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This research investigates the potential implementation of Electronic Road Pricing (ERP) in Bandung City, Indonesia, focusing on its effectiveness in reducing traffic congestion. The study employs a quantitative approach using a survey method, experiments, and statistical analyses to evaluate ERP's impact on road traffic performance and cost efficiency. The research design includes traffic volume analysis, vehicle operating costs, and data collection through questionnaires from Bandung residents selected randomly. The research subjects include frequent road users in congested areas, and the study was conducted in 2023. Using binary logistic regression, the results show significant shifts in road user behavior, with reductions in traffic volumes of 33% on Sukajadi Road, 38% on Dr. Djunjunan Road, and 23% on Terusan Jakarta Road. Additionally, ERP was found to improve cost efficiency in traffic management. The study concludes that ERP is a promising solution for managing congestion in Bandung, with broader implications for other congested cities in Indonesia. [ABSTRACT FROM AUTHOR]

In today's business world, it is extremely important for companies to train newly hired employees quickly and effectively. In this context, learning curve analysis offers valuable information to better understand workers' learning processes and predict their future performance. This study addresses learning curve analysis in order to evaluate the performance of newly hired workers during the training process and predict their future success. This study aims to demonstrate how businesses can strategically apply the learning curve and regression model to help them manage new workers more effectively and improve their training programs. In this context, suggestions are offered for companies that want to gain a competitive advantage in the business world and secure long-term success. Additionally, since the data used in this study are hypothetical, the focus is on the applicability of the analyzes to real-world scenarios. [ABSTRACT FROM AUTHOR]

We propose a Competitive Leverage model, and apply it to analyze the impact of tariffs on the attitudes of domestic import-competing firms, especially regarding their disincentives to maintain a Competitive Stance against foreign competitors in the domestic market. We propose that tariffs are a disincentive to the pursuit and maintenance of production efficiency in firms and industries. When countries implement tariff protection for their domestic firms, the most common excuse sounds reasonable, except that it is also economically flawed. While the short-run impacts of such a measure might seem plausible, its long-term effects appear to be less than favorable, and may, in fact, turn out to be damaging to the economy. The paper applies the competitive leverage concept in a unique way to highlight how tariffs distort the output levels of domestic firms, and gives an empirical analysis of the model, using USA data to verify the predictions of the model. Particularly, we develop a Cournot-competition type Competitive Leverage model, and use it to examine the role played by tariffs as a disincentive to a typical firm's pursuit and maintenance of production efficiency. The competitive leverage model is formulated and applied to verify the effects of tariff protection from the typical domestic firm's strategic interaction standpoint. We further apply crosssectional data to carry out an empirical analysis of the model, to verify how tariffs impact the domestic firm's output and pricing decisions. Our findings would enable us to contribute to the debate about the need to remove protective tariffs, on the grounds that tariffs do not only enable domestic firms to operate inefficiently, but also tends to distort the output and pricing outcomes that would otherwise have been realized in the free market. The results from the study are used to propose some major policy implications of imposing tariff protection, among which are that there is need for implementation of more deliberately sustained Research and development program on the part of domestic firms in the economy, to enable them withstand vigorous competition in a free-trade world. Also, since protective tariffs significantly increase firms' profit rates, which in turn enables them to unduly earn and accumulate economic rents that amount to inefficiencies and distortions in free-market prices and quantities outcomes, governments should always resist any pressures from big businesses to impose protective tariffs against competition from international rivals. Yet a clear public policy implication from this paper is that, at the macro level, as the results suggest that a government policy that aims at protecting domestic firms through imposition of tariffs may have an adverse effect on the firms' competitive stance in the industry, a practical message is for the government to impose only a moderate tariff at the most, if it must, especially as it relates to agricultural products. [ABSTRACT FROM AUTHOR]

Assessing the potential relationship between ownership and performance of water utilities is relevant for water regulators. Incorporating technological heterogeneity among groups of water utilities could solve any incomparability issues and lead to more appropriate policy implications. This can be done with the use of the metafrontier framework which assumes that utilities operate under different technologies. The study applies this framework to compare the efficiency of private water utilities (PWU) and concessionary water utilities (CWU) in Chile using Bayesian Stochastic Frontier Analysis (SFA) techniques. The results indicated that PWU performed better than CWU. Nevertheless, both types of water utilities presented considerable cost inefficiency. PWU and CWU should considerably reduce costs by 34% and 48% using the industry technology as a whole, respectively. The methodological approach proposed in this study could be used to compare the performance of other groups of water utilities to support the decision making of water regulators. [ABSTRACT FROM AUTHOR]

Cloud computing has emerged as a pivotal technology that transforms business development, offering flexibility, scalability, and cost-efficiency. This research paper discusses how cloud computing is revolutionizing business models across industries. The paper examines the benefits of cloud adoption, reviews existing literature, and explores the challenges of integration and possible solutions. Additionally, key cloud technology resources are identified, and the paper provides a comprehensive outlook on the future of cloud computing in business growth. [ABSTRACT FROM AUTHOR]

Inverse Data Envelopment Analysis (IDEA) has gained significant attention among researchers as an analytical tool for assessing efficiency. Estimating input values while ensuring cost efficiency through changes in output quantities is complex and sensitive. In contrast to conventional data envelopment analysis methods, IDEA enables the quantification of input/output variations resulting from output/input reductions or expansions while preserving the measurement efficiency level. This paper aims to introduce a novel approach for estimating input values by incrementally increasing the value of each output of decision-making units (DMUs) during the evaluation process, thereby maintaining or improving cost efficiency. By utilizing IDEA and manipulating the output values of the DMU under evaluation, the input values are estimated while ensuring constant or enhanced cost efficiency. A simple numerical example and a case study from a Turkish automotive company are presented to validate the proposed method. The obtained results demonstrate significant improvements and hold promising prospects, indicating the potential applicability of this approach to other similar problems and research areas. [ABSTRACT FROM AUTHOR]

IntroductionOnions are an imperative root crop that can be grown both under irrigation and rain-fed conditions. It is considered a complementary product to tomatoes and is a globally commercial crop. Onions are a popular crop in Ethiopia for human consumption and export.MethodsFor this study, 150 smallholder producers were surveyed to collect cross-sectional data. A single-step Cobb–Douglas stochastic frontier model was used to estimate both the technical and cost efficiency of irrigated onion production.ResultsThe results from the maximum likelihood stochastic frontier model result indicated that the technical efficiency in onions was influenced by the age of the household head, slope of the land, number of extension contacts with development agents, distance from the sampled respondent’s residence to the office of the kebele agriculture office, and the number of oxen owned by the sampled households. Cost efficiency, on the other hand, was determined by the age and educational status of the household head, family size in man equivalent, and the size of irrigated land owned by the onion farmer. The study found that the average technical efficiency score for irrigated onions in the study area was 87%, while the average cost efficiency score was 84%.DiscussionThis indicates that, on average, onion farmers in the study area could potentially increase their technical efficiency by 13% and their cost efficiency by 16% with existing inputs, technologies, and current environmental conditions. Thus, the study suggests institutional interventions such as providing extension services to farmers who are far from agriculture offices, advising on fertility reclamation measures, facilitating young farmers in onion production, and assisting in asset building, particularly in acquiring oxen, to maximize technical and cost efficiency in the study area.

Abstract Background The expansion of sequencing technologies as a result of the response to the COVID-19 pandemic enabled pathogen (meta)genomics to be deployed as a routine component of surveillance in many countries. Scaling genomic surveillance, however, comes with associated costs in both equipment and sequencing reagents, which should be optimized. Here, we evaluate the cost efficiency and performance of different read lengths in identifying pathogens in metagenomic samples. We carefully evaluated performance metrics, costs, and time requirements relative to choices of 75, 150 and 300 base pairs (bp) read lengths in pathogen identification. Results Our findings revealed that moving from 75 bp to 150 bp read length approximately doubles both the cost and sequencing time. Opting for 300 bp reads leads to approximately two- and three-fold increases, respectively, in cost and sequencing time compared to 75 bp reads. For viral pathogen detection, the sensitivity median ranged from 99% with 75 bp reads to 100% with 150–300 bp reads. However, bacterial pathogens detection was less effective with shorter reads: 87% with 75 bp, 95% with 150 bp, and 97% with 300 bp reads. These findings were consistent across different levels of taxa abundance. The precision of pathogen detection using shorter reads was comparable to that of longer reads across most viral and bacterial taxa. Conclusions During disease outbreak situations, when swift responses are required for pathogen identification, we suggest prioritizing 75 bp read lengths, especially if detection of viral pathogens is aimed. This practical approach allows better use of resources, enabling the sequencing of more samples using streamlined workflows, while maintaining a reliable response capability.

This study investigates peer effects and agglomeration impacts on the cost efficiency of South Korean rice farms using a five-year panel dataset of production costs. We employed a time-varying stochastic frontier cost function approach to estimate cost efficiency and a linear-in-means model to quantify peer influences. The findings underscore peer effects as central to understanding and enhancing farm productivity, particularly in rice farming regions. Both specialisation and diversity of agglomeration positively influenced efficiency, with specialisation having a larger impact. Peer effects were stronger in highly rice-specialised areas. These findings indicate the necessity of incorporating peer influences and regional specialisation in agricultural policymaking for productivity enhancement. A nuanced, evidence-based approach leveraging peer dynamics and agglomeration economies is advocated to boost the efficiency of farming practices.

Background: The expansion of sequencing technologies as a result of the response to the COVID-19 pandemic enabled pathogen (meta)genomics to be deployed as a routine component of surveillance in many countries. Scaling genomic surveillance, however, comes with associated costs in both equipment and sequencing reagents, which should be optimized. Here, we evaluate the cost efficiency and performance of different read lengths in identifying pathogens in metagenomic samples. We carefully evaluated performance metrics, costs, and time requirements relative to choices of 75, 150 and 300 base pairs (bp) read lengths in pathogen identification. Results: Our findings revealed that moving from 75 bp to 150 bp read length approximately doubles both the cost and sequencing time. Opting for 300 bp reads leads to approximately two- and three-fold increases, respectively, in cost and sequencing time compared to 75 bp reads. For viral pathogen detection, the sensitivity median ranged from 99% with 75 bp reads to 100% with 150–300 bp reads. However, bacterial pathogens detection was less effective with shorter reads: 87% with 75 bp, 95% with 150 bp, and 97% with 300 bp reads. These findings were consistent across different levels of taxa abundance. The precision of pathogen detection using shorter reads was comparable to that of longer reads across most viral and bacterial taxa. Conclusions: During disease outbreak situations, when swift responses are required for pathogen identification, we suggest prioritizing 75 bp read lengths, especially if detection of viral pathogens is aimed. This practical approach allows better use of resources, enabling the sequencing of more samples using streamlined workflows, while maintaining a reliable response capability. [ABSTRACT FROM AUTHOR]

The efficiency evaluation of organizational units provides managers with a perspective on the current state of the organization and solutions for their improvement. One of the methods of organizational evaluation is to determine the organization’s minimum cost or cost efficiency. Cost efficiency in practice can be calculated when the input prices are available. In traditional models of cost efficiency, input and output data are crisp. However, there are situations where input and/or output may be imprecise. For such cases, experts are invited to model their opinion. Then uncertainty theory can be applied which is introduced by Liu as a mathematical branch rationally dealing with belief degrees. In this paper, a model is proposed to estimate the cost of decision-making units in the uncertain environment, where inputs and outputs are uncertain but the input prices are crisp. Several theorems are presented to discuss some features of the introduced model. When the data has a linear distribution, the cost efficiencies of the decision-making units are calculated. Also, the model is implemented on two numerical examples. The obtained results are compared with previous results. Finally, in the presence of input prices, a different cost efficiency score for the decision-making units is obtained. The proposed model helps decision-makers to improve their performance by using experts’ opinions. [ABSTRACT FROM AUTHOR]

The integration of software sensors in industrial processes offers substantial economic benefits by enhancing operational efficiency, reducing costs, and enabling real-time monitoring and decision-making. Unlike traditional physical sensors, which incur significant expenses for installation, calibration, and maintenance, software sensors rely on advanced computational algorithms to estimate parameters that are otherwise difficult or costly to measure directly. This study explores the key economic advantages of software sensors, including significant cost savings on hardware, extended equipment lifespan, and improved process optimization. Detailed examples illustrate how industries can leverage software sensors to minimize waste, enhance product quality, and achieve considerable energy savings. By relying on historical data and predictive models, software sensors allow for proactive decision-making that reduces downtime, improves asset utilization, and optimizes resource consumption. The research highlights how software sensors facilitate greater flexibility in industrial environments by enabling real-time adjustments and continuous monitoring, crucial for industries seeking to stay competitive in a data-driven economy. Moreover, this study underscores the broader economic and environmental impacts of software sensors, demonstrating their role in sustainability and regulatory compliance. Through reducing resource consumption, minimizing waste, and optimizing energy efficiency, software sensors not only drive direct cost reductions but also support the achievement of environmental goals. The findings emphasize the transformative potential of software sensors as a cost-effective solution for industries focused on enhancing both economic performance and environmental responsibility. In conclusion, this paper advocates the scaling of software sensor technologies, calling for strategic investments in data management, workforce development, and system compatibility to fully realize their potential. The insights gained provide a solid foundation for future research and the broader adoption of software sensors, presenting them as a key tool for industrial transformation in both economic and ecological terms. The study highlights the crucial intersection of economics and informatics in revolutionizing industrial operations, with significant implications for future growth and sustainability. [ABSTRACT FROM AUTHOR]

The article examines consumers' perceptions about electric vehicle (EV) adoption and user satisfaction in Southern Kerala, India. The study evaluates the vehicle preferences of youthful, educated men and factors that influence buying decisions including demographic characteristics, economic issues, environmental concerns, financial gains and operational efficiency. It summarizes EV sales trends and cost-benefit of EVs and outlines opportunities and challenges in EV adoption.

Using panel data from major meat sheep producing provinces in China from 2011 to 2022, this study empirically examines whether market-oriented reforms can improve the cost efficiency of free range meat sheep farming. Research showed that market-oriented reforms had a significant positive impact on the cost efficiency of free range sheep farming, indicating that market-oriented reforms could improve the cost efficiency of free range sheep farming. The threshold effect test showed that the market-oriented reform had a non-linear impact on the marginal increase in cost efficiency of free range sheep farming. Heterogeneity testing showed that compared to the central and western regions, the market-oriented reform in the eastern region had the strongest impact on the cost efficiency of free range sheep farming. Therefore, the article explores the classification and promotion of market-oriented allocation reform of rural factors, and enhances the synergy of market-oriented reform according to local conditions, in order to promote the high-quality development of free range sheep farming. [ABSTRACT FROM AUTHOR]

With pervasive network access, cloud computing offers on-demand access to a shared pool of computing resources. To guarantee high quality cloud services, cloud task scheduling algorithms need to be dependable and efficient. Cloud infrastructure, however, are vulnerable to errors and malfunctions that may affect how tasks are carried out. In this research, a metaheuristic approach for adaptive fault tolerant job scheduling in cloud systems is proposed. The method efficiently schedules work while optimizing fault tolerance by adaptively applying numerous fault tolerance strategies and meta-heuristic based optimization. Additionally, a thorough analysis of modern Meta-heuristic based job scheduling algorithms is presented in this work, with an emphasis on the algorithm's fault tolerance and adaptability. Through simulation tests using CloudSim toolkit, adaptability, scalability, energy efficiency, and reliability matrices are used to compare the suggested algorithm against existing approaches. The suggested methodology works better than current techniques, according to the results, which indicate increased task throughput, scalability, energy efficiency, and fault tolerance across a range of cloud workloads. An efficient method for ensuring consistent task execution in unstable cloud environments is offered by the innovative scheduling architecture that incorporates six metaheuristics, redundancy, checkpointing and migration based fault tolerance in an adaptable manner. [ABSTRACT FROM AUTHOR]

Through the integration of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP), this study investigates the evaluation of delivery efficiency in online food delivery platforms. Maintaining timely and effective deliveries has become essential for retaining client happiness and competitive advantage in the rapidly expanding online meal delivery market. The complex interplay of delivery efficiency--which takes into account variables including delivery time, cost, customer happiness, and environmental impact--means that traditional assessment techniques frequently fall short in this regard. In order to improve delivery efficiency in online food delivery platforms, this research first uses AHP to determine the relative importance of various criteria influencing delivery efficiency. AHP helps to structure the problem into a hierarchical model, making it easier to assign weights to each criterion based on expert judgment. In order to rank different delivery options, the TOPSIS method is then used, which compares them to an ideal solution. This combination of AHP and TOPSIS provides a comprehensive, multi-criteria decision-making framework that facilitates a more nuanced assessment of delivery performance. The results indicate that combining AHP and TOPSIS methods can greatly improve the evaluation process. [ABSTRACT FROM AUTHOR]

Fisheries sector provides livelihood to about 25 million fishers and fish farmers at the primary level and almost twice the number along the value chain. The purse-seiner and trawlers are major means of large-scale harvest of marine fishery resources along Karnataka coast. Gangolli landings centre is one of the key marine fish landing centre of Udupi district of Karnataka. The present study evaluated the economic performance of both single day trawler and purse-seiner operated from the landing centre. The key economic indices like Benefit-cost (BC) ratio, operating ratio (OR), net present value (NPV), internal rate of return (IRR) and cost efficiency were estimated to evaluate the economic performance. The BC ratios for purse-seiner were estimated at 1.20, whereas it was 1.12 for the single day trawlers. The respective operating ratio were 0.56 and 0.67. The estimated IRR for the purse-seiner was 37.18%, a slightly higher IRR was observed for single day trawler (39.01%). The cost efficiencies for purse-seiner were 0.847 and 0.939 at constant and variable return to scale, respectively. Similar cost efficiencies were also observed for the single day trawlers. It was observed that the mechanized fishing sector is operating under narrow profit margin. The declining revenue due to decrease in quantum of high valued fishes in catches and escalating fuel prices have been identified as the major factor leading to deteriorating economics of the mechanized sector in the region. [ABSTRACT FROM AUTHOR]

The Surabaya Raya toll network encompasses two critical sections connected by the Wringinanom Junction and links the Trans Java Toll Road Surabaya -- Mojokerto at KM 723 with the Krian -- Gresik Toll Road at KM 3+300 in Wringinanom District, Gresik Regency. This junction includes four ramps to facilitate connectivity, with Ramp 5 intersecting the Surabaya -- Mojokerto Toll Road Rest Area at KM 725A and serves traffic from Gresik to Surabaya. This intersection necessitates a design adjustment to enhance traffic flow and safety. There are several problems that will be resolved, including what alternative designs can be implemented, wheter alternative designs affect efficiency in terms of costs and time, which alternative designs are more efficient. Accordingly from these problems, the aim of this research is to analyse several design alternative, calculate and analyse time and cost comparison, analyse factors that can influence potential delays in construction completion and decide on the most efficient design alternative in terms of time and cost. The value engineering process comprised information gathering, creative ideation, analysis using the paired comparison method, and recommendation. In the creative phase, three design alternatives were proposed. The paired comparison analysis revealed that the third design alternative that features the tunnel construction under the rest area, is the most efficient, with an estimated cost of IDR 126,236,641,897.46, a duration of 98 days, and a more practical construction aspect. Consequently, the third design alternative was recommended for implementation in this study. [ABSTRACT FROM AUTHOR]

This study investigates the effects of efforts to digitally transform on cost effectiveness in banking services for retail customers. As the banking industry embraces digital technology, understanding the link between these efforts and operating expenses becomes crucial for sustaining a competitive edge. A descriptive study approach was used to obtain data from a sample of workers at various retail banks via structured questionnaires. The data, which were analysed using ANOVA, show a substantial association between technological change efforts and financial efficiency, implying that improvements in technological capacity lead to better operational performance. To maximise the advantages of digital transformation, banks should engage in staff training, implement a staged integration of technological advances, and cultivate an innovative culture. [ABSTRACT FROM AUTHOR]

The Iran-Pakistan gas pipeline, also known as the peace pipeline, extend huge potential to lessen the incessant energy shortages and nurture economic growth for Pakistan. Multifarious proposals have been made on the pipeline project since its commencement in the 1990s, underscoring the strategic cooperation between the two countries. From economic outlook, the pipeline would ameliorate energy security, upgrade industrial production, and mitigate Pakistan’s energy expenses. From a strategic perspective, the pipeline portrays an essential component of regional collaboration and integration. Nevertheless, numerous hurdles stand in the way of its progression, encompassing budgetary limitations, regional security concerns, and geopolitical squabbles like the US sanctions against Iran. Additionally, the viability of project is impeded by convoluted political factors existing in Pakistan and the larger international community. To bridle these hurdles, Pakistan requires exploitation of multiple approaches. Although the Iran-Pakistan gas pipeline ensures massive economic and strategic benefits for Pakistan, comprehending its potential entails a multifaceted strategy embracing diplomatic briskness, energy diversification, multilateral cooperation, and adhesive security measures. The qualitative method is utilized and case study design to inspect the Iran-Pakistan gas pipeline conundrum. A comprehensive analysis of documents is given using secondary resources to explore the geopolitical and economic options available for Pakistan.

This paper investigates the effects of cost efficiency on non-performing loans (NPLs) in Zimbabwe during dollarisation. The research applies the random effects and bootstrap quantile regression models using the full dollarisation era dataset for 13 banks from 2009 to 2017. The obtained results revealed that: (i) the average cost efficiency score for the Zimbabwean banking industry is 81.36%, (ii) improvement in cost efficiency leads to an increase in NPLs but begins to fall for a cost inefficiency level of 7.14% and below, (iii) the effect of bank cost efficiency on NPLs is prominent and highly significant at a higher quantile (90th), (iv) the interaction effect between cost efficiency and bank size on NPLs is negative and significant. According to these results, NPLs tend to fall when large banks are more cost-efficient. Thus, the present study recommends that banks employ strategies that simultaneously improve the asset base and cost efficiency.

AbstractThis study aims to examine the factors influencing the cost efficiency of microfinance institutions in Sub-Saharan African countries. A ten-year unbalanced panel data consisting of 128 microfinance institutions from 34 countries was used for the analysis. The study included all microfinance institutions in Sub-Saharan Africa that reported to the Microfinance Information Exchange database and had financial reports for at least five consecutive fiscal years between 2009 and 2018. The cost efficiency of the institutions was investigated using a stochastic frontier approach. The findings indicate that microfinance institutions operating in Sub-Saharan African countries are operating beyond the cost frontier line, with only 13% demonstrating efficiency. Key determinants of cost efficiency in microfinance institutions in SSA include the size of the institution, cost per borrower, women’s participation, institutional type, and country income category. Notably, increased women’s participation as board members, loan officers, and borrowers significantly improves cost efficiency. Microfinance institutions are encouraged to transform their custom practices in line with the rapid changes in the technology and techniques of modern financial service provisions and ensure the involvement of women in board members, supervisory positions and borrowing services. We also recommend that institutions appoint women selectively on nominated work positions.

The INDDEX24 Dietary Assessment Platform (INDDEX24) was developed to facilitate the collection of 24-h dietary recall (24HR) data. Alongside validation studies in Viet Nam and Burkina Faso in 2019-2020, we conducted activity-based costing studies to estimate the cost of conducting a 24HR among women of reproductive age using INDDEX24 compared with the pen-and-paper interview (PAPI) approach. We also modelled alternative scenarios in which: (1) 25-75 % of dietary reference data were borrowed from the INDDEX24 Global Food Matters Database (FMDB); (2) all study personnel were locally based and (3) national-scale surveys. In the primary analysis, in Viet Nam, the 24HR cost US $111 004 ($755/respondent, n 147) using INDDEX24 and $120 483 ($820/respondent, n 147) using PAPI. In Burkina Faso, the 24HR cost $78 105 ($539/respondent, n 145) using INDDEX24 and $79 465 ($544/respondent, n 146) using PAPI. In modelled scenarios, borrowing dietary reference data from the FMDB decreased the cost of INDDEX24 by 17-34 % (Viet Nam) and 5-15 % (Burkina Faso). With all locally based personnel, INDDEX24 cost more than PAPI ($498 v. $448 per respondent in Viet Nam and $456 v. $410 in Burkina Faso). However, at national scales (n 4376, Viet Nam; n 6500, Burkina Faso) using all locally based personnel, INDDEX24 was more cost-efficient ($109 v. $137 per respondent in Viet Nam and $123 v. $148 in Burkina Faso). In two countries and under most circumstances, INDDEX24 was less expensive than PAPI. Higher INDDEX24 survey preparation costs (including purchasing equipment) were more than offset by higher PAPI data entry, cleaning and processing costs. INDDEX24 may facilitate cost-efficient dietary data collection.

Inadequate subgrade conditions often diminish the lifespan of pavements built on these soils. However, this challenge can be addressed through various methods, including soil stabilization, which enhances soil strength. This research focuses on soil stabilization using two types of waste materials (rubber and plastic) as additives in concentrations of 5%, 10%, and 15%, along with a consistent cement inclusion of 3% across all samples. Different tests, such as Sieve analysis, Atterberg Limits, Specific Gravity, Standard proctor Test and California Bearing Ratio, were performed for both the soil and the additive materials. As a result, this stabilization approach improved the California Bearing Ratio (CBR), leading to thinner pavement layers, which potentially lowers construction costs. Notably, the highest CBR observed was 49.95% with 10% plastic, while the top result for rubber was a 28.01% CBR at 5% inclusion. These enhancements in CBR values contributed to reducing the total thickness of the pavement layers by (435 mm) for both materials.

Shallot is a perennial crop that is grown as an annual to harvest bulb seeds and produced widely in Vietnam. This is an easy-to-grow crop, suitable for land conditions in the local area and brings high economic efficiency. Although shallot is a relatively new crop to the farmers in Tra Vinh province, it is considered one of the key crops in the agricultural development strategy of the province. This study was conducted to assess the efficiency of shallot farming in Tra Vinh province using data envelopment analysis (DEA) approach. The findings revealed that the average cost efficiency was 0.770 and only five farms (2.5%) were fully cost-efficient. The score for average allocative efficiency was slightly superior to that for technical efficiency (0.917 and 0.838); thus, inefficient shallot farms could reach higher cost efficiency by increasing technical efficiency. Accordingly, factors influencing technical and cost efficiency in shallot production were determined in this study. Household size and cultivation experience of the farmers demonstrated negative effects on the levels of technical and cost efficiency. The analysis further revealed that those shallot farmers who had larger shallot farm sizes and those who had better access to technical training tended to be more technical and cost-efficient. Consequently, this study suggests that research to improve shallot-farming techniques should be prioritised support and the quality of technical training programmes for local farmers needs to be raised to increase the technical and cost efficiency in shallot production

The implementation of the policy of 'grain to feed' has a great impact on Chinese mutton sheep breeding industry. Based on the macro statistical data of domestic mutton sheep breeding cost-benefit, combined with the field survey data of 10 typical provinces from 2017 to 2022, this paper compares and analyzes the cost-efficiency changes and influencing factors of mutton sheep breeding in various scales in 2017 before the implementation of 'grain to feed' and in 2022 after the full implementation, so as to explore an effective way to improve the cost-efficiency of mutton sheep breeding in China under the background of 'grain to feed'. It is found that after the implementation of the policy of 'grain to feed', the cost efficiency of mutton sheep breeding in China has improved significantly. There is a positive correlation between the cost efficiency of farming and the scale of farming, and the cost efficiency of small-scale farming increases most obviously. Increasing technical guidance investment can steadily improve the cost efficiency of mutton sheep breeding. There are obvious regional differences in cost efficiency of mutton sheep breeding in different scales. The study indicates that under the background of the continuous release of the policy dividend of 'grain to feed', a technical guidance center for mutton sheep breeding should be established, the whole industrial chain of differentiated mutton sheep should be built, and the large-scale breeding project of 'grain to feed' should be implemented to provide a useful reference for improving the cost efficiency of mutton sheep breeding. [ABSTRACT FROM AUTHOR]

Under the background of large-scale breeding, improving the cost efficiency of broiler breeding is of great significance to accelerate the high-quality development of broiler breeding industry. In order to clarify the cost efficiency and its influencing factors of broiler breeding under the background of large-scale breeding, based on the macro statistical data of domestic broiler breeding cost-benefit, the stochastic frontier analysis method beyond logarithmic cost function was used to empirically test the changes and influencing factors of cost efficiency of broiler breeding of different scales from 2012 to 2022. It was found that under the background of large-scale breeding, the total cost of broiler breeding in different scales in China increased significantly, and the feed cost increased the most. The cost efficiency of broiler breeding showed a downward trend as a whole, and there were obvious differences among different regions. Therefore, we should optimize the feed ratio of broiler breeding, formulate differentiated broiler breeding schemes, promote large-scale broiler breeding according to local conditions, and accelerate the cultivation of talents in the field of broiler breeding. [ABSTRACT FROM AUTHOR]

The relationship between farm size expansion and efficiency is a key topic in agricultural economics, especially for achieving sustainable land use and food security. While existing literature focuses on land productivity, technical efficiency, and total factor productivity, the link between farm size and cost efficiency remains less explored. Cost efficiency is a critical indicator of production effectiveness and directly impacts agricultural sustainability and food security. This paper analyzes how farm size expansion affects the cost efficiency of Chinese rapeseed production, with a particular emphasis on sustainable agricultural production and food security. Our findings indicate an average cost efficiency of 0.740 for rapeseed in China, suggesting potential for improvement. We observe an inverted U-shaped relationship between farm size and rapeseed cost efficiency, with variations based on regional and topographic conditions. Optimal rapeseed farm size is between 10 and 30 mu in eastern and central China, and smaller than 10 mu in western China. Interestingly, in central China and plains regions, larger farm sizes have a less negative impact on cost efficiency. Finally, increasing plot size positively moderates the relationship between farm size and rapeseed cost efficiency, suggesting benefits from expanding both plot and farm sizes simultaneously. These findings provide empirical evidence to inform policy decisions related to sustainable land use, cost-efficient agriculture, and food security. [ABSTRACT FROM AUTHOR]

The transportation of shipments by rail is usually more expensive than other modes of transport. The costs are dependent on different factors, like the length of the train route, energy consumption based on traction, or the number of crew members in the train. The total price for using the railway infrastructure is also calculated, as is the total weight of the railway vehicle—the weight of the shipment and the weight of the wagon. The different types of wagons have different properties. For the operators, it is an ideal situation to have good values of the technical coefficient of tare. In the case of good values, the operator has effectively used their vehicle park. Railway transport should be affordable for customers. By operating non-efficient wagons, transport is more expensive and has low efficiency. By reducing the dead weight of the wagon, it is possible to reduce the cost rate. In synergy with this, more efficient and eco-friendly transportation can be achieved by reducing energy consumption. By reducing energy consumption, it is possible to get closer to the goal of the European Union, which is to reduce greenhouse gases from transport. [ABSTRACT FROM AUTHOR]

In this paper, we seek to break new ground by empirically investigating the relationship between cooperating entities, local government institutions and transaction costs and its effect on cost efficiency for water services through consortia in Brazilian local government. Drawing on an institutional and transaction cost framework, our results show that the institutional arrangements employed in water service provision have had a significant effect on cost efficiency, measured by total expenditure per user, between 2011 to 2019. Through a Generalized Estimating Equations (GEE), we found that cost efficiency increases slowly for those units performing under bureaucracies and faster under public enterprises. In all instances, dedicated asset specificities and contract management complexity explained differences in water service provision cost efficiency. These findings have theoretical significance as well as significant public policy implications for intermunicipal cooperative agreements. [ABSTRACT FROM AUTHOR]

Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of distributed generation units and capacitor banks. This placement is crucial not only for optimizing energy loss and enhancing bus voltage stability but also for promoting sustainable energy use and reducing environmental impact over the long term. By minimizing energy loss and voltage fluctuations, the optimizer contributes to a more sustainable and resilient energy system. It achieves this through the optimal allocation of resources across various load patterns within a 24 h period and is tested on the ALG-AB-Hassi-Sida 157-bus distribution network in South Algeria. Comparative analysis with existing algorithms—such as the Liver Cancer Algorithm, Walrus Optimization Algorithm, and Zebra Optimization Algorithm—demonstrates the superior performance of the Energy Valley Optimizer. It not only enhances technical and economic efficiencies but also significantly lowers the total cost of energy over 24 years, thus supporting sustainable development goals in energy management. [ABSTRACT FROM AUTHOR]

Objectives of our study are to develop a procedure for intertemporal comparison of both technical and cost efficiency and estimate farm efficiency for the Korean rice industry from 2003 to 2017. The newly developed base‐year procedure excludes frontier shift and price effects from the standard procedure for intertemporal comparison. An adjusted central limit theorem for sample T‐tests is applied to avoid potential bias from efficiency scores by the Data Envelope Analysis. Our empirical results show that the two procedures yield different scores and trends. The standard approach indicates declining efficiency, while the base‐year method shows overall improvement in farm efficiency. [ABSTRACT FROM AUTHOR]

Hand gesture recognition has become increasingly popular as a practical means of enhancing human-computer interaction, especially with its widespread adoption in gaming devices like Xbox and PS4, as well as in other devices such as laptops and smartphones. This technology finds applications in various fields, including accessibility support, crisis management, and medicine. Typically, these systems employ Java and a comprehensive database, showcasing various evolutionary methods and precise descriptions, along with the output and tests conducted to refine the software artifact. The proposed system is at the intersection of machine learning and image processing, utilizing different APIs and tools to streamline processes and enhance customization. It aims to be developed using OpenCV and Python, leveraging the former for image processing and the latter for machine learning. This results in a lighter system with less complex code and a reduced database footprint. This approach enables the system to run efficiently even on mini computers without compromising user experience, leading to a cost-effective solution capable of handling various tasks. [ABSTRACT FROM AUTHOR]

Peptide pools consist of short amino acid sequences and have proven to be versatile tools in various research areas in immunology and clinical applications. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products which makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. Usually, this would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, worsening the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector at 214 nm for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF advanced, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein–Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of cost efficiency on non-performing loans (NPLs) in Zimbabwe during dollarisation. The research applies the random effects and bootstrap quantile regression models using the full dollarisation era dataset for 13 banks from 2009 to 2017. The obtained results revealed that: (i) the average cost efficiency score for the Zimbabwean banking industry is 81.36%, (ii) improvement in cost efficiency leads to an increase in NPLs but begins to fall for a cost inefficiency level of 7.14% and below, (iii) the effect of bank cost efficiency on NPLs is prominent and highly significant at a higher quantile (90th), (iv) the interaction effect between cost efficiency and bank size on NPLs is negative and significant. According to these results, NPLs tend to fall when large banks are more costefficient. Thus, the present study recommends that banks employ strategies that simultaneously improve the asset base and cost efficiency. [ABSTRACT FROM AUTHOR]

The policy of "changing grain to forage" is an important means to optimize the structure of farming and breeding, a powerful measure to boost the agricultural economy, and the core of promoting high-quality development of the aquaculture industry. Based on the double difference model, panel data from eight provinces implementing the "changing grain to forage" policy was selected to explore the impact of the implementation of the "changing grain to forage" policy on the scale of livestock and poultry breeding. The research results show that the implementation of the "changing grain to forage" policy has a certain driving effect on the expansion of livestock and poultry breeding scale in China. The level of intelligent breeding and fixed asset investment has a significant promoting effect on the scale of livestock and poultry breeding. The price of calves and the intensity of disease occurrence have inhibitory effects on the scale of livestock and poultry farming. Further research has found that the implementation of the "changing grain to forage" policy can significantly promote the large-scale development of livestock and poultry in breeding farms. The level of intelligent breeding has a more significant positive effect on large-scale breeding farms. Compared to medium scale farms, the intensity of disease occurrence has a relatively small adverse impact on large-scale farms. [ABSTRACT FROM AUTHOR]

This research has investigated the impact of market competition on efficiency and profitability in banking sector of Pakistan with mediating role of credit risk. Panel data of 19 conventional banks operating in Pakistan has been used for the time period of 2006-2016. By using Panel data techniques this study has found that market competition has significant impact on profitability and efficiency of Pakistani banks. Credit risk is positively and significantly related with market competition. Moreover, the impact of credit risk on banks profitability and efficiency is significant and negative. The empirical findings show that credit risk mediates the relationship between market competition and ROA as well as market competition and cost efficiency. The results of this study may help to suggest modifications in current banking principles to boost market competition, to certify financial stability and to increase banks efficiency and profitability. [ABSTRACT FROM AUTHOR]