Cost Allocation Research Articles

A generalized data envelopment analysis approach for fixed cost allocation with preference information

Exploring a commonly acceptable fixed cost allocation (FCA) scheme is a challenging yet significant task, since one may contend with conflicting objectives. In this paper, we propose a new data envelopment analysis based FCA technique. The proposed approach aims to balance individual efficiency guarantees and collective preference objectives simultaneously. Particularly, a preference value loss (PVL) index is explicitly constructed to quantify the impact of preference considerations. Moreover, our generalized FCA strategy guarantees a minimal PVL and provides a reasonable and realizable lexicographic evaluation procedure to single out the final FCA scheme. Interestingly, the efficiency invariance and efficiency variance approaches from the prior literature are special cases of our proposed approach. Finally, the proposed approach is validated with a numerical example and an empirical application to bank maintenance fee distribution.

Molecular analysis of broad-spectrum induced resistance in rice by the green leaf volatile Z-3-hexenyl acetate.

Green leaf volatiles (GLVs), volatile organic compounds released by plants upon tissue damage, are key signaling molecules in plant immunity. The ability of exogenous GLV application to trigger an induced resistance (IR) phenotype against arthropod pests has been widely reported, but its effectiveness against plant pathogens is less well understood. In this study, we combined mRNA sequencing-based transcriptomics and phytohormone measurements with multispectral imaging-based precision phenotyping to gain insights into the molecular basis of Z-3-hexenyl acetate-induced resistance (Z-3-HAC-IR) in rice. Furthermore, we evaluated the efficacy of Z-3-HAC-IR against a panel of economically significant rice pathogens: Pyricularia oryzae, Rhizoctonia solani, Xanthomonas oryzae pv. oryzae, Cochliobolus miyabeanus, and Meloidogyne graminicola. Our data revealed rapid induction of jasmonate metabolism and systemic induction of plant immune responses upon Z-3-HAC exposure, as well as a transient allocation cost due to accelerated chlorophyll degradation and nutrient remobilization. Z-3-HAC-IR proved effective against all tested pathogens except for C. miyabeanus, including against the (hemi)biotrophs M. graminicola, X. oryzae pv. oryzae, and P. oryzae. The Z-3-HAC-IR phenotype was lost in the jasmonate (JA)-deficient hebiba mutant, which confirms the causal role of JA in Z-3-HAC-IR. Together, our results show that GLV exposure in rice induces broad-spectrum, JA-mediated disease resistance with limited allocation costs, and may thus be a promising alternative crop protection approach.

Pricing and Coordinating the Lease-Oriented Closed-Loop Supply Chain for Construction Machinery in the Era of Carbon Tax

Promoting sustainable production and consumption practices in the construction machinery industry is crucial for achieving energy savings and reducing carbon emissions. However, there is a lack of targeted studies addressing the challenge of scaling up leasing and recycling while maximizing economic benefits for enterprises. To fill this gap, this paper presents a lease-oriented closed-loop supply chain model that incorporates a carbon tax policy to investigate the impact of the carbon tax rate and consumer preferences for remanufactured products on the supply chain and introduces a leasing compensation–cost apportioning combined contract to achieve supply chain coordination in the construction machinery sector. The model considers differential selling and leasing prices for new and remanufactured products, as well as the recovery rate, under both centralized and decentralized decision-making approaches. The study explores the interrelationships between various parameters through sensitivity analysis and numerical simulation. The results demonstrate that within a certain range of the cost apportioning proportional coefficient and leasing compensation proportional coefficient, the combined contract can lead the supply chain to achieve Pareto optimality. As the carbon tax rate increases, it was observed that the profits for all parties in the supply chain tend to decrease. However, due to the increased demand for remanufactured products, the product recovery rate improves, resulting in a reduction in total carbon emissions in the closed-loop supply chain of construction machinery. Moreover, the profits of all parties and the total supply chain profits initially decrease and then increase with an increasing preference coefficient for remanufactured products among consumers. By leveraging these factors and adopting effective strategies, such as enhancing consumer recognition of remanufactured products and optimizing pricing and cost allocation, it is indeed possible for the profits of all parties and the total profits in the supply chain to surpass the initial values, even in the face of increasing carbon tax rates. This demonstrates the potential for aligning sustainability objectives with economic benefits in the construction machinery industry.

Improving the Allocation of Indirect Costs Using the FABC Method (Based on the Example of a Paper and Cardboard Manufacturing Company)

Every enterprise seeks to determine as accurately as possible the cost of the products or services it produces. The allocation of indirect costs causes considerable difficulties in this process. In the search for the most accurate alternatives for allocating indirect costs, the Activity Based Costing (ABC) method has become more popular in recent decades and is increasingly used by companies. The ABC method has many advantages, but it also has disadvantages, which have led to further development of the method by proposing newer versions. These include Fuzzy Activity Based Costing (FABC), which reduces the risk of uncertainty in data collection conditions and inaccurate cost allocation. However, while the literature provides a theoretical model of the FABC approach, there is very little research focused on sector-specific companies. Given that the issue of indirect cost allocation is particularly relevant for manufacturing companies, this paper explores the possibilities of applying the FABC method in manufacturing companies, using the example of a paper and cardboard manufacturing company. The aim of the research: after revealing the principles of ABC and FABC implementation, to improve the indirect cost allocation process in a paper and cardboard manufacturing company using the FABC method. The methods used for the study were document analysis, observation, conversation, interview, and fuzzy set analysis. The results showed that the FABC method has lower cost drivers for some activities and higher cost drivers for others than the ABC method. The improvement path developed for the allocation of indirect costs using the FABC approach could serve as a good model for its implementation in other manufacturing sectors.

Optimisation of Buffer Allocations in Manufacturing Systems: A Study on Intra and Outbound Logistics Systems Using Finite Queueing Networks

Optimal buffer allocations can significantly improve system throughput by managing variability and disruptions in manufacturing or service operations. Organisations can minimise waiting times and bottlenecks by strategically placing buffers along the flow path, leading to a smoother and more efficient production or service delivery process. Determining the optimal size of buffers poses a challenging dilemma, as it involves balancing the cost of buffer allocation, system throughput, and waiting times at each service station. This paper presents a framework that utilises finite queueing networks for performance analysis and optimisation of topologies, specifically focusing on buffer allocations. The proposed framework incorporates a finite closed queuing network to model the intra-logistics material transfer process and a finite open queueing network to model the outbound logistics process within a manufacturing setup. The generalised expansion method (GEM) is employed to calculate network performance measures of the system, considering the blocking phenomenon. Discrete event simulation (DES) models are constructed using simulation software, integrating optimisation configurations to determine optimal buffer allocations to maximise system throughput. The findings of this study have significant implications for decision-making processes and offer opportunities to enhance the efficiency of manufacturing systems. By leveraging the proposed framework, organisations can gain valuable insights into supply chain performance, identify potential bottlenecks, and optimise buffer allocations to achieve improved operational efficiency and overall system throughput.

Water resources allocation considering water supply and demand uncertainties using newsvendor model-based framework

A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.

Does affirmative action in politics hinder performance? Evidence from India

This paper examines the consequence of affirmative action for a “middle” ranked group on equity and the leader's overall performance or “efficiency.” The literature on electoral quotas is invested in the equity question for disadvantaged groups, but is mostly silent on this issue. We use a randomized electoral quota for an intermediately ranked caste group (OBCs) in a large state in India to show that overall, such a quota does not affect delivery of public projects, or redistribute projects away from disadvantaged groups (SC/STs). Moreover, we show that when the group is large, the quota may in fact improve leader's performance. The improvement in overall performance does not come at a cost of lower allocation to the most disadvantaged group. We argue and provide suggestive evidence that when the group is large, such a quota for the group increases within-group electoral competition in villages. The result highlights that “efficiency” concerns regarding affirmative action may need reevaluation. It further justifies the targeting of electoral quota policy in India towards jurisdictions where the group is numerous.

Fixed cost allocation based on data envelopment analysis from inequality aversion perspectives

In many real-world cases, fixed cost allocation frequently occurs in constructing the common platform of an organization: all divisions related to the platform must share the platform's fixed cost. Addressing the fixed cost allocation issue has become a vital topic, and numerous approaches have been used, including data envelopment analysis (DEA). However, inequality aversion, one vital concept of fairness concern, is frequently ignored in the previous publications. This paper is devoted to guaranteeing fairness for all decision-making units (DMUs) in allocation solutions from DEA. Firstly, we discuss how inequality impacts DMUs by proposing the concept of “fairness concern disutility” and using various parameters to reflect the negative impact of an unfair allocation plan on DMUs. Secondly, we discuss fixed cost allocation from three perspectives: optimistic, pessimistic, and mixed. Moreover, we give algorithms to obtain a unique, optimal solution and propose theorems to better understand our model. Lastly, we use a numerical example to illustrate the proposed models and theorems before applying our approach to address a fixed allocation issue in a commercial bank. Our analysis results show that the proposed approaches can guarantee fairness in fixed cost allocation.

Analysis of Public Technology Collaborative Innovation Based on Private Technology: A Tripartite Evolutionary Game Approach

Public technology collaborative innovation serves as an essential driving force to implement the innovation-driven strategy as well as promote national and regional economic sustainable development. Moreover, strengthening the construction of public technology collaborative innovation system is likewise of great significance for strengthening the quality and technology level of enterprises, enhancing their independent innovation capability, and achieving strategic transformation. Particularly, collaborative innovation of public technology in accordance with mature private technology enables the efficient allocation of technological and economic resources. In practice, there are still issues including high innovation costs, insufficient motivation, and low efficiency of innovation. Existing research typically ignores the technical cooperation among multiple parties. An evolutionary game model of public technology collaborative innovation is established in this paper to examine the interaction mechanism among the government, enterprises, and technology owners. For the purpose of analyzing the dynamic evolution of public technology collaborative innovation behavior and its influencing factors, numerical simulation experiments were conducted with meaningful results: (1) Setting the cost and benefit allocation coefficient in a scientific manner contributes to system stability and promotes cooperation among game players. (2) Reasonable government subsidies and penalties can assist in the formation of an active technological innovation between the firm and the technology owner. (3) The pricing method of private technology transfer is a significant factor influencing the evolution process. Besides, the adoption of a technology pricing method on the basis of government interests is conducive to the formation of a stable tripartite win-win situation. The research on collaborative innovation of public technology is further expanded in this paper, offering a reference for the formulation of relevant policies aimed at promoting cooperation in public technology innovation.

Can carbon emissions trading improve corporate total factor productivity?

This paper first researches the influence of carbon emissions trading (CET) on corporate total factor productivity (TFP) from three aspects of innovation effect, factor allocation effect and cost effect, and then uses the data of listed corporations from 2008 to 2021, and empirically analyzes each effect by multi-temporal difference-in-difference-in-difference (DDD) model. We find that CET can suppress the corporate TFP through direct effect (cost effect), and improve corporate TFP through indirect effects (innovation effect and factor allocation effect). Overall, the indirect effects are more effective. Moreover, the CET can significantly improve corporate TFP, and it is still true after a set of robustness checks. Heterogeneity analysis indicates that CET has a different influence on different types of corporate TFP, and there are also certain differences in their mechanisms.

Efficiency improvement and balance in fixed cost allocation: A trade-off approach based on DEA

Fixed cost allocation (FCA) is a problem that decision-makers usually encounter in practice. The existing FCA studies based on data envelopment analysis (DEA) have not recognized the trade-off between improving efficiency and balancing FCA result and failed to provide an approach to generate an equilibrium solution between the two goals. In this study, under DEA common-weight evaluation mechanism, we propose an approach for centralized FCA using several principles featuring fairness in the situation where the fixed cost is regarded as a complement of one of the current inputs. It first considers the principle of making equal-proportional efficiency improvements for all the decision-making units (DMUs) in FCA. Then, we define a measure, called “balanced indicator”, to measure the balance of a FCA result. Finally, a bi-objective model is built that considers both the objectives of maximizing the proportional efficiency improvement of the DMUs and improving the balance of the FCA result. A bargaining-game-like model and a trade-off algorithm are provided to generate the final FCA result. Our research contributes by elucidating the trade-off between enhancing efficiency and achieving balance in FCA result. It also makes a distinct contribution by proposing a bargaining-game-like model and a trade-off algorithm to generate a FCA result that is an equilibrium solution between the two goals and ensures no DMU is allocated zero cost. Finally, we demonstrate the superiority of our approach by comparing it with a previous representative approach and applying it to a case study of China National Heavy Duty Truck Group.

Cost Allocation and Strategyproof Mechanism for Cover-set Games

In this paper, we discuss several cost-sharing methods for cover-set games, for example, approximately budget-balanced, in the core, and/or strategyproof. Different from the traditional set cover game, in cover-set game, the elements stand for services, and each agent is both a service provider and receiver. In this study, for unselfish agents, we design a cost allocation method that can recover no less than [Formula: see text] fraction of the total cost, where [Formula: see text] and [Formula: see text] is the maximum number of receiving services among all agents. In addition, for agents who are selfish service providers with privately known valuations, we present a strategyproof charging mechanism, further, the total cost is no more than [Formula: see text] times that of an optimal solution.

Local and utility-wide cost allocations for a more equitable wildfire-resilient distribution grid

Local and utility-wide cost allocations for a more equitable wildfire-resilient distribution grid

On the preferences for an environmentally friendly and fair energy transition: A stated choice experiment for Germany

Based on data from a stated choice experiment in Germany, this paper empirically examines individual preferences for several components of three hypothetical energy policy packages and the status quo policy package of the German energy transition. Our econometric analysis with mixed logit and latent class logit models reveals a high preference for higher targeted shares of renewable energies and for the nuclear phase-out. With respect to the allocation of energy policy costs, we find that the polluter-pays rule is significantly preferred over the ability-to-pay and equal-pay rules. Furthermore, citizens have a significantly positive preference for the financial support for low-income households. These results suggest a strong support for environmentally ambitious energy policy measures that are additionally associated with a fair burden sharing of the corresponding costs. In terms of preference heterogeneity, our empirical analysis reveals that political identification plays an important role for the preferences for environmentally ambitious energy policy measures. Furthermore, high equivalent income has a significantly negative effect on the preferences for the ability-to-pay rule, suggesting the relevance of economic self-interest. In addition, our empirical analysis reveals a strong relevance of trust (besides altruism and perceived unfair cost distribution) for the preferences for social cushioning. This result suggests that it is important for policymakers to convince the population that such social cushioning measures are actually implemented.

Deep Learning Enhanced Volumetric Photoacoustic Imaging of Vasculature in Human.

The development of high-performance imaging processing algorithms is a core area of photoacoustic tomography. While various deep learning based image processing techniques have been developed in the area, their applications in 3D imaging are still limited due to challenges in computational cost and memory allocation. To address those limitations, this work implements a 3D fully-dense (3DFD) U-net to linear array based photoacoustic tomography and utilizes volumetric simulation and mixed precision training to increase efficiency and training size. Through numerical simulation, phantom imaging, and in vivo experiments, this work demonstrates that the trained network restores the true object size, reduces the noise level and artifacts, improves the contrast at deep regions, and reveals vessels subject to limited view distortion. With these enhancements, 3DFD U-net successfully produces clear 3D vascular images of the palm, arms, breasts, and feet of human subjects. These enhanced vascular images offer improved capabilities for biometric identification, foot ulcer evaluation, and breast cancer imaging. These results indicate that the new algorithm will have a significant impact on preclinical and clinical photoacoustic tomography.

Analisis Alokasi Biaya Bersama ddengan Menggunakan Metode Nilai Jual Relatif Pada Usaha Martabak Manis

This study aims to prove how the process of allocating shared costs in the sweet martabak business on Jalan Pintu Air IV, Kwala Bekala, Medan Johor District, Medan. Data collection techniques used observation and interview methods. Researchers made direct observations of financial recording methods at the Sweet Martabak Business on Jalan Pintu Air IV Kwala Bekala. The result of this study is that sweet martabak businesses do not calculate in detail and do not use special methods to calculate joint cost allocation for sweet martabak. Through joint costs using the relative selling price method, the business has an allocation of joint costs of IDR 5,004,500 with a gross profit of IDR 2,273,500. The selling price method is the most appropriate method because this method has the advantage that the selling price can reflect the amount of costs absorbed by each type of product produced.

Two-stage stochastic facility location problem with disruptions and restricted shortages

In this study, we consider a reliable facility location problem where an uncertain disruptive event might affect the demand of the nodes, the allocation costs, and the available capacities at the facilities. We assume that the decision maker decides the locations and the types (size and reliability levels) of the facilities under uncertainty, while the allocation and shortage decisions are made in response to the realizations of the uncertain parameters. Motivated from a humanitarian facility location problem, we enforce an upper bound on the risk of shortages under any scenario using the popular risk measure conditional value-at-risk (CVaR). We formulate the problem as a two-stage stochastic programming model, and solve it using the L-Shaped method accelerated with additional enhancements. Our computational experiments show the value of our modeling scheme, and the effectiveness of our solution method.

Improving of Transmission Cost Allocation Method to Accelerate the Investment Recovery for Transmission lines in Deregulated Power System

Improving of Transmission Cost Allocation Method to Accelerate the Investment Recovery for Transmission lines in Deregulated Power System

Inverse Optimization Method for Safety Resource Allocation and Inferring Cost Coefficient Based on a Benchmark

Due to cost-push inflation, the trade-off between safety costs and risk prevention (safety) has become difficult worldwide. Most companies experience the difficulty of safety cost overruns and allocate safety resource inefficiently. In this paper, a forward model maximizing safety input is formulated. Because there is a wide range of variation of safety resource cost coefficient parameters, it is hard to determine safety resource cost coefficients in the forward model, to make the decisions on which types of safety resources are allocated to which potentially risky locations with what prices, and to ensure total input is as close to the benchmark as possible. Taking allocation, themes, resources, and cost coefficient parameters as new decision variables, the inverse optimization model is formulated based on a bi-level model. With consideration of quaternion decision, bi-level programming, and NP-hard problem, based on the comparison of exact penalty algorithm and an improved PSO algorithm, in which the inertia weight is adaptively changing with the number of iterations, the PSO is suitable for solving the specific inverse model. Numerical experiments demonstrated the effectiveness of the PSO algorithm, proving that it can allocate the right amount and types of safety resources with the right prices at the right places.

The Basic Core of a Parallel Machines Scheduling Game

Problem definition: We consider the parallel machine scheduling (PMS) under job-splitting game defined by a set of manufacturers where each holds uniform parallel machines and each is committed to produce some jobs submitted to her by her clients while bearing the cost of the sum of completion times of her jobs on her machines. An efficient algorithm for this scheduling problem is well known. We consider the corresponding cooperative game, where the manufacturers are players that want to join forces. We show that collaboration is profitable. Yet, the stability of the cooperation depends on the cost allocation scheme; we focus on the core of the game. Methodology/results: We prove that the PMS game is totally balanced and its core is infinitely large, by developing a sophisticated methodology of linear complexity that finds a line segment in its symmetric core. We call this segment the basic core of the game. Managerial implications: This PMS game has the potential for various applications both in traditional industry and in distributed computing systems in the hi-tech industry. The formation of a partnership among entrepreneurs, companies, or manufacturers necessitates not only a plan for joining forces toward the achievement of the ultimate goals, but also an acceptable agreement regarding the cost allocation among the partners. Core allocations guarantee the stability of the partnership as no subset of players can gain by defecting from the grand coalition. Funding: This work was supported by the Henry Crown Israeli Institute for Business Research, the Coller Foundation, and the Israel Science Foundation [Grant 1489/19].