Fair Allocation Research Articles

공급이 제한된 필수 자원의 공정성을 고려한 분배 방법 연구

This study addresses methods for efficiently and equitably distributing limited essential resources in crisis situations such as pandemics and climate change. In these scenarios, it is crucial to consider public welfare alongside efficiency when distributing scarce resources like medical supplies or food. This study introduces a fairness measure based on the Gini coefficient, grounded in utility, and employs a bi-objective optimization model to balance efficiency and fairness. The proposed distribution method is validated through a simulation model. The effects of various policy scenarios are compared and analyzed. Through the simulation experiments, the study demonstrated that distribution policies considering the elderly population ratio and equity are effective in achieving both efficiency and fairness in resource allocation. These findings provide practical approaches for policymakers, helping them make better decisions during emergencies with limited supply.

An analysis of high school students perceptions of school culture under the new general education program with emphasis on academic achievement, extracurricular participation, and career guidance: A case in Ho Chi Minh City, Vietnam

This study examines the viewpoints of public high school students in Ho Chi Minh City regarding the culture of their school under the implementation of the new General Education Program (the 2018 General Education Program) with a specific focus on several aspects of their educational surroundings. The participants consist of students from diverse backgrounds, including different schools and exhibiting varying degrees of academic and extracurricular engagement. The study revealed that 59.8% of pupils obtained remarkable academic outcomes, whereas 33.5% received exemplary achievements. Just 6.5% were considered to be qualified, while a slight 0.1% were considered to be unqualified. The training results revealed that 75.7% of pupils were categorized as distinguished, 20.4% as good, and 3.9% as qualified. With regards to extracurricular involvement, 13.7% of students assumed the role of class officials, 20.5% were club members, 8.3% held the post of youth union secretary, and 8.1% held numerous roles. Nevertheless, 49.4% of individuals were not involved in any official roles. The evaluation of students' learning culture indicated favourable perceptions, namely in regard to the esteem of educators and classmates, as well as the mindset towards independent study and continuous learning. Several aspects, such as the process of selecting a suitable profession and making decisions regarding elective topics, received a lower score of 2.23, suggesting that there is a need for enhancing career advising. The results emphasize both the positive and negative aspects of the school culture in public high schools in Ho Chi Minh City, Vietnam. They stress the importance of constantly improving educational strategies, career guidance, and the fair allocation of resources in order to enhance the learning environment and promote student development, specifically in the 2018 General Education Program.

Equity and efficiency of health resource allocation in the Chengdu-Chongqing Economic Circle of China.

This study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably. The fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives. The Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066-0.283, and the Gini coefficient for geographical area allocation was 0.297-0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch. The fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu-Chongqing Economic Circle.

Fair and efficient allocations when preferences are single-dipped

One unit of an infinitely divisible and non-disposable commodity has to be allocated among a group of agents with single-dipped preferences. We combine Pareto optimality with equal treatment of equals, the equal division lower bound, the equal division core, envy-freeness, and group envy-freeness. For each of these fairness requirements, we provide a necessary and sufficient condition for compatibility with Pareto optimality and we characterize all corresponding allocations for each preference profile.

Integrated planning for a multiproduct, multisite reforestation value chain: a Canadian case study

This paper addresses integrated supply and distribution planning for a multiproduct, multisite reforestation value chain (RVC) in a make-to-order context. The aim is to develop a tactical planning tool to determine the quantities of seedling species and sizes to order from nurseries to satisfy reforestation site needs while minimizing purchase and distribution costs. A mixed-integer linear programming model was developed and applied to the publicly managed RVC in the province of Quebec, Canada. This tool was also used to analyze scenarios considering the three pillars of sustainability: environmental (climate risk management to bolster resilience), social (fair production allocation), and economic (supply and distribution costs) aspects. This strategic analysis highlights the trade-offs between purely economic and more sustainable scenarios and discusses strategic deployment opportunities to improve the RVC. Ultimately, it serves as a powerful tool for efficiently allocating yearly seedling supply, minimizing costs, and promoting sustainable practices in reforestation planning which provides valuable insights for RVC managers.

DEMPE – Still a Long Way to Go

An integral part of the BEPS Action Plan is the Development, Enhancement, Maintenance, Protection and Exploitation (DEMPE) concept, which is intended to ensure a fair allocation of profits stemming from transactions that involve intangible assets. However, even though the DEMPE concept was included in the OECD Transfer Pricing Guidelines, its impact on the activities and profits of MNEs remains unclear. A survey conducted in 2023 revealed differing attitudes to the impact of DEMPE on MNEs’ income distribution and business operations, indicating a growing awareness of the concept but also highlighting the importance of clearer guidance on its application and integration with existing transfer pricing methodologies.

Two-echelon collaborative many-to-many pickup and delivery problem for agricultural wholesale markets with workload balance

In the context of cooperation distribution among multiple wholesale markets, each customer can place orders with multiple agricultural wholesale markets, and each agricultural wholesale market can supply different products. To improve their distribution efficiency and avoid traffic congestion, cargoes need to be transshipped among collaborative distribution of different agricultural wholesale markets owing to their product heterogeneity. Each agricultural wholesale market undertakes the cost of completing the task for the reassigned customers of finding a balance among them, respectively. Fairness of allocation is achieved through workload balance and individual rationality constraints instead of monetary transfer payments. Aimed at the collaboration problem, a two-echelon collaborative many-to-many pickup and delivery problem with workload balance (2E-MPDP-WB) is presented in this study. A mixed-integer programming model for 2E-MPDP-WB is established, and a two-stage iterative algorithm combining branch-and-bound algorithm and adaptive large neighborhood search algorithm is proposed according to the problem structure. Some valid inequalities are also proposed. Finally, computational experiments show the correctness of the model and effectiveness of the algorithm, and sensitivity analysis is performed from four aspects, namely, costs before and after collaboration, workload balance, market geographical distribution, and demand mixing degree. The findings provide management insights for the collaborative distribution of multiple wholesale markets.

TRUST-ME: Trust-Based Resource Allocation and Server Selection in Multi-Access Edge Computing

Multi-access edge computing (MEC) has attracted the interest of the research and industrial community to support Internet of things (IoT) applications by enabling efficient data processing and minimizing latency. This paper presents significant contributions toward optimizing the resource allocation and enhancing the decision-making process in edge computing environments. Specifically, the TRUST-ME model is introduced, which consists of multiple edge servers and IoT devices, i.e., users, with varied computing tasks offloaded to the MEC servers. A utility function was designed to quantify the benefits in terms of latency and cost for the IoT device while utilizing the MEC servers’ computing capacities. The core innovation of our work is a novel trust model that was designed to evaluate the IoT devices’ confidence in MEC servers. This model integrates both direct and indirect trust and reflects the trustworthiness of the servers based on the direct interactions and social feedback from other devices using the same servers. This dual trust approach helps with accurately gauging the reliability of MEC services and ensuring more informed decision making. A reinforcement learning framework based on the optimistic Q-learning with an upper confidence bounds action selection algorithm enables the IoT devices to autonomously select a MEC server to process their computing tasks. Also, a multilateral bargaining model is proposed for fair resource allocation of the MEC servers’ computing resources to the users while accounting for their computing demands. Numerical simulations demonstrated the operational effectiveness, convergence, and scalability of the TRUST-ME model, which was validated through real-world scenarios and comprehensive comparative evaluations against existing approaches.

Are Deaf College Students More Sensitive to Unfair Information? Evidence from an ERP Study.

To better understand the individual differences in fairness, we used event-related potentials (ERPs) to explore the fairness characteristics of deaf college students through the ultimatum game task. Behaviorally, the significant main effect of the proposal type was found, which meant both deaf and hearing college students showed a lower acceptance rate for the more unfair proposal. Interestingly, we found a significant interaction between group and proposal type in the early stage (N1). Moreover, in the deaf college group, N1 (induced by moderately and very unfair proposals) was significantly larger than that of fair proposals. However, we found that deaf college students had smaller amplitudes on P2 and P3 than hearing college students. These results suggested that deaf college students might pursue more equity strongly so they are more sensitive to unfair information in the early stage. In a word, we should provide more fair allocations for deaf college students in our harmonious society.

The circular balancing problem

We propose a balancing problem with a minmax objective in a circular setting. This balancing problem involves the arrangement of an even number of items with different weights on a circle while minimizing the maximum total weight of items arranged on any half circle. Due to its generic structure, it may have applications in fair resource allocation schemes. We show the NP-hardness of the problem and develop polynomial-time algorithms when the number of distinct weights is a fixed constant. We propose for the general case a tight 7/6-approximation algorithm and show that it performs better than two existing algorithms designed for an equivalent problem in the literature. The worst-case performance ratio is derived through a linear combination of valid inequalities that are obtained from the problem definition, the properties of the proposed algorithm, and the optimal circular permutation structure. Furthermore, we formulate a more general problem of minimizing the maximum total weight of items on equally divided circular sectors and present its computational complexity and a tight approximation algorithm.

Fair Shares: Feasibility, Domination, and Incentives

We consider fair allocation of indivisible goods to n equally entitled agents. Every agent i has a valuation function vi from some given class of valuation functions. A share s is a function that maps [Formula: see text] to a nonnegative value. A share is feasible if for every allocation instance, there is an allocation that gives every agent i a bundle that is acceptable with respect to vi, one of value at least her share value [Formula: see text]. We introduce the following concepts. A share is self-maximizing if reporting the true valuation maximizes the minimum true value of a bundle that is acceptable with respect to the report. A share s ρ-dominates another share [Formula: see text] if [Formula: see text] for every valuation function. We initiate a systematic study of feasible and self-maximizing shares and a systematic study of ρ-domination relation between shares, presenting both positive and negative results. Funding: The research of M. Babaioff is supported in part by a Golda Meir Fellowship. The research of U. Feige is supported in part by the Israel Science Foundation [Grant 1122/22].

How to Extend China’s Rural Land Contracts for Another 30 Years: A Psychological Ownership Perspective

In China’s rural land system, the collective owns the land, and farmers, as members of the collective, can acquire land contractual management rights through land contracting. With the second round of land contracts nearing expiration, the central government has announced that the term should be extended for 30 years. This paper introduces the theory of psychological ownership to explore the implementation paths of the 30-year extension policy. The study finds that (1) farmers generally exhibit strong psychological ownership towards the contracted land. (2) The Household Contract Responsibility System satisfies the three routes for the formation of psychological ownership—control, intimate knowledge, and self-investment. As the duration of farmers’ possession of contracted land extends, their psychological ownership gradually forms and strengthens. (3) Farmers’ psychological ownership has both positive and negative effects. The 30-year extension policy must adhere to the path dependence formed by the evolution of the land contract system, comply with the institutional constraints imposed by rural land collective ownership, and simultaneously meet the practical demands posed by urban–rural integration and agricultural development. Drawing on the complex effects of farmers’ psychological ownership and considering the historical, institutional, and practical contexts of policy implementation, this study proposes the dual necessity of facilitating and restraining farmers’ psychological ownership when extending for another 30 years and offers corresponding policy suggestions. Facilitation requires empowering farmers with more stable land possession and stronger land rights. Restraint requires preventing the permanent locking of rural land allocation patterns to achieve fair and efficient land allocation.

Harmonizing economies and ecologies: Towards an equitable provincial carbon quota allocation for China’s peak emissions

Rational provincial allocation of carbon quotas serves as the foundational premise for attaining China’s carbon peak. Yet, prevailing strategies often overlook the holistic integration of trade-induced carbon transfers and ecological carbon sequestration, resulting in equity and scientific robustness deficiencies. This study addresses these shortcomings by examining historical carbon sources and sinks across China’s provinces and proposing a novel provincial allocation scheme based on the ‘equal consumption-based cumulative per capita net emission’ principle. Our findings reveal significant disparities in the carbon quotas between provinces, ranging from ‒98 Mt in Shanghai to 1016 Mt in Sichuan, primarily influenced by factors such as population size, historical emissions, and carbon sinks. The proposed scheme, integrating considerations of carbon transfers and sinks, safeguards the interests of less developed provinces (e.g., Hebei and Inner Mongolia) and those with valuable ecosystems (e.g., Yunnan and Inner Mongolia). Furthermore, the impact of carbon transfers on provincial carbon allocation quotas is more pronounced than that of carbon sinks. For instance, the inclusion of carbon transfers has increased Inner Mongolia’s quotas by 238 Mt, compared to 125 Mt attributed to carbon sinks. Considering the disparities in emissions reduction pressure and capacity across different provinces, combining fair carbon quota allocation with a nationwide carbon market can achieve cost-effective emissions reduction while ensuring the attainment of carbon peak.

An ethics analysis of antipsychotic dose reduction and discontinuation: Principles for supporting recovery from psychosis.

To examine the evidence and practice of antipsychotic dose reduction from the lens of biomedical ethics (specifically principlism) to support evidence-based practice and patient choice and self-determination. An overview of the evidence from randomized controlled trials of antipsychotic dose reduction versus maintenance is presented. This is followed by a theoretical examination of the four key biomedical ethical principles of autonomy, nonmaleficence, beneficence, and justice and how they apply in the case of antipsychotic dose reduction. Existing clinical trial research is dominated by relapse as the primary outcome, with dose reduction associated with a higher risk of relapse than maintenance. Few studies have measured other patient-centered outcomes but have shown preliminary evidence for superior cognitive functioning, lower negative symptoms, and better functioning following dose reduction. Respect for autonomy is a cornerstone of psychiatric rehabilitation, and this includes the right of people to choose to reduce or discontinue antipsychotic medication. Reduced capacity for treatment decision making can be supported. Autonomy and appraisal of nonmaleficence and beneficence associated with dose reduction can be facilitated through shared or supported decision making. Clinicians should continue to strive for justice through the fair allocation of resources to support all people who request antipsychotic dose reduction. Clinicians have a responsibility to balance the four core ethical principles to the best of their ability when supporting a person in their recovery journey. Exploring, trialing, and supporting antipsychotic dose reduction may be part of this process if that is the patient's choice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The relationship between organizational justice and bullying behaviors among nurses: the role of nurse managers’ caring behaviors

BackgroundOrganizational justice is pivotal in fostering a fair and supportive workplace culture, which strengthens the connections between managers and nurses, among nurses themselves, and ultimately, between nurses and their patients. Assessing the perceived levels of organizational justice and managerial behaviors can identify key areas for improving nurses’ commitment and loyalty, while simultaneously reducing incidents of workplace bullying.PurposeThis study aims to investigate how bedside nurses perceive organizational justice, nurse managers’ caring behaviors, and their exposure to workplace bullying. Additionally, it seeks to explore the relationship between organizational justice, nurse managers’ caring behaviors, and nurses’ perceived exposure to workplace bullying.MethodsA descriptive-correlational study was conducted in the inpatient care unit of a Saudi hospital. A convenience sample of 256 nurses participated, completing the Organizational Justice Questionnaire (OJQ), the Caring Factor Survey: Caring of the Manager (CFS-CM), and the Negative Acts Questionnaire-Revised (NAQ-R). The collected data were analyzed using descriptive statistics and regression analysis.ResultsDescriptive statistics revealed moderate levels of perceived organizational justice and managerial caring behaviors among nurses, alongside low reported exposure to workplace bullying. Significant correlations were found among the studied variables, indicating that higher perceived organizational justice was associated with higher managerial caring and lower workplace bullying (p < 0.05). Mediation analysis demonstrated a significant indirect effect of organizational justice on workplace bullying through the mediating role of nurse managers’ caring behaviors (a×b = -0.0652, p < 0.001). Furthermore, the direct effect of organizational justice on workplace bullying remained significant even when accounting for the mediator (c = -0.5509, p < 0.001).ConclusionThis study highlights the vital role of organizational justice and managerial caring in cultivating a positive work environment and mitigating workplace bullying. Implementing clear policies and procedures while promoting fairness and equality in resource allocation, decision-making processes, and interactions are essential strategies for fostering positive attitudes and work behaviors among nurses.

Principles and Optimization of China’s Unconventional Water Management: From a Brand-New Perspective of Responsibility Allocation

Unconventional water includes reclaimed water, harvested rainwater, desalinated seawater, and mine water. Unconventional water use is considered more of a “mandatory responsibility” in China. The initial allocation of unconventional water emphasizes quantity-centered responsibility allocation while the minimum utilization reflects this responsibility. The unconventional water use responsibility (UWUR) should be tailored to the characteristics of each area, moving away from a ‘more is better’ mindset. However, there is a large research gap in this field. This paper first presented six fundamental principles for unconventional water allocation. Ensuring fairness in allocation involves aligning the allocated amount with urban water usage characteristics. Hence, based on four key features, this paper integrated various socioeconomic and environmental factors to build an initial allocation model. To enhance efficiency, an optimal allocation model was constructed using the zero-sum gains–data envelopment analysis (ZSG-DEA) method. The models were then applied to Jiangsu Province, China, to verify their applicability. The results showed that the projected minimum UWUR allocation (unit: 100 million m3) for each city in 2025 is 1.482 (Nanjing), 1.501 (Wuxi), 0.919 (Xuzhou), 1.029 (Changzhou), 2.977 (Suzhou), 1.497 (Nantong), 0.818 (Lianyungang), 0.766 (Huai’an), 0.875 (Yancheng), 0.920 (Yangzhou), 0.790 (Zhenjiang), 0.858 (Taizhou), and 0.766 (Suqian). The rational and feasible results indicated that the allocation framework proposed in this paper has a certain practicability. Lastly, this paper considered the differences in unconventional water utilization conditions across 13 cities and proposed corresponding measures to improve the utilization. This paper represents a tentative exploration of unconventional water allocation in China and offers theoretical and practical insights for policy-makers to improve territorial spatial planning and sustainable water management.

New approach to NOMA optimization based on individual discrete input continuous output memoryless channel capacity

In NOMA achieving fairness in data transmission for all users is one of the key challenges. It implies a fair allocation of resources among users according to a given criterion. NOMA systems are based on the discreteness of the data source, since the specific nature of data allows to extract information in overloaded systems. Well-known C.E. Shannon capacity equation does not take into account the discrete nature of NOMA group signals, considering them as Gaussian source of information. Therefore, it does not take into account the characteristics of discrete signals used in NOMA systems, which makes it difficult to solve the optimization problem, especially for types of NOMA that use code division. For this task it is necessary to use DCMC capacity. When optimizing total capacity of DCMC, individual properties of users are not taken into account, as a result of which the allocation of resources with such optimization might not be fair. This paper proposes an approach to optimizing NOMA based on the analysis of an-individual mutual information (capacity). The proposed optimization approach allows analyzing the individual characteristics of each user in order to improve NOMA system performance by optimizing NOMA signals parameters.

Analysis of regional water resources spatial pattern and allocation equity

Water scarcity is a worldwide concern, and with the impact of climate change and human activities, the imbalance in the distribution of water resources has further intensified. The equitable allocation of water resources has become a thorny issue for water resources management authorities. It is challenging to find a relatively equitable method of water resources allocation. This study aims to propose a method for evaluating the fairness of water resources allocation, which can be used both to evaluate the fairness of water resources allocation and as a basis for water resources allocation decisions. The specific approach is to first analyze the spatial pattern of regional water resources by using water resources abundance and water resources intensity, and then to conduct a comprehensive analysis of regional water resources allocation fairness by combining Lorenz curve, Gini coefficient and Theil index to form an index system that can systematically analyze the spatial pattern of water resources, allocation fairness and its changes. A real-world example study was conducted in the Yangtze River Delta region of China, and the results showed that the index system can well reflect the allocation of water resources among regions and cities within the region. The results obtained using this method can provide some reference for promoting coordinated regional development.

Rightful Rewards: Refining Equity in Team Resource Allocation through a Data-Driven Optimization Approach

In group management, accurate assessment of individual performance is crucial for the fair allocation of resources such as bonuses. This paper explores the complexities of gauging each participant’s contribution in multi-participant projects, particularly through the lens of self-reporting—a method fraught with the challenges of under-reporting and over-reporting, which can skew resource allocation and undermine fairness. Addressing the limitations of current assessment methods, which often rely solely on self-reported data, this study proposes a novel equitable allocation policy that accounts for inherent biases in self-reporting. By developing a data-driven mathematical optimization model, we aim to more accurately align resource allocation with actual contributions, thus enhancing team efficiency and cohesion. Our computational experiments validate the proposed model’s effectiveness in achieving a more equitable allocation of resources, suggesting significant implications for management practices in team settings.

IF-City: Intelligible Fair City Planning to Measure, Explain and Mitigate Inequality.

With the increasing pervasiveness of Artificial Intelligence (AI), many visual analytics tools have been proposed to examine fairness, but they mostly focus on data scientist users. Instead, tackling fairness must be inclusive and involve domain experts with specialized tools and workflows. Thus, domain-specific visualizations are needed for algorithmic fairness. Furthermore, while much work on AI fairness has focused on predictive decisions, less has been done for fair allocation and planning, which require human expertise and iterative design to integrate myriad constraints. We propose the Intelligible Fair Allocation (IF-Alloc) Framework that leverages explanations of causal attribution (Why), contrastive (Why Not) and counterfactual reasoning (What If, How To) to aid domain experts to assess and alleviate unfairness in allocation problems. We apply the framework to fair urban planning for designing cities that provide equal access to amenities and benefits for diverse resident types. Specifically, we propose an interactive visual tool, Intelligible Fair City Planner (IF-City), to help urban planners to perceive inequality across groups, identify and attribute sources of inequality, and mitigate inequality with automatic allocation simulations and constraint-satisfying recommendations (IF-Plan). We demonstrate and evaluate the usage and usefulness of IF-City on a real neighborhood in New York City, US, with practicing urban planners from multiple countries, and discuss generalizing our findings, application, and framework to other use cases and applications of fair allocation.