Type of the article: Research ArticleAbstractThis study examines the adoption and implementation of cost accounting practices in Saudi Arabian public universities following their shift from cash-based to accrual-based accounting. Guided by the resource-based view (RBV) framework, it tests four hypotheses related to drivers of cost adoption, cost tracking and allocation abilities, calculation method frequencies, and resources needed for successful cost implementation. Data from 171 financial managers and accountants across all 30 public universities were analyzed using descriptive statistics, correlations, and regression models. Results reveal a negative correlation between cost adoption and organizational factors, with external pressures – including regulatory requirements and negotiations over funding – serving as the primary catalysts. Universities demonstrate a strong capacity to track and allocate direct costs, with over 90% able to manage them; however, indirect cost management remains limited, with only 12% able to allocate indirect costs, indicating early-stage development. Cost implementation is further positively associated with the use of detailed cost calculation and allocation methods and perceived organizational resource needs, including financial policies, skilled personnel, and advanced management systems. Findings suggest that, despite external pressures, resource constraints hamper full implementation. These findings support the RBV assertion that internal capabilities are crucial for gaining a strategic advantage. Successful cost implementation depends on internal resource development and organizational capacity-building, which can transform cost accounting from a symbolic compliance exercise into a strategic tool for transparency, decision-making, and institutional efficiency.

This study addresses the scientific and practical challenges of determining finished product costs in pharmaceutical enterprises operating in the Republic of Uzbekistan, a critical issue in the context of economic reforms, stricter state regulation of drug pricing, and the ongoing transition to International Financial Reporting Standards that demand modern cost accounting systems. The research aims to identify deficiencies in current cost determination practices and propose improved methodologies tailored to the unique technological, regulatory, and organizational characteristics of pharmaceutical firms. Employing analytical, comparative, and monographic methods, the study examines actual accounting records and internal management reports from pharmaceutical enterprises, with particular attention to cost allocation across supply, production, laboratory testing, and packaging processes, and compares cost structures between imported and domestically manufactured products. Results reveal that material costs dominate the cost structure at approximately 50 percent, while wages and depreciation together account for nearly 30 percent; however, existing reporting practices fail to adequately disclose the distribution of indirect costs across production stages, limiting managerial control effectiveness. The novelty of this research lies in developing context-specific definitions for pharmaceutical business processes and proposing enhanced reporting formats that improve cost transparency and align with international standards. These findings have significant implications for strengthening management decision-making capabilities, improving financial reporting quality, and facilitating compliance with International Financial Reporting Standards in Uzbekistan's pharmaceutical sector.Keywords : Pharmaceutical Costing, Cost Allocation Methods, Financial Reporting Transparency, Indirect Cost Distribution, International Accounting Standards, Production Cost StructureHighlight : Material costs dominate pharmaceutical product costs, averaging 50 percent of total expenses. Current reporting inadequately discloses indirect cost allocation across production stages and functions. Study introduces simplified definitions and enhanced formats improving cost transparency and managerial control.

The article investigates the development of accounting and control systems for freight forwarding enterprises amidst the implementation of Industry 4.0 technologies. The study analyzes the fragmentation of scientific research regarding the impact of digitalization on forwarding activities and identifies a lack of systematic approaches to assessing implementation risks. Three key benefits of utilizing Internet of Things (IoT), Artificial Intelligence (AI), and Big Data are revealed: 1) Visibility (ensuring real-time supply chain transparency); 2) Optimization (increasing resource efficiency); 3) Analytics (strategic data-driven planning). The directions for transforming the accounting and control system are defined by transitioning from periodic documentation to continuous monitoring, replacing simplified cost allocation methods with precise costing based on sensor data, and evolving from retrospective reporting to predictive analytics. The main challenges of digitalization are systematized into: 1) Technological (scalability, device incompatibility, data security); 2) Organizational (staff resistance, competency deficits, low implementation success rates); 3) Regulatory (absence of accounting standards for new business models). Strategies to overcome these barriers include investing in training, engaging consultants, implementing iteratively, and developing an organizational culture. Perspectives for further research include unifying digital asset accounting methods and transforming professional competencies for accounting personnel.

This study introduces the Product Variety Costing Method (PVCM), a data-driven framework that addresses the limitations of existing costing approaches, which fail to accurately present the cost of product and part variety, thereby constraining cost-informed decision-making in modular product development. Traditional cost allocation methods often lack one or more of the following: a full life-cycle perspective, a lower level of granularity according to the product structure, or a combined integration of qualitative and quantitative data. The PVCM bridges these gaps by combining Time-Driven Activity-Based Costing (TDABC) with hierarchical product structures and empirical enterprise data, enabling the quantification of variety-induced resource consumption across components, subsystems, and complete products. An industrial application demonstrates that the PVCM enhances cost accuracy and transparency by linking resource use directly to specific product abstraction levels, thereby highlighting the true cost impact of product variety. In this case, results revealed deviations of up to 60% in the adjusted contribution margin ratio relative to traditional overhead-based methods, clearly indicating the influence of product variety on cost assessments. The method supports design and managerial decision-making by allowing evaluation of modularization based on detailed cost insights. While the study’s scope is limited to selected life-cycle phases and a single company case, the findings highlight the method’s future potential as a generalizable tool for evaluating economic benefits of modularization. Ultimately, the PVCM contributes to a more transparent and analytically grounded understanding of the cost of variety in complex product portfolios.

Abstract Ministerial Decree 414/2023 implements Legislative Decree 199 which defines the conditions and methods under which producers, consumers, and prosumers have the right to organize themselves into Renewable Energy Communities (REC), promoting the production and sharing of electricity from renewable sources. The economic feasibility of an energy community is largely influenced by its investment options: public capital only, third-party co-financing, or direct investment by interested households. A common issue in these cases is the allocation of costs among local community members to ensure cost recovery. To evaluate the feasibility of an Energy Community, an economic analysis with different technical and economical options is conducted, considering various cost allocation methods. The analysis is carried out in the case study of Pattada, a small municipality in northern Sardinia, and is focused on the availability of hourly consumption of public buildings and of two energy-intensive utilities in the tertiary sector. Residential consumption has been modelled based on the indications provided by the GSE and validated for some practical cases through targeted experimental measurements. Different scenarios were analysed by varying the size of the plants intended for self-production, the percentage of capital financing, the types of users and the number of residents adhering to the REC. He results confirm that the most favourable incentive tariff is obtainable minimizing the amount of energy fed into the grid. From an economic point of view, the participation of residents in energy generation is always favourable to the improvement of the NPV for all the prosumers. The higher profits are obtained without capital contributions, obviously due to the higher amount of the corresponding premium rate. On the other hand, capital contributions play an important role in the entry of new prosumers, especially in the residential sector, contributing to broadening the community pool. The interplay between distributed generation, energy storage and active participation in grid flexibility not only improves overall energy efficiency but also helps to reduce environmental impacts and promote greater energy independence.

The high complexity of operational activities in service-based companies such as insurance firms has led to an increase in operational costs, many of which do not add significant value. In the era of digital transformation, insurance companies are required to improve cost efficiency with greater accuracy; however, traditional cost allocation methods are considered inadequate in reflecting actual resource consumption. This issue highlights the need for a more adaptive cost accounting approach. This study aims to analyze the effectiveness of implementing the Activity-Based Costing (ABC) method in improving operational cost efficiency in insurance companies in the digital era. The research method used is a literature review with a qualitative narrative approach by examining several relevant scientific publications published within the last five years. The findings indicate that the ABC method is capable of identifying inefficient activities, increasing the accuracy of cost allocation, and strengthening strategic decision-making based on activity- based data. In the context of digitalization, the development of the method into Time-Driven Activity-Based Costing (TDABC) is also considered more practical for implementation. This study confirms that Activity-Based Costing (ABC) is also considered more practical for implementation. This study confirms that ABC and its variants represent a strategic cost control approach that can promote sustainable efficiency in the insurance sector.

Energy communities enable prosumers to jointly operate distributed energy resources and thereby generate economic benefits that exceed those achievable individually. A central challenge in their implementation is selecting a Cost Allocation Method (CAM) that distributes these benefits fairly among heterogeneous participants. Although numerous CAMs have been proposed, they are often evaluated under different assumptions, making direct comparison difficult. This paper develops a unified axiomatic framework for assessing CAMs in energy communities and applies it to eight representative methods classified in three families: simple rules, savings-based, and price-based. The framework is built around seven desirable properties capturing principles of fairness, environmental friendliness, and continuity. Our main contribution is a comparative table that positions all methods within a single evaluative space and reveals the structural trade-offs that arise across CAMs. The analysis shows that the Average-Price CAM satisfies the same axiomatic properties as the Shapley method while remaining computationally trivial, making it an attractive practical option. We also show that the Extreme-Price CAM is the only price-based method that ensures the property of Beneficial Group Participation (core stability); however, this method violates other properties related to environmental friendliness and continuity—trade-offs we prove to be unavoidable for price-based rules. Finally, we conjecture that the nucleolus satisfies all seven properties, although its computation is rarely feasible in practice. The proposed framework provides researchers and practitioners with a transparent foundation for selecting and designing cost allocation methods in emerging energy communities.

Distribution Use of Network (DUoN) charges are crucial for recovering the costs of installing, operating, and maintaining the distribution network (DN) assets. This article presents a pricing algorithm to charge consumers and distributed energy resources (DERs) based on their impact on the distribution network. This method utilizes a sensitivity approach to calculate the deviation in system annual chargeable cost based on the incremental change in a) the real and reactive power flow of the facilities, b) the MW-Miles and MVAr-Miles flow of the system, and c) the power factor of the system. This provides the cumulative impact of all these parameters and provides the incentive to consumers based on the amount of real and reactive power they are consuming, the distance used to support customers' real and reactive power injection/withdrawal, the capacity of DN assets being utilized while power is being delivered to consumers and influence on system power factor. The main advantage of the proposed approach is that it is not dependent on the tracing algorithm to detect the power flow paths, hence capable of computing DUoN for decent-sized DNs embedded with DERs, where the contribution of power to the consumers by the DERs or from the grid is difficult to determine or trace. Additionally, due to the appraising and penalizing characteristics of the proposed DUoN charging mechanism, the proposed pricing algorithm may encourage users to act based on local economic signals. This algorithm has been tested on a modified Western network, the IEEE-15 bus network, the IEEE-69 bus network, and the IEEE-123 bus network.

The increasingly complex and competitive business environment requires micro, small, and medium enterprises (MSMEs) to manage accurate cost information in determining production costs and selling prices. This study aims to analyze the calculation of cost of goods manufactured using full costing and variable costing methods to determine the selling price of Chelsilo Banana Chips MSME. This research employed a quantitative descriptive approach by collecting data directly from the enterprise’s financial records and production activities. The results show that the enterprise’s existing calculation produced a cost of IDR 65,376 per kilogram with a selling price of IDR 80,000 per kilogram. Using the full costing method resulted in IDR 74,820 per kilogram, while the variable costing method resulted in IDR 68,485 per kilogram. Determining the selling price using the mark-up method produced a selling price of IDR 89,784 per kilogram (20% mark-up) under full costing and IDR 82,866 per kilogram (21% mark-up) under variable costing. These findings highlight the importance of accurate cost allocation methods to improve pricing decisions and profitability for MSMEs.

This study develops integrated bioeconomic management strategies for the common squid (Todarodes pacificus) fishery in Korea’s coastal waters, addressing both biological conservation and economic sustainability amid severe stock depletion and declining fishery profitability. Drawing on recent catch data and cost structures for six Total allowable Catch (TAC)-managed fishery types, common squid-specific economic indicators were estimated using a stepwise cost allocation method. Based on previous research using the Catch—Maximum Sustainable Yield (CMSY) model with limited Catch Per Unit Effort (CPUE) data, the biomass in 2020 was estimated at approximately 56% of Biomass at Maximum Sustainable Yield (BMSY), indicating an overfished state. Scenario-based simulations identified TAC allocation thresholds at which net profits reach zero, providing a benchmark for adaptive quota redistribution. Results show variation in economic sensitivity and common squid dependency among fishery types: common squid-dependent gears such as offshore jigging and East Sea trawl exhibit high vulnerability, while multi-species fisheries such as purse seine remain resilient. These results provide a basis for developing tailored management strategies for each fishery, thereby enhancing the effectiveness of interventions. Accordingly, policy recommendations include dynamic TAC adjustments, expanded monitoring, introduction of an Individual Transferable Quota system, and coordinated stock assessments with China and Japan. These findings contribute to refining Korea’s TAC system by aligning stock recovery goals with the economic viability of fishing operations.

This community service aims to apply the joint and by-product cost calculation method in the production process of one of the tofu MSMEs, Pabrik Tahu 212, located in Nagari Cupak. The main product produced is tofu, while tofu dregs, as a by-product, are utilized as cattle feed. The activity was carried out through the collection and analysis of production cost data, including raw materials, direct labor, and overhead costs. A cost allocation method was used to separate the costs between the main product and the by-product.

Full cost accounting, as a comprehensive cost measurement method, integrates direct and indirect costs to reallocate costs across departments. Performance evaluation serves as a method to assess a hospital’s overall performance and management capabilities. Both full cost accounting and performance evaluation are critical tools in the financial management of public hospitals, playing pivotal roles in accounting practices. The concepts of full cost accounting and performance evaluation were investigated in this study, and the existing challenges and the theoretical basis for their integration were analyzed. An integrated model was constructed, and its application cases and effectiveness in the financial management of public hospitals were discussed. Finally, measures to integrate full cost accounting and performance evaluation were proposed, including improving full cost accounting mechanisms, standardizing accounting practices, optimizing cost allocation methods, establishing a unified management platform, and fostering collaboration among stakeholders. This study provides new insights to enhance the quality and efficiency of financial management in public hospitals, laying a foundation for their sustainable development.

The article explores the theoretical and methodological principles of enterprise cost and asset management in the context of a strategic choice between the “risk” and “control” development models. It is substantiated that modern economic instability, digitalization of business processes, and increasing uncertainty in the external environment necessitate a differentiated approach to forming a costing and asset management system that considers both strategic goals and risk factors of enterprise activities. The key parameters of costing and asset utilization for each activity model are determined, including the dynamics of cost and asset structure and analytical requirements for the “risk” strategy, as well as the standardization and normativity of costs and asset allocation for the “control” strategy. Methods of cost calculation and allocation of indirect costs are systematized, demonstrating the correspondence between selected cost-accounting methodologies, asset management practices, and the strategic orientations of the enterprise. In particular, the effectiveness of standard costing and rationing methods is highlighted for the control strategy, while variable-cost and marginal analytics methods (direct-costing, ABC) are recommended for growth and adaptation strategies. It is emphasized that strategic cost and asset management should combine traditional approaches with modern analytical tools to ensure competitive advantages in a changing market environment and support enterprise strategic decisions. A generalized model of the relationship between enterprise risk level, cost structure, and asset management has been developed, which contributes to improving the quality of managerial decision-making under challenging economic conditions.

The adoption of multi-cloud strategies has introduced significant complexity in managing and allocating cloud costs across several cloud platforms. Traditional cost allocation methods, heavily dependent on manual processes, face challenges in providing timely insights and accurate attribution. Artificial Intelligence (AI) and Machine Learning (ML) are transforming this landscape by automating resource tagging, enabling real-time cost attribution, and providing predictive analytics capabilities. Through pattern recognition and automated response mechanisms, these technologies enhance cost visibility, optimize resource utilization, and improve financial governance across cloud environments. The implementation of AI-driven solutions demonstrates substantial improvements in cost attribution accuracy, reduction in manual efforts, and enhanced ability to forecast and optimize cloud spending patterns across different business units and projects.

Collaboration in logistics is an effective tool not only for cost savings but also for reducing the carbon footprint. Hub networks take advantage of scale economies by bundling flows. Merging hub networks through horizontal collaboration unlocks further economic and environmental advantages. We consider the problem of designing a collaborative hub network as a cooperative game and show that the core of the game might be empty, meaning that an efficient and stable cost allocation does not exist. Our key novelty lies in formulating this design problem as a cooperative game and demonstrating the potential absence of a fair and stable solution. Various game theoretical approaches are used for the allocation of joint costs due to the collaboration. Each approach is also tested through extensive numerical experiments to gain insight into the features and behavior of the corresponding cost allocation game. These experiments are conducted on both randomly generated and also real-world hub location instances. Achieving a stable and also fair cost allocation among collaborators is critical for the future of the organization. Finally, we compare the performance of the nucleolus, the Shapley value and the least core cost allocation methods based on different fairness measures such as relative savings, stability concepts and coalition satisfaction. This work ultimately paves the way for more efficient and sustainable logistics operations by measuring the value of collaboration in hub network design and minimizing the operating costs and also environmental footprint of the logistics industry.

Cost analysis of kerosene production from power-based syngas via the Fischer-Tropsch and methanol pathway

Calculating the cost of medical services is an important aspect of healthcare management that affects decision-making, pricing and the overall efficiency of medical institutions. The article investigates and summarizes the theoretical foundations of cost medical services with regard to the specifics of the healthcare industry.The study emphasizes the complexity of determining costs in a market economy, as various fundamental concepts, such as cost accounting objects, costing units, and cost allocation methods, are important for accurate calculations. The choice of the costing method is particularly important, as it affects the formation of economically justified costs and the ability to analyze and optimize costs. The article emphasizes the need for an individual approach to cost accounting in healthcare institutions, suggesting that the object of calculation should be individual medical services, and cost accounting should focus on specific units (centres of responsibility) of healthcare institutions.In addition, allocating indirect (overhead) costs is a significant problem, as these costs can account for a significant portion of total costs. The study analyzes various methods of allocating indirect costs, including direct, sequential and simultaneous allocation. It emphasizes the importance of selecting appropriate cost factors to ensure accurate pricing of healthcare services. Accurate cost allocation supports fair pricing and improves resource management and decision-making processes in healthcare organizations. Ultimately, the study emphasizes adapting traditional costing theories to the healthcare industry to increase healthcare delivery transparency, accountability, and efficiency.

Under the carbon peaking and carbon neutrality target background, efficient collaborative scheduling between distribution networks and multi-microgrids is of great significance for enhancing renewable energy accommodation and ensuring stable system operation. Therefore, this paper proposes a collaborative optimization method for the operation of distribution networks and multi-microgrids with shared energy storage based on a multi-body game. The method is modeled and solved in two stages. In the first stage, a multi-objective optimization configuration model for shared energy storage among multi-microgrids is established, with optimization objectives balancing the randomness of renewable energy fluctuations and the economics of each microgrid undertaking shared energy storage. The charging and discharging interactive power of energy storage and each microgrid at various time periods are obtained and passed to the second stage. In the second stage, with the distribution network as the leader and shared energy storage and multi-microgrids as followers, a game optimization model with one leader and 2 followers is established. The model is solved based on an outer-layer genetic algorithm nested with an inner-layer solver to determine the electricity purchase and sale prices among the distribution network, multi-microgrids, and shared energy storage at various time periods, thereby minimizing operational costs. Finally, based on the power interaction of microgrids to measure their contributions, an improved Shapley value cost allocation method is proposed, effectively achieving a balanced distribution of benefits among the distribution network, shared energy storage, and multi-microgrids, thereby improving overall operational revenue. Meanwhile, a new method for calculating the shared energy storage capacity and the upper limit of charging and discharging power based on a game framework was proposed, which can save 37.23% of the power upper limit and 44.89% of the capacity upper limit, effectively saving the power upper limit and capacity upper limit.

The classified water pricing system is an effective measure for promoting the rational utilization of water resources under market mechanisms. Studying the water prices of three different types of water sources, including reservoir water, river water, and wastewater treatment plant effluent, is the basis for promoting the use of reclaimed water. However, there remains a spectrum of viewpoints on how to establish a pricing mechanism for reclaimed water at present. This study primarily focuses on the multi-level quality-separated water supply system in Yiwu City, China. It analyzes the limitations of the current water pricing formation mechanism and the externality of integrating reclaimed water into the unified allocation of multiple water sources. Based on the principles of full-cost water pricing and externality theory, a supply-side classified water pricing permit cost and pricing calculation model, covering the entire process of the social water cycle, is proposed. It focuses on the analysis of the impact of equity costs and environmental costs on supply-side classified water pricing. The Shapley value method is used for the technology of cost allocation among stakeholders to reasonably distribute the calculated water pricing of reclaimed water. The price of reclaimed water varies depending on the user type, with residential users paying 2.93 CNY/t, industrial users 4.00 CNY/t, and government allocations at 8.52 CNY/t. Compared with the classified water prices of various stakeholders on the user side of reservoir water, reclaimed water has a significant price advantage. This research demonstrates that the supply-side classified water pricing model, which includes a permit cost and pricing calculation framework, can encourage the supply of higher-quality water at corresponding higher prices, while also providing the internalization of external costs. Furthermore, the Shapley value method of cost allocation can realize the fair burden of stakeholders on the calculated water price and maintain the competitive advantage of reclaimed water prices.

Energy storage (ES) units are vital for the reliable and economical operation of the power system with a high penetration of renewable distributed generators (DGs). Due to ES’s high investment costs and long payback period, energy management with shared ESs becomes a suitable choice for the demand side. This work investigates the sharing mechanism of ES units for low-voltage (LV) energy prosumer (EP) communities, in which energy interactions of multiple styles among the EPs are enabled, and the aggregated ES dispatch center (AESDC) is established as a special energy service provider to facilitate the scheduling and marketing mechanism. A shared ES operation framework considering multiple EP communities is established, in which both the energy scheduling and cost allocation methods are studied. Then a shared ES model and energy marketing scheme for multiple communities based on the leader–follower game is proposed. The Karush–Kuhn–Tucker (KKT) condition is used to transform the double-layer model into a single-layer model, and then the large M method and PSO-HS algorithm are used to solve it, which improves convergence features in both speed and performance. On this basis, a cost allocation strategy based on the Owen value method is proposed to resolve the issues of benefit distribution fairness and user privacy under current situations. A case study simulation is carried out, and the results show that, with the ES scheduling strategy shared by multiple renewable communities in the leader–follower game, the energy cost is reduced significantly, and all communities acquire benefits from shared ES operators and aggregated ES dispatch centers, which verifies the advantageous and economical features of the proposed framework and strategy. With the cost allocation strategy based on the Owen value method, the distribution results are rational and equitable both for the groups and individuals among the multiple EP communities. Comparing it with other algorithms, the presented PSO-HS algorithm demonstrates better features in computing speed and convergence. Therefore, the proposed mechanism can be implemented in multiple scenarios on the demand side.