水利建设市场主体信用评价指标体系改进——以施工单位为例

针对现行水利建设市场主体信用评价指标体系,以施工单位为例,在比较分析已有信用评价结果的基础上,采用问卷调查统计方法,得到市场主体对现有评价指标的认同度,并分析不同指标认同度差异的原因,进而提出删除门户网站及平台信息、固定资产占总资产比例及施工年产值等认同度低的指标,提高管理层素质、人员素质及管理制度等认同度高的指标的权重。     

Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

基于均方差法的郑州市土地综合承载力评价

［目的］开展土地综合承载力评价是科学编制国土空间发展战略的基础。通过构建包含水土资源承载力、经济承载力和生态承载力3个维度土地综合承载力评价指标体系，定量刻画郑州市城市土地综合承载力的特征与轨迹。［方法］运用均方差法，选取2010—2016年郑州市城市土地综合承载力评价指标，分析其土地综合承载力特征。［结果］（1）总体上，郑州市城市土地综合承载力不断增强，水土资源承载力呈现先升—降—升的动态演变特征； 经济承载力持续增长，这源于郑州市土地经济效益的大幅提升； 生态承载力呈现波动性增强的演变特征。（2）郑州市城市土地综合承载力经历了较低—中等—较高发展历程，但土地综合承载力处于低层次的较高阶段，仍有较大提升空间。（3）为提高郑州市城市土地综合承载力，应加快“多规合一”规划的编制，科学划定城市增长边界和“三生”空间，转变城市发展理念，优化发展发展路径，提升城市土地综合承载力水平。［结论］郑州市城市土地综合承载力仍有较大提升空间，应加快建立土地综合承载力扩容的有效机制。     

Large scale infrastructure investment and economic performance – a case study of Oresund

We analyse the effect of a large scale infrastructure investment, namely the construction of the Oresund bridge, on the local and supra-regional economy. We employ the synthetic control method to construct counterfactual regions that mimic the trajectory of Malmo and Southern Sweden without treatment. Our results point to a positive effect. However, placebo tests in space and time only reveal statistical significance at a larger regional level. The results suggest that spillover effects are eminent.     

河南省农业生态旅游产业可持续发展评价研究

[目的]河南农业生态旅游作为一种可持续发展的旅游形式,为河南的经济发展作为了重要贡献。对河南农业生态旅游产业可持续发展进行评价研究,是促进农业生态旅游可持续健康发展的重要保证。[方法]文章通过实地调研构建河南农业生态旅游产业可持续发展评价指标体系,运用层次分析法,确定指标权重,结合专家评分法,对各项评价指标打分,并计算河南农业生态旅游产业可持续发展的综合得分,结合农业生态旅游产业可持续发展评价标准,得出目前河南农业生态旅游产业可持续发展水平。[结果]河南农业生态旅游产业可持续发展评价得分为72.45,处于基本可持续发展阶段,并对当前河南农业生态旅游发展现状和存在的农业生态旅游意识淡薄、旅游产品特色不明显、缺少政府资金扶持和缺乏经营管理人才等问题进行了分析。[结论]基于上述问题,提出了提高环保意识、走可持续发展之路;开发特色原生态旅游产品;加强政府支持和引导;加强专业培训,打造专业队伍等对策。     

基于经济新常态的长春市水资源开发利用潜力评价

以长春市为研究对象,基于未来经济处于新常态的发展态势,构建包含水资源、社会、经济、生态环境4个子系统的评价指标体系,并确定各指标的评价等级标准;基于模糊数学理论以及层次分析法构建包括目标层、准则层、指标层的3层模糊综合评价模型,以2015年为现状水平年,应用模型对长春市水资源开发利用潜力进行综合评价。结果表明:长春市水资源开发利用程度处于中等偏上水平,各辖区水资源开发利用规模不平衡,可通过产业结构调整提高全市用水效率,为经济持续增长提供保障。     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Influential factors on Chinese airlines’ profitability and forecasting methods

We establish profit models to predict the performance of airlines in the short term using the quarterly profit data collected on the three largest airlines in China together with additional recent historical data on external influencing factors. In particular, we propose the application of the LASSO estimation method to this problem and we compare its performance with a suite of other more modern state-of-the-art approaches including ridge regression, support vector regression, tree regression and neural networks. It is shown that LASSO generally outperforms the other approaches in this study. We concluded a number of findings on the oil price and other influential factors on Chinese airline profitability.     

颠覆性技术识别与预测方法研究进展

为了把握颠覆性技术识别与预测方法研究进展，首先对颠覆性的内涵、特征和运行机制进行论述；然后，通过对已有文献进行系统梳理，将识别与预测方法分为5类，分别展开详述；最后，对各类方法进行比较分析。研究发现，已有颠覆性技术识别与预测方法仍处于发展的初期阶段，所有识别研究方法均围绕颠覆性技术的外部影响或内在特征中的某一方面展开，并未将二者有机结合起来。未来，应综合把握颠覆性技术内外部特征，构建全面、系统的识别与预测框架。     

Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.