价值共创引导乡村旅游价值链重构

［目的］通过充分发挥移动互联时代消费者对于价值链、创新链、产业链构建的作用，实现价值共创视角下乡村旅游价值链的重构，解决乡村旅游产业中消费者需求和产业供给不平衡不充分之间的矛盾，推动乡村旅游高效、有序、协调、综合发展。［方法］基于价值共创理论，通过文献研究法和系统论方法，探索性重构乡村旅游价值链。［结果］（1）价值共创引导下的乡村旅游价值链是由基本价值活动、辅助价值活动和价值共创活动共同组成，通过虚拟价值链和传统价值链的互动与融合，实现乡村旅游价值链的新价值创造。（2）价值共创活动是以虚拟价值链为基本特征，以“产消者”创新社区为表现形式，依托移动互联网时代的先进技术，创新性赋予旅游者产品生产者和旅游消费者的“产消者”双重属性，通过将消费者从传统价值链的幕后拉向幕前，实现乡村旅游价值链重构和价值增值。［结论］价值共创引导的乡村旅游价值链需要依托平台思维、共享思维和创新思维进行建设，以消费者需求为导向形成的价值链的开放和互动对于实现乡村旅游供给侧结构性改革具有重大意义。     

资本外逃的经济效应与应对政策选择研究

资本外逃是一个复杂的经济问题,是由多种原因造成的,并会给一国经济发展带来不可估量的风险和损失。基于此,论文梳理了资本外逃的研究现状,提出了资本外逃所产生的经济效应,在此基础上,提出了资本外逃的政策选择,为一国在治理资本外逃时提供了政策选择和借鉴。     

新能源材料物理化学课程教学改革探究

新能源材料物理化学课程内容抽象、概念多、涉及面广、公式应用严格,与生活和科学前沿联系紧密。为提高课程教学质量,教师引入案例教学抓住课程核心;联系材料发展历史,增加课堂教学的趣味性;结合科学发展前沿,使教学内容能够与时俱进;注重概念和公式的融会贯通,增加材料调研大作业;线上线下教学模式相结合,采用多样化的教学方法及教学手段;通过形成性评价考核,加强教学过程监管。     

政府购买服务中高校参与及提升服务能力路径研究

高校是政府购买服务的承接方,但其对政府购买服务的响应还处在起步探索阶段。文章首先厘清政府购买服务中高校的角色定位,接着从外在驱动和内在诉求两个角度分析了高校参与政府购买服务的可行性,并在此基础上阐述高校参与政府采购服务的实施路径以及提升服务能力的路径。文章认为,高校应该把握好参与政府服务项目这个良好契机,以积极的态度参与政府购买服务,拓宽自身的发展路径,促成政府和高校实现双赢。     

富水砂层盾构接收技术

针对富水砂层盾构接收易发生渗漏、涌砂、安全风险大等问题。在大量工程实践基础上,总结出以控制地下水为重点、坚持预防为主的施工理念,形成端头加固、止水帷幕、环箍注浆及止水装置的富水地层盾构接收技术,牢筑三道止水防线。技术成果在多项依托工程中成功应用,确保了该类地层盾构接收安全和风险可控。     

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。     

Brexit: How Will UK Agriculture Fare?

There is little doubt that Brexit would have significant implications for UK agriculture, a sector with strong trade links to the EU and strong reliance on CAP income support. This article reports preliminary results from employing a Computable General Equilibrium Model, a Partial Equilibrium Model and Farm Level Models to explore selected trade and domestic policy scenarios post‐Brexit. These allow for the estimation of changes in producer prices, production and farm incomes against a baseline scenario of continued EU membership. Under a Free Trade Agreement with the EU, agricultural impacts are relatively modest. By contrast, unilateral removal of import tariffs has significant negative impacts on prices, production and incomes. Adoption of the EU's WTO tariff schedule for all imports favours net importers (e.g. dairy) and harms net exporters (e.g. sheep). Given the strong dependence of most UK farms on direct payments, their removal worsens negative impacts of new trade arrangements and offsets positive impacts. Impacts vary across different types and sizes of farm, but also regionally. However, the period of adjustment to new trade and domestic policy conditions may prove very challenging for a large number of farm businesses.     

The Moderating Effects of Status-Consumption Motive and Age in the Relationship between CSR Advertising Appeal Type and Purchase Intentions

The primary purpose of this study was to examine factors that influence the effectiveness of benefit appeal types (i.e., help-other vs. help-self) in Corporate Social Responsibility advertising. To that end, we designed and administered a between-subjects experiment where participants viewed one of the two CSR advertisements crafted with help-self and help-other benefit appeals. Results provided evidence supporting the moderating effects of status-consumption motives and age on purchasing intentions. Additional analysis suggested consumers younger than 48 years old were more likely to be persuaded by a help-other ad appeal when they didn't have strong desires for status consumption. Results were discussed in light of the self-concept theory and value-expressive framework in CSR advertising.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.