The Impact of the Digital Economy on Financial Regulatory Costs: An Empirical Analysis Based on the Solow Growth Model

As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.

Cost-Benefit Assessment of Inspection and Repair Planning for Ship Structures Considering Corrosion Model Uncertainty

Owing to high costs and unnecessary inspections necessitated by the traditional inspection planning for ship structures, the risk-based inspection and repair planning should be investigated for the most cost-effective inspection. This paper aims to propose a cost-benefit assessment model of risk-based inspection and repair planning for ship structures subjected to corrosion deterioration. Then, the benefit-cost ratio is taken to be an index for the selection of the optimal inspection and repair strategy. The planning problem is formulated as an optimization problem where the benefit-cost ratio for the expected lifetime is maximized with a constraint on the minimum acceptalbe reliability index. To account for the effect of corrosion model uncertainty on the cost-benefit assessment, two corrosion models, namgly, Paik＇ s model and Guedes Soares＇ model, are adopted for analysis. A numerical example is presented to illustrate the proposed method. Sensitivity studies are also providet. The results indicate that the proposed method of risk-based cost-benefit analysis can effectively integrate the economy with reliability of the inspection and repair planning. A balance can be achieved between the risk cost and total expected inspection and repair costs with the proposed method, which is very. effective in selecting the optimal inspection and repair strategy. It is pointed out that the corrosion model uncertainty and parametric uncertaintg have a significant impact on the cost-benefit assessment of inspection and repair planning.

Cost-benefit Analysis of Scale Pig Breeding in Shandong Province Based on Modified Entropy Weight-TOPSIS Model

According to the relevant statistical data in National Agricultural cost-benefit Data Compilation(2001- 2013),we use the modified entropy weight- TOPSIS model to research the cost-benefit status of scale pig breeding in Shandong Province from the perspective of comparing it with that of the entire country and 9 other main pig producing areas. The results show that compared with the national average,the cost-benefit ratio of small scale pig breeding in Shandong Province is lower,while the cost-benefit ratio of medium scale and large scale pig breeding is significantly improved; the cost-benefit ratio of small scale pig breeding in Shandong Province is basically the same as that in 9 other main pig producing areas,while the cost-benefit ratio of medium scale and large scale pig breeding is higher; the output value of main products and the purchase price of piglet are two major bottlenecks restricting the cost-benefit improvement of scale pig breeding in Shandong Province.

Model of Cost-benefit Flow in Six Green Projects in China

From the point of cost-benefit flow and with the Six Green Projects in China as the case and background, it is criticized that the current natural resource and environmental management and the policies in China have some problems unsolved since the model of cost-benefit flow is still centralized and mainly in an administrative way in spite of many efforts made theoretically and practically. It is suggested that a new model based on market-oriented economy from the point of cost-benefit flow with Six Green Projects Management and Policies System consist of complete natural reserve (NR). Management system included environmental nature reserves in addition to biodiversity nature reserve, paid using nature resources, an environmental conservation and construction industry and renewable resource production incentive system that turn the direct administration and operation to management and services. The detail figure of the new model of cost-benefit flow is provided and the main points related are discussed in this paper.

Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

基于COST-DEA指数法对某三甲医院临床病区成本效率分析

目的测量某三甲医院各临床病区的成本效率、技术效率和配置效率,为实现医院高质量发展和精细化管理提供数据参考。方法利用数据包络法中的CCR、BCC和COST-DEA模型,测量该三甲医院各临床病区的相关效率值。结果2019年该三甲医院各临床病区的成本效率均值为0.675,配置效率均值为0.782,技术效率均值为0.853,纯技术效率均值为0.902,规模效率均值为0.944。51个临床病区中,7个处于规模报酬递增状态,占比13.73%;23个处于规模报酬不变状态,占比45.10%;21个处于规模报酬递减状态,占比41.17%。结论该三甲医院各临床病区成本效率主要受到配置效率的影响,需要合理配置医疗资源;部分临床病区需要提高内部精细化管理水平实现产出增加。

Research on workflow meta model supporting activity based costing

Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.

CGE model-based analysis of the neutralized hybrid carbon policy and its decomposed effects on economic growth,carbon reduction,and energy utilization costs

The hybrid policy is a flexible policy tool that combines features of carbon trading and carbon taxation.Its economic and environmental effects under China's background are still not studied in detail.Given the exogenous carbon reduction targets,carbon prices,and carbon tax-rates,by computable general equilibrium modeling methods and factor decomposition methods,this article investigates direct and cascaded effects of the hybrid policy on economic growth,energy utilization,and carbon emission on the national level and the sector level,with China's national input-output data-set.Stepwisely,policy scenarios with irrational estimated results are selectively excluded based on comprehensive evaluation among economic,carbon reduction and other policy targets.As a result,against national economic conditions in 2007,the hybrid policy,with a carbon reduction target of -10%,a carbon tax-rate of around $10,and a ceiling carbon price of $40,is highly recommended,because of its significant lower economic loss,lower energy utilization cost,and practical robustness against fluctuation of energy market and carbon market.Furthermore,by decomposition analysis,carbon reduction-related costs are decomposed into a direct part that includes carbon allowance price and carbon tax,and an indirect part as the energy price incremental induced by direct carbon costs.Gross carbon reduction may be decomposed into three parts such as energy intensity,economic scale,and technical progress.And,carbon taxation is the main policy tool that stimulates to improve the energy efficiency.

A novel model for cost performance evaluation of pulverized coal injected into blast furnace based on effective calorific value

The combustion process of pulverized coal injected into blast furnace involves a lot of physical and chemical reactions. Based on the combustion behaviors of pulverized coal, the conception of coal effective calorific value representing the actual thermal energy provided for blast furnace was proposed. A cost performance evaluation model of coal injection was built up for the optimal selection of various kinds of coal based on effective calorific value. The model contains two indicators: coal effective calorific value which has eight sub-indicators and coal injection cost which includes four sub-indicators. In addition, the calculation principle and application of cost performance evaluation model in a Chinese large-scale iron and steel company were comprehensively introduced. The evaluation results finally confirm that this novel model is of great significance to the optimal selection of blast furnace pulverized coal.

Modelling spatial variation in the treatment costs of nonpoint source pollution in mountainous regions of southwest China

Non-point source(NPS) pollution is considered to be one of the main threats of the aquatic environment. Mountainous regions are particularly important water sources for urban areas. The various driving factors of NPS pollution such as terrain, precipitation, and vegetation type in mountainous regions show clear spatial heterogeneity. Consequently, the management systems required for NPS pollution in mountainous regions are complex. In this study, we developed a framework to estimate and map the treatment costs for NPS pollution in mountainous regions and applied this method in Baoxing County, a typical mountainous county in Sichuan Province of southwest China. The export levels of total nitrogen(TN) and total phosphorus(TP) in Baoxing County were estimated using the water purification model in InVEST(Itegrated Valuation of Ecosystem Services and Tradeoffs) tool. NPS pollutant treatment costs were calculated based on the level of pollutants exports, water yield, water quality targets, and treatment costs of NPS pollutants per unit mass. The results show that at the watershed level the amounts of TN and TP exported in Baoxing County were below threshold limits. However, at the sub-watershed level, TN and TP excesses of 291.64 and 2.96 tons per year were found, respectively, with mean TN and TP treatment costs of 6.58 US$/hm^2 and 0.35 US$/hm^2. Appraising pollution treatment cost intuitively reflects the overall expenditure in NPS pollution reduction from an economic perspective. This study provides a foundation for the implementation of Payment for Ecosystem Service(PES) and the prevention and control of NPS pollution.

Collaborative optimization model of renewable energy development considering peak shaving costs of various flexibility resources

China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.

NPV risk simulation of an open pit gold mine project under the O'Hara cost model by using Gas

This paper analyzes an open pit gold mine project based on the O'Hara cost model. Hypothetical data is proposed based on different authors that have studied open pit gold projects, and variations are proposed according to the probability distributions associated to key variables affecting the NPV, like production level, ore grade, price of ore, and others, so as to see what if, in a gold open pit mine project of 3000 metric tons per day of ore. Two case scenarios were analyzed to simulate the NPV, one where there is low certainty data available, and the other where the information available is of high certainty. Results based on genetic algorithm metaheuristic simulations, which combine basically Montecarlo simulations provided by the Palisade Risk software, the O'Hara cost model, net smelter return and financial analysis tools offered by Excel are reported, in order to determine to which variables of the project is more sensitive the NPV.

Modeling Anthrax with Optimal Control and Cost Effectiveness Analysis

Anthrax is an infection caused by bacteria and it affects both human and animal populations. The disease can be categorized under zoonotic diseases and humans can contract infections through contact with infected animals, ingest contaminated dairy and animal products. In this paper, we developed a mathematical model for anthrax transmission dynamics in both human and animal populations with optimal control. The qualitative solution of the model behaviour was analyzed by determining Rhv, equilibrium points and sensitivity analysis. A vaccination class was incorporated into the model with waning immunity. Local and global stability of the model’s equilibria was found to be locally asymptotically stable whenever Rhv Rhv. It was revealed that reducing animal and human interaction rate, would decrease Rhv. We extended the model to optimal control in order to find the best control strategy in reducing anthrax infections. It showed that the effective strategy in combating the anthrax epidemics is vaccination of animals and prevention of humans.

Green Investment Cost Optimization Model in the Supply Chain

The objective of this study is to develop a model that determines the optimal points for investment in green management by defining a mathematical relationship between carbon trading profits and investments in green management using a company’s supply chain information. To formulate this model, we first define and analyze a green supply chain in a multi-dimensional and quantitative manner. The green investment alternatives considering in our model are as follows: 1) purchasing eco-friendly raw materials that cost more than conventional raw materials but whose use in production results in lower CO2 emissions;2) replacing current facilities with new eco-friendly facilities that have the capability to reduce CO2 emissions;and 3) changing modes of transport from less eco-friendly to more eco-friendly modes. We propose a green investment cost optimization (GICO) model that enables us to determine the optimal investment points. The proposed GICO model can support decision-making processes in green supply chain management environments.

A Review of Energy-Related Cost Issues and Prediction Models in Cloud Computing Environments

With the expansion of cloud computing,optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important,since it directly affects providers’revenue and customers’payment.Thus,providing prediction information of the cloud services can be very beneficial for the service providers,as they need to carefully predict their business growths and efficiently manage their resources.To optimize the use of cloud services,predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs.However,such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine(PM)but also at the level of the Virtual Machine(VM)in order to make improved cost decisions.Therefore,this paper presents a comprehensive literature review on the subject of energy-related cost issues and prediction models in cloud computing environments,along with an overall discussion of the closely related works.The outcomes of this research can be used and incorporated by predictive resource management techniques to make improved cost decisions assisted with energy awareness and leverage cloud resources efficiently.

A Heuristics-Based Cost Model for Scientic Workow Scheduling in Clou

Scientic Workow Applications(SWFAs)can deliver collaborative tools useful to researchers in executing large and complex scientic processes.Particularly,Scientic Workow Scheduling(SWFS)accelerates the computational procedures between the available computational resources and the dependent workow jobs based on the researchers’requirements.However,cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate(near-optimal)solution within polynomial computational time.Motivated by this,current work proposes a novel SWFS cost optimization model effective in solving this challenge.The proposed model contains three main stages:(i)scientic workow application,(ii)targeted computational environment,and(iii)cost optimization criteria.The model has been used to optimize completion time(makespan)and overall computational cost of SWFS in cloud computing for all considered scenarios in this research context.This will ultimately reduce the cost for service consumers.At the same time,reducing the cost has a positive impact on the protability of service providers towards utilizing all computational resources to achieve a competitive advantage over other cloud service providers.To evaluate the effectiveness of this proposed model,an empirical comparison was conducted by employing three core types of heuristic approaches,including Single-based(i.e.,Genetic Algorithm(GA),Particle Swarm Optimization(PSO),and Invasive Weed Optimization(IWO)),Hybrid-based(i.e.,Hybrid-based Heuristics Algorithms(HIWO)),and Hyper-based(i.e.,Dynamic Hyper-Heuristic Algorithm(DHHA)).Additionally,a simulation-based implementation was used for SIPHT SWFA by considering three different sizes of datasets.The proposed model provides an efcient platform to optimally schedule workow tasks by handing data-intensiveness and computational-intensiveness of SWFAs.The results reveal that the proposed cost optimization model attained an optimal Job completion time(makespan)and total computational cost for small and large sizes of the considered dataset.In contrast,hybrid and hyper-based approaches consistently achieved better results for the medium-sized dataset.

Guaranteed Cost Control for Uncertain Nonlinear Time-Delay Neutral Systems Based on T-S Fuzzy Model

The problem of guaranteed cost fuzzy controller is studied for a class of nonlinear time-delay neutral sys-tems with norm-bounded uncertainty based on T-S model. The sufficient conditions are first derived for the existenceof guaranteed cost fuzzy controllers. These sufficient conditions are equivalent to a kind of linear matrix inequalities.Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteedcost controller.

The Calculation Model for Operation Cost of Coal Resources Development Based on ANN

On the basis of analysis and selection of factors influencing operation cost of coal resources development, fuzzy set method and artificial neural network (ANN) were adopted to set up the classification analysis model of coal resources. The collected samples were classified by using this model. Meanwhile, the pattern recognition model for classifying of the coal resources was built according to the factors influencing operation cost. Based on the results achieved above, in the light of the theory of information diffusion, the calculation model for operation cost of coal resources development has been presented and applied in practice, showing that these models are reasonable.