网络关系对企业创新能力的影响研究

创新网络理论是研究产业区内各种节点往来关系对区域创新能力的影响机制,目前针对它的大部分研究还是以定性的分析为主,因此对定量研究的探索就显得非常重要。以企业为研究切入点。提出网络关系成熟度及其测度构面对创新能力的影响假设,以创新能力及网络关系的各自测度指标作为变量,根据影响假设建立结构方程模型及备选模型。最后,通过问卷调查研究对哈尔滨开发区进行实证研究,结果表明,正式网络对创新能力有显著的正向影响,非正式网络关系对创新能力需要作用于正式网络关系才能起到正向的影响作用;强度、密度是网络关系最好的测度指标,并且对创新能力的贡献也最大。研究也表明哈尔滨开发医内创新网络的作用较差,尤其是本区域内的网络关系不能对当地企业的创新有很好的作用。     

Delay causes analysis in complex construction projects: a Semantic Network Analysis approach

Delays are among the most crucial adversaries to the success and performance of construction projects, making delay analysis and management a critical task for project managers. This task will be highly complicated in large-scale projects such as construction, which usually consist of a complex network of heterogeneous entities in continuous interaction. Traditional approaches and methods for the analysis of delays and their causes have been criticised for their ability to handle complex projects, and for considering the interrelationships between delay causes. Addressing this gap, this research introduces an alternative approach for delay causes analysis by adopting Semantic Network Analysis (SNA) method. The paper reports the results from an investigation of delays in construction projects in the Oil-Gas-Petrochemical sector using SNA. The method’s capacity to identify and rank delay causes, which can assist managers in selecting appropriate measures for eliminating them, are empirically examined and discussed. The paper argues that SNA leads to a more comprehensive understanding of the main causes of delay in large and complex projects, allowing a better identification and mapping of the interrelationships between these discrete factors.     

Tweeting about emergency: A semantic network analysis of government organizations’ social media messaging during Hurricane Harvey

While social media like Twitter have been increasingly adopted by public-sector organizations, it remains less explored as to how government and emergency management (EM) organizations use these platforms to communicate with the public in response to emerging natural disasters. Extending the Situational Crisis Communication Theory (SCCT) to the realm of social media, this study examines the emerging semantic networks from 67 government and EM organizations’ official tweets during Hurricane Harvey over a three-week period. It identifies how multiple crisis response strategies—including instructing information, adjusting information, and bolstering—are constituted of different issues, actions, and organizational actors before, during, and immediately after the disaster event. Results suggest that government agencies use the strategy of instructing information predominantly before and during the disaster, whereas adjusting information and bolstering strategies are utilized more during post-disaster recovery. The study offers theoretical and practical implications of using a semantic network approach to studying organizational crisis responses.     

Secondhand social capital: Boundary spanning,secondhand closure,and individual performance

We move beyond the performance returns of individuals’ direct network connections to study the effects of “secondhand” social capital, i.e., from the networks of one’s contacts. We propose that certain colleagues may be more valuable to one’s job performance than others when their spillovers of novel information combine with spillovers of the cooperation needed to obtain that novelty. In a study of 1273 research and development employees across 16 business units, we find that the most benefit to one’s own performance comes from having ties that span business units and that also include secondhand closure (i.e., where one’s contacts are each embedded in a constrained, dense network). Bridging the organizational boundary provides the novelty; and secondhand closure provides the cooperation. Further, by examining who in the network is constraining these contacts, we are able to trace their cooperative motivation both to reputational and organizational identity concerns, which each create a spillover of cooperation toward the focal individual, who reaps the returns.     

Mobility types,transnational ties and personal networks in four highly skilled immigrant communities in Seville (Spain)

In this study, we explore how different mobility patterns influence the composition and structure of the transnational social support networks and how personal networks allow us to elicit insightful data of mobile individuals. Ninety-five mobile individuals were selected from four distinct communities based in Seville (Spain), namely: Erasmus students, Flamenco artists, musicians from the symphonic orchestra and partners of European Commission researchers. Data were collected through an electronic survey sent by email with multiple name generators and a structured face-to-face interview utilizing a network visualization tool, VennMaker. Two distinct methods, namely qualitative case studies and cluster analysis were used to characterize mobility types. Findings reveal a heterogeneous foreign population, in which different forms of mobility are reflected in the personal networks of mobile individuals. Respondents who were settled in the city were more likely to have networks in which social support was mainly derived by hosts and people in the host location and with whom they communicated predominantly through face-to-face communication. Those who were in the host location for a study exchange, knowing that return to the county of origin is imminent were more likely to have networks linked to the home location. They relied heavily on strong transnational ties in the home country using social media to sustain their relationship. Respondents with an itinerant mobility profile, also had networks dominated by strong transnational ties, however, such ties had a higher degree of geographical spread due to previous international mobility. Participants who had a high number of hosts in the network but low connection between the ties were more likely to be linked to a specific subculture in the host society. The integration in the host location follows a different pattern to other settled individuals, mainly because their connection in the city tends to be community specific.     

SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELS

Semiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more naturally handled within the graphical model architecture. Directed acyclic graphs, also known as Bayesian networks, play a prominent role. Graphical model-based Bayesian 'inference engines', such as bugs and vibes , facilitate fitting and inference. Underlying these are Markov chain Monte Carlo schemes and recent developments in variational approximation theory and methodology.     

Good health and the bridging of structural holes

Bridges that span structural holes are often explained in terms of the entrepreneurial personalities or rational motivations of brokers, or structural processes that lead to the intersection of social foci. I argue that the existence and use of bridges in interpersonal networks also depends on individuals’ health. Poor health may make it more difficult to withstand the pressures and to execute some of the common tasks associated with bridging (e.g., brokerage). I examine this possibility using egocentric network data on over 2500 older adults drawn from the recent National Social Life, Health, and Aging Project (NSHAP). Multivariate regression analyses show that both cognitive and functional health are significantly positively associated with bridging, net of sociodemographic and life-course controls. The relationship between functional (kinesthetic) health and bridging appears to be partially mediated by network composition, as older adults who have poorer functional health also tend to have networks that are richer in strong ties. Several potential mediation mechanisms are discussed. Cognitive function remains significantly associated with bridging net of network composition, suggesting that the inherent challenges of maintaining bridging positions may be more difficult to cope with for those who have cognitive impairments than for those who have functional impairments such as limited mobility. An alternative explanation is that cognitively impaired individuals have more difficulty recognizing (and thus strategically using) bridges in their networks. Theoretical implications and possibilities for future research are discussed.     

Clustering in weighted networks

In recent years, researchers have investigated a growing number of weighted networks where ties are differentiated according to their strength or capacity. Yet, most network measures do not take weights into consideration, and thus do not fully capture the richness of the information contained in the data. In this paper, we focus on a measure originally defined for unweighted networks: the global clustering coefficient. We propose a generalization of this coefficient that retains the information encoded in the weights of ties. We then undertake a comparative assessment by applying the standard and generalized coefficients to a number of network datasets.     

An intuitive risk factors search algorithm: usage of the Bayesian network technique in personalized medicine

The article focuses on the application of the Bayesian networks (BN) technique to problems of personalized medicine. The simple (intuitive) algorithm of BN optimization with respect to the number of nodes using naive network topology is developed. This algorithm allows to increase the BN prediction quality and to identify the most important variables of the network. The parallel program implementing the algorithm has demonstrated good scalability with an increase in the computational cores number, and it can be applied to the large patients database containing thousands of variables. This program is applied for the prediction for the unfavorable outcome of coronary artery disease (CAD) for patients who survived the acute coronary syndrome (ACS). As a result, the quality of the predictions of the investigated networks was significantly improved and the most important risk factors were detected. The significance of the tumor necrosis factor-alpha gene polymorphism for the prediction of the unfavorable outcome of CAD for patients survived after ACS was revealed for the first time.     

Networks for Welfare Provision: Getting a Grip on Processes of Social Exclusion by Evaluating Network Effectiveness

It has been repeatedly stated that the topic of network effectiveness has often been neglected. This has led to a situation of ‘network euphoria’ amongst practitioners and policymakers with regard to the creation of networks as a means to (re‐)organize welfare provision. Starting from a case study of networks for welfare provision in two Belgian cities, this article focuses on the effectiveness of service delivering networks at the client level, which is understood as the contribution of the network in improving the conditions of life of those being served or targeted by the network. Therefore, we focused on the collective efforts via these networks (e.g. by creating a night shelter or by conducting case consultations) to look after a population of homeless people who face multiple problems and are not able yet to benefit from welfare provision. Our findings revealed that these networks were able to realize a ‘collaborative advantage’ by filling in service gaps and by overcoming fragmentation of care. Nevertheless, these networks equally maintained criteria that restricted the accessibility or usefulness of welfare services provided to homeless people. In the concluding section, we highlight some of the factors that could help us to explain our findings and highlight the tension between the effectiveness of networks at the client level and the effectiveness at the organizational level.