浅谈发出存货计价方法的选择

对存货计价问题的产生进行说明,详细介绍了5种发出存货计价方法,并且通过它们之间的比较,重点阐述了企业如何根据自己选择恰当的存货计价方法。这样,选择比较合理的发出存货计价方法,可以有效达到企业管理的目标。     

基于AHP的设备管理成熟度评价指标权重配置

基于成熟度模型构建的设备管理评价体系由众多的评价指标构成,其中包含大量的定性描述,本文尝试通过AHP层次分析法对该评价体系的指标进行权重系数配置,为后续的量化评价提供条件。     

高职院校思政课教学有效性研究——教学情景设计研究

长期以来,高职院校思想政治理论课教学一直面临一种尴尬的境地:一方面,学生对课程本身存在偏见和抵触,另一方面,课堂以教师为主体,学生被动地听,这种教学忽视了学生的自主学习和探究,使学生缺少独立思考的时间和空间,因而教学效果差。而情景教学法能较好地激发学生学习兴趣、发挥其主体性,因此,情景教学法成为职教院校思想政治课教学方法改革的重要内容之一。本文结合教学实践,从教学内容,教学开展方式等方面阐述了情景教学法在高职思政课教学中的应用。     

粮食移动式输送及装仓设备安全性评价方法

本文建立粮食移动式输送及装仓设备安全性评价方法,量化此类设备安全等级,以期对生产厂家在设计、制造上有一定的指导意义,对使用单位的选择上有借鉴意义。     

高职院校环境监测实践教学改革探索

本文分析了高职院校环境监测实践教学中存在的问题,从实践参与教学模式、实践教学方法及考核、评价方式等方面进行了一系列的探索和尝试。     

An examination of the effects of 2014 concealed weapons law in Illinois on property crimes in Chicago

The purpose of the present study is to determine the effects of ‘may issue’ Concealed Carry Weapons (CCW) law implemented in early 2014 in Chicago. Based on the daily community-level crime data from January 2006 to December 2015, using zero-inflated negative binomial difference-in-difference specification with Philadelphia as the control group, the property crimes in Chicago declined after the implementation of ‘may issue’ CCW law. The findings are robust to alternate treatment windows and to a placebo test using time windows before implementation of the law.     

钢铁行业成本核算制度研究

为了解决钢铁行业普遍亏损、经营困难等问题，对当前钢铁行业成本核算面临的各种问题进行分析，相应的提出新制度实施的必要性。而后详细阐述了钢铁行业成本核算制度的基本步骤，且针对行业现有问题说明了新制度的优越性，提出可以选择性使用的作业成本法，最后阐释了新制度可能会对钢铁行业产生的影响和企业在面对新制度想要改善目前严峻形势必须用辩证的眼光看待这一现象，具体问题具体分析，对症下药才是关键。     

Advancing tourism research through multilevel methods: research problem and agenda

Tourism research often encounters social phenomena and research problems that involve multiple levels. However, most researchers assume that the phenomena exist in a single level and perform analyses that do not reflect the hierarchical nature of social dynamics. This article heeds the call from Current Issues in Tourism by illustrating multilevel methods and proposing an agenda for multilevel research. In particular, this article seeks to reconcile the limitations of single-level analysis and to delineate how multilevel methods could be applied in tourism research. It further seeks to advance tourism theories by introducing more complex multilevel design with broader applications in various tourism settings. This article presents two common tourism research scenarios, critiques their limitations, and proposes how multilevel methods could not only address these limitations, but also how they could advance tourism theories. An empirical study is offered to demonstrate multilevel design and analytical techniques.     

“撤县设区”能促进区域发展吗——基于浙江省1993-2013年县际面板数据的分析

本文通过对国内外学者在县（区）域经济领域十几年研究成果的梳理,整理浙江省原69（现58）个县（市）近30年经济发展的数据,对县域经济进行规模分析和产业结构分析。首次对柯布-道格拉斯生产函数模型改进,把技术增长中重要的因素,即劳动力要素的受教育程度内生化分析,并运用该模型对县域经济和＂撤县设区＂后区（以余杭市等为例）经济作对比研究,证明＂撤县设区＂的政策并没有促进区域经济的发展。     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.