Project description:Seed industry plays a pivotal role in the advancement of national agricultural growth, with seed companies serving as the primary drivers of seed production. The existence of seed companies with the ability to integrate innovation and adapt to market demand plays a crucial role in a nation's capacity to ensure food security over time. This study utilizes micro-data from listed seed companies in China spanning the years 2019-2023 to conduct a comprehensive analysis of enterprise innovation efficiency. The research aims to identify strategies for enhancing innovation efficiency and ultimately fostering development within these seed companies. The findings indicate that: (1) The general level of innovation efficiency among listed seed companies in China exhibits significant potential for enhancement, with technology research and development stage demonstrating higher efficiency levels compared to stage of achievement transformation; (2) The enhancement of innovation efficiency in listed seed companies does not rely solely on any individual factor, but rather necessitates the combined influence of two or more antecedent variables; (3) Listed seed companies in China can enhance their innovation capability through five key approaches: employee-centric, talent and management-focused, talent and scale diversity-driven, talent and government collaboration, and talent and diversity enhancement strategies. The findings presented in this paper are expected to enhance the innovation efficiency of seed companies and offer both policy recommendations and practical guidance for fostering seed industry.
Project description:This research paper provides for the identification of dry bulk terminal efficiencies on the basis of 10 key performance factors in Malaysian ports. Data were collected from 18 dry bulk ports in Malaysia in 2017 through an online questionnaire and distributed via e-mail. The dispersion of the respondents corresponds approximately to the structure of the Malaysian maritime terminal in dry bulk. The data provides port management perceptions towards 10 variables that have been surveyed. Each perception assessed the level of efficiency factors based on a percentage rate of 100%. Efficiency factors in dry bulk terminals have been identified with varying characteristics based on a descriptive analysis table. The dataset presented consists of a brief analysis of all 10 variables involved, including the minimum, maximum, mean, interquartile median and standard deviation. In addition to the descriptive analysis, the normality test and histogram were also performed. Data can be used to measure ports-efficiency factors in another research.
Project description:The coordinated development of regional logistics and the economy is crucial for regional economic progress and for reducing regional development disparities. This study applies regional coordinated development theory and coupling theory, utilizing the Coupling Coordination Degree Model (CCDM) to analyze data from 31 provinces and cities in China in 2021, with the analysis results serving as the outcome variable. Additionally, we use data from four dimensions: infrastructure investment (II), technological innovation (TI), industrial structure (IS), and human capital (HC), as the conditional variables, conducting a multi-factor configurational analysis using fsQCA. Three paths with high coupling coordination and one path with non-high coupling coordination are identified, and the reasons for each path are analyzed. The results indicate that: 1) there are significant regional disparities in China regarding economic development, logistics development, and the degree of their coupling and coordination, with the eastern regions exhibiting higher levels and the western regions and other remote areas exhibiting lower levels. 2) The three paths with high coupling coordination are: "Infrastructure Investment-Technological Innovation", "Technological Innovation-Industrial Structure-Human Capital", and "Infrastructure Investment-Fundamental Innovation-Industrial Structure". These three types facilitate the well-coordinated progress of regional logistics and the economy. The article concludes by highlighting policy suggestions that underscore the significance of fortifying the bond between the logistics industry and the economy, alongside earnest efforts to enhance regional logistics standards. This will foster a mutually reinforcing and co-developing situation, further promoting coordinated development among regions, achieving high-quality regional development, and reducing the imbalances in logistics and economic development among different regions.
Project description:In China, industrial pollution has become an urgent problem for policy makers and enterprise managers. To better support industrial development, we need to determine the effectiveness of policies through efficiency evaluation. China's provincial industrial system consists of two stages: production and emission reduction. The emission reduction stage is composed of three parallel sub stages: solid waste treatment, waste gas treatment and wastewater treatment. In this process, the treatment capacity of industrial wastewater treatment facilities can be used as carry forward variable, which is not only the desirable output of the previous emission reduction stage, but also the input of the current emission reduction stage. Therefore, this paper proposes a dynamic hybrid two-stage data envelopment analysis (DEA) model for eco-efficiency evaluation of industrial systems, and applies it to a case study of Chinese regional industry. Applying the data collected from 2011 to 2015 to the model, the following conclusions can be drawn: (1) During the whole survey period, the average eco-efficiency was 0.9027. The overall eco-inefficiency of China's provincial industrial system during the study period is mainly due to low efficiency of solid waste treatment and waste gas treatment. (2) The average eco-efficiency of provincial industrial system increased steadily from 2011 (0.6448) to 2014 (0.6777), but decreased slightly in 2015 (0.5908). (3) The carry forward treatment capacity of industrial wastewater treatment facilities has a remarkable impact on provincial industrial system efficiency scores, especially at the wastewater treatment stage (0.6002 vs 0.3691). (4) Provincial industrial system exists distinct geographical characteristics of low efficiency. This study has important guiding significance for policy makers and enterprise managers who are concerned about industrial pollution control.
Project description:The study aims to provide an in-depth analysis of a transportation capacity shortage issue affecting Australian logistics service providers. Transportation capacity shortage is an important issue in all transportation modes. In this study, the driver shortage is viewed as an antecedent variable to estimate the impact of transportation capacity shortage on logistics performance. This study investigates the underlying relationships between driver shortage, logistics capability, and logistics performance according to resource-based theory. Structural equation modeling (SEM) was used to analyze the measurement models and structural model. The empirical results illustrate that driver shortage indirectly influences logistics performance, the logistics capability is a mediator factor in the relationship between driver shortage and logistics performance in logistics service providers. We argue that this provides valuable insights for transportation capacity shortage management.
Project description:This paper proposes a two-step approach to build portfolio models. The first step employs the Data Envelopment Analysis (DEA) to select assets attaining efficient financial performance according to a set of indicators used as inputs and outputs. The second step builds interval multiobjective portfolio models to obtain the optimal composition of efficient portfolios previously identified with respect to investor preferences. The usefulness of this proposed methodology is illustrated through a selected sample of diversified Exchange Traded Funds (ETFs) operating in the US energy sector. Our results with respect to all models and time horizons mainly show that: (i) ETFs related to nuclear energy are more often viewed as efficient according to all DEA models considered; (ii) the efficient portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios.Supplementary informationThe online version contains supplementary material available at 10.1007/s10479-021-04323-6.
Project description:BACKGROUND:The maturing of gene expression microarray technology and interest in the use of microarray-based applications for clinical and diagnostic applications calls for quantitative measures of quality. This manuscript presents a retrospective study characterizing several approaches to assess technical performance of microarray data measured on the Affymetrix GeneChip platform, including whole-array metrics and information from a standard mixture of external spike-in and endogenous internal controls. Spike-in controls were found to carry the same information about technical performance as whole-array metrics and endogenous "housekeeping" genes. These results support the use of spike-in controls as general tools for performance assessment across time, experimenters and array batches, suggesting that they have potential for comparison of microarray data generated across species using different technologies. RESULTS:A layered PCA modeling methodology that uses data from a number of classes of controls (spike-in hybridization, spike-in polyA+, internal RNA degradation, endogenous or "housekeeping genes") was used for the assessment of microarray data quality. The controls provide information on multiple stages of the experimental protocol (e.g., hybridization, RNA amplification). External spike-in, hybridization and RNA labeling controls provide information related to both assay and hybridization performance whereas internal endogenous controls provide quality information on the biological sample. We find that the variance of the data generated from the external and internal controls carries critical information about technical performance; the PCA dissection of this variance is consistent with whole-array quality assessment based on a number of quality assurance/quality control (QA/QC) metrics. CONCLUSIONS:These results provide support for the use of both external and internal RNA control data to assess the technical quality of microarray experiments. The observed consistency amongst the information carried by internal and external controls and whole-array quality measures offers promise for rationally-designed control standards for routine performance monitoring of multiplexed measurement platforms.
Project description:Coronavirus disease 2019 (COVID-19) has brought about a significant and far-reaching impact on the world's business environment, corporations, and individuals. In the face of the general shortage of funds caused by the pandemic, assuming corporate social responsibility (CSR) is a problem for every enterprise manager. In the recent years, as corporate social responsibility (CSR) has become a hot topic globally, many enterprises have chosen to incorporate social responsibility into their development strategies. The food industry is a basic industry related to people's livelihood, especially in the pandemic. Its social responsibility efficiency deserves our attention. This article takes 17 sample enterprises whose CSR performance between 2012 and 2020 in China and reports are above the industry level as examples. Constructing the super-efficiency data envelopment analysis (DEA)-Malmquist-Tobit model explores the social responsibility efficiency of these enterprises. It analyzes the pandemic's impact on CSR efficiency. The results show that COVID-19 has promoted the social responsibility efficiency of the sample enterprises in the food industry. Besides, the level of technical efficiency and technological progress in the food industry is relatively high. Still, most enterprises are below the industry's average level. Before the outbreak of the pandemic, the size of enterprises is the key factor affecting the efficiency of CSR. After then, the listing years of enterprises then become the key factor.
Project description:The efficient allocation of sports resources for optimal outcomes remains a pressing national endeavour in China. Over the past two decades, substantial investments by provincial and national governments have been directed toward sports infrastructure development. This initiative aims to foster sports talent, facilitate excellence, host major sporting events, and enhance national pride and soft power. This study employs a comprehensive methodology encompassing Data Envelopment Analysis-Slack Based Measure (DEA-SBM), Meta Frontier Analysis, and Malmquist Productivity Index to assess Sports Resource Utilization Efficiency (SRUE), Technological Gap Ratio (TGR), and Productivity Growth (MI) across China's 31 provinces and 3 distinct regions for the period 2010-2021. The findings indicate that China's average SRUE stands at 0.6307, revealing an inefficiency of 36.93% in sports resource utilization. Noteworthy efficiency was observed in Beijing, Chongqing, Henan, Shaanxi, Shanghai, and Tianjin during the study duration. Furthermore, a consistent upward trajectory in SRUE from 2010 to 2021 highlights gradual and sustained progress. Comparatively, the eastern region showcases higher technological advancement (average TGR of 0.7598) than the central and western regions. The Malmquist Productivity Index (MI), with an average value of 1.05391, highlights a substantial 5.39% productivity growth. Notably, technological advancement emerges as the primary driver of this productivity increase, evident through the higher Total Factor Productivity Change (TC) of 1.0312 compared to the Efficiency Change (EC) of 1.0209. The Central region's outperforming productivity growth is noteworthy relative to the Eastern and Western regions. Conclusively, the Kruskal-Wallis test confirms significant disparities in the average MI, EC, TC, and TGR among all three regions of China.
Project description:BackgroundIn order to measure and analyse the technical efficiency of district hospitals in Ghana, the specific objectives of this study were to (a) estimate the relative technical and scale efficiency of government, mission, private and quasi-government district hospitals in Ghana in 2005; (b) estimate the magnitudes of output increases and/or input reductions that would have been required to make relatively inefficient hospitals more efficient; and (c) use Tobit regression analysis to estimate the impact of ownership on hospital efficiency.MethodsIn the first stage, we used data envelopment analysis (DEA) to estimate the efficiency of 128 hospitals comprising of 73 government hospitals, 42 mission hospitals, 7 quasi-government hospitals and 6 private hospitals. In the second stage, the estimated DEA efficiency scores are regressed against hospital ownership variable using a Tobit model. This was a retrospective study.ResultsIn our DEA analysis, using the variable returns to scale model, out of 128 district hospitals, 31 (24.0%) were 100% efficient, 25 (19.5%) were very close to being efficient with efficiency scores ranging from 70% to 99.9% and 71 (56.2%) had efficiency scores below 50%. The lowest-performing hospitals had efficiency scores ranging from 21% to 30%.Quasi-government hospitals had the highest mean efficiency score (83.9%) followed by public hospitals (70.4%), mission hospitals (68.6%) and private hospitals (55.8%). However, public hospitals also got the lowest mean technical efficiency scores (27.4%), implying they have some of the most inefficient hospitals.Regarding regional performance, Northern region hospitals had the highest mean efficiency score (83.0%) and Volta Region hospitals had the lowest mean score (43.0%).From our Tobit regression, we found out that while quasi-government ownership is positively associated with hospital technical efficiency, private ownership negatively affects hospital efficiency.ConclusionsIt would be prudent for policy-makers to examine the least efficient hospitals to correct widespread inefficiency. This would include reconsidering the number of hospitals and their distribution, improving efficiency and reducing duplication by closing or scaling down hospitals with efficiency scores below a certain threshold. For private hospitals with inefficiency related to large size, there is a need to break down such hospitals into manageable sizes.