to transport and food when patients went to DOT; nutritional supplements and additional food to the regular diet accounted also for a non-negligible cost. Almost half of patients suffer a catastrophic cost, especially those who came from an urban province, those who were older than 55 years, and those having a low economic income.&#x0D; &#x0D;

Big data and machine learning in cost estimation: An automotive case study

This paper presents a case study on the applicability of machine learning and big data technology for product cost estimation, using data on the material cost of passenger cars. The study provides contributions to six research aspects. First, we show which machine learning algorithms are appropriate when dealing with product cost estimation for highly complex products with more than 2000 parts and hundreds of cost drivers. Second, our case study provides a novel approach to increasing the predictive accuracy of cost estimates for subsequent product generations. Third, we show that the accuracy is up to 3.5 times higher when using big data compared to an intermediate size of data. Fourth, machine learning can outperform cost estimates from cost experts during the early stage of new product development, even when dealing with highly complex products. Then, we evaluate the use cases, issues, and benefits of machine learning and big data from the perspective of cost experts. Specifically, the case study shows that machine learning can reliably select the most important cost drivers (fifth aspect) and calculate the average cost of cost drivers over thousands of product configurations (sixth aspect). However, cost experts must be knowledgeable about the product and remain careful when interpreting machine learning outcomes, as they can yield misleading outcomes in some exceptional cases. In conclusion, machine learning and big data empirically proved to be able to generate additional value in many aspects for managing costs during the early phase of new product development.

Firms’ margins behaviour in response to energy shocks: Evidence from the UK

How have profits behaved in the current period of sustained inflation? In part, the answer depends on how ‘profits’ are defined. Some broad measures suggest increasing profits, but conflate market and non-market sector dynamics and omit important corporate costs. This paper constructs an alternative measure of corporate profits to capture UK firm earnings in excess of all production costs. This measure has been declining since the start of 2022, consistent with evidence from historical energy shocks. This decline has not been uniform across firms, however: firms with higher market power have been better able to protect their margins; others have experienced large declines.

Structural and topology optimization of steel construction profiles in solar energy systems

In recent years, significant investments have been made for Solar Power Plants (SPP) plants in many countries. The installation costs of SPP plants are quite high. This situation increases the amortization period of investments. Lowering these costs during the installation phase will pave the way for more investments. One of the most important cost items of Solar Power Plants (SPP) is steel construction costs. In this study, it is aimed to reduce the cost by designing the best performance product by reducing the weight of C profiles, one of the steel constructions used during the installation of solar panels, with shape and topology methods. The results obtained show that shape and topological optimization can provide significant gains in terms of cost.

Energy Consumption &amp; Economic Growth in Nigeria (1971 - 2021): A Multifaceted Analysis Using Descriptive Statistics, Charts, Logistic Regression, and Neural Networks

This study examines the intricate interplay between electricity consumption and economic growth, specifically Gross Domestic Product (GDP), in Nigeria. Despite the acknowledged influence of electricity consumption on GDP, the research takes a comprehensive approach by scrutinizing various economic factors that may contribute to Nigeria's remarkable GDP performance within the African context. Utilizing a meticulous methodology, the investigation explores the relationships between GDP and variables such as unemployment, population, lending interest rates, importation costs, and inflation rates across a 50-case observational dataset. The findings highlight the substantial impact of electric power consumption, population, and lending interest rates on Nigeria's GDP, while revealing the relatively minor effects of other predictors.

Agile Effort Estimation: Comparing the Accuracy and Efficiency of Planning Poker, Bucket System, and Affinity Estimation Methods

Published studies on agile effort estimation predominantly focus on comparisons of the accuracy of different estimation methods, while efficiency comparisons, i.e. how much time the estimation methods consume was not in the forefront. However, for practical use in software development, the time required can be a very important cost factor for enterprises, especially when the accuracy of different agile effort estimations is similar. In this study, we thus try to advance the current standard accuracy comparison between methods by introducing efficiency, i.e. time it takes to use a method as an additional dimension of comparison. We conduct this comparison between three agile effort estimation methods that were not yet compared in the literature, namely, Planning Poker, Bucket System and Affinity Estimation. For the comparison, we used eight student teams with 29 students who had to use all the effort estimation methods during the course where they had to finish a programming project in 3 weeks. The results indicate that after the students get used to using the different methods the accuracy between them is not statistically significantly different, however, the efficiency is. On average, Bucket System and Affinity Estimation methods take half as much time as Planning Poker.

The Influence of Federal Reserves Interest Rates Hike Cycle on Transnational Corporations

The monetary policy of the United States has a broad and profound impact on the world economy and financial markets. Due to the critical position of the US dollar in the world economy, the US monetary policy will directly affect countries and economies worldwide, and the liquidity of the US dollar is also the foundation of global liquidity. The series of interest rate increases implemented by the Federal Reserve starting in 2022 has led to the appreciation of the US dollar index, which has significantly impacted the import costs and overseas sales of domestic and multinational companies in the United States. This article selects the global multinational technology company Apple and extracts daily closing data from June 2022 to April 2023 and the USD index for the same period. This study applies the VAR model to assess the correlation between both and uses the ARMA-GARCH-X model to analyze the impact of USD index on the volatility of Apple stocks. This study analyzes the impact of interest rate hikes on multinational corporations and provides management and investment advice to their stakeholders.

A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid

Vehicle-to-building interaction as one of emerging and promising techniques shows powerful functions, to address intermittence of renewable energy, stochastic demand of buildings, power grid stability, and frequency regulation. The energy interaction magnitude is highly dependent on stochastic vehicle schedules, whereas a few studies focus on stochastic model development and guidelines on vehicle schedules. In this study, a series of stochastic models were developed to characterise the arrival time, departure time, and detention time-duration of vehicles in buildings. Considering the schedule difference between private cars and shuttle buses, both Chi-square distribution and Normal distribution were adopted, to quantify the distribution degree of vehicle numbers, together with parametrical analysis on standard deviation. Comparative analysis between different stochastic models can guide vehicle schedules and provide flexible vehicle-to-building interactions. Research results indicate that, normal distribution on arriving time and detention time-duration of vehicles shows the minimum annual import cost (ICannual) at 128.1 HK$/m2·a, while the normal distribution on arriving time and departure time with Chi-square distribution for detention time-duration shows the minimum equivalent CO2 emission (ECEannual) at 38.6 kg/m2·a. Furthermore, in respect to the distribution degree of vehicle numbers, the sharper curve for vehicle numbers in buildings (with lower standard deviation) will lead to a lower ECEannual and ICannual. Dynamic energy management strategy for the optimal stochastic vehicle schedule indicates that, marginal impacts on import cost saving can be provided to local power grid due to the limited difference between off-peak and peak grid electricity prices. This study provides new insight into the stochastic vehicle schedule model for an interactive vehicle-to-building energy interaction framework. Research results can provide frontier guidelines on stochastic vehicle schedules and flexible vehicle-to-building interactions for techno-economic-environmental performance improvement.

Flood-tolerant rice for enhanced production and livelihood of smallholder farmers of Africa

Climate change has intensified food security challenges, especially in Africa, where a significant portion of produce is reliant on smallholder farmers in rainfed conditions. Prolonged flooding and droughts, driven by erratic weather patterns, have significantly elevated the risk of food scarcity. Floods, in particular, have been responsible for severe crop losses, raising concerns about increasing import costs if this issue is not mitigated. Africa is actively working to mitigate the impacts of flooding and enhance food security, although progress has been gradual. Developing flood-resilient varieties is a promising strategy to address this challenge. We explored various flood types common in the region and observed a scarcity of research on flood-resilient varieties, particularly those adapted for anaerobic germination and stagnant flooding. Conversely, varieties bred for flash flooding, such as FARO 66 and FARO 67, have seen limited distribution, primarily confined to a few West African countries, falling short of the intended impact. In contrast, deepwater tolerance research dates back to the early 1900s, but commercialization of the varieties remains limited, with scarce information regarding their cultivation, coverage, and performance. Newly developed varieties, such as Kolondieba 2 and Kadia 24, have received less attention, leaving many farmers dependent on locally adapted cultivars specific to particular areas. Remarkably, despite the limited information, both released and local stress-tolerant cultivars exhibit substantial survival rates and yield advantages. For instance, FARO 66 and FARO 67 have demonstrated 1–3 t/ha yield advantages over recurrent parents under flooding stress. Nonetheless, further efforts are required to address various forms of flooding. To this end, AfricaRice collaborates with National Rice Development Strategies, IRRI, and other partners to promote research and development. While improved flood-tolerant varieties remain limited in scope across Africa, the financial gains for farmers are significant when compared to susceptible cultivars. As the continent’s population continues to grow rapidly, there is untapped potential in African germplasms, making ongoing research and breeding strategies essential. Therefore, this review highlights the importance of intensifying efforts in screening and identifying flood-tolerant rice. Furthermore, it underscores the value of utilizing traditional flood-resilient cultivars in breeding to enhance the productivity of widely distributed and cultivated varieties.

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.