在消费者需求向着个性化和多元化发展的背景下,如何在互联网时代通过开发消费者隐性需求打开消费市场,取得竞争优势成为企业亟需解决的现实难题.文章从信息失衡角度出发,构建消费者隐性需求影响结构方程模型,探讨消费者成本性认知、规范性认知、信息失衡、隐性需求之间的关系,旨在为企业开发消费者隐性需求提供对策建议.研究结果表明:成本性认知和规范性认知会对消费者隐性需求产生正向影响,信息失衡在上述影响中起到部分中介作用.

线上线下混合式教学打破了传统教学形式、时间及空间的限制,提升了课堂教学效率.该文分析了电子商务数据分析与应用课程的特点,并阐述了传统教学模式的不足.在此基础上,从教学团队建设、课程总体设计和教学内容拆解等五个方面提出了电子商务数据分析与应用的混合式课程建设方案,凸显混合式课程建设特色.最后,对混合式教学模式实施了动态多主体教学效果评价,保障了混合式教学的质量.

应用跨界营销是企业赢得目标消费者偏好,解决品牌老化、用户增长、产品推广问题的良好途径,而消费者对跨界营销的接受、认可是其广泛应用的关键.文章基于SOR(刺激—机体—反应)理论,利用SEM(结构方程模型)探讨国货意识、品牌匹配、市场匹配、感知价值对跨界营销接受意愿的影响.利用问卷法获取数据,分析后得出品牌匹配、市场匹配显著正向影响跨界营销接受意愿,感知价值在品牌匹配、市场匹配对跨界营销接受意愿的作用中起部分中介作用,在国货意识对跨界营销接受意愿的作用中起完全中介作用.本研究结论可以为企业掌握消费者对跨界营销的情感倾向、提升跨界营销效能提供参考.

互联网时代,企业对电子商务人才的要求不断提高,提升电子商务专业教学质量尤为重要.围绕电子商务专业教学质量要求,探讨教学质量评估指标体系.通过AHP法对教学质量进行评价,实践表明该指标体系有助于电子商务专业教学质量提升.

应用智能化技术提供服务是电商产业扩大交易规模、提升服务质量的重要途径,而用户对智能化服务的接受与采纳是影响其应用推广的关键.文章基于模糊集定性比较分析法(fsQCA)提出影响用户接受智能化服务的三个命题:任一因素都不是结果的必要条件;因素需以组合的形式发挥作用;存在多个不同因素组合路径引致用户接受意愿的实现.通过问卷调查发现引致用户接受意愿的4种组合路径:1)存在较高水平的绩效预期和努力预期,且心理障碍不存在或存在水平低;2)存在较高水平的绩效预期、努力预期和社会影响;3)存在较高水平的努力预期、社会影响且失控感知和心理障碍不存在或存在水平低;4)存在较高水平的绩效预期、社会影响、失控感知和心理障碍.本研究旨在为企业提供多种方案以供选择,希望能实现资源的最大化利用及智能化服务的进一步推广.

社交网络已经成为重要的营销渠道之一.但是,目前微信、微博等社交网络平台内容同质化现象严重,与用户的互动性差,使得用户参与意愿不高,最终影响信息传播的效果.围绕如何提高用户在社交网络营销中的参与度问题,提出了利用游戏化设计的相关理论和方法改进社交网络营销中用户参与度的研究思路.具体而言,通过运用心流理论和个体—环境匹配理论探讨了游戏化设计对社交网络平台用户参与的作用机理,分析了社交网络平台采用游戏化设计策略的可行性,进而调查问卷收集数据并进行了数据分析.研究结果表明:用户在体验游戏化设计服务和活动时感知到的一致性匹配和互补性匹配能正向促进用户在社交网络平台上的参与度.此外,心流体验在一致性匹配与用户参与中起完全中介作用,在互补性匹配与用户参与中具有部分中介作用.

随着移动互联网、大数据、人工智能等技术的发展,电子商务专业发展面临着新的机遇与挑战.如何使电子商务专业适应新时代的发展需求,是目前国内外电子商务专业发展的关键问题.提出一个电子商务专业质量评估体系,设置了各级指标;对电子商务专业的未来发展提出了若干建议.

该文运用网络调查、描述性统计分析和文本分析等方法调研了主流慕课平台上电子商务专业课程资源的基本情况,包括开课单位、教学团队和课程内容等方面.然后,运用回归分析方法研究影响选课人数的关键因素.在此基础上,探讨慕课建设和教学存在的问题,并尝试提出应对策略.该研究对于高等学校教育教学理论的发展具有重要理论意义;同时,对于慕课资源建设、高校教学安排调整和教师教学方法改进具有重要的现实意义.

With the rapid development of Web technologies,the competition among electronic business area has become more and more serious. It has been an important problem for electronic business companies to acquire competitive intelligence in the Web era and further to enhance their competition powers. Aiming at solving this problem,in this paper we focus on the competitor analysis issue for electronic business area,which is based on the analysis on Web user logs. Web user logs record users' behaviors in the Web. Web user logs are much different from traditional Web server logs,in which only the users' behaviors in a specific server are captured. In this paper,we use statistical and mining approaches to obtain the competitive information hidden in Web user logs,and then use them to evaluate the competition situations among different electronic business companies. Besides,the reasons as well as some possible counter measures are also discussed. Compared with previous works in this area,the main contributions of the paper are threefold. First,we present a new viewpoint for competitor analysis. Second,we propose a Web-user-log-based analyzing model to evaluate the competition situations among electronic business companies. And finally,we conduct experimental studies for 11 electronic business companies on a real data set. The research of this paper is expected to bring some new referential values to the acquirement of competitive intelligence in the Web.

战略性新兴产业已成为世界各国新一轮经济竞争的焦点,在此运用SWOT分析法,对我国发展战略性新兴产业所拥有的优势和劣势,以及所面临的外部机遇和威胁进行了分析,在此基础上提出了发展我国战略性新兴产业的对策与建议,为我国在战略性新兴产业发展中获取竞争优势提供有价值的参考。

微博情感分析已成为目前研究的热点,对于企业营销策划、产品反馈分析、舆情检测、竞争情报挖掘等具有十分重要的作用.微博情感分析通常包含观点句识别、情感要素抽取以及观点分类等一系列工作.由于情感倾向主要通过文本中的观点句来表达,因此观点句识别是影响微博情感分析效果的决定性因素.本论文针对微博观点句识别问题,提出了一种基于新词扩充和特征选择的观点句识别新方法.该方法首先基于微博表情符号和新浪微博实际数据对情感词典进行了扩充,同合并词项的方法将网络新词扩充到分词集合中以提高分词准确率,并进一步融合微博特有特征和情感词、文法、句法、主题等传统特征,使用SVM分类方法进行观点句识别.在来自腾讯微博的20个主题45 566条真实微博上的实验表明,我们的方法具有较好的准确率和F测试值.

B2B作为电子商务模式中的一种,近年来得到了快速的发展。阿里巴巴是我国B2B电子商务的代表,其发展理念对我国B2B电子商务发展有着重要影响。本文以阿里巴巴为例,分析了目前我国B2B电子商务发展中存在的问题,并针对出现的问题提出了若干对策。

In this paper,based on the development of the innovative experimental teaching system in Anhui University,we present a framework to construct a systematic,interdisciplinary,and active experimental system,aiming at solving the problems existing in current teaching system for management specialty.Furthermore,some experimental teaching mechanisms designed for the cultivation of innovative capabilities are proposed.The study in this paper is expected to provide a basic solution on the problems that have occurred in current course teaching for management specialty,as well as to form an exemplified teaching system so as to offer new insights for the research and practice on experimental teaching.

The models of minimal spanning tree,minimal road,maximal flow,minimal flow of cost and salesman problem were established using LINGO in the experiment teaching of operations,and the difficulties in the models were particularly explained.With the models,the best solution of minimal spanning tree,minimal road,maximal flow,minimal flow of cost and salesman problem can be obtained easily and references can be provided for other problems in the experiment teaching of operations.

Moving objects in indoor space has been a research focus in recent years, as most people live and work in indoor space, e.g. working in office, living in apartment, etc. In this paper, we make a first step in indoor moving object management. We focus on the conceptual modeling of indoor space as well as indoor moving objects, and aim to describe the semantics and properties of indoor moving objects. Firstly, a conceptual modeling framework for indoor space is defined, based on which we propose a semantic description of indoor moving objects. Compared with previous models, our model takes into account the relationships among rooms, doors, sensors and moving objects, and uses a layered approach to represent indoor space and indoor moving objects. The model proposed can be further extended to meet different needs in indoor moving object monitoring and tracking.

Time plays important roles in Web search, because most Web pages contain temporal information and a lot of Web queries are time-related. In this paper, we concentrate on the extraction of the focused time for Web pages, which refers to the most appropriate time associated with Web pages. In particular, two critical issues are deeply studied. The first issue to extract implicit temporal expressions from Web pages, and the second is to determine the focused time among those extracted temporal information. For the first issue, we propose a new dynamic approach to resolve the implicit temporal expressions in Web pages. For the second issue, we present a score model to determine the focused time for Web pages. We conduct experiments on real data sets to measure the performance of our algorithms. The results show that our approach outperforms the competitor algorithms.

互联网已经成为企业和组织获取竞争对手情报的主要来源之一.建立基于Web的竞争对手情报自动获取系统已成为企业的迫切需求.在竞争对手情报自动获取系统中,商业机构名的识别是基础,它为竞争对手的标识和进一步情报抽取提供了依据.本文提出了一种基于互联网的商业机构名识别新方法.该方法考虑了商业机构名与其上下文之间的语义关联性,通过语义标注和隐马尔可夫模型相结合的方法进行商业机构名识别.我们以互联网上的真实中文网页为数据集对提出的识别算法进行了性能评估,并从召回率、准确率和F指标三个方面与CHMM(基于层叠隐马尔可夫模型的机构名识别算法)、MEM(基于最大熵模型的机构名识别算法)以及SVM(基于支持向量机的机构名识别算法)进行了对比.实验结果表明,本文提出的算法改善了商业机构名识别效果,并且具有很好的普适性.

Google Scholar,an integrated academic platform consisting of several Chinese and English literature databases,is able to reflect the citation of literatures in an objective manner.Therefore,it has gradually become a popular platform for literature searching both at home and abroad.In this paper,we use Google Scholar as literature source to make a comparative analysis of the academic influence of 6 top LIS journals in CSSCI database in China in recent 5 years.We mainly check the total citation number,the average citation number per article,the h index and the g index of each journal in each year.Based on the computer software tool and the statistical results,the academic influence of the 6 journals in recent 5 years are discussed,and their trend of academic influence in the future is analyzed.

Web has been one of major information sources for enterprises to acquire competitive intelligence. However, traditional approaches focus on collecting Web pages and fail to generate practical competitive intelligence from Web pages. Another problem in the research on Web-based competitive intelligence is that Web pages may contain a lot of incredible information which will have big influence on the effectiveness of competitive intelligence. Aiming at solving these problems, we propose a framework in this paper for the extraction and credibility evaluation of Web competitive intelligence. We present an entity-based approach to extracting Web competitive intelligence, and a social-network-based method to evaluate the credibility of acquired competitive intelligence. The entity-based extracting approach is based on an ontology of Web competitive intelligence, which represents competitive intelligence as a set of competitor intelligence and competition environment intelligence. Some critical issues about the entity-based approach and the social-network-based method are analyzed in detail. The results show that our system is useful to improve the effectiveness of the extraction and credibility evaluation of Web competitive intelligence.