Using the h-index to measure the quality of journals in the field of business and management

This paper considers the use of the h-index as a measure of a journal’s research quality and contribution. We study a sample of 455 journals in business and management all of which are included in the ISI Web of Science (WoS) and the Association of Business School’s peer review journal ranking list. The h-index is compared with both the traditional impact factors, and with the peer review judgements. We also consider two sources of citation data – the WoS itself and Google Scholar. The conclusions are that the h-index is preferable to the impact factor for a variety of reasons, especially the selective coverage of the impact factor and the fact that it disadvantages journals that publish many papers. Google Scholar is also preferred to WoS as a data source. However, the paper notes that it is not sufficient to use any single metric to properly evaluate research achievements.     

学术期刊来源指标与影响力关系的实证研究

摘要：对学术期刊来源指标与影响力关系进行研究,总结其中潜在规律,对期刊评价与期刊管理具有重要意义。从期刊来源指标的角度系统分析其与期刊影响力关系的研究不多。本文利用散点图、回归分析和分组统计三种方法相结合,以中国科学技术信息研究所医学类学术期刊为例,分析了基金论文比、平均引文数、平均作者数、地区分布数、引用半衰期5个期刊来源指标与期刊影响力之间的关系。发现期刊来源指标较好并不代表期刊影响力就很大。各期刊来源指标与影响力之间存在着较低的相关关系,但是在不同数据段他们的相关程度又不一样。不同期刊来源指标与期刊影响力之间的关系各有特点。建议在期刊学术质量评价中舍弃来源指标。     

基于构件的信息系统开发项目成功因素

在结合西安高新技术产业开发区实地调查研究的基础上，对基于构件的信息系统开发成功因素进行了讨论，采用定性分析方法构建了一个理论分析框架。该框架将基于构件的信息系统开发成功因素划分为6类：组织因素、项目因素、技术因素、人员因素、工程因素、商品构件特有因素，并对每个因素进行了进一步的分析。最后，给出了一个成功因素列表。     

Examining the Authority and Ranking Effects as the result list depth used in data fusion is varied

The Authority and Ranking Effects play a key role in data fusion. The former refers to the fact that the potential relevance of a document increases exponentially as the number of systems retrieving it increases and the latter to the phenomena that documents higher up in ranked lists and found by more systems are more likely to be relevant. Data fusion methods commonly use all the documents returned by the different retrieval systems being compared. Yet, as documents further down in the result lists are considered, a document’s probability of being relevant decreases significantly and a major source of noise is introduced. This paper presents a systematic examination of the Authority and Ranking Effects as the number of documents in the result lists, called the list depth, is varied. Using TREC 3, 7, 8, 12 and 13 data, it is shown that the Authority and Ranking Effects are present at all list depths. However, if the systems in the same TREC track retrieve a large number of relevant documents, then the Ranking Effect only begins to emerge as more systems have found the same document and/or the list depth increases. It is also shown that the Authority and Ranking Effects are not an artifact of how the TREC test collections have been constructed.     

面向开源设计演化过程的关键影响因素综述

开源成为近年来发展较快的设计与创新模式，它在产品的创意转化、技术转化、市场导向、创新程度等方面具有显著的低成本和高客户满意度的优势。寻找关键影响因素对提高开源设计的效率和成功率有着积极的推动意义。首先，运用扎根理论文献综述的方法对相关领域的文献进行筛选和整理；其次，基于Crowston的开源软件进化过程模型，本文从输入要素和过程要素两大方面分析了影响开源设计成功的相关因素，主要包括：人员动机与行为、产品模块化的特点、项目许可的约束程度、社区规模与结构、知识共享的机制以及企业支持等。最后，根据上述分析，总结了开源设计演化过程中的两阶段影响因素，进而提出“两个持续”的目标对应两个阶段：在Pre-阶段成员的持续加入和在Post-阶段成员的持续创新，是开源设计成功的关键。     

Incorporating message format into user evaluation of microblog information credibility: A nonlinear perspective

The spreading of misinformation and disinformation is a great problem on microblogs, leading user evaluation of information credibility a critical issue. This study incorporates two message format factors related to multimedia usage on microblogs (vividness and multimedia diagnosticity) with two well-discussed factors for information credibility (i.e., argument quality and source credibility) as a holistic framework to investigate user evaluation of microblog information credibility. Further, the study draws on two-factor theory and its variant three-factor lens to explain the nonlinear effects of the above factors on microblog information credibility. An online survey was conducted to test the proposed framework by collecting data from microblog users. The research findings reveal that for the effects on microblog information credibility: (1) argument quality (a hygiene factor) exerts a decreasing incremental effect; (2) source credibility (a bivalent factor) exerts only a linear effect; and (3) multimedia diagnosticity (a motivating factor) exerts an increasing incremental effect. This study adds to current knowledge about information credibility by proposing an insightful framework to understand the key predictors of microblog information credibility and further examining the nonlinear effects of these predictors.     

Combining evidence with a probabilistic framework for answer ranking and answer merging in question answering

Question answering (QA) aims at finding exact answers to a user’s question from a large collection of documents. Most QA systems combine information retrieval with extraction techniques to identify a set of likely candidates and then utilize some ranking strategy to generate the final answers. This ranking process can be challenging, as it entails identifying the relevant answers amongst many irrelevant ones. This is more challenging in multi-strategy QA, in which multiple answering agents are used to extract answer candidates. As answer candidates come from different agents with different score distributions, how to merge answer candidates plays an important role in answer ranking. In this paper, we propose a unified probabilistic framework which combines multiple evidence to address challenges in answer ranking and answer merging. The hypotheses of the paper are that: (1) the framework effectively combines multiple evidence for identifying answer relevance and their correlation in answer ranking, (2) the framework supports answer merging on answer candidates returned by multiple extraction techniques, (3) the framework can support list questions as well as factoid questions, (4) the framework can be easily applied to a different QA system, and (5) the framework significantly improves performance of a QA system. An extensive set of experiments was done to support our hypotheses and demonstrate the effectiveness of the framework. All of the work substantially extends the preliminary research in Ko et al. (2007a). A probabilistic framework for answer selection in question answering. In: Proceedings of NAACL/HLT.     

国内生态经济研究热点与趋势——基于12种中文核心期刊

为了明确国内生态经济研究热点与趋势，采用传统文献研究与知识图谱相结合的方法进行探究。选取中国知网（CNKI）生态经济主题下发文量较多且影响因子较高的12种期刊作为文献数据来源，基于图谱可视化工具CiteSpace实现该领域热点主题、知识基础和研究前沿演进轨迹的呈现。研究发现：国内生态经济研究近37年来发文量上扬，研究者分布呈“一体两翼”态势；拥有较为明显的演进主体，研究内容宽广多元，研究前沿随演进主体而动；可持续发展思想导向明显，尤其受到国家层面可持续发展战略、生态文明建设推进的影响，具有较为清晰的发展脉络。     

On-line serials collection analysis.

A design for an on-line serials decision-making and collection analysis system is proposed. It is composed of four basic components: citation data, conventional serial records data, utility/cost ratio compilation and journal ranking techniques, and user interface software. The system would have the ability to respond specifically to user interest profiles and to integrate locally generated data. It is postulated that such a system is capable of satisfactorily resolving the major criticisms of the use of citation data for selection purposes: that libraries are diverse in their interests and that no aggregate list can be more than generally relevant; that the inclusion of cost data is essential and that citation ranking without regard to cost can be misleading; and that other relevant data should be considered as well.     

知识型服务企业知识存量的增长机理——工程咨询企业的扎根研究

以工程咨询企业为例来说明知识型服务企业知识存量增长的机理。通过扎根理论研究方法和共生理论的研究框架,研究发现共生是工程咨询企业知识存量增长的主要原因。在一定的共生关系中,核心范畴共生包括共生单元、共生界面和共生环境三大主范畴及一个判别准则信息丰度。共生单元包括质参量(硬实力、软实力)、象参量(资历、合作意愿)和物理参数(共生密度、共生维度)三个影响因子;共生界面包括有形界面和无形界面两个影响因子;共生环境包括内部环境(组织激励、企业氛围、自我满足、组织内部支持)和外部环境(组织外部支持)两个影响因子。在一定共生关系中,上述因素交互作用,最终导致共生的行为过程(即知识共享)和共生的行为结果 (即知识存量)。     

The challenge of commercial document retrieval,Part I: Major issues,and a framework based on search exhaustivity,determinacy of representation and document collection size

With the growing focus on what is collectively known as “knowledge management”, a shift continues to take place in commercial information system development: a shift away from the well-understood data retrieval/database model, to the more complex and challenging development of commercial document/information retrieval models. While document retrieval has had a long and rich legacy of research, its impact on commercial applications has been modest. At the enterprise level most large organizations have little understanding of, or commitment to, high quality document access and management. Part of the reason for this is that we still do not have a good framework for understanding the major factors which affect the performance of large-scale corporate document retrieval systems. The thesis of this discussion is that document retrieval—specifically, access to intellectual content—is a complex process which is most strongly influenced by three factors: the size of the document collection; the type of search (exhaustive, existence or sample); and, the determinacy of document representation. Collectively, these factors can be used to provide a useful framework for, or taxonomy of, document retrieval, and highlight some of the fundamental issues facing the design and development of commercial document retrieval systems. This is the first of a series of three articles. Part II (D.C. Blair, The challenge of commercial document retrieval. Part II. A strategy for document searching based on identifiable document partitions, Information Processing and Management, 2001b, this issue) will discuss the implications of this framework for search strategy, and Part III (D.C. Blair, Some thoughts on the reported results of Text REtrieval Conference (TREC), Information Processing and Management, 2002, forthcoming) will consider the importance of the TREC results for our understanding of operating information retrieval systems.     

基于TAM的百度百科用户参与意向的影响因素研究

基于TAM的模型框架和相关文献,运用结构方程方法,探查了百度百科用户参与意向的影响因素。结果表明:兴趣动机和态度直接影响参与意向;求知动机、互惠动机和易用性感知通过其他变量间接影响参与意向;有用性感知既直接影响参与意向,又通过其他变量间接影响参与意向。各因素按对参与意向的总影响程度从大到小排序为兴趣动机、有用性感知、易用性感知、求知动机、态度和互惠动机。     

Document replication strategies for geographically distributed web search engines

Large-scale web search engines are composed of multiple data centers that are geographically distant to each other. Typically, a user query is processed in a data center that is geographically close to the origin of the query, over a replica of the entire web index. Compared to a centralized, single-center search engine, this architecture offers lower query response times as the network latencies between the users and data centers are reduced. However, it does not scale well with increasing index sizes and query traffic volumes because queries are evaluated on the entire web index, which has to be replicated and maintained in all data centers. As a remedy to this scalability problem, we propose a document replication framework in which documents are selectively replicated on data centers based on regional user interests. Within this framework, we propose three different document replication strategies, each optimizing a different objective: reducing the potential search quality loss, the average query response time, or the total query workload of the search system. For all three strategies, we consider two alternative types of capacity constraints on index sizes of data centers. Moreover, we investigate the performance impact of query forwarding and result caching. We evaluate our strategies via detailed simulations, using a large query log and a document collection obtained from the Yahoo! web search engine.     

Dynamic discovery of favorite locations in spatio-temporal social networks

A large volume of data flowing throughout location-based social networks (LBSN) gives support to the recommendation of points-of-interest (POI). One of the major challenges that significantly affects the precision of recommendation is to find dynamic spatio-temporal patterns of visiting behaviors, which can hardly be figured out because of the multiple side factors. To confront this difficulty, we jointly study the effects of users’ social relationships, textual reviews, and POIs’ geographical proximity in order to excavate complex spatio-temporal patterns of visiting behaviors when the data quality is unreliable for location recommendation in spatio-temporal social networks. We craft a novel framework that recommends any user the POIs with effectiveness. The framework contains two significant techniques: (i) a network embedding method is adopted to learn the vectors of users and POIs in an embedding space of low dimension; (ii) a dynamic factor graph model is proposed to model various factors such as the correlation of vectors in the previous phase. A collection of experiments was carried out on two real large-scale datasets, and the experimental outcomes demonstrate the supremacy of the proposed method over the most advanced baseline algorithms owing to its highly effective and efficient performance of POI recommendation.     

Big data and dynamic capabilities in the digital revolution: The hidden role of source variety

Recent research frames big data as a resource enhancing dynamic capabilities through improved prediction, decision-making, and data-driven innovation. In contrast, this study frames big data as an evolutionary driver that channels firms' knowledge and attention in specific directions, implying that firms need multiple big data sources to be receptive and dynamically capable. I apply this framework to the context of the digital revolution and focus on the impact of big data on firms' digitalization priorities. By leveraging a large-scale survey of more than twenty thousand Italian firms of all sizes, I find that big data improves the digitalization awareness of firms only if they gather big data from more than one source (otherwise, counterintuitively, it may even decrease it). I also find a positive effect of source variety both on the likelihood of prioritizing individual digitalization factors and on the variety of digitalization factors prioritized. Such effects appear to be stronger for small firms relative to their larger counterparts. Given the path dependence of digitalization trajectories, these findings have relevant policy implications in the context of initiatives like the European strategy for data and the SME strategy for a sustainable and digital Europe.     

A knowledge schema for organisational learning in academic libraries

This article introduces a formal methodology for deriving conceptual knowledge schema for today's academic libraries. This knowledge schema is defined in the form of a set of knowledge structures and their relationships, and with the purpose of identifying organisational learning requirements. These schemas will then form basis for an organisational knowledge base that assists collaborating librarians to identify appropriate links to relevant knowledge sources within the context of the tasks that they perform. The article demonstrates that the proposed schema when used in conjunction with a specialised knowledge map called the Awareness Net will constitute a suitable conceptual framework for identifying knowledge sharing and organisational learning requirements in today's university libraries.     

Knowledge transfer in alliances: the moderating role of the alliance type

We analyse how the impact of determinants of inter-firm knowledge transfers in alliances can be moderated by the proximity of the resources pooled by partners. Six factors are examined: relative absorptive capacity (RAC), inter-partner trust, cultural distance between allies, knowledge ambiguity, knowledge protection, and the partners’ learning intent. We distinguish alliances mobilizing similar resources by partners (called ‘endogamies’ as allies build on their similarities) from alliances pooling different resources (called ‘exogamies’ as allies build on their differences). We propose that: (a) the impact of RAC on knowledge transfers is reinforced in exogamies, but reduced in endogamies; (b) the knowledge ambiguity and cultural distance effect is less in endogamies than in exogamies; (c) the trust and knowledge protection impact is stronger in exogamies than in endogamies; (d) the learning intent impact on knowledge transfers is similar in endogamies and exogamies.     

基于知识地图和蚁群算法的知识识别模型研究

知识在其属性空间内是存在联系的,知识地图作为可视化表达工具,是具有属性空间知识的理想载体,它是知识空间形象思维的再现。在杂乱无章的知识群中,企业如果能够准确、高效地对知识加以识别,将会给企业带来相当大的隐性收益。这些收益虽然不能直接体现在企业的财务报表上,但是它们确实是影响企业组织规模和运营模式的内在因素。本文以知识地图和蚁群算法为研究工具,建立了企业的知识管理体系中知识识别的模型,通过实证中相关数据的采集绘制出企业相关技术实现的知识地图,并通过蚁群算法在地图中找到了一条较为合理的知识识别路径。     

Business Innovation based on artificial intelligence and Blockchain technology

The growing business evolution and the latest Artificial Intelligence (AI) make the different business practices to be enhanced by the ability to create new means of collaboration. Such growing technology helps to deliver brand services and even some new kinds of corporate interactions with customers and staff. AI digitization simultaneously emphasized businesses to focus on the existing strategies and regularly and early pursue new market opportunities. While digital technology research in the framework of business innovation is gaining greater interest and the privacy of data can be maintained by Blockchain technology. Therefore in this paper, Business Innovation based on artificial intelligence and Blockchain technology (BI-AIBT) has been proposed to enhance the business practices and maintain the secured interaction among the various clients. The collection of qualitative empirical data is made up of few primary respondents from two distinct business sectors. BI-AIBT has been evaluated by undertaking and exploring the difference and similarities between digitalization's impact on value development, proposal, and business capture. Besides, organizational capacities and staff skills interaction issues can be improved by BT. The experimental result suggests that digital transformation is usually regarded as essential and improves business innovation strategies. The numerical result proposed BI-AIBT improves the demand prediction ratio (97.1%), product quality ratio (98.3%), Business development ratio (98.9%), customer behavior analysis ratio (96.3%), and customer satisfaction ratio (97.2%).     

图书情报学领域施引文献特征的计量分析

基于Web of Science数据库,以中美英图书情报学领域1990-1994年和2010-2014年期间文献的施引文献为样本,计量分析了：1）美国在1990-1994年和2010-2014年期间的施引文献特征：国别、机构、来源期刊、开源、类型和语言及其之间的差异;2）中美英2010-2014年期间图书情报学领域的施引文献特征及其之间的差异,揭示出中美英3国1990-1994年和2010-2014年期间图书情报学领域的施引特征分布情况及科学交流概况。研究发现：1）1990-2015年美国的年均发文数量是中国年均发文数量的24倍;2）中美英图书情报学领域的主要施引国家基本一致;3）美英图书情报学领域新时期（2010-2014）的主要施引机构中,出现香港城市大学、中国科学院大学和武汉大学等中国大学的身影;4）美国图书情报学领域施引文献的开源程度最高,比例达到10.73%;5）中美英3国图书情报学领域的主要施引文献类型基本一致,全部为论文、会议论文、综述、专著和社论材料,且论文和会议论文的占比均在91%以上。