Social networks and coordination performance of distributed software development teams

In this study, we explore the coordination performance of the geographically distributed software development teams by exploring OSS (Open Source Software) development dataset available through SourceForge.com. OSS team structures have traditionally been geographically dispersed and therefore, the coordination of post release activities such as testing efforts have been carried out by means of communication via electronic forms, such as email or message boards and forums. In our current communication-enriched environment, best practices for coordination are adopted by all software projects yet some still fail to achieve their target performance. Does team structure have any bearing on the performance outcome of the project? How does the communication between teams and their external parties affect ultimate success or failure of projects? We seek to answer above questions by applying existing theories and analytical methods from social networks for exploring the coordination performance of defect management activities found in OSS projects. We propose social networks based theoretical model for exploring distributed coordination structure and apply that for the case of OSS defect management process for exploring the structural properties, which induce the greatest coordination performance. The outcome of our suggest that there is correlation between certain network measures such as density, centrality and betweenness and coordination performance measures of defect management systems such as quality and timeliness.     

“关系-结构”双重社会网络对工作绩效作用机制研究——N城地产销售业调查结果的实证分析

通过对地产销售从业人员的实证调查,探究销售人员的"关系性"和"结构性"社会网络对其工作绩效的影响机理。实证研究发现:关系社会网对工作绩效的影响具有稳定性,但对工作绩效的不同维度的影响变量存在显著差异;结构社会网对工作绩效影响力度小,主要集中在情感网络程度中心性和情报网络中介中心性两个变量上;结构社会网在关系社会网与工作绩效关系中不起中介作用。     

Egocentric analysis of co-authorship network structure,position and performance

In this study, we propose and validate social networks based theoretical model for exploring scholars’ collaboration (co-authorship) network properties associated with their citation-based research performance (i.e., g-index). Using structural holes theory, we focus on how a scholar’s egocentric network properties of density, efficiency and constraint within the network associate with their scholarly performance. For our analysis, we use publication data of high impact factor journals in the field of “Information Science & Library Science” between 2000 and 2009, extracted from Scopus. The resulting database contained 4837 publications reflecting the contributions of 8069 authors. Results from our data analysis suggest that research performance of scholars’ is significantly correlated with scholars’ ego-network measures. In particular, scholars with more co-authors and those who exhibit higher levels of betweenness centrality (i.e., the extent to which a co-author is between another pair of co-authors) perform better in terms of research (i.e., higher g-index). Furthermore, scholars with efficient collaboration networks who maintain a strong co-authorship relationship with one primary co-author within a group of linked co-authors (i.e., co-authors that have joint publications) perform better than those researchers with many relationships to the same group of linked co-authors.     

Towards a method to disseminate knowledge from the post project review

In this paper we review several issues associated with post project review and dissemination of knowledge in information technology projects. We reflect on our practice of coaching project teams. In identifying the role of social pressure in forming teams’ perception of their performance, we suggest what could potentially be an interesting and fruitful avenue of future research on an approach to post project review and dissemination of knowledge in organizations.     

基于社会网络分析的兴趣图谱口碑传播者角色分析

兴趣图谱商业应用的优势在于拥有社会化的信息分享、互动传播机制,社会化营销借助兴趣图谱的形式可以实现丰富而高质量口碑分享,获得高质量的品牌传播效果.本文利用社会网络理论分析了口碑传播行动者间的联系网,对基于兴趣图谱的网络口碑传播网络中的行动者角色进行分析,分别从点度中心性、中间中心性和接近中心性3个方面对口碑传播的行动者中心性进行了探讨,对口碑传播中行动者的的权力维度进行划分,并利用归纳出的3个权力维度对样本数据分层聚类,最后提出了相应的传播策略启示及建议.     

群体成员差异性对社会网络的影响:个体及群体层次的实证研究

基于相似-吸引典范及社会归类理论,本研究认为群体中人口统计变量和工作价值观的个体间差异性及组成差异性分别对个体情感网络中心性与整体情感网络密度产生影响。本研究用45个工作群体(246个个体)样本对假设进行验证,结果表明:社会互动及自我实现取向的差异性对个体情感网络中心性有显著负向影响,人口统计变量的差异性则对个体情感网络中心性没有显著影响;群体层次的情感网络密度假设也得到相似的验证结果。最后,讨论了本研究的理论和实践意义以及研究限制。     

网络嵌入性与创新绩效的Meta分析

学术界对网络嵌入性的研究方兴未艾,实证与理论性的研究层出不穷,但关于网络嵌入性对创新绩效影响的研究结论仍然存在争议。研究采用Meta分析方法,对68篇独立样本实证研究进行了再统计分析。研究结果表明,网络关系嵌入性(联系强度、关系稳定性、关系质量、网络互惠性)以及网络结构嵌入性(网络规模、网络密度、网络异质性、网络中心性)对创新绩效存在显著的正向影响。此外,调节效应分析结果表明高新技术企业的网络关系及结构嵌入性对创新绩效作用更强,而产业分布对各网络嵌入性变量与创新绩效关系的调节程度及方向皆不相同。同时,测量特性也会导致主效应的结果产生差异。     

社会网络位置和企业R&D绩效

传统观点认为,在社会网络中占据一个能获取更多外部资源的位置,对于企业R&D绩效提升来说是一种优势。然而一些实证研究结果并不支持这种观点。本研究对这种理论和现实的矛盾进行了分析。经过文献的梳理,我们认为技术积累是社会网络位置和企业R&D绩效之间的重要调节变量。利用中国上市公司数据,本研究构建了中国上市公司的二模社会网络,并用结构洞、点度中心性、中介中心性、接近度中心性测量了焦点企业的社会网络位置。企业R&D绩效则通过DEA方法测量得出。面板数据的门槛回归分析结果表明技术积累的门槛效应是显著的,但对不同性质的社会网络位置的门槛作用有差异。本研究从技术积累的视角解释了社会网络位置和企业R&D绩效之间的非线性关系,为企业管理决策提供了新的理论基础。     

网络节点中心性与均衡性结合的作者网络特征分析

【目的/意义】为丰富拓展作者网络分析方法,将均衡性分析与社会网络中的节点中心性分析相结合,从不同视角分析作者网络的结构特征。【方法/过程】以"情报学"学科领域下发文量较高的44位作者为研究对象,构建其耦合网络,得到44位作者的点度中心度、中介中心度和接近中心度的排名;然后,利用Gini指数计算作者耦合网络中的中心均衡性,包括点度中心均衡性、中介中心均衡性和接近中心均衡性,以全面分析作者耦合网络的结构特征。【结果/结论】实验表明,"节点中心性"与"中心均衡性"结合对作者网络结构描述结果与事实相符,对作者网络结构的描述更加全面、立体。     

社会资本、知识利用与共有协同创新绩效

已有研究将社会资本作为获取外部知识的渠道,隐含假设是社会资本具有知识流入效应。由于知识分享的相互性,社会资本实质上还具有知识流出效应。已有研究主要强调知识流入效应,是因为私有协同创新中的知识分享存在有意识的控制机制和组织边界,从而有效地抑制了知识流出。在共有协同创新网络中,创新团队间边界模糊且知识分享不受限制,导致知识流出效应显著增强。本文以共有协同创新网络为背景,探讨创新团队社会资本对新产品流行度的差异化影响以及如何控制该影响。通过收集开源平台SourceForge上1595个项目和8186个志愿者信息,结果发现创新团队度中心性对新产品流行度具有倒U型作用;桥中心性和接近中心性可提升新产品流行度。团队知识利用则有利于延缓社会资本的负面效应,强化其正面效应。     

Empowering teams through social network ties

Effective teamwork and knowledge coordination are becoming increasingly important for all kinds of organizations given the growing use of teams to tackle competitive challenges and sustain competitive advantage. In this study, we develop and validate a model of how two types of social network ties – expressive and instrumental – contribute to team efficacy and performance, mediated by three dimensions of a transactive memory system (TMS) – specialization, credibility and coordination within teams. We test the model in an empirical study drawing on data from 66 teams in a variety of organizations. The results suggest that both instrumental and expressive ties within teams can facilitate the formation of TMS and the three dimensions of TMS are all, even though to different extents, positively related to team efficacy. Team efficacy is also a powerful predictor of team performance. The findings in our study bridge the literature gap about social networks and TMS and explain the underlying process and mechanisms by which social network ties exert their influence on team outcomes. The results have implications for organizations that wish to leverage teams to take advantage of team members’ differentiated expertise and coordinate their work more effectively and efficiently.     

Emerging coordination and knowledge transfer process during disease outbreak

When multiple agencies respond to a disease outbreak (i.e., H1N1 and SARS), the coordination of actions is complex and evolves over time. There has not been any systematic empirical study of the dynamics of emerging coordination behaviour and knowledge transfer process during a disease outbreak. In this paper, we first introduce our approach for the analysis of multi-agency intervention during a disease outbreak using the study of social networks. Using social networks and its analytic framework, we explore questions such as: How does the multi-agency coordination emerge for supporting the complex knowledge transfer process during different phases of disease outbreak? How effective are these formal and informal coordination mechanisms in achieving a robust outcome in response coordination through effective knowledge transfer process during the outbreak? What are the key lessons learned by studying the emerging coordination and knowledge transfer process during past disease outbreak in improving the multi-agency preparedness for dealing with future outbreaks? The discussion is supported by a qualitative study of the implementation of the results of the analysis. We reveal that profound understanding of social network behaviour and emerging coordination concepts are pivotal to the optimisation of knowledge transfer process which is a prerequisite for successful outbreak intervention. We look qualitatively at how Hunter New England Area Health Services applied these concepts to lead a successful coordination plan during an H1N109 endemic.     

Towards a real-time processing framework based on improved distributed recurrent neural network variants with fastText for social big data analytics

Big data generated by social media stands for a valuable source of information, which offers an excellent opportunity to mine valuable insights. Particularly, User-generated contents such as reviews, recommendations, and users’ behavior data are useful for supporting several marketing activities of many companies. Knowing what users are saying about the products they bought or the services they used through reviews in social media represents a key factor for making decisions. Sentiment analysis is one of the fundamental tasks in Natural Language Processing. Although deep learning for sentiment analysis has achieved great success and allowed several firms to analyze and extract relevant information from their textual data, but as the volume of data grows, a model that runs in a traditional environment cannot be effective, which implies the importance of efficient distributed deep learning models for social Big Data analytics. Besides, it is known that social media analysis is a complex process, which involves a set of complex tasks. Therefore, it is important to address the challenges and issues of social big data analytics and enhance the performance of deep learning techniques in terms of classification accuracy to obtain better decisions.In this paper, we propose an approach for sentiment analysis, which is devoted to adopting fastText with Recurrent neural network variants to represent textual data efficiently. Then, it employs the new representations to perform the classification task. Its main objective is to enhance the performance of well-known Recurrent Neural Network (RNN) variants in terms of classification accuracy and handle large scale data. In addition, we propose a distributed intelligent system for real-time social big data analytics. It is designed to ingest, store, process, index, and visualize the huge amount of information in real-time. The proposed system adopts distributed machine learning with our proposed method for enhancing decision-making processes. Extensive experiments conducted on two benchmark data sets demonstrate that our proposal for sentiment analysis outperforms well-known distributed recurrent neural network variants (i.e., Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BiLSTM), and Gated Recurrent Unit (GRU)). Specifically, we tested the efficiency of our approach using the three different deep learning models. The results show that our proposed approach is able to enhance the performance of the three models. The current work can provide several benefits for researchers and practitioners who want to collect, handle, analyze and visualize several sources of information in real-time. Also, it can contribute to a better understanding of public opinion and user behaviors using our proposed system with the improved variants of the most powerful distributed deep learning and machine learning algorithms. Furthermore, it is able to increase the classification accuracy of several existing works based on RNN models for sentiment analysis.     

团队成员网络中心性、网络信任对知识转移成效的影响研究

 实现个人知识在研发团队内部的有效转移对组织的知识创造至关重要,而团队内社会网络又是影响团队内知识转移的重要渠道。研究考察了团队成员个人团队内的社会网络中心性和网络信任对团队内部知识转移成效的影响。研究认为团队成员个人在团队内的社会网络中心性对个人知识在团队内转移的成效以及个人团队内的网络信任均具有促进作用,在此基础上进一步提出了团队成员的网络信任在网络中心性影响知识转移成效中的中介作用。研究对所提假设进行了实证检验,并对结果进行了进一步的解释,旨在进一步剖析知识活动的规律,从而为企业有效的管理知识提供指导。     

农业网站的链接关系研究

运用社会网络的分析方法,选择中国农业网站排行的前50个网站,研究农业网站之间的链接关系,并根据农业网站之间的链接数构建了网络关系图,通过中心度和凝聚子群的分析,找到了最权威的农业网站。并描绘了中间中心度与入度中心度、出度中心度之间的线性关系,在此基础上建立了回归方程,得出中间中心度在一定程度上受到入度中心度和出度中心度的影响。     

Distributed coordination on state-dependent fuzzy graphs

Multiagent systems are increasingly becoming popular among researchers spanning multiple fields of study. However, existing studies only models communication interaction between agents as either fixed or switching topologies described by crisp graphs supported by algebraic graph theories. In this paper, we propose an alternative approach to describing agent interactions using fuzzy graphs. Our approach is aimed at opening up new research avenues and defining new problems in coordination control especially in terms of dynamics between agents’ states, graph topologies and coordination objectives. This paper studies distributed coordination on fuzzy graphs where the edge-weights modeling network topologies are dependent on the states of the agents in the network. In hindsight, the network weights are adjustable based on the situational state of the agents. First, we introduce the concept of fuzzy graphs and give some distinguishing features from the crisp or fixed graphs. Next, we provide some membership functions to define the state-dependent weights and finally we use some simulations to demonstrate the convergence of the proposed consensus algorithms especially for cases where the agents are subject to system failures.     

利益相关者网络视角的企业社会创新过程——案例研究

企业作为社会创新三大主体（政府、社会、企业）之一,日益受到关注。但企业社会创新涉及众多利益相关者的权利关系却被研究者忽略,也造成了实际工作的举步维艰。本文首先阐明了基于权利关系的利益相关者网络概念,进而构建了利益相关者网络视角的企业社会创新过程理论模型,运用社会网络密度、节点度和中心度的计算方法,对浙江九仓再生资源开发公司的垃圾回收社会创新过程的不同阶段进行详细的案例研究,得出的结论是,在企业社会创新过程中,利益相关者有不同的权利诉求,由此形成的权利关系决定的网络密度、节点度、中心性也因不同阶段而演化,其中高管、政府和社区是主要利益相关者,股东、员工、客户、合作者、供应商也是不可或缺的利益相关者,他们在社会创新过程的四个阶段中因不同的权利关系而发挥着不同的作用。     

Countering user risk in information system development projects

User related issues have long been broadly discussed in the information system development (ISD) project research area. In this study, we focus on user risk and identify two risk countering approaches to demonstrate how to deal with user risk and its negative impact on ISD projects. We hypothesize that (1) user risk has a negative impact on project performance, (2) users’ bond with the project and the development team can help reduce user risk, and (3) developers’ task knowledge and vertical coordination can ease the negative impact of user risk and increase project performance. A quantitative approach with survey data collected from 240 practitioners confirmed our hypotheses. In addition, we interviewed seven developers and three user representatives to complete our understanding of this issue. Implications for academia and practitioners are discussed at the end of this paper. Suggestions for future research directions are also provided.     

创新项目大众筹资:资助人公民行为的价值

互联网与民间资本的结合产生了大众筹资模式(简称众筹),资助人不仅在众筹网站为创新项目提供资金,而且主动辅助项目的执行。如何利用资助人的公民行为提高项目实施绩效是一个重要的学术问题。本文基于价值共创、价值与满意度方面理论,采用问卷调查法研究资助人公民行为对满意度的作用,以及公民行为的影响因素。主要有三点贡献:1首次从价值共创角度分析众筹项目的执行过程;2揭示了资助人公民行为、社区收益与满意度的关系;3验证了感知的项目风险、项目新颖度、社会责任感对资助人公民行为的影响。