Evaluation of the green technology innovation efficiency of China's manufacturing industries: DEA window analysis with ideal window width

Data Envelopment Analysis (DEA) window analysis with ideal window width is applied to evaluate the green technology innovation efficiency of 28 manufacturing industries in China during 2006–2014. The obtained results are compared with those calculated using the traditional DEA model, and convergence analysis of the efficiency is conducted. Five years is the obtained ideal window width and DEA window analysis with ideal window produces results closer to reality for China's manufacturing industry. The overall efficiency of the green technology innovation in the manufacturing sector is low following a wave-shaped curve – first decreasing, then increasing and decreasing again, with large inter-industrial differences. There are 8 high-, 14 medium- and 6 low-efficiency industries. A convergence trend in the green technology innovation efficiency within the 28 manufacturing industries exists, implying a catch-up effect between them.     

基于运行规划的能源综合服务系统能效管理研究

以浙江电网企业转型现代能源综合服务的具体战略与发展规划为研究背景，针对能源综合服务系统的运行规划目标，开展基于运行规划的能源综合服务系统能效管理研究。从系统工程的视角出发，以能源流为纽带，基于多尺度能源系统建模方法，构建了能源综合服务系统模型，并结合系统综合能效，采用粒子群优化算法来优化系统各设备单元的运行策略，以实现基于运行规划的最优能效管理。通过能源综合服务系统模型计算表明，大规模清洁能源和可再生能源的接入，可以明显提高系统综合能效；随着区域用户总冷量和/或总热量需求占总电力需求的比值增大，系统最优综合能效逐渐增大；与使用内燃机、燃气轮机及汽轮机为原动机的热电联产系统相比，使用燃料电池为原动机的热电联产系统可以使能源综合服务系统综合能效更优。     

耕地流转与规模经营改善了农业环境吗？ ——基于耕地利用行为对农业环境效率的影响检验

研究目的:基于2007—2016年26省农业生产数据,测算"面源污染"和"碳排放"两类非期望产出下的农业环境效率,构建"耕地流转—利用规模—利用方式与利用强度—农业环境效率"的传导路径并进行计量检验。研究方法:超效率SBM模型,中介效应模型。研究结果:(1)耕地流转并未显著提高农业环境效率,但耕地利用规模对农业环境效率的影响呈倒U型;(2)耕地流转有助于扩大耕地利用规模,进而在样本中对农业环境效率呈现负向影响。与此同时,耕地流转对农业环境效率也存在正向的直接效应,正负效应基本抵消;(3)耕地利用规模主要通过改变化肥和机械投入强度进而负向影响农业环境效率。研究结论:农业环境效率受耕地流转、利用规模、利用方式和强度等多重因素影响,呈现明显的传导路径,因此,为了提高农业环境效率,在积极推行土地流转和规模化经营政策时,要注意结合地区农业生产力和地理环境,避免盲目扩大经营规模,同时鼓励规模经营主体引进农业绿色环保技术,注重农业生产资料的合理利用。     

Determinants of total efficiency in water utilities in Mexico

By using panel data analysis across 368 water utilities in Mexico over the period 2010–2014, we find that small firms are more efficient than medium and large providers and that increasing production is associated with less efficiency. Billing, income collection and profitability are relevant factors to improve efficiency. Medium and large firms require to measure consumption by service with meters in order to increase efficiency, while small firms do not require it.     

Using methods of Multi-Criteria Decision Making to provide decision support concerning local bioenergy projects

The public sector plays an important role in the German “Energiewende”. Besides energy management in municipal properties the local government can also support the switch to renewable energy sources through a change in energy supply structures within in their region. Methods of Multi-Criteria Decision Making (MCDM) from Operations Research are helpful regarding that challenge, as they are able to assess the sustainability of local energy concepts, since they not only offer stakeholders the opportunity to participate, but also consider multiple conflicting criteria. In that way, the acceptance of local energy projects and the participation of stakeholders in the decision process are supported. The case study presented in this paper illustrates the results of a MCDM process employed to identify a sustainable bioenergy concept in a rural village in Lower Saxony, Germany. Our analysis revealed not only the opportunities and challenges associated with executing an MCDM process to support the realization of local bioenergy projects, but also discusses potential limitations of the methods.     

Advancing environmental productivity: Organizational mindfulness and strategies

This study investigates the importance of mindfulness‐based organization systems and policies on the organization's continuous efforts to become a greener company. The study is devised as a pooled cross‐sectional time series analysis of productivity in energy consumption, water utilization, and waste generation and recycling of U.S. companies. The data set taken from U.S. Newsweek 500 recorded 600 companies dispersed into 63 industries during the period of 2012–2014 and provided 1,498 company–industry–year observations. The study found that systems and policies (e.g., deployment of third‐party auditors for its environmental metrics report; linkage of the remuneration of company's senior executive team with the achievement of environmental performance targets; and establishment of a committee at the Board of Directors' level whose mandate includes sustainability of the company in environment‐ and resource‐related matters) connect the company's mindfulness to its effort in improving the environmental quality through the company's productivity in energy consumption, water utilization, and waste generation and recycling. The relationships are positive and significant. Also, systems and policies serve as a motivator for the firm to continue to improve upon the current achievements. The study emphasizes the importance of translating organizational and individual mindfulness into organization policies and systems in order to motivate the organization to continuously improve its productivity in energy consumption, water utilization, and waste generation and recycling leading to improvements in environmental quality.     

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization*

Improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.     

Do country risk and financial uncertainty matter for energy commodity futures?

Using an instrumental variable quantile regression technique, this paper assesses whether country risk and financial uncertainty exert an impact on energy commodity futures prices under different commodity conditional return distributions over the period from January 1994 to July 2017. We also discuss whether the correlations change with different dimensions of country risk, that is economic, financial, and political. The results reveal that country risk and financial stress do have a significant impact on energy commodity returns of futures contracts with different maturities, but their direction, intensity, and significance differ, caused by the distinct market situations and divergent channels of country risk.     

The influence of school size,principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle schools

The aim of the paper is to identify which among the aspects that relate to the composition of the student body, school (district) size, management practices and the school principals' own characteristics are associated with the performance of Italian students at grade 8, measured through standardised test scores in reading and mathematics. The analysis makes use of a student-level efficiency model, and several school level variables are included as explanators for efficiency scores. The results show that, especially for reading, the most influential variables relate to the composition of the student body, while the students' performance in mathematics is partly correlated with the management practices adopted by the school principal/head teacher. Schools and schooling can only explain a minor part of the variance in achievement scores, however, and the characteristics of the students themselves play the most significant role.     

中国海外耕地投资的区位特征及其影响因素*——基于2000—2016年土地矩阵网络数据

［目的］分析中国海外耕地投资的区位特征及其影响因素，以促进我国海外耕地投资的合理布局，提高农业投资效率。［方法］以2000—2016年中国137宗海外耕地投资项目及其所涉及的35个东道国作为研究样本，运用Spearman相关分析方法，分别以耕地投资面积和耕地投资项目数量作因变量，研究其与各影响因素的相关关系，并用对应分析法进一步探究各东道国的相对优势。［结果］（1）我国海外耕地投资区域集中在东南亚且由周边国家向外扩展，被投资耕地用途多样，投资规模自2004年开始急剧上升，近年来呈下降趋势。（2）我国海外耕地投资以效率寻求型和市场寻求型为主，倾向于资源丰富、与我国距离较近、制度相似、经济关系良好但发展水平不高的国家。（3）根据各地区的比较优势，亚洲国家适合效率寻求型和市场寻求型的企业投资，欧洲和美洲国家适合资源寻求型和战略资产寻求型的企业投资，非洲国家适合资源寻求型、效率寻求型和市场寻求型的企业投资。［结论］中国农业企业应结合企业投资目标和各地区的比较优势，合理选择投资区位，适时转变投资策略与模式，积极防范海外耕地投资过程中的自然风险、政治环境风险和道德风险等，以提高投资效果。