重大水利工程项目决策社会稳定风险评估中公众参与成熟度的影响路径

重大水利工程项目决策社会稳定风险评估中,公众是重要的参与主体,个体间生活环境、知识背景及心理素质的差异性会直接影响稳评结果。公众参与成熟度是公众参与的衡量要素,由能力成熟度和心理成熟度两个方面构成。从能力与心理两个角度设计调查问卷,运用结构方程模型,探究内部影响路径。结果表明,公众参与心理成熟度直接影响能力成熟度,而能力成熟度又通过参与意愿影响着心理成熟度,两者间存在相互影响的关系。政府可以通过开展道德素质教育,改善公众参与动机,以提高公众参与心理成熟度及能力成熟度,最终整体提高公众参与成熟度,保证稳评工作的质量,提升重大水利工程项目决策科学性。     

服务业内部结构异质性演化与行业发展差距研究——基于全要素生产率视角下的分析

基于1990—2017年行业面板数据，采用超越对数生产函数对服务业各细分行业TFP增长率进行分解和测度，揭示我国服务业内部结构生产率演化进程及其异质性现象，并采用可导性对数方差分解法、VAR协整模型和误差修正模型（VECM）考察TFP及其构成部分对服务业行业发展差距的贡献度，评估其异质性作用于行业发展差距的长短期效应。研究发现，在服务业内部结构演化过程中，TFP、技术进步和技术效率改进呈逐步下降趋势，其中技术进步是推动TFP增长的核心，规模效率改进发展水平一直滞后，配置效率改进在服务业发展初期较为滞后，但水平逐步提升；生产性和生活性服务业行业间TFP及构成部分异质性在演化过程中呈下降趋势，且生活性服务业行业间异质性程度要小于生产性服务业，行业间异质性变化幅度最大的是规模效率改进，技术效率改进异质性波动程度最小；TFP异质性是造成行业间发展差距扩大的主要原因，其中技术效率改进是主导因素，且该效应的发挥只有在长期具有显著性。     

社会资本视角下农村基础设施管护效果影响因素分析——基于甘肃省9个市县的实证研究

以甘肃省9个县市的调查数据为基础,将社会资本划分为社会参与、社会规范、互惠网络三个维度,运用结构方程模型,来探讨三个维度对农村基础设施管护效果的影响。结果表明:(1)社会规范对农村基础设施管护效果显正向影响。(2)互惠网络对农村基础设施管护效果显负向影响。(3)社会参与对农村基础设施管护效果的直接影响不显著,但通过社会规范及互惠网络间接产生影响。(4)就总效应而言,社会规范对农村基础设施管护效果的影响要大于社会参与及互惠网络产生的影响。     

Interpretive structural modeling of quality factors in both medical and hospitality services in the medical tourism industry

This study aims to theoretically integrate quality factors of both medical and hospitality services in medical tourism. Medical tourism comprises both medicine and tourism. Although the core product in medical tourism is medical treatment, attractive hospitality and travel options are also essential. Despite the dual nature of medical tourism, the two aspects of this concept have not been integrated in a unique framework. This study attempts to fill this gap using interpretive structural modeling (ISM). According to ISM, although factors of medical services and hospitality services are independent from each other, these factors have vital impacts on perceived value, satisfaction, and loyalty.     

Green human resource management: Development of a valid measurement scale

The objective of the study was to develop a valid measurement scale for green human resource management (HRM). Even though the common practices of green HRM have been presented in much of the literature, the previous studies focused only on a small number of functions in integrating environmental management with HRM. Additionally, the measurement of green HRM practices still calls for empirical validation. The two‐stage methodology of structural equation modeling in AMOS was employed for data analysis. Exploratory factor analysis revealed seven dimensions of the construct measured by 28 items. Confirmatory factor analysis confirmed the factor structure. The measuring instruments revealed convergent and discriminant validity. Several model fit indices indicated the model fitness. The study provided supplementary evidence on the underlying structure of the construct that can be valuable to researchers and practitioners in this area.     

Structural production layer decomposition: a new method to measure differences between MRIO databases for footprint assessments

Recent empirical assessments revealed that footprint indicators calculated with various multi-regional input–output (MRIO) databases deliver deviating results. In this paper, we propose a new method, called structural production layer decomposition (SPLD), which complements existing structural decomposition approaches. SPLD enables differentiating between effects stemming from specific parts in the technology matrix, e.g. trade blocks vs. domestic blocks, while still allowing to link the various effects to the total region footprint. Using the carbon footprint of the EU-28 in 2011 as an example, we analyse the differences between EXIOBASE, Eora, GTAP and WIOD. Identical environmental data are used across all MRIO databases. In all model comparisons, variations in domestic blocks have a more significant impact on the carbon footprint than variations in trade blocks. The results provide a wealth of information for MRIO developers and are relevant for policy makers designing climate policy measures targeted to specific stages along product supply chains.     

基于模态应变能密度理论的网架结构损伤识别方法

为了研究网架结构的损伤检测方法,根据应变能密度理论,提出采用单元模态应变能密度差值作为网架结构损伤识别指标的方法,以损伤单元模态应变能密度差值的大小初步确定单元的损伤程度。分析了5种具有代表性的损伤工况,并在数值计算结果中引入了白噪声。结果显示,在一阶模态下,针对单损伤、多损伤和轻微损伤、严重损伤等不同损伤工况,损伤杆件的模态应变能密度差值均为高值。因此,该方法可以有效识别出网架结构的损伤位置,根据损伤单元的模态应变能密度差值大小初步确定单元的损伤程度,且在一定的噪声水平下具有较强的鲁棒性,对网架结构损伤识别具有参考价值。     

Why has China’s vertical specialization declined?

Vertical specialization (VS) is quantified by the VS share, which measures the average import content per dollar of exports. A characteristic of China’s export trade is its strong dependence on assembly and processing activities. To take proper account of this, China’s VS shares should explicitly distinguish processing export production from other production. We estimate China’s annual VS shares from 2000 to 2012—the latest year for which a special input–output table is available that makes such an explicit distinction. We find that VS shares increased from 2000 to 2004 and subsequently started to decrease. To explore why it has declined, we introduce a new structural decomposition approach. We find that the decrease of the VS share appears to have been driven mainly by the substitution of imported intermediates by domestic products. This occurred in particular in the production of exports, which implies an upgrading of China’s position in global value chains.     

供给侧结构性改革中加强小型水利工程管理能力建设的思路与重点

围绕深化小型水利工程管理体制改革和管护机制创新,以推进供给侧结构性改革为主线,分析当前我国小型水利工程管理能力面临的新形势,结合小型水利工程管理现状及存在的主要问题,探讨供给侧结构性改革中如何加强工程管理单位能力建设,并从供给侧结构性改革角度,提出创新管护模式、拓宽经费渠道、加强农民用水合作组织建设、建立考核评价机制等建议。     

Forecasting value‐at‐risk in oil prices in the presence of volatility shifts

Recent evidence suggests shifts (structural breaks) in the volatility of returns causes non‐normality by significantly increasing kurtosis. In this paper, we endogenously detect significant shifts in the volatility of oil prices and incorporate this information to estimate Value‐at‐Risk (VaR) to accurately forecast large declines in oil prices. Our out‐of‐sample performance results indicate that the model, which incorporates both time varying volatility (without making any distributional assumptions) and shifts in volatility, produces more accurate VaR forecasts than several benchmark methods. We make a timely contribution as the recent more frequent occurrences of unexpected large oil price declines has gained significant attention because of its substantial impact on the financial markets and the global economy.