Prospects for Digitalization of the Electoral Process in the Republic of Belarus

Based on a micro-entity perspective, this paper empirically examines the effect of regional integration on the efficiency of enterprise resource allocation. Firstly, regional integration can significantly reduce the degree of resource mismatch of enterprises and improve the efficiency of resource allocation of enterprises overall. Secondly, regional integration can improve the efficiency of resource allocation of enterprises mainly through three channels, which are alleviating the financing constraints of enterprises, improving the degree of talent agglomeration, and reducing the operating costs of enterprises. Thirdly, the effect of regional integration on improving the efficiency of enterprise resource allocation is heterogeneous, which has a greater effect on the efficiency of resource allocation for state-owned enterprises, enterprises in non-monopoly industries, large-scale enterprises, and enterprises in coastal areas. Finally, regional integration improves the productivity of enterprises by optimizing their resource allocation level. The enterprise management level positively moderates the effect of regional integration on the efficiency of enterprise resource allocation. Therefore, some countermeasures and suggestions are put forward.

The transportation infrastructure is widely regarded as an important factor for the improvement of economic performance in developing countries, but its effect mechanism remains controversial. In recent years, people widely argue that the efficiency of resource allocation among enterprises mainly accounts for a large economic performance difference between different nations. To test whether the transport infrastructure actually affects enterprise resource allocation and thereby improves economic performance, this paper uses the data matching industrial enterprises and highway construction in China, and empirically analyzes the impact of Chinese transportation infrastructure on the efficiency of enterprise resource allocation and its effect mechanism. The results show that transportation infrastructure does improve the efficiency of enterprise resource allocation and enterprises which are located in cities with nearer distance from the expressway have a smaller difference between real size and optimal size. Specifically speaking, transportation infrastructure reduces output distortion resulting in both capital and labor input distortion, thereby making real sizes of enterprises closer to the optimal sizes. The analysis based on mediation effect further indicates the factors concerning the effect of expressway on the efficiency of enterprise resource allocation mainly include price markup, industry concentration, and so on, and expressway does not play a significant role in the efficiency of enterprise resource allocation through inventories.

To analyze the regional disparities, dynamic evolution, and influencing factors of medical resource allocation efficiency in TCM hospitals across China from 2016 to 2022, providing references for optimizing resource allocation in TCM hospitals. The study employed a super-efficiency Slack-Based Measure (SBM) model considering undesirable outputs to assess regional equity in efficiency, utilized the Dagum Gini coefficient to measure regional disparities in efficiency, and applied kernel density estimation and spatial econometric models to analyze the dynamic evolution and spatial spillover effects of medical resource allocation efficiency in TCM hospitals. In 17 provinces, the efficiency is higher than the average value of 0.839, and in 8 provinces, the average value has exceeded 1. The regional pattern of efficiency shows a gradient characteristic of "high in the east and stable in the west, with the Northeast lagging behind." There is a significant spatial difference in the efficiency of resource allocation. The overall difference in the allocation of resources for traditional Chinese medicine (TCM) hospitals shows a fluctuating upward trend. The contribution rate of regional differences reaches 53.45%, which is the dominant factor. The largest regional differences are found within the central region, while the gaps between the eastern and central regions continue to widen, and those between the western and northeastern regions tend to become more balanced. The most significant interregional differences are observed between the central and western regions. The efficiency of resource allocation for TCM hospitals is on the rise, with the kernel density curve shifting to the right. The main peak height first decreases and then increases, while the width first expands and then contracts. The absolute difference first increases and then decreases. The rightward convergence of the tail indicates that there are efficient hospitals, but the gaps are narrowing. The multi-peak distribution reveals a multi-level differentiation pattern with the coexistence of low-efficiency and high-efficiency clusters. Per capita GDP, urbanization level, aging rate, population density, and the number of graduates from higher medical colleges can promote efficiency improvement. Population density and the proportion of TCM physicians have a positive spatial spillover effect on efficiency, while per capita GDP has a negative spatial spillover effect. The efficiency of medical resource allocation in traditional Chinese medicine (TCM) hospitals is steadily improving, and the regional differences are continuously narrowing. The degree of efficiency multi-polarization is becoming more moderate, and the development of regional equilibrium is being achieved. Both internal and external environmental factors jointly influence the improvement of medical resource allocation efficiency in TCM hospitals. It is recommended to take measures such as technological empowerment, institutional constraints, financial support, and talent absorption to enhance the efficiency of medical resource allocation in TCM hospitals and bridge the regional gaps.

BackgroundCounty-level Centers for Disease Control and Prevention (CDCs) are the foundational units of China’s public health system. The COVID-19 pandemic has highlighted the shortcomings of the system, making it urgent to strengthen the functions of county-level CDCs. The efficiency and equity of resource allocation are crucial for enhancing public health outcomes. Therefore, this study aimed to evaluate six-year trends (2018–2023) in equity and efficiency of resource allocation among the ten county-level CDCs in Qingdao and to identify actionable measures for optimizing grassroots public-health capacity in the post-COVID-19 era.MethodsWe used Gini coefficient and Lorenz curve to assess the equity of resource allocation in the county-level CDCs in Qingdao. The efficiency of CDCs was evaluated using data envelopment analysis (DEA) and Bootstrap DEA. Efficiency change was analyzed by employing the Malmquist productivity index (MPI).ResultsThe health resources at the Qingdao CDCs showed an overall upward trend from 2018 to 2023. During 2018–2023, CDC personnel allocation showed good equity in demographic and economic dimensions (Gini < 0.3), but suboptimal equity in geographic distribution (Gini 0.3–0.5). The average technical efficiency was 0.940, pure technical efficiency averaged 0.995, and scale efficiency was 0.944. Among 10 CDCs, 50% achieved DEA efficiency. According to the total factor productivity (TFP) reflected by the indicator system constructed in this study, TFP grew at a rate of 6.0% between 2022 and 2023. Changes in technical efficiency change (TEC) and scale efficiency change (SEC) generally exceeded those in technological progress (TC).ConclusionIn order to enhance the equity and efficiency of resource allocation in county-level CDCs in Qingdao City. The government needs to adopt targeted policies, such as implementing flexible staffing adjustments, increasing the number of technical personnel and senior experts, and strengthening continuous training to enhance workforce capabilities. Also, fiscal efficiency should be enhanced by linking fund allocation with performance evaluation. Meanwhile, accelerating technological modernization and enhancing technological capabilities through digital tools and management innovation are crucial. Overall, these comprehensive measures aim to enhance resource utilization efficiency and strengthen the resilience of public health services.Clinical trial numberNot applicable.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12913-025-13478-y.

The impact of rural-urban student mobility on the efficiency of resource allocation in China’s rural households is crucial for refining policies related to rural migrant settlement and the balanced allocation of urban and rural educational resources. Drawing on theoretical insights, this study employs a mixed methods approach—primarily qualitative, with quantitative support—to empirically test the impact of rural-urban student mobility on the resource allocation efficiency of rural households in China. Utilizing micro-survey data from China Family Panel Studies (CFPS), this study applies ordinary least squares (OLS) models, propensity score matching difference-in-differences (PSM-DID) models, and endogenous switching regression (ESR) models to ascertain the direction of this impact. Furthermore, this study incorporates in-depth interview data gathered from field research in D County to explore the dynamic mechanisms of resource allocation adjustments within these households. The results show that rural-urban student mobility significantly reduces the efficiency of labor resource allocation and agricultural production in China’s rural households. The impact is heterogeneous across different groups, most negatively affecting households with limited labor resources, lower educational levels, lower incomes, more productive fixed assets, and less self-owned land. Mobility leads to suboptimal occupational choices, resulting in decreased labor resource efficiency. Additionally, it distorts agricultural production by leading to labor loss, reduced investments in agricultural productivity, and misaligned land allocation decisions.

Cloud computing is one among the emerging platforms in business, IT enterprise and mobile computing applications. Resources like Software, CPU, Memory and I/O devices etc. are utilized and charged as per the usage, instead of buying it. A Proper and efficient resource allocation in this dynamic cloud environment becomes the challenging task due to drastic increment in cloud usage. Various promising technologies have been developed to improve the efficiency of resource allocation process. But still there is some incompetency in terms of task scheduling and power consumption, when the system gets overloaded. So an energy efficient task scheduling algorithm is required to improve the efficiency of resource allocation process. In this paper an improved task scheduling and an optimal power minimization approach is proposed for efficient dynamic resource allocation process. Using prediction mechanism and dynamic resource table updating algorithm, efficiency of resource allocation in terms of task completion and response time is achieved. This framework brings an efficient result in terms of power reduction since it reduces the power consumption in data centers. The proposed approach gives accurate values for updating resource table. An efficient resource allocation is achieved by an improved task scheduling technique and reduced power consumption approach. The Simulation result gives 8% better results when comparing to other existing methods.

Fog computing is an emergent and powerful computing paradigm to serve latency-sensitive applications by executing internet of things (IoT) applications in the proximity of the network. Fog computing offers computational and storage services between cloud and terminal devices. However, an efficient resource allocation to execute the IoT applications in a fog environment is still challenging due to limited resource availability and low delay requirement of services. A large number of heterogeneous shareable resources makes fog computing a complex environment. In the sight of these issues, this paper has proposed an efficient levy flight firefly-based resource allocation technique. The levy flight algorithm is a metaheuristic algorithm. It offers high efficiency and success rate because of its longer step length and fast convergence rate. Thus, it treats global optimization problems more efficiently and naturally. A system framework for fog computing is presented, followed by the proposed resource allocation scheme in the fog computing environment. Experimental evaluation and comparison with the firefly algorithm (FA), particle swarm optimization (PSO), genetic algorithm (GA) and hybrid algorithm using GA and PSO (GAPSO) have been conducted to validate the effectiveness and efficiency of the proposed algorithm. Simulation results show that the proposed algorithm performs efficient resource allocation and improves the quality of service (QoS). The proposed algorithm reduces average waiting time, average execution time, average turnaround time, processing cost and energy consumption and increases resource utilization and task success rate compared to FA, GAPSO, PSO and GA.

The ever-expanding scale of cloud datacenters necessitates automated resource provisioning to best meet the requirements of low latency and high energy-efficiency. However, due to the dynamic system states and various user demands, efficient resource allocation in cloud faces huge challenges. Most of the existing solutions for cloud resource allocation cannot effectively handle the dynamic cloud environments because they depend on the prior knowledge of a cloud system, which may lead to excessive energy consumption and degraded Quality-of-Service (QoS). To address this problem, we propose an adaptive and efficient cloud resource allocation scheme based on Actor-Critic Deep Reinforcement Learning (DRL). First, the actor parameterizes the policy (allocating resources) and chooses actions (scheduling jobs) based on the scores assessed by the critic (evaluating actions). Next, the resource allocation policy is updated by using gradient ascent while the variance of policy gradient is reduced with an advantage function, which improves the training efficiency of the proposed method. We conduct extensive simulation experiments using real-world data from Google cloud datacenters. The results show that our method can obtain the superior QoS in terms of latency and job dismissing rate with enhanced energy-efficiency, compared to two advanced DRL-based and five classic cloud resource allocation methods.

Fairness and efficiency are two fundamental topics in resource allocation. In resource allocation problems, we need to allocate a set of items to a set of agents. From an efficiency perspective, our goal is to maximize the total reward of the allocation. From the perspective of fairness, we want to ensure that every agent feels the allocation is fair. This thesis aims to identify required allocations from these different perspectives. We present our findings in three parts: (i) efficiency in online resource allocation, (ii) fairness in offline resource allocation, and (iii) fairness and efficiency in offline resource allocation.&#13;\n&#13;\nIn Part I, we study the efficiency guarantees in the fully online matching problem, which is a constrained resource allocation problem. Since efficiency is easily guaranteed in the offline setting, we focus on the fully online setting where both agents and items arrive dynamically. For this problem, we provide a randomized algorithm that achieves a competitive ratio of $0.1549$.&#13;\n&#13;\nIn Part II, we investigate fairness guarantees in the offline resource allocation problem.&#13;\nIn this part, we first consider a mixed goods setting where some items can be divided into arbitrarily small pieces, while others can only be fully allocated to an agent. &#13;\nIn this problem, we propose two ``up to a fraction'' relaxations of some classical fairness concepts, and prove the existence of such fair allocations in the mixed goods setting.&#13;\nWe then return to the indivisible goods setting, where every item must be fully allocated to a single agent.&#13;\nIn this setting, we allow some uncertainties in agents' preferences towards items and provide some complexity analysis of finding allocations that can be fair with a high probability.&#13;\n&#13;\nIn Part III, we aim to find a fair and efficient allocation in the offline resource allocation problem.&#13;\nWe first study the price of fairness, which measures the efficiency loss when considering the fairness constraints.&#13;\nFor this, we consider both the indivisible goods and the mixed goods settings, and provide a tight analysis of the price of fairness in these two settings.&#13;\nWe then come to a resource allocation problem for cloud computing, where agents have Leontief preferences over items. &#13;\nIn this setting, we propose several new mechanisms that can produce a fair allocation with better social welfare guarantee.

Increasing the efficiency of resource allocation is the basis and guarantee for boosting high-quality economic development. Based on the panel data of Chinese industrial enterprises and cities from 2008 to 2013, this paper studies the influence of infrastructure construction demand shocks represented by local government debt expansion on the efficiency of sectoral resource allocation from the perspective of sectoral linkage. According to the empirical findings, local government debt significantly reduces the resource allocation efficiency of manufacturing sector that is highly related to infrastructure construction. This conclusion is still tenable after the robustness test using the simulated local government debt as an instrumental variable. Further mechanism tests show that there are two reasons for the decline of the efficiency of resource allocation in manufacturing sector that is highly related to infrastructure construction. First, more product demands and investments brought by the expansion of local government debt flow to less productive enterprises in the sector. Second, resource misallocation reduces the probability of high-productivity enterprises entering the market and low-productivity enterprises exiting the market, and the effect is more prominent in cities with high dependence on state-owned enterprises and high pressure on officials to be promoted. According to this study, the performance management of local government debt should be further strengthened, and particular attention should be paid to the influence of local government debt on enterprise investment and financing crowding out and resource misallocation.

In the face of increasingly growing health demands and the impact of various public health emergencies, it is of great significance to study the regional differences in the allocation efficiency of the rural public health resources and its improvement mechanism. In this paper, the game competition relationship is included in the evaluation model, and the game cross-efficiency model is used to measure the allocation efficiency of the rural public health resources in 31 provinces of China from 2008 to 2017. Then, the Theil index model and the Gini index model are applied in exploring the regional differences in the allocation efficiency of rural public health resources and its sources. Finally, the bootstrap truncated regression model is used to analyze the influencing factors of the allocation efficiency of the rural public health resources in China. The results show that, first, the total allocation efficiency level of the rural public health resources in China from 2008 to 2017 is relatively low, and it presents a U-shaped trend, first falling and then rising. Second, the changing trend of the allocation efficiency of the rural public health resources in the eastern, central, and western regions of China is similar to that in the nationwide region, and it shows a gradient trend that “the allocation efficiency in the eastern region is high, the allocation efficiency in the western region is low, and the allocation efficiency in the Central region is at the medium level”. However, the gap among the three regions is continually narrowing. Third, the calculation results of the Theil index and the Gini index show that intra-regional differences are the major source of the regional differences in the allocation efficiency of the rural public health resources in China, and the inter-regional differences demonstrate an expansion trend. Finally, the improvement of the education level and the social support level will generally improve the allocation efficiency of the rural public health resources in China and its three regions. The increased governmental financial support and urbanization level will reduce the allocation efficiency of the rural public health resources in China and its three regions. The economic development level, the living conditions and the population density are the important influencing factors of the allocation efficiency differences of the rural public health resources in the three regions. Therefore, on the basis of ensuring the increase of the total supply of the rural public health resources, more attention should be paid to the improvement of the allocation efficiency. Moreover, on the basis of continually narrowing the inter-regional differences among the eastern, central, and western regions, more attention should be paid to the intra-regional differences of the allocation efficiency of the rural public health resources among the different provinces. The various economic and social policies should be constantly optimized to jointly improve the allocation efficiency of the rural public health resources.

Research on development of digital finance in improving efficiency of tourism resource allocation

As a core part of the modern market economy system, the financial market has a direct impact on the development of national economic construction. Based on Jeffrey Wurgler's Capital Allocation Efficiency Model and relying on the 2007–2014 data of A-share market, empirical research shows that China's resource allocation efficiency is low. The direct factors that affect the allocation efficiency of China's stock market are investor heterogeneity belief, agency cost and enterprise value. Through the multiple linear regression analysis, it is found that the investors' heterogeneous beliefs and agency costs have an inhibitory effect on the efficiency of resource allocation in China's stock market, while the value of the enterprises has played a catalytic role. Investors' heterogeneous beliefs have the greatest impact on stock market resource allocation efficiency. According to the results of the research, a scheme to solve the efficiency of stock market resource allocation is designed. The scheme puts forward the solution from weakening the government's administrative intervention, perfecting the stock market's market mechanism and strengthening the investors' judgment ability. At the same time, the scheme is analyzed from the viewpoints of feasibility, rationality and applicability.

International evidence on the effects of directed credit programmes on efficiency of resource allocation in developing countries: The case of development bank lendings

Education has the purpose of serving economic and social development, and the efficiency of resource allocation in the higher education system has become an important factor affecting the quality of economic development. Based on the panel data of China's higher education from 2014 to 2023, the adoption of data envelopment analysis (DEA) model was used to evaluate the efficiency of China's higher education resource allocation. The evaluation results show that China's higher education resource allocation efficiency has not reached the effective state of DEA, but the overall level is high; there are certain differences in the higher education resource allocation efficiency in different regions; the negative growth of China's higher education resource allocation efficiency is obvious, and technological progress is the main factor hindering the improvement of total factor production efficiency. Therefore, based on the relevant policies, this paper puts forward rationalization suggestions for the improvement of the allocation efficiency of higher education resources in China from the perspectives of human, financial and material resources.