Allocation Mechanism Research Articles

The Complexity of State-Led Housing Planning: Lessons from Implementation in Southern California

California’s current housing planning system is comprised of a complex housing target allocation mechanism and enforcement mechanisms to ensure that local governments effectively accommodate the development of the allocated housing units. This study illustrates the complexity in California’s planning requirements and discusses the implications for implementation. Drawing on interview data and observations of public events, this study also reveals implementation challenges perceived by front-line workers. This study contributes to the planning and policy implementation literature by addressing the implementation of complex rules in the context of top-down planning.

A truthful randomized mechanism for task allocation with multi-attributes in mobile edge computing

Mobile Edge Computing (MEC) aims at decreasing the response time and energy consumption of running mobile applications by offloading the tasks of mobile devices (MDs) to the MEC servers located at the edge of the network. The demands are multi-attribute, where the distances between MDs and access points lead to differences in required resources and transmission energy consumption. Unfortunately, the existing works have not considered both task allocation and energy consumption problems. Motivated by this, this paper considers the problem of task allocation with multi-attributes, where the problem consists of the winner determination and offloading decision problems. First, the problem is formulated as the auction-based model to provide flexible service. Then, a randomized mechanism is designed and is truthful in expectation. This drives the system into an equilibrium where no MD has incentives to increase the utility by declaring an untrue value. In addition, an approximation algorithm is proposed to minimize remote energy consumption and is a polynomial-time approximation scheme. Therefore, it achieves a tradeoff between optimality loss and time complexity. Simulation results reveal that the proposed mechanism gets the near-optimal allocation. Furthermore, compared with the baseline methods, the proposed mechanism can effectively increase social welfare and bring higher revenue to edge server providers.

Study on the Legal Risks of Social Entities' Participation in Non-Emergency Transfers

Non-emergency transfer multi-level protection system is an important livelihood project in China and an important diversified support for a sound Chinese-style modern social security system, as well as an ideal governance tool to effectively solve the problems of non-emergency demand crowding out the emergency capacity, unbalanced transfer resources and differences in the quality of service, imperfect management mechanism and laws and regulations, and low social acceptance. We use structural theory to analyse the main problems in the current practice of China's non-emergency transfer security system, accordingly construct the non-emergency transfer security system, and put forward suggestions to promote the development of the system in a benign cycle. Improve the internal resource allocation mechanism to enhance the efficiency of non-emergency transfer services; focus on the cultivation of the talent team to steadily improve the quality of services; optimise the management system and strengthen the articulation mechanism to boost patients' beliefs in recovery; and strengthen the all-round management of information technology for market supervision to deepen the emotional communication and connection.

Взаимодействие стейкхолдеров при формировании и управлении децентрализованными фондами капитального ремонта жилищно-коммунального хозяйства

Introduction. The purpose of this study is a systematic analysis of the stakeholder relations on the issue of the formation and management of decentralized capital repair funds. The high social significance of capital repairs of residential real estate, coupled with a high degree of wear and tear, determines the need for coordinated and effective stakeholder interaction, the involvement of public authorities in co-financing expenses and the development of effective mechanisms for the rational allocation of funds from decentralized capital repair funds formed in special accounts in banking organizations and protecting them from inflationary processes.Materials and methods. The authors explore institutional factors in the implementation of major renovations of apartment buildings, identify the key stakeholders of these processes, their interests and risks, and reveal the presence of an agency problem. Based on statistical data and regulations, the authors conduct economic modeling of the formation of a decentralized capital repair fund using the example of an existing homeowners' association, and calculate target indicators for the efficiency of capital repair fund management.Results. The conducted research revealed inconsistency of the current management approaches and the impossibility of forming major overhaul funds in sufficient size to replace elevator equipment after the shelf life expiry without external financing. The authors conduct a study of the agency problem that arises when managing funds placed in special accounts for major overhaul, and identify the presence of informal institutional factors that prevent the formation of a "mature real estate owner".Discussion. Based on the results of the study, the authors proposed regulatory measures that could positively affect the effectiveness of relations on the issue of formation and management of decentralized capital repair funds. In addition to regulatory measures, the authors consider it necessary to involve municipal deputies in awareness-raising activities aimed at creating a “mature property owner.” The scientific novelty of this study consists in the development of management and regulation methods for the formation of decentralized capital repair funds on the basis of the synthesis of stakeholder and institutional approaches.

Real-time service task scheduling with fine-grained resource utilization to benefit important industrial business

Scheduling of service-oriented industrial businesses to meet the real-time requirements and improve the computing resources utilization is important. To this end, a Fine-grained Online Service Task Scheduling (FOSTS) method is proposed. First, a service task model that separates the invoked service from the task is established. Then, a service invocation-oriented allocation mechanism that allocates the invoked tasks based on priority is proposed to achieve fine-grained resource utilization. In addition, a task suspension mechanism to release resources for important tasks by suspending non-important tasks is proposed. The proposed FOSTS is tested in a typical industrial scenario and its performance is compared with many common and state-of-the-art methods. The simulation results show the effectiveness and superior performance of the proposed FOSTS compared to the other methods.

Reliability-centered availability collaborative optimization allocation approach for machine tools

The availability of computer numerical control (CNC) machine tools is a comprehensive reflection of reliability and maintainability. To ensure the availability requirements of products, it is necessary to allocate the availability indicators of the entire machine to all units. Traditional methods based on reliability allocation or maintainability allocation ignore the coupling relationships among them, which cannot comprehensively improve the availability level of machine tools. Therefore, in this paper, a availability collaborative optimization allocation model for CNC machine tools is proposed to maximize the availability under the optimal combination of failure rate and repair rate. Firstly, a two-stage reliability allocation model based on different allocation mechanisms is established by taking the Function-Motion-Action (FMA) decomposition tree as the allocation path. In the first stage, the allocation weights are determined based on global sensitivity analysis. In the second stage, the reliability optimization allocation model based on Copula function is established. Then, with reliability as the center, an availability collaborative optimization allocation model constrained by maintainability is constructed, and the non-dominated sorting genetic algorithm II (NSGA-II) algorithm is used to solve the model. Finally, a CNC gear milling machine is taken as an example to verify the rationality and effectiveness of the method on product availability requirements under collaborative allocation.

Can the ‘21st Century Maritime Silk Road’ initiative improve the opening-up of China’s coastal provinces?

The Belt and Road Initiative (BRI) serves as China’s blueprint and major strategy for opening-up in the new era. This study theoretically examines three mechanisms of the ‘21st Century Maritime Silk Road’ (CMSR) to promote the opening up of provinces and cities along the line, including the allocation, integration, and circulation mechanisms. Using 2009–2021 data from prefecture-level cities, this study designed a quasi-natural experiment based on the CMSR by combining propensity score matching (PSM) and differences-in-differences (DID) methods. The study findings show CMSR significantly promoted China’s opening-up. Various robustness tests demonstrate that our findings are robust. Mechanism analysis shows that CMSR improved China’s opening-up by promoting the flow of production factors, integrating domestic and international product markets, and accelerating circulation. Heterogeneity analysis shows that CMSR strongly influences large, coastal, and nonprovincial cities. These findings provide a new perspective for evaluating the policy effects of the 21st CMSR.

Enhancing treatment performance of Chlorella pyrenoidosa on levofloxacin wastewater through microalgae-bacteria consortia: Mechanistic insights using the transcriptome

Microalgae-bacteria consortia (MBC) system has been shown to enhance the efficiency of microalgae in wastewater treatment, yet its effectiveness in treating levofloxacin (LEV) wastewater remains unexplored. This study compared the treatment of LEV wastewater using pure Chlorella pyrenoidosa (PA) and its MBC constructed with activated sludge bacteria. The results showed that MBC improved the removal efficiency of LEV from 3.50–5.41 % to 33.62–57.20 % by enhancing the growth metabolism of microalgae. The MBC increased microalgae biomass and extracellular polymeric substance (EPS) secretion, yet reduced photosynthetic pigment content compared to the PA. At the phylum level, Proteobacteria and Actinobacteriota are the major bacteria in MBC. Furthermore, the transcriptome reveals that the growth-promoting effects of MBC are associated with the up-regulation of genes encoding the glycolysis, the citrate cycle (TCA cycle), and the pentose phosphate pathway. Enhanced carbon fixation, coupled with down-regulation of photosynthetic electron transfer processes, suggests an energy allocation mechanism within MBC. The up-regulation of porphyrin and arachidonic acid metabolism, along with the expression of genes encoding LEV-degrading enzymes, provides evidence of MBC’s superior tolerance to and degradation of LEV. Overall, these findings lead to a better understanding of the underlying mechanisms through which MBC outperforms PA in treating LEV wastewater.

Optimizing task allocation with temporal‐spatial privacy protection in mobile crowdsensing

AbstractMobile Crowdsensing (MCS) is considered to be a key emerging example of a smart city, which combines the wisdom of dynamic people with mobile devices to provide distributed, ubiquitous services and applications. In MCS, each worker tends to complete as many tasks as possible within the limited idle time to obtain higher income, while completing a task may require the worker to move to the specific location of the task and perform continuous sensing. Thus the time and location information of each worker is necessary for an efficient task allocation mechanism. However, submitting the time and location information of the workers to the system raises several privacy concerns, making it significant to protect both the temporal and spatial privacy of workers in MCS. In this article, we propose the Task Allocation with Temporal‐Spatial Privacy Protection (TASP) problem, aiming to maximize the total worker income to further improve the workers' motivation in executing tasks and the platform's utility, which is proved to be NP‐hard. We adopt differential privacy technology to introduce Laplace noise into the location and time information of workers, after which we propose the Improved Genetic Algorithm (SPGA) and the Clone‐Enhanced Genetic Algorithm (SPCGA), to solve the TASP problem. Experimental results on two real‐world datasets verify the effectiveness of the proposed SPGA and SPCGA with the required personalized privacy protection.

Trade-Off and Synergy Mechanism of Agricultural Water Resource Spatial Allocation in Monsoon Climate Areas Based on Machine Learning: A Case Study of Reservoir Layout Optimization in Shandong Province, China

Influenced by increasing global extreme weather and the uneven spatiotemporal distribution of water resources in monsoon climate areas, the balance of agricultural water resources supply and demand currently faces significant challenges. Conducting research on the spatial allocation trade-offs and synergistic mechanisms of agricultural water resources in monsoon climate areas is extremely important. This study takes the spatial layout of reservoir site selection in water conservancy projects as an example, focusing on Shandong Province as the research area. During the site selection process, the concept of water resource demand is introduced, and the suitability of reservoir siting is integrated. It clarifies ten influencing factors for suitability degree and five influencing factors for demand. A bi-objective optimization model that includes suitability degree and demand degree is established. Utilizing machine learning methods such as the GA_BP neural network model and the GA-bi-objective optimization model to balance and coordinate the supply and demand relationship of agricultural water resources in the monsoon region. The study found that: (1) in the prediction of suitability degree, the influencing factors are most strongly correlated with the regulatory storage capacity (regulatory storage capacity > total storage capacity > regulating storage coefficient); (2) compared with single-objective optimization of suitability degree, the difference between water supply and demand can be reduced by 74.3% after bi-objective optimization; (3) according to the spatial layout optimization analysis, the utilization of water resources in the central and western parts of Shandong Province is not sufficient, and the construction of agricultural reservoirs should be carried out in a targeted manner. This study provides new ideas for promoting the efficient use of water resources in monsoon climate zones and the coordinated development of humans and nature, reflecting the importance of supply and demand balance in the spatial allocation of agricultural water resources, reducing the risk of agricultural production being affected by droughts and floods.

An ordinal-cardinal consensus adjustment allocation mechanism for large-scale group decision making based on the consistency of distributed preference relations under fuzzy uncertainty

Large-scale group decision making (LSGDM) problem is common in real life. With the increase in the number of alternatives and the limited rationality of human beings, consistency problem is inevitable when pairwise comparison method is used. We propose an improved consistency calculation approach to generate consistent distributed preference relations (DPRs), which adopts adjacent score intervals to calculate the score intervals of non-adjacent alternative pairs. By using optimization model, the initial DPR is preserved as much as possible on the premise of order consistency. As for the consensus analysis, the concept of relationship-possibility degree is defined to capture the ignorance and fuzzy uncertainty in assessments. An ordinal consensus measure method considering absolute position difference and relative position dissimilarity with relationship-possibility degree is proposed. Ordinal-cardinal consensus adjustment model based on DPR is then constructed to obtain the minimum consensus adjustment of decision makers or subgroups coalition which are considered as coalition payoff. In addition, to distribute the ordinal-cardinal minimum consensus adjustment reasonably, we construct a two-stage consensus adjustment allocation mechanism adopting the improved multi-weighted Shapley function in the cooperative game. Several optimization models are constructed to obtain the adjusted DPRs of decision makers or subgroups. Finally, an illustrative example is presented to demonstrate the validity of the proposed method in dealing with the decision problems of product development engineering. It is expected to make the LSGDM procedure in a more intelligent way.

A Cooperative Game Approach for Optimal Design of Shared Energy Storage System

The energy sector’s long-term sustainability increasingly relies on widespread renewable energy generation. Shared energy storage embodies sharing economy principles within the storage industry. This approach allows storage facilities to monetize unused capacity by offering it to users, generating additional revenue for providers, and supporting renewable energy prosumers’ growth. However, high investment costs and long payback periods often hinder the development of battery storage. To address this challenge, we propose a shared storage investment framework. In this framework, a storage investor virtualizes physical storage equipment, enabling prosumers to access storage services as though they owned the batteries themselves. We adopt a cooperative game approach to incorporate storage sharing into the design phase of energy systems. To ensure a fair distribution of cooperative benefits, we introduce a benefit allocation mechanism based on contributions to energy storage sharing. Utilizing realistic data from three buildings, our simulations demonstrate that the shared storage mechanism creates a win–win situation for all participants. It also enhances the self-sufficiency and self-consumption of renewable energy. This paper provides valuable insights for shared storage investors regarding optimal design and benefit allocation among multiple stakeholders.

Collaborative Service Network Design for Multiple Logistics Carriers Considering Demand Uncertainty

Collaborative designing of service networks using multiple logistics carriers can bring advantages in both economic and environmental terms, and these carriers have symmetry in their service areas. To enable such a collaborative service network and the corresponding benefits, this study proposes a problem of collaborative service network design (CSND) considering demand uncertainty. This problem is formulated as a two-stage robust optimization model using a budget uncertainty set to handle the uncertain demand. A column-and-constraint generation algorithm is developed to accurately solve the robust model. Numerical experiments show that the proposed algorithm outperforms the Benders decomposition algorithm in terms of solving efficiency and quality. Through comparative experiments, this research validates the advantages of collaborative designing and the robustness of model solutions. In addition, three allocation mechanisms are tested to investigate the importance of allocation in CSND.

Corporate governance effects of digital finance: Evidence from corporate tax avoidance in China

This paper tries to uncover the corporate governance effects of digital finance based on the corporate tax avoidance perspective. We find strong evidence that digital finance is negatively associated with corporate tax avoidance. The governance role digital finance plays is primarily mediated through the mechanisms of resource allocation and information governance effects. Further analysis shows that the negative effects of digital finance are more pronounced among higher profitability and non-state-owned firms. Additionally, multiple major shareholders and stronger internal control quality(corporate internal governance) as well as higher institutional investor shareholding and more analyst attention(corporate external governance) can strengthen their negative connection, manifesting the complementarity between digital finance and modern corporate governance mechanisms. Overall, this paper reveals the spillover effects of changes in the financial development environment on corporate tax avoidance strategies. It also contributes to enriching the literature on the corporate governance value of digital finance and the factors influencing corporate tax avoidance.

Strategic priority-based course allocation

We introduce the conditional acceptance mechanism for solving the course allocation problem under priorities. This mechanism implements the set of stable allocations in both Nash equilibrium and undominated Nash equilibrium when preferences and priorities are substitutable. We model a post-allocation adjustment mechanism using a repeated version of the conditional acceptance mechanism that mitigates the inefficiencies caused by deviating from equilibrium. Both mechanisms are straightforward to implement, simplify the elicitation of students’ preferences, and share features with currently employed course allocation mechanisms.

Cooperative operation for multiple virtual power plants considering energy-carbon trading: A Nash bargaining model

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases.

Benefit Distribution Mechanism of a Cooperative Alliance for Basin Water Resources from the Perspective of Cooperative Game Theory

At present, global water resource security is facing serious threats, and the construction of a cooperative, open, and mutually beneficial water resource community is a potential solution to the global water resource crisis and water resource hegemony. Previous studies on the formation and beneficial distribution of water resources in cooperative alliances have more often focused on the idea that participants take all of their water resources when they join a cooperative alliance (i.e., a crisp cooperative alliance), while fewer studies have focused on participants including different proportions of their water resources and joining multiple cooperative alliances (i.e., fuzzy cooperative alliances), and even fewer comparative studies concern the use of different benefit-sharing mechanisms. In this paper, in order to improve the efficiency of water use, allocate water resources more optimally, and generate higher returns for water users in a given basin, we propose the establishment of a traditional crisp and improved fuzzy cooperative alliance for water resources in the basin from the perspective of cooperative game theory; we examine the water resource allocation mechanism within the alliance based on the principle of priority; we construct a benefit allocation mechanism for the cooperative alliance based on the core, least core, weak least core, and Shapley value method; and we carry out empirical research using the example of the Tarim River Basin. Our findings are as follows: (1) A cooperative alliance based on the perspective of cooperative game theory can effectively improve overall benefits and individual benefits, and a fuzzy cooperative alliance is more effective than a crisp cooperative alliance in improving the overall water benefits of the region. (2) The participants in the fuzzy cooperative alliance can obtain more benefits than in the crisp cooperative alliance, and the benefit distribution mechanism of the cooperative alliance helps the participants to determine the object of cooperation while maintaining the sustainable existence of the alliance. (3) The different methods of benefit distribution within the cooperative alliance directly affect the overall water benefits of the region. (4) The different methods of benefit distribution directly affect the stability of the alliance, and the players in the game have heterogeneous preferences for different distribution schemes. The resource-sharing mechanism and benefit distribution mechanism of a water resource cooperative alliance have good applicability as solutions to the problem of water resource optimization and allocation in river basins, and they may provide policy references for the efficient use of water resources and optimization of water resource allocation and management in areas with a shortage of water resources, such as arid and semi-arid zones.

Research on the distribution of educational resources from the perspective of public service equalization in China—Based on government responsibility and fiscal input

This paper explores the distribution of educational resources from the perspective of public service equalization in China, with a particular focus on government responsibility and fiscal input. Initially, the paper reviews the theoretical foundations and empirical studies concerning the distribution of educational resources, analyzing the role of government in educational equity and the impact of fiscal expenditure. By employing quantitative analysis methods, this study utilizes data on provincial education expenditures over several years to examine the relationship between government fiscal input and the equalization of educational resources. Empirical results indicate that increasing educational fiscal input and optimizing the allocation mechanism significantly enhance the level of equalization in educational resources. Furthermore, through case analyses of several local governments, effective policy recommendations are proposed to promote the fair distribution and optimization of educational resources. Lastly, the paper discusses potential obstacles in policy implementation and suggests corresponding strategies.

Where projects and non-projects coexist in the core challenges for frontline managers

PurposeThere are different organizational contexts for projects. Here, the focus is on a balanced co-existence organization (BCO) where core activities combine project-based and non-project based work, a context that differs from both project-based organizations (PBOs) and project-supported organizations (PSOs). Through differentiating between the role of resource and project manager, and encompassing a specific combination of projects and ongoing, recurrent work, the authors extend the understanding of frontline managers and HRM in project settings.Design/methodology/approachThis is a case study of a 1000+ department in a Norwegian firm with 38 interviews with the use of qualitative analysis.FindingsThe empirical study of one case of BCO reveals a HRM system with four different constellations of front line managers, each with their own perceived advantages and challenges. Based on the findings here, we have drawn implications for research on the BCO category, as well as comparative research on the three different contexts for projects. Issues that would benefit from comparative studies of polyadic HRM include constellations of front line manager roles, tensions involving projects, mechanisms for allocation of human resources, as well as the sources and mechanisms of stability and change.Research limitations/implicationsThe findings are limited to one organization.Practical implicationsThis study provides a potential for further research on HRM issues in the BCO category.Originality/valueThe analysis develops the BCO category and introduces a category of three organizational contexts for projects. We provide better understanding of the three types and its HRM challenges.

Blockchain-Based Resource Allocation Mechanism for the Internet of Vehicles: Balancing Efficiency and Security

Blockchain-Based Resource Allocation Mechanism for the Internet of Vehicles: Balancing Efficiency and Security