Could Executive Compensation Incentive Enhance the Efficiency of Enterprise Resource Allocation? An Empirical Study from China

Corporate executives have the decision-making power of resource allocation, and efficient resource allocation is an important measure of high-quality development of enterprises. It is a focal issue whether the compensation incentive can promote the executives to make better use of the enterprise resource allocation. We investigate this question using the data of the Chinese listed companies in 2015–2019 based on Data Envelopment Analysis (DEA) and fixed effect model. The results show the following: (1) both monetary compensation incentive and equity incentive can significantly improve the efficiency of resource allocation, and the former is more significant; (2) there is an inverted U-shaped relationship between perquisite consumption incentive and resource allocation efficiency; (3) the above conclusion is still true in state-owned enterprises; (4) in private enterprises, the effect of equity incentive is more effective, but the effect of perquisite consumption incentive is less significant. The results highlight the relationship between compensation incentive and enterprise resource allocation. Our study is expected to guide the executives to formulate reasonable compensation incentives and improve the efficiency of resource allocation.

Transmission Effectiveness of Resource Allocation Efficiency in Multitier Capital Market System

With the continuous development of the capital market, in order to study the effectiveness of the multilevel capital market, the operation status of the multilevel capital market is used as the research object, and the Pareto analysis paradigm is used to study the effectiveness of the transmission mechanism of the resources allocation efficiency of the multilevel capital market. Research has shown that Pareto analysis model can be used to analyze the multilevel capital markets. Investors’ irrationality and lack of professionalism further aggravate market volatility. Research on resource allocation of multilevel capital market systems and the effectiveness of the transmission mechanism has certain theoretical significance and practical value.

Impact of capital enrichment on resource allocation efficiency in China’s manufacturing industry

Capital enrichment (CE) results from capital flows, which reflect the capital distribution among different regions and industries. This paper constructs the evaluation model of resource allocation efficiency from the perspective of capital and innovation resources. It expounds on CE’s theoretical mechanism by using the panel data from 2011 to 2018 for system GMM estimation. It finds that the manufacturing capital allocation efficiency (CAE) and innovation resource allocation efficiency (IRAE) show a volatile development trend. Both static and dynamic panel models show that there is a significant U-shaped curvilinear relationship between CE and CAE, CE and IRAE. CE’s inhibitory effect on CAE and IRAE decreases with the improvement of CE until it exceeds the critical value of 8.27 and 8.93. After that, its impact on CAE and IRAE changes from negative to positive.

Allocation Efficiency of Higher Education Resources in China

This paper uses the super-efficiency data envelopment analysis (DEA) model to measure the higher education resource allocation efficiency (HERAE) of 30 provinces from China 2005-2018, and analyzes the regional difference and dynamic evolution law of the HERAE with Theil index and kernel density estimation, respectively. The results show that: The HERAEs of most provinces are DEA effective, but the HERAEs of a few provinces are DEA ineffective, calling for further improvement to the allocation of higher education resources in these places. There was a certain difference in the HERAE trend between eastern, central, and western regions. In the sample period, eastern region had higher HERAE than central and western regions. With the elapse of time, the internal gap of HERAE decreased to different degrees in the three regions. Eastern region had the largest gap, followed in turn by central and western regions. In addition, China’s HERAEs were polarized in time. With the passage of time, the polarization of regional HERAEs slowly weakened.

Impact of Financial R&D Resource Allocation Efficiency Based on VR Technology and Machine Learning in Complex Systems on Total Factor Productivity

With the development of the globalization of science and technology, innovation has become an important driving force for regional economic development. As a core element of regional innovation, financial R&D resources have also become a key element to enhance national innovation capabilities and national economic competitiveness. National and regional innovation capabilities have a direct impact. There are also many deep-seated problems behind the world-renowned achievements, such as irrational industrial structure, insufficient independent innovation capabilities, low resource utilization efficiency, and the service quality and efficiency of financial institutions for the transformation of total factor productivity. These problems extremely restrict the efficiency upgrade and further development of our country’s total factor productivity. This study uses the DEA-Malmquist index model to measure the efficiency of fiscal R&D resource allocation in 28 provinces and regions in China in the past 10 years and uses Mapinfo12.0 software to analyze regional differences in the efficiency of fiscal R&D resource allocation in China from a spatial perspective. During the year, the overall R&D resource allocation efficiency of 28 provinces and autonomous regions in China has shown an upward trend. The efficiency of fiscal R&D resource allocation and the concentration of financial factors have had a positive impact on total factor productivity, transform and upgrade factors, increase total factor productivity, and provide empirical evidence for building a strong country.

Study on human resource allocation efficiency based on DEA analysis

As a new resource, human resource has attracted wide attention in many social fields. The competition of human resource is the competition of productivity between different enterprises. With the reform and opening up, national economy of China continues to develop rapidly. The sound macro-economy and rapidly development of capital market lead the banking industry to have a good development prospect. Whether the human resource allocation of commercial Banks is effective or not has a great impact on the bank earning. This study aims to further clarify the human resource allocation efficiency of banks to improve the efficiency and realize the improvement of bank profits. In this study, computer software was used to calculate the scale efficiency, pure technical efficiency, the change of scale interval and data envelopment analysis (DEA) efficiency of some selected representative banks according to the DEA model. The analysis showed that the DEA scale of many banks could reach the valid value 1, and the human resource allocation efficiency was optimized. The pure technical efficiency of some banks was valid value 1, but the scale efficiency was low and ineffective, which needed to be enlarged appropriately. And the DEA efficiency of some banks was invalid, which was caused by the valid value 1 of the scale efficiency and relatively low pure technical efficiency, and such banks need to make reasonable allocation of human resources.

Overcoming inefficiencies arising due to the impact of the modifiable areal unit problem on single-aggregation disease maps

Background In disease mapping, fine-resolution spatial health data are routinely aggregated for various reasons, for example to protect privacy. Usually, such aggregation occurs only once, resulting in ‘single-aggregation disease maps’ whose representation of the underlying data depends on the chosen set of aggregation units. This dependence is described by the modifiable areal unit problem (MAUP). Despite an extensive literature, in practice, the MAUP is rarely acknowledged, including in disease mapping. Further, despite single-aggregation disease maps being widely relied upon to guide distribution of healthcare resources, potential inefficiencies arising due to the impact of the MAUP on such maps have not previously been investigated. Results We introduce the overlay aggregation method (OAM) for disease mapping. This method avoids dependence on any single set of aggregate-level mapping units through incorporating information from many different sets. We characterise OAM as a novel smoothing technique and show how its use results in potentially dramatic improvements in resource allocation efficiency over single-aggregation maps. We demonstrate these findings in a simulation context and through applying OAM to a real-world dataset: ischaemic stroke hospital admissions in Perth, Western Australia, in 2016. Conclusions The ongoing, widespread lack of acknowledgement of the MAUP in disease mapping suggests that unawareness of its impact is extensive or that impact is underestimated. Routine implementation of OAM can help avoid resource allocation inefficiencies associated with this phenomenon. Our findings have immediate worldwide implications wherever single-aggregation disease maps are used to guide health policy planning and service delivery.