企业家社会网络对企业绩效的影响机制

本文在国内外文献就企业家的社会网络关系研究进行回顾与综述的基础上,总结了社会网络的类型及其正反两方面的影响,指出了当前许多研究片面强调企业家外部网络的作用,而忽视了内部网络。国内外研究表明,企业家社会网络对企业绩效有着正向的影响,其影响机制存在多种变量。本文根据这些研究结果,在理论上提出了企业家内、外社会网络对企业绩效影响机制的模型,并指出了其实践意义以及未来研究方向。     

知识网络中的社会资本及其作用

知识网络的绩效,在一定程度上取决于网络伙伴间社会资本与信任关系的形成。社会资本在知识网络中起着不可忽视的重要作用,其积极作用主要有:促进组织间交互学习;减少交易费用;促进风险分担;形成知识网络的竞争优势,进而增强网络成员的竞争优势;有利于解决知识网络中产生的\"囚徒困境\"等问题。而其消极作用主要有:易帮派化;易冒进;易产生锁定。     

The structure of information networks

We develop a strategic model of information acquisition in networks where agents pay for all the pieces of information they acquire, including those through indirect links. The cost of information depends on the distance it traverses in the network. We consider two possibilities in this context: (1) costs increasing with distance, and (2) costs decreasing with distance. The paper also examines situations where it is more expensive to acquire information of higher value. We show that there is almost no divergence between the efficient and Nash equilibrium information architectures. We then study the effect of decay in networks where information through longer paths is cheaper. Finally, we also examine a model with costly link formation that combines both types of cost related assumptionsWe are grateful to Hans Haller, Rob Gilles, Susanne Maria Schmidt, Sumit Joshi, Georg Erber, Beth Allen, Mark Machina, Bob Martin, Johanna Francis, Cheryl Long, Raja Kali, Kaz Miyagiwa, Micheal Kosfeld, Bibhudutta Panda and two anonymous referees for helpful suggestions. The paper has further benefited from the comments of participants at Game Theory and Applications Mumbai 2003, Royal Economic Society Meetings 2003, SED 2004 and GAMES 2004. Sudipta Sarangi acknowledges the hospitality of DIW Berlin where a part of this research was carried out. Rajgopal Kannan acknowledges the support of NSF grants IIS-0329738 and IIS-0312632     

Returns from social capital in open source software networks

Open Source Software projects base their operation on a collaborative structure for knowledge exchange in the form of provision or reception of information, expertise and feedback on the creation of source code. Here, we address the direction of these knowledge flows among projects throughout social networks and their impact on project success. We identify the roles of membership or contribution that individuals play within projects. We found that connections through contributors who bring their knowledge to the project, improve project success, and that connection through members, who transfer their knowledge towards other projects, enhance project success. Finally, we found that ties through shared membership and contributions hamper project success. The analysis of knowledge flows and their impact on project success imply a translation of returns from investment in social capital, where investment takes the shape of knowledge flows and the returns mean the projects’ diffusion over the network.

Bayesian learning in social networks

We extend the standard model of social learning in two ways. First, we introduce a social network and assume that agents can only observe the actions of agents to whom they are connected by this network. Secondly, we allow agents to choose a different action at each date. If the network satisfies a connectedness assumption, the initial diversity resulting from diverse private information is eventually replaced by uniformity of actions, though not necessarily of beliefs, in finite time with probability one. We look at particular networks to illustrate the impact of network architecture on speed of convergence and the optimality of absorbing states. Convergence is remarkably rapid, so that asymptotic results are a good approximation even in the medium run.     

Social learning with private and common values

Summary. We consider an environment where individuals sequentially choose among several actions. The payoff to an individual depends on her action choice, the state of the world, and an idiosyncratic, privately observed preference shock. Under weak conditions, as the number of individuals increases, the sequence of choices always reveals the state of the world. This contrasts with the familiar result for pure common-value environments where the state is never learned, resulting in herds or informational cascades. The medium run dynamics to convergence can be very complex and non-monotone: posterior beliefs may be concentrated on a wrong state for a long time, shifting suddenly to the correct state.Received: 6 January 2005, Revised: 5 May 2005, JEL Classification Numbers: C72, D82.Jacob K. Goeree: Correspondence toFinancial support from the National Science Foundation NSF (SBR-0098400 and SES-0079301) and the Alfred P. Sloan Foundation is gratefully acknowledged. We thank Richard McKelvey posthumously for insights and conjectures about information aggregation that helped shape our thinking about the problem. We also acknowledge helpful comments from Kim Border, Tilman Börgers, Bogachen Celen, Luis Corchon, Matthew Jackson and seminar participants at University College London, the University of Arizona, Universitat Autonoma de Barcelona, the California Institute of Technology, the 2003 annual meeting of ESA in Pittsburgh, the 2003 Malaga Workshop on Social Choice and Welfare Economics, the 2003 SAET meetings in Rhodos, and the 2003 ESSET meetings in Gerzensee.     

Regional social capital: Embeddedness, innovation networks and regional economic development

Technology is a necessary but not a sufficient condition for regional economic development. Regional innovation networks transform technology into competitiveness of firms and thus contribute to economic development. Intangible assets, such as social capital, decide how effective regional innovation networks function. Differences in regional social capital thus help explain regional differences in economic development. Regional social capital originates from the embeddedness of firms in regional webs of social relations. The norms, values and customs of these networks facilitate collaboration for mutual benefit. As innovation is increasingly a network effort, embeddedness and social capital also help explain how and why networks of innovating companies are successful, as the case study of the Stimulus Cluster Scheme shows.     

基于SNA的项目群管理信息共享研究

文章运用社会网络分析法(SNA)对一家英国大型公用企业的项目群管理展开研究,主要参与主体客户方、一级承包商和咨询公司形成信息共享网络,文章通过阐述三方在项目群生命周期的收尾阶段如何在网络中共享信息以快速关闭项目来探寻组织间网络中行动者和他们之间的联结。由此研究项目群管理环境中不同组织如何在网络中分享信息、知识和创新观点以加速完成项目群绩效目标。研究发现：信息共享网络中,组织属性和任职时间属性有利于理解组织间信息共享;一级承包商和咨询公司员工在项目群收尾阶段位于网络中心位置,反映了他们协助客户加速关闭项目的行为;组织间信息共享不仅能提升合作关系,而且能提高信息共享网络的效率。     

Learning to update your reservation wage while looking for a new job

We combine post-displacement survey data with information from personnel files of a displacing firm in order to reveal sources of worker heterogeneity in search time and wage losses. The Fokker Personnel Files and Survey are described in detail. We develop a dynamic reservation wage with updating. The method of updating is based on the simple idea that job seekers are informed about successful matches of their former colleagues similar to them. The data offer empirical support for the updating model.     

Contemporary Capitalism as a New Monetary Economy of Production: The Logic of Conventions,M&A,and LBOs

Social interaction models, i.e. the changing sequence of actions between individuals who modify their behavior under the influence of their peers, have rarely enjoyed as high a profile in economic analysis as they do today. However, the literature growth has not been accompanied by a process of academic consolidation. The difficulties encountered in research are largely but not entirely the result of data constraints. The main argument of this article is that the source of problems may be traceable to the lack of a complementary approach between economics and other disciplines. The difficulties presented by the deficit in academic exchange among social scientists are compounded by the current analytical framework, which still concentrates on the fundamental, but mutually exclusive, traditions of thought: homo oeconomicus and homo sociologicus. In spotlighting these ideas, this article reviews the economic body of literature on social interactions and their effect on individual unemployment status. Two directions in current research are analyzed: the impact of social (work) norms on unemployment and the role of social networks in the job search process. The theoretical and methodological challenges encountered in research suggest that the future of social interactions models might be found at the crossroads of economics and other social sciences.     

Social networks and industrial geography

In many industries, production resides in a small number of highly concentrated regions; for example, several high tech industries cluster in Silicon Valley. Explanations for this phenomenon have focused on how the co-location of firms in an industry might increase the efficiency of production. In contrast, this article argues that industries cluster because entrepreneurs find it difficult to access the information and resources they require when they reside far from the sources of these valuable inputs. Since existing firms often represent the largest pools of these important factors, the current geographic distribution of production places important constraints on entrepreneurial activity. As a result, new foundings tend to arise in the same areas as existing ones, and hence reproduce the industrial geography. In support of this thesis, the article reviews empirical evidence from the shoe manufacturing and biotechnology industries.JEL Classification: L11, M13, R30Adapted from a plenary talk delivered at the 8 ^th annual meetings of the International Schumpeter Society in Gainesville, FL. Constança Esteves and Lee Fleming provided comments useful to developing this written version.