高中生学业成就归因、心理韧性与心理资源投入的关系

为了解高中生学业成就归因、心理韧性与心理资源投入之间的现状及其关系,采用多维度—多归因因果问卷、中学生心理资源投入量表、中学生心理韧性问卷对1113名高中生进行调查。结果表明：（1）高中生学业成就归因整体呈内归因倾向,心理资源投入与心理韧性整体处于中上水平;（2）高中生内归因显著预测心理韧性与心理资源投入,心理韧性显著预测心理资源投入;（3）高中生心理韧性在学业成就内归因与心理资源投入之间具有部分中介效应。     

精准扶贫背景下贫困山区旅游扶贫效率研究——以安徽皖南山区18个县(区、市)为例

皖南山区旅游扶贫效率接近中等水平,区域差异大但呈波状缩小趋势。现阶段,旅游扶贫的主要支撑为规模效率,快速的旅游发展、不断扩大的旅游业规模是提升旅游扶贫效率的有效途径。技术进步是导致全要素生产率指数波动的主要因素,旅游体制机制、旅游模式创新是进一步提高其扶贫效率的核心路径。旅游扶贫效率由"局部突出,环线梯度"的点状格局向"四周连片,中部塌陷"的漏斗状格局演化,旅游产业出现外溢。为提升区域旅游扶贫效率,应根据潜力期、朝阳期、黄金期、夕阳期不同的效率形态类型,实施精准的旅游扶贫模式。     

政府补偿下基于私人公平偏好的PPP项目投资决策分析

针对PPP （Private-Public Partnership）项目收益的不确定性,引入政府补偿契约问题。考虑私人投资者对政府补偿存在公平偏好倾向,借鉴BO模型的思想,将私人投资要求的特许收益作为其公平参考点,并通过对FS模型加以改进,构建私人公平偏好效用函数,从而给出私人在政府补偿下的投资决策模型。通过模型求最优解和概率分析,探讨私人公平偏好对其最优投资决策的影响,并借助数值分析给予检验。结果表明:当政府补偿使私人感知有利不公平时,私人将选择期望效用最大的最优投资,并随其感知程度的增加而增加;而当政府补偿使私人感知不利不公平时,私人最优投资及可能性将在有限公平偏好内随其感知程度的增加而减小。     

政务大厅服务效能影响因素实证分析

政务大厅在积极开展创新实践的同时,也存在区域发展不平衡、部门协调难、窗口忙闲不均等诸多问题。量化政务大厅的服务效能,有效识别影响服务效能的关键因素,对于更快更好发挥大厅在"放管服"改革中的作用具有重要的现实意义。文献回顾与理论推演相结合提炼出大厅服务效能评价指标以及效能影响因素指标,基于普查数据量化指标,采用主成分分析法评价服务效能,构建回归模型,同时考虑大厅发展的区域性差异,分别从总体和分区域进行实证分析。研究结果表明,服务模式、生产要素、服务内容均会对大厅服务效能产生影响,且各区域大厅的具体影响因素和因素的影响程度均存在较大差异。基于此,应因地制宜开展大厅服务模式创新;推动大厅建设标准制定;落实审批事项全面进驻大厅,丰富大厅服务种类,优化服务结构。     

企业社会责任与企业投资水平——基于企业生命周期的视角

基于利益相关者理论、代理理论和社会网络理论,以企业社会责任增加企业的投资能力和提升管理层投资意愿两方面为切入点,通过理论分析与实证检验深入研究企业社会责任对于企业投资的动态影响效应。研究发现:企业社会责任可以显著提升企业的投资水平。在对样本企业划分生命周期后发现,成长期和成熟期的企业履行社会责任能够显著增加企业投资,然而社会责任对企业投资的促进作用在衰退期企业中并不明显。     

Randomized Response Techniques Using Maximum Likelihood Estimator

The randomized response (RR) technique with two decks of cards proposed by Odumade and Singh (2009) can always be made more efficient than the RR techniques proposed by Warner (1965), Mangat and Singh (1990), and Mangat (1994) by adjusting the proportion of cards in the decks. Arnab et al. (2012) generalized Odumade and Singh strategy (2009) for complex survey designs and wider class of estimators. In this paper improvement of Arnab et al. (2012) estimator has been made by using maximum likelihood method.     

Multi-factor prediction of water flooding efficiency based on a time-varying system

ABSTRACT

The neural network prediction method gets good historical matching between prediction indices and influence factor indices, while the differential simulation prediction method can reflect the changing trend of prediction indices; considering these new traits, a new multi-factor prediction method is proposed to organically combine these two prediction methods. At first, the input–output relation between water flooding efficiency in ultra-high water cut stage and their influence factors is viewed as a time varying system, then the BP neural network is introduced in parameter identification of differential simulation to obtain a new multi-factor prediction method of functional simulation based on the time varying system. This new prediction model has got good self-adaptability since its parameters change by time. Moreover, it has better results in the mid-long-term water flooding efficiency prediction because the non convergence problem appeared in the coupling process can be overcome in the training process of the neural network by variable learning rates. In the end, practical output prediction cases in two different oilfield blocks in China are given. The computational results show that the prediction results obtained using the new multi-factor prediction method are in good agreement with the reality, even much better than the results obtained by other prediction methods.     

Random quotients and robust estimation

This paper compares the tail-heaviness of certain random quotients in terms of the asymptotic relative efficiences of the sample median to a large class of estimators containing the mean, trimmed mean and Huber's M-estimator. The random quotients are generalizations of the "Normalllndependent" distributions and include the Student's t, contaminated normal, double exponential and slash distributions.     

A unified approach to estimating parameters in some generalized poission distributions

A family of distributions labelled as Poisson v Katz is formulated, which includes, as particular or limiting cases, the Negative Binomial, Neyman Type A, Poisson v Pascal, and Poisson v Binomial. Thus, while analyzing data, estimating the parameters in the Poisson v Katz family obviates the necessity of having to choose from among the particular or limiting cases. In this article minimum chi-square estimators are presented and their asymptotic relative efficiency obtained. An example is presented to illustrate the procedure