网络媒体对大学生价值观的影响及对策

网络媒体已成为影响大学生价值观的强势媒体，在大学生价值观的形成与发展中发挥着重要作用。网络媒体不仅给大学生带来前所未有的海量信息，同时也对大学生的价值观造成了一定的影响。网络媒体就像一把双刃剑，对大学生的价值观既能产生正面的影响，也能产生负面的影响。本文试图对网络媒体对大学生价值观的影响、形成原因和应对策略进行分析。     

网络政治文化发展的困境与对策研究

随着网络信息技术的发展，我国逐渐形成了一种全新的政治参与文化形态，即网络政治文化。网民政治素养水平参差不齐、政府电子政务建设水平不高、网络法律与道德体系不健全、网络中各种政治文化冲突日益加剧等原因影响着网络政治文化的形成与发展。我们应该坚持以社会主义核心价值观引导网络政治文化的方向、全面提高网民的政治素养使其自觉规范网络言行、加强网络信息监管营造网络政治文化良好氛围等，从而构建先进的网络政治文化。     

Activation and variation of the United Nation’s cluster coordination model: a comparative analysis of the Haiti and Japan disasters

The coordinated response to extreme events is critical as illustrated by recent disasters in Haiti and Japan. As a way for coordinated provision of international humanitarian assistance to disaster-hit countries, the Office for the Coordination of Humanitarian Affairs (OCHA) developed cluster coordination model (CCM). With content analysis and network analysis of OCHA situation reports, this study checked four premises regarding activation of CCM, interaction between national and international actors, roles of proximity country, and level of cluster coordination. This study found that there were meaningful variations in implementing the CCM for 2010 Haiti and 2011 Japan disasters. From the analyses, we found that the current CCM may be vulnerable to black swan disasters; thus, extensive and active estimation of national disaster management capacities should be conducted to prevent collapse of national disaster management system. However, the reconciliation of state sovereignty and international humanitarian assistance also should be considered.     

Efficiency Determinants and Capacity Issues in Angolan Insurance Companies

This paper describes a variety of approaches used to assess the efficiency of a sample of major insurance companies in Angola between 2003 and 2012. Starting out with the bootstrapping technique, several data envelopment analysis (DEA) estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels and input‐decreasing/output‐increasing potentials. Previous studies have focused on the measurement and explanation of the factors affecting the performance rather than the prediction. The use of neural networks combined with DEA results as part of an attempt to produce a model for insurance companies’ performance with effective predictive ability is investigated. The findings indicate that older insurance companies with Portuguese origin tend to be more efficient. Results also suggest that opportunities for accommodating future demand appear to be scarce.     

What about people in cycle network planning? applying participative multicriteria GIS analysis in the case of the Athens metropolitan cycle network

The bicycle is gaining ground as an inexpensive, fast, healthy, and enjoyable mode of transport, but the development of cycle infrastructures appears to be a necessary prerequisite for supporting further growth in cycling rates. Thus far, few studies have developed comprehensive methodologies for the prioritisation of cycling infrastructure investments, and the role of end users has been underestimated in this process. The unique relationship that cyclists develop with the bicycle itself, their co-cyclists, bicycle facilities, and the urban environment as a result of sensory, kinaesthetic, symbolic, or even political reasons can assist in designing cycle facilities that are more efficient and closer to fulfilling the needs and desires of users. We propose a comprehensive four-step methodology for cycle network planning, which both accounts for the city structure and the zones in which higher cycling demand is possible and uses participative multicriteria GIS processes to incorporate cyclists’ views with regard to choosing the cycle network segments. Our case study is Athens, Greece, where cycling facilities are few and heavily fragmented, although cycling demand has recently grown. This methodology may be useful for cities attempting to introduce and prioritise cycling infrastructures because it focuses on determining where cyclists would prefer to cycle to make such investments more successful in attracting users.     

网络社区环境下企业营销分析

网络社区环境下企业营销存在的问题是暴力营销帖、营销信息遭质疑、即时沟通有待提高。为有效解决这些问题,企业应实施话题营销策略,提高企业的社区关注度,增加用户对企业的认知度;通过意见领袖评价企业产品的质量特性以及不同产品间的优缺点,对用户消费行为发挥导向作用;配备专门的社区营销人员,及时对社区舆论进行引导,传播产品信息,引导用户的消费观;企业应借助或建立恰当的广告平台,在不同的社区内投放不同的广告,创建新型的广告模式,从而有效提升企业营销效果。     

A theory of supplier network-based innovation value

To understand how a supplier helps a buying company create value through innovations, studies have focused on a supplier's internal resources or its relationship with a buying company. Building upon this body of literature, we develop a theory of supplier network-based innovation value in this conceptual paper. This theory explains how a supplier's upstream and downstream value network can be a source of competitive advantage for a buying company. Specifically, it proposes that the levels and types of supplier innovation value is contingent on the configuration of a dual-ego value network, characterized by the locus and degree of buyer-supplier structural equivalence. This theory also explains how a supplier's ties with a buying firm's competitors can pose both opportunity and risk to buying company innovation. This theory contributes to the literature by showing when “seemingly undesirable” suppliers, due to a lack of technical capability or strong relationship with a buying company, might still be valuable to a buying company's innovation.     

基于知识产权的组织间关系网络的演化特征

分析了基于知识产权的组织间关系网络的基本内涵和构成要素,将基于知识产权的组织间关系网络的生命周期划分为5个阶段——创立阶段、成长阶段、成熟阶段、衰退阶段和解散阶段,具体论述了各阶段的组织间关系网络的演化特征。以对450家企业的深度访谈和问卷调查为基础,通过描述性统计分析、因子分析以及多元方差分析来实证研究目标一致性、信息沟通以及信任等关系属性在各阶段的传递规律。研究结果表明,基于知识产权的组织间关系属性的顶峰阶段并非都出现在关系生命周期的成熟阶段。     

Design and development of inventory knowledge discovery system

Inventory management (IM) performance is affected by the forecasting accuracy of both demand and supply. In this paper, an inventory knowledge discovery system (IKDS) is designed and developed to forecast and acquire knowledge among variables for demand forecasting. In IKDS, the TREes PArroting Networks (TREPAN) algorithm is used to extract knowledge from trained networks in the form of decision trees which can be used to understand previously unknown relationships between the input variables so as to improve the forecasting performance for IM. The experimental results show that the forecasting accuracy using TREPAN is superior to traditional methods like moving average and autoregressive integrated moving average. In addition, the knowledge extracted from IKDS is represented in a comprehensible way and can be used to facilitate human decision-making.     

Modelling property values in Nigeria using artificial neural network

Unreliable and inaccurate property valuation has been associated with techniques currently used in property valuation. A possible explanation for these findings may be due to the utilisation of traditional valuation methods. In the current study, an artificial neural network (ANN) is applied in property valuation using the Lagos metropolis property market as a representative case. Property sales transactions data (11 property attributes and property value) were collected from registered real estate firms operating in Lagos, Nigeria. The result shows that the ANN model possesses a good predictive ability, implying that it is suitable and reliable for property valuation. The relative importance analysis conducted on the property attributes revealed that the number of servants’ quarters is the most important attribute affecting property values. The findings suggest that the ANN model could be used as a tool by real estate stakeholders, especially valuers and researchers for property valuation.