基于包装视角的绿色壁垒对企业出口的影响

几乎每个国家对进口产品包装是否有益于国民身体健康,以及是否有益于生态环境都有严格的规定和标准.在理论分析包装绿色壁垒对企业出口影响的基础上,选取2003-2018年荣成富邦制笔有限公司出口产品均价、数量等时间序列数据,运用虚拟变量模型进行实证分析.研究发现,虽然随着时间的不同而存在差异,但包装绿色壁垒对企业出口有显著的阻碍作用.因此,建议通过转移目标市场、调整产品结构、提高生产效率、建立预警和协调机制来应对包装绿色壁垒,提升企业出口.     

应用型本科高校教学督导工作实践研究

教学质量是高校生存与发展的基本保障.对应用型本科高校教学来说,教学督导具有非常重要的作用,做好教学督导工作,能够使教学质量和教学水平大幅度提升,为现代社会培育出更多的优质人才.概述教学督导,明确教学督导的职能,分析应用型本科高校教学督导工作存在的问题,并提出具体的工作实践路径,可供高校参考.     

信息社会个人信息法律关系的构造

信息社会的本质是能够产生个人信息法律关系,信息流是解构个人信息法律关系的关键,也是个人信息法律关系产生的直接动力.个人信息法律关系的主流构造分别以信息自决、隐私和人格权益为基础,其中,国家利益成为个人信息法律关系构造中不可忽视的力量.三种构造模式分别体现出个人与企业,个人与国家,个人、企业和国家三者之间的利益平衡.由于利益平衡体现出的幸存者偏差效应,个人信息法律关系的构造以主体场域信息自治为中心,具有合理性和现实性.     

苏轼词中的孤鸿意象探析

鸿是我国古诗词中经常使用的意象之一,它有着丰富的内涵和情感。苏轼在传统意象的基础上,在他的词作中把传统的鸿意象与自己的独特个性结合起来赋予了这个意象更为深广的感情生发空间。     

雷锋生命价值的三重维度及当代意蕴

雷锋的生命价值从历史、空间、境界三重维度上表现为延伸性、普遍性和超越性。雷锋的生命价值符合人与社会全面发展进步的需要,即符合人的超越性的要求、符合群体共同发展的要求、符合中华民族道德实践的要求、符合中国共产党的宗旨要求,是对生命为什么有价值、生命价值是什么、怎样实现生命价值问题的直接解答。     

论学术期刊在科研诚信建设中的责任与作为

科研诚信是当下全社会关注的一个热点问题。中央和国家有关管理部门近期连续下发相关文件,规范科研诚信行为。学术期刊诚信建设是科研诚信建设不可或缺的部分。学术期刊诚信建设主要体现在三个方面:一是编辑人员的政治立场、政治原则和对学术质量的坚守等道德操守影响学术期刊的诚信原则;二是建立科学严格的管理制度,规范编辑行为是学术期刊诚信建设的必要前提;三是正确把握刊物的价值取向,坚持社会效益第一,兼顾经济效益的原则,理性对待期刊评价,是学术期刊诚信建设的基础。     

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.