Cost Model Research Articles

The real effects of monetary shocks: Evidence from micro pricing moments

Empirically, what pricing moments are informative about monetary non-neutrality? The frequency of price changes is robustly informative among a set of pricing moments and across specifications: A lower frequency is statistically significantly associated with higher monetary non-neutrality, in line with models of price rigidities. Other moments that describe the price change distribution are not consistently or significantly related to monetary non-neutrality. While the frequency explains the largest share of variation in non-neutrality, no pricing moments individually or jointly explain a majority of the variation in a linear empirical setting. Non-pricing moments explain additional variation, however are not consistently associated with monetary non-neutrality. A multi-sector menu cost model featuring different price adjustment technologies across sectors can rationalize our main findings.

A generalized inefficiency model with input and output dependence

In this paper we propose a general inefficiency model, in the sense that technical inefficiency is, simultaneously, a function of all inputs, outputs, and contextual variables. We recognize that change in inefficiency is endogenous or rational, and we propose an adjustment costs model with firm-specific but unknown adjustment cost parameters. When inefficiency depends on inputs and outputs, the firm's optimization problem changes as the first order conditions must take into account the dependence of inefficiency on the endogenous variables of the problem. The new formulation introduces statistical challenges which are successfully resolved. The model is estimated using Maximum Simulated Likelihood and an empirical application to U.S. banking is provided.

Environmental Costing Model, Applied to a Lasallian University Case Study

Objective: to develop an environmental costing model by applying a case study to the Lasallian University of the municipality of Caldas (Colombia), which will serve as a support and motivation for private and public organizations, in order to measure the cost and benefits. Method: As the world evolves, the importance of taking into account the environment has been recognized, and the desire to pay attention and reduce environmental damage, pollution, has increased dramatically, therefore, it will be analyzed by means of a case study the environmental costing and its impact on the Lasallian University. Results and Conclusions: The result obtained is beneficial for the environment and the company, according to this model, investing in the environment yields a great percentage of financial savings and a great protection to the planet earth, guaranteeing the social responsibility that one has in front of the subject. Repercussions of the research: Some large organizations, other medium and small companies, do not take into account the associated environmental impacts, lack of will. Mostly they prefer to pay penalties and environmental taxes, rather than make a small investment to protect the planet, the implementation of environmental costs can positively affect financial issues. Originality/value: This paper provides an overview of the challenges and enablers of environmental costs in organizations.

A compact environmental performance testing apparatus for ceramic matrix minicomposites

Minicomposite, as the elementary scale of the full-scale ceramic matrix composites (CMCs), has been commonly considered as the appropriate specimen type for basic research on environmental behavior of CMCs due to its simple structure, low fabrication cost and mature modeling foundation. However, its size is too small relative to the full-scale CMCs, resulting in the existing environmental performance testing equipment developed for macrocomposites not matching it in all respects. In order to fill this gap, a compact environmental performance testing apparatus, which consists mainly of a two-zone furnace, gas humidifier, control system and a pair of quartz tubes and high temperature specimen grips, has been designed and built here. Creep test of SiC fiber at elevated temperatures from 800 to 1100 °C with water vapor and oxidation test of SiC/SiC minicomposite at 1316 °C in stress-free wet oxygen environment were carried out respectively to verify the accuracy and reliability of the rig. With the apparatus, the environmental degradation mechanism of CMCs can be quantitatively analyzed, which lays a foundation for the service life prediction and environmental performance optimization of CMCs.

Assembly-based flood repair cost and time models for industrial buildings in Turkey

Flooding is one of the most frequent hazard events significantly affecting the industry in Turkey, leading to severe economic losses and business disruptions. To predict the direct flood losses and business downtimes on the industry, this study proposes probabilistic cost and time models of repairing direct physical flood damage to industrial buildings in Turkey. Using field notes and literature reviews, a typical industrial building was first disassembled into a list of building components vulnerable to flooding. With a focus on façade and interior building components, the flood damage potential of each component was assessed at different flood depths and velocities. Damage state relationships were established for the building components to connect their damage levels under flood actions to their individual repair work. Using the assembly-based approach, costs and times of repairing each flood-damaged component and their associated variabilities were assembled in a probabilistic approach to develop total flood repair cost and time models. The results show that typical repair costs and times for facilities subjected to significant flood depths and velocities might reach substantial levels, up to 28% of building replacement costs and 165 working days on average. The proposed models systematically incorporate existing important uncertainties, therefore, provide reliable estimates.

Pricing method of shared energy storage bias insurance service based on large number theorem

Under the goal of “double carbon”, energy storage is gradually recognized by the society as a means to adjust the output deviation of new energy sources. However, the development of energy storage industry is limited due to the high cost and unclear revenue model of energy storage batteries. Based on this, this paper proposes a business model in which shared energy storage operators provide bias insurance services for new energy sources. Firstly, based on the perspective of commercial insurance, the business model of the shared energy storage operator providing deviation insurance service is designed; secondly, based on the law of large numbers and the actuarial theory of insurance; and finally, the validity of the model is verified through calculation examples, and the feasibility of the proposed business model is also proved. The research results show that compared with the installed capacity of shared energy storage deviation insurance mode reduces 81.57 % compared with new energy storage, and the insurance cost of unit installed capacity of new energy station saves 71.07 % compared with the cost of self-built energy storage cost and deviation assessment cost, which greatly improves the energy storage utilization efficiency and the economic benefits of energy storage operators. The insurance, a financial product explored in this paper, enriches the profit model of energy storage, provides a feasible path for energy storage investors to lock in profits in advance, helps to stimulate the enthusiasm of energy storage investment, and promote the development of China's new energy and energy storage industry.

A fuzzy goal programming model for time, cost, and quality trade-off problem in metro construction projects considering sustainable development

When it comes to sustainable development in a country, transportation plays a significant role. It goes without saying that among various modes of transportation, metro has obtained an outstanding place in the intra-city transportation sector. Thus, accurately assessing the development condition of the urban metro system is inevitable to achieve its sustainable development. Given the importance of this issue, the main purpose of this study is to apply a new fuzzy model to the trade-offs of time, cost, and quality when planning metro construction projects to help achieve sustainable development. This model focuses on three pillars of sustainability: social, economic, and environmental. The research methodology used in this study is a survey and mathematical modelling. For this purpose, a new fuzzy goal programming model is developed. Finally, the model’s efficiency is investigated using sensitivity analysis. For decision-makers, the proposed model provides highly useful results. They are able to fulfil the social and environmental pillars of sustainable development by significantly reducing the completion time and improving the quality of the project. Moreover, by controlling the increase in costs, they can meet the economic pillar. The presented model provides appropriate answers to the problem by the scenarios considered by project managers.

Comparative Analysis of Educational Approaches: Unveiling Strengths across Attributes

Design plays a pivotal role in the successful development of any interactive learning environment (ILE). Furthermore, in the realm of technology-enhanced learning (TEL), the design process necessitates contributions from a wide array of expertise areas. Therefore, individuals engaged in tool development must directly confront the design challenge from multiple standpoints. This article aims to present a comprehensive analysis of current research that centers on the utilization of various approaches as a means of enhancing technology-driven learning environments. The objective is to investigate how much of its instructional promise is genuinely put into practical implementation. The review exclusively considers empirical studies that have been published in peer-reviewed scholarly journals, focusing specifically on the application of diverse approaches as educational environments. Over the past ten years, the methodology of design-based research has proven its potential in both the research and design aspects of technology-enhanced learning environments (TELEs). This article delineates and characterizes design-based research, outlining its significance in the development of technology-enhanced learning environments (TELEs). It also introduces principles for the integration of design-based research into TELEs, and deliberates on the forthcoming challenges associated with this approach. The introduction of technology-enhanced learning (TEL) techniques has transformed the allocation of the most crucial resource in the education system: the time of educators and learners. Although new technology holds the promise of increased personalization and efficiency, the impact on staff time must be meticulously analyzed. Without careful consideration, TEL methods might escalate expenses without proportionate advantages. The paper evaluates various methods of comparing teaching time costs between TEL and traditional approaches. The conclusion suggests that cost-benefit modeling conducted within the institution provides the most accurate means of comprehending how educators can leverage technology to attain the level of efficiency that renders personalization economically viable. Options explored include Interactive Online Courses, Virtual Reality Classrooms, Gamified Learning Platforms, Personalized Learning AI, and Collaborative Social Learning. Assessment criteria encompass Learning Effectiveness, Engagement, Adaptability, Skill Transfer, Cost, Accessibility, User Experience, and Data Privacy. The examination serves as a foundation for establishing prerequisites tailored to a forward-looking cost-benefit framework. The process commences with strategic decisions aimed at realizing the advantages of Technology-Enhanced Learning (TEL). These decisions, in turn, inform the identification of probable essential expenditures, thus delineating the inherent "benefits-oriented cost model." A key benefit of this approach is that it empowers innovators to strategically plan and comprehend the dynamic between anticipated educational gains and potential teaching expenses.

Robotic organism targets regional coverage capture path planning for marine aquafarm based on value iteration network

The application of robots in the field of Marine aquatic organisms capture can greatly improve the fishing efficiency and economy of seafood. The purpose for path planning of underwater vehicle manipulator system (UVMS) is to capture the most organisms in the shortest time with no obstacle collisions. This paper has proposed a novel cost modelling algorithm for the collision avoidance, manipulation and vehicle movement during the target capture process. On the underwater unknown and blurred environment, a novel double value iteration network with long short-term memory (LSTM) network has been proposed on the basis of value iteration networks. The proposed improved double value iteration network can predict the blurred and unknown environment, plan capture strategy with the calculated collision risk and movement cost. In the value iteration module, the use of LSTM network can improve the stability of training and the performance of the model. Moreover, a novel cooperative path planning model for task allocation has been proposed to improve capture efficiency. Simulations on robot and multiple robots capture planning have verified the network performance.

Understanding Ride-Hailing Sharing and Matching in Chicago Using Travel Time, Cost, and Choice Models

Ride-hailing data is sparingly available throughout the U.S., which limits researchers’ understanding of the mode. Chicago is one of a few cities that have mandated ride-hailing companies to submit detailed trip data to their local transportation agency. The dataset is one of the few to contain trip-level attributes such as fare, travel time, and trip length. Most research using the Chicago dataset has focused on understanding why people use ride-hailing. This study focuses on why ride-hailing passengers choose shared over private trips and what influences the shared trips to be matched. Trips to/from airports are less likely to be shared. Trips to/from low-income areas are more likely to be shared. Longer shared trips are more likely to be matched, shared trips to/from dense areas are more likely to be matched, and shared trips between areas with a high number of shared trips are more likely to be matched. Matching an additional shared trip with another adds approximately 4 min to a trip. Ride-hailing users’ value of time is found to be $48.23 per hour. Understanding travel behavior is important for all modes of transportation including ride-hailing. The results of this paper can be applied to guide polices aiming to promote more sustainable transportation modes.

Towards a DISSECT-CF extension for simulating function-as-a-service

ABSTRACT Serverless computing is a new way of delivering cloud services that abstracts a user from the burden of managing resources and infrastructure. Although a few serverless simulators have been developed, they do not compare to services that are offered by commercial providers. Developing a comprehensive serverless simulation framework is essential towards evaluating scenarios reliant on the serverless paradigm. This paper focuses on introducing a serverless computing model to the DIScrete event baSed Energy Consumption simulaTor for Clouds and Federations (DISSECT-CF) simulator to enable simulating realistic function-as-a-service (FaaS) solutions. This new model is capable of imitating serverless providers in terms of cost model, associating triggers, extracting performance metrics, and customising the configurations of functions.

Responsive Parallelism with Synchronization

Many concurrent programs assign priorities to threads to improve responsiveness. When used in conjunction with synchronization mechanisms such as mutexes and condition variables, however, priorities can lead to priority inversions, in which high-priority threads are delayed by low-priority ones. Priority inversions in the use of mutexes are easily handled using dynamic techniques such as priority inheritance, but priority inversions in the use of condition variables are not well-studied and dynamic techniques are not suitable. In this work, we use a combination of static and dynamic techniques to prevent priority inversion in code that uses mutexes and condition variables. A type system ensures that condition variables are used safely, even while dynamic techniques change thread priorities at runtime to eliminate priority inversions in the use of mutexes. We prove the soundness of our system, using a model of priority inversions based on cost models for parallel programs. To show that the type system is practical to implement, we encode it within the type systems of Rust and C++, and show that the restrictions are not overly burdensome by writing sizeable case studies using these encodings, including porting the Memcached object server to use our C++ implementation.

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water.

Simulations of carbon dioxide (CO2) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. We show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

The construction of environmental cost accounting system - based on ecological perspective

Abstract Re-conceptualization of environmental costs based on the ecological economy perspective. Through the analysis of the general domestic and international environment, it is found that the development of ecological economy is an inevitable choice in China at this stage. Therefore, we take the ecological perspective of environmental cost accounting as the basis of research. The research is based on the resources consumed in the production process and the need to spend a certain amount of money for treatment and protection after causing the decline of environmental service functions, respectively. A set of environmental cost accounting system based on CPCA-environmental cost model is constructed. The calculation shows that in the production cost stage, the environmental cost caused by resource depletion accounts for 23%. The percentage of environmental cost caused by human damage is 36%. The environmental cost caused by environmental degradation is the highest. The percentage is 43%. In the maintenance phase, the environmental cost of wastewater treatment is 18%. The share of environmental costs for waste gas treatment is 27%. The highest environmental cost is the environmental protection cost. Its share is as high as 55%.

Optimizing Keyword Search Over Federated RDF Systems

The issue of keyword search in federated resource description framework(RDF) systems is revisited in this paper. Numerous independent SPARQL endpoints that solely offer SPARQL query interfaces make up a federated RDF system. Others find it challenging to remotely build up the global inverted indices over the full RDF network by downloading the dataset at various SPARQL endpoints. This poses a challenge for existing keyword search approaches. In this paper, we propose a keyword search approach for federated RDF systems without building up global inverted indices on the entire RDF graph. We build an offline schema graph for the federated RDF system. During query evaluation, the full-text search interfaces provided by existing SPARQL endpoints were used to map keywords to vertices in the schema graph. Subsequently, the schema graph was explored to construct SPARQL queries from the keywords. The constructed queries were evaluated over the underlying federated RDF systems. Some cost models were proposed to measure keyword mapping and query construction. On the other hand, to further improve the efficiency, a multiple query optimization strategy was designed to rewrite the queries and share the common computation during evaluation. Extensive experiments on real RDF datasets show that the proposed techniques are effective.

Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions

In this article, we study the problem of multiple stochastic agents interacting in a dynamic game scenario with continuous state and action spaces. We define a new notion of stochastic Nash equilibrium for boundedly rational agents, which we call the entropic cost equilibrium (ECE). We show that ECE is a natural extension to multiple agents of maximum entropy optimality for a single agent. We solve both the “forward” and “inverse” problems for the multi-agent ECE game. For the forward problem, we provide a Riccati algorithm to compute closed-form ECE feedback policies for the agents, which are exact in the linear-quadratic-gaussian case. We give an iterative variant to find locally ECE feedback policies for the nonlinear case. For the inverse problem, we present an algorithm to infer the cost functions of the multiple interacting agents given noisy, boundedly rational input and state trajectory examples from agents acting in an ECE. The effectiveness of our algorithms is demonstrated in a simulated multi-agent collision avoidance scenario, and with data from the INTERACTION traffic dataset. In both cases, we show that, by taking into account the agents' game theoretic interactions using our algorithm, a more accurate model of agents' costs can be learned, compared with standard inverse optimal control methods.

EE27 A Novel Cost Impact Analysis Framework and Model to Evaluate Medications for Opioid Use Disorder within the US Criminal Justice System

Opioid use disorder (OUD) is common among incarcerated, but access to FDA-approved medications for OUD (MOUD) is limited. The purpose of this study was to develop a novel model framework to assess the cost impact of implementing a MOUD program within the criminal justice system (CJS).

Difference Analysis of Different Explosion Load Simulation Methods Based on LS-DYNA

LS-DYNA provides a variety of different explosion load simulation methods, which are widely used in the field of explosion shock. Compared with the direct application of explosion load on the structural surface, the simulation method of establishing the air domain is more complex, but it can reproduce the evolution process of the explosion flow field and consider the interaction between the shock wave and the structure. The simulation results are more consistent with the actual situation. In this paper, the four commonly used explosion load simulation methods in LS-DYNA software are compared and analyzed, and the sensitivity analysis of grid size is carried out. The differences in the results of the four explosion load simulation methods under typical explosion conditions are compared and analyzed from the aspects of explosion shock wave waveform, arrival time, overpressure peak and specific impulse. The analysis results show that the proportional detonation distance of 0.8 m/kg1/3 is the boundary point of grid sensitivity ; under the same grid size, different explosion load simulation methods have little effect on shock wave arrival time, but have obvious influence on overpressure peak value and specific impulse. It is critical to reasonably select the termination time of the low-dimensional model when using the mapping method ; method 1 and method 2 are preferred for simulation without considering the computational cost or small model size. When the model is large, method 3 and method 4 should be preferred to improve the computational efficiency.

Enhancing colon cancer care in restricted-resource settings.

Colon cancer ranks third among the most frequently diagnosed cancers worldwide and was projected to claim more than 900 000 lives in 2020, according to the International Agency for Research on Cancer's GLOBOCAN data. 1 Sung H Ferlay J Siegel RL et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; 71: 209-249 Crossref PubMed Scopus (30514) Google Scholar The overall survival rate for colon cancer varies on the basis of clinical and pathological factors, such as staging, performance status, and geographical location. Despite the lower incidence, survival of colon cancer in low-income and middle-income countries (LMICs) is considerably reduced compared with high-income and very-high-income countries, which is probably attributable to disparities in diagnostic and treatment access. Considering expected increases in colon cancer incidence due to demographic and dietary changes, there is an urgent and unmet need to enhance cancer care in LMICs through better resource allocation and cost-effective interventions to achieve optimal value for money and reduce health inequalities. 2 Khan SZ Lengyel CG Challenges in the management of colorectal cancer in low- and middle-income countries. Cancer Treat Res Commun. 2023; (published online April 6.)https://doi.org/10.1016/j.ctarc.2023.100705 Crossref Scopus (0) Google Scholar Global application of National Comprehensive Cancer Network resource-stratified guidelines for systemic treatment of colon cancer: a population-based, customisable model for cost, demand, and procurementWe have developed a customisable model that can be applied at global, national, and subnational levels to estimate systemic treatment needs, forecast drug procurement, and calculate expected drug costs on the basis of local data. This tool can be used to plan resource allocation for colon cancer globally. Full-Text PDF

Global application of National Comprehensive Cancer Network resource-stratified guidelines for systemic treatment of colon cancer: a population-based, customisable model for cost, demand, and procurement.

Resource-stratified guidelines (RSGs) can inform systemic treatment decisions in the face of limited resources. The objective of this study was to develop a customisable modelling tool to predict the demand, cost, and drug procurement needs of delivering National Comprehensive Cancer Network (NCCN) RSG-based systemic treatment for colon cancer. We developed decision trees for first-course systemic therapy for colon cancer based on the NCCN RSGs. Decision trees were merged with data from the Surveillance, Epidemiology, and End Results programme, the International Agency for Research on Cancer's GLOBOCAN 2020 national estimates for colon cancer incidence, country-level income data, and data on drug costs from Redbook (USA), the Pharmaceutical Benefits Scheme (Australia), and the Management Sciences for Health 2015 International Medical Products price guide to estimate global treatment needs and costs, and forecast drug procurement. Simulations and sensitivity analyses were used to explore the effect of scaling up services globally and the effect of alternative stage distributions on treatment demand and cost. We generated a customisable model, in which estimates can be tailored to local incidence, epidemiological, and costing data. First-course systemic therapy is indicated in 608 314 (53·6%) of 1 135 864 colon cancer diagnoses in 2020. Indications for first-course systemic therapy are projected to rise to 926 653 in 2040; the indications in 2020 might be as high as 826 123 (72·7%), depending on stage distribution assumptions. Adhering to NCCN RSGs, patients with colon cancer in low-income and middle income countries (LMICs) would constitute 329 098 (54·1%) of 608 314 global systemic therapy demands, but only 10% of global expenditure on systemic therapies. The total cost of NCCN RSG-based first-course systemic therapy for colon cancer in 2020 would be between about US$4·2 and about $4·6 billion, depending on stage distribution. If all patients with colon cancer in 2020 were treated according to maximal resources, global expenditure on systemic therapy for colon cancer would rise to around $8·3 billion. We have developed a customisable model that can be applied at global, national, and subnational levels to estimate systemic treatment needs, forecast drug procurement, and calculate expected drug costs on the basis of local data. This tool can be used to plan resource allocation for colon cancer globally. None.