企业人力资源结构的神经网络预测

以企业人力资源结构为研究对象,将企业人力资源分为管理人员、科技人员和普通员工,根据这三类人员的影响因素,采用人工神经网络理论建立了预测模型,并以中国船舶重工集团公司为实例,对其人力资源结构进行了预测。结果表明,相对误差较小,预测精度达到了要求。     

Lightning strikes twice: Lessons learned from two food poisoning incidents in Japan

This case study examines the unique occurrence of two food contamination crises at Snow Brand Milk Products Co., Ltd., the top company in the Japanese milk product industry. The separate incidents of food poisoning occurred in 1955 and 2000; the latter incident, involving more than 10,000 victims, was the worst case of food poisoning in Japanese history.     

王夫之民族关系思想初探

始终怀有反清复明抱负的王夫之,通过对历史上民族关系的研究、反思和评论,系统阐述了“不以信义结夷狄”“夷狄相攻,中国之害”“战与和,两用则成,偏用则败”及“和亲无耻”等思想观点。王夫之民族关系思想的形成,既有家庭和社会的影响,又有传统儒家思想的浸染,也有个人对民族关系的体验,还有历代政治家和思想家的影响。民族关系思想与政治思想的统一、经验理性和托古论今是王夫之民族关系思想的主要特征。王夫之的民族关系思想具有时代局限、阶级局限、认识局限以及狭隘性和片面性。     

基于灰色BP神经网络的员工需求预测

人员配置直接影响企业的生产经营活动,一份科学合理的员工需求预测对企业的作用不言而喻。以某制造业为研究对象,搜集整理2005—2017年数据。利用SPSS做相关性分析,选取固定资产、开发支出等6项员工需求影响因素。运用灰色BP神经网络理论,预测未来3年员工需求。结果表明：灰色BP神经网络比灰色预测模型具有更高的精确度;虽然灰色BP神经网络具有较高的精确度,但其结果受参数影响较大,如何确定参数则是未来研究的一个方向;灰色BP神经网络的预测结果对企业招聘、员工关系管理等模块具有一定的指导意义。     

论高校网络文化的意识形态功能

高校网络文化是一种由高校师生共建、传播、共享的以大学校园为聚合点的网络文化,具有舆论引导、理论阐释、力量凝聚、思想教育等意识形态功能。当前,由于存在主体参与缺位、内容质量不高等问题,高校网络文化意识形态功能发挥受到一定程度的制约。文章从坚持和加强党对高校网络文化工作的领导、大力提升高校网络文化内容品质、构建高校网络文化平台体系、提升高校网络文化工作队伍能力四个方面,提出了强化高校网络文化的意识形态功能的对策。     

Dynamic evolution of alliance portfolios

This research advances in the conceptualization and the operationalization of the factors or microdynamics that determine the choice of partners. Most of the literature in this area of research has centered on the individual alliance without taking into account the set of alliances that a firm makes. This research applies a holistic approach, analyzing the set of alliances as a whole and points to the factors related to alliance portfolios that affect the choice of partners. The authors propose a longitudinal model that allows us to analyze the evolution of interorganizational networks. A Simulation Investigation for Empirical Network Analysis (SIENA) has been applied to a sample of 229 firms, analyzing 10,556 strategic alliances established between them over a 12 year period. The results show that certain factors over which managers exercise a degree of control (deliberate endogenous microdynamics) exert significant influences on the choice of partners by the focal actor and thereby on the dynamic configuration of alliance portfolios.     

Can a team have too much cohesion? The dark side to network density

The goal of most work teams is high performance. Prior studies suggest that performance within work groups is influenced by that group’s social network topology. Research has generally revealed to date that group cohesion (i.e., network density) is positively related to team performance under certain conditions. However, more recent research has indicated that this is not the full story. Recent research suggests that an inverse curvilinear relationship exists between social network measures (of which group cohesion is one) and team performance. In response to the need for understanding this relationship more fully, and leveraging the promising new insights that can be garnered with the use of social network analysis (SNA), this study employs SNA as a tool to explore the structural cohesiveness of teams of travel agents. This research extends our understanding of the relationship between intragroup social network relations and team performance by confirming an inverse curvilinear relationship exists between group cohesion and team performance. This paper leverages email communication to determine the social networks of each team, and then examines such in light of team performance. In total, an analysis of more than 7 million emails was undertaken. This study was conducted with work teams within a service organization. Each team in the study carries out the same tasks, i.e., identical task contingency, yet represents a distinct unit of analysis. The study confirms that social network topology is a valuable predictor of team performance and confirms that, like so many other social network measures, group cohesion and team performance share an inverse ‘U’ shaped relationship, not strictly a positive one as previously posited.     

人工神经网络在湖北省地区生产总值拟和中的应用

在“十二五”背景下,湖北省作为华中地区的重要省份,发挥着不可替代的作用。地区生产总值是衡量一个省份综合经济水平的重要因素,从而备受关注。神经网络,作为复杂非线性数据处理的方法之一,相比于传统的回归分析对多元非线性关系的拟合效果更好。因而本文借助人工神经网络对湖北省的地区生产总值进行了拟合,发现,进出口、地方一般预算收入、工业总产值、投资等对其影响较大,且检验组的误差均在5%以内,拟合效果较好,另外这与凯恩斯的理论也是相符合的。本文在此基础上提出了相应的政策建议,如保持投资增长力度,调整地方收入的流向,调整政府支出比例等。     

Differential impact of Web site content: Exploring the influence of source (public relations versus news), modality,and participation on college students’ perceptions

This experiment examined the impact of source, modality, and participation on perceptions of credibility, salience, attitudes, and general Web site evaluation. The data showed no significant differences between online stories coming from either public relations or news sources on any of the study's dependent variables. However, significant differences did emerge for the effects of multimedia and audience engagement.     

多目标模糊优化潮流模型及其基于神经网络的算法

提出了一种计算交流潮流的多目标模糊优化模型。模型中,同时考虑了发电费用最少及网损最小等多重目标。针对该模型,还提出了一种基于神经网络模型的新算法。该算法分别采用神经网络模型进行模糊集隶属函数的表达及优化问题的求解,从而将模糊优化同神经网络有机地结合起来。通过算例对所提模型及算法进行了验证。