Structure and evolution of global cluster networks: evidence from the aerospace industry

Turkina, Ekaterina; Assche, Ari Van; Kali, Raja

doi:10.1093/jeg/lbw020

Cited by 61 publications

(72 citation statements)

References 62 publications

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“…Do differences in the system segregation across a brain network impact the functional distinctions of its community's nodes? Observations in other domains of network science have demonstrated how alterations in community organization impact node function [74], and there is evidence consistent with this observation in human brain networks as well. Connector and non-connector nodes of the brain exhibit differing patterns and magnitudes of task-related activity in healthy young adults [75].…”

Section: Functional Specialization and Heterogeneity Of Processing Rolesmentioning

confidence: 62%

Segregated Systems of Human Brain Networks

Wig

2017

Trends in Cognitive Sciences

276

273

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The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior.

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Section: Functional Specialization and Heterogeneity Of Processing Rolesmentioning

confidence: 62%

Segregated Systems of Human Brain Networks

Wig

2017

Trends in Cognitive Sciences

276

273

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“…From the result of the study, a student who establishes relationship, professional contacts and networks with business person had higher probability (OR = 1.503) of being self-employed than students who did not make any professional contacts and networks because an entrepreneur acts to develop and maintain business contacts by establishing good working relationship and uses deliberate strategies to influence others. The ability to establish and maintain positive relationship is crucial to the success of the students' business venture (Turkina, Assche, and Kali, 2016). Hence, social relationship among formal inter-governmental organization networks to informal networks such as friendships and family ties affect decision-making and business performance.…”

Section: Parameter Estimation Of the Binary Logistic Modelmentioning

confidence: 99%

Modeling the impact of entrepreneurial attitude on self-employment intention among engineering students in Ethiopia

Ayalew

Zeleke

2018

J Innov Entrep

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Entrepreneurship is a worldwide phenomenon with economic growth across the globe that is rendered by the emergence of new and innovative business start-ups. Thus, the main objective of this research was to model the impact of entrepreneurial attitudes on self-employment intention among final year engineering students in Bahir Dar Institute of Technology, Debre Markos University and University of Gondar, Ethiopia, in 2017. To achieve the objective of the study, a survey research approach was employed. Questionnaire and interview were the instruments used, and stratified sampling technique was adopted to select 921 respondents from a population of 4327 final year undergraduate engineering students in 2016/2017 academic session. To analyze the data, descriptive statistics, chi-square test, principal component factor analysis, and binary logistic regression analysis were employed. The descriptive result revealed that about 57.4% of the students had an intention to be self-employed while 42.6% do not have an intention. The principal component factor analysis was used to reduce the set of variables by grouping variables with similar characteristics together and generates new variables (factors). These methods help the researchers to transform the number of correlated variables into a smaller number of uncorrelated variables. The logistic regression analysis was performed to investigate the effect of the predictor variables on self-employment intention status of students. The results showed that entrepreneurial education/training and entrepreneurial attitudes significantly predicts students' selfemployment intention. Accordingly, information and opportunity seeking, creativity and problem solving skills, achievement and instrumental readiness, self-confidence and self-esteem, goal setting, entrepreneurship education/training, business-owned family background, prior business experience with family, access to finance/capitals for startup, and networking and professional contacts were found to be significant predictors at 5% level of significance. These factors had positive relationship with self-employment intention at 5% level of significance. In the meanwhile, demographic factors (such as age, gender, and marital status) and socio-economic factors (such as parents' occupation, colleagues' business background, means of finance, discouragement by external environment, and clear future business idea) are not significant predictors at 5% level of significance. The study recommends that the government as well as the universities should design programs that facilitate entrepreneurship to change the mindset, attitude, and intention of those students who do not have knowhow about entrepreneurship as a future career.

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“…Except for the studies on firms' centrality in the network, most studies on firms' roles or positions have been descriptive. This is presumably due to the difficulty in obtaining data on the formal linkages between firms in the cluster [51].…”

Section: Literature Review and Analytical Frameworkmentioning

confidence: 99%

Industrial Clusters as Drivers of Sustainable Regional Economic Development? An Analysis of an Automotive Cluster from the Perspective of Firms’ Role

et al. 2020

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This paper examined the relationships among firms in a rapidly growing specialized industrial cluster—the Chery automotive cluster located in the Wuhu Economic and Technology Development in eastern China. After demonstrating how the Chery automotive cluster contributed to sustainable regional economic development, it focused on defining the roles that major firms play in the localized production network. Based on three attributes of the firm (network linkages, network position, and network power), the study identified a typology of firms’ role, including the dominant core, lead firms, gatekeepers, intermediaries, club of foreigners, peripherals, and loners. By revealing the heterogeneity of the firms and discussing the differing roles they play in the network, the paper made some policy recommendations to promote the sustainable development of the cluster, including providing policy supports to core firms, encouraging inter-firm networking and interaction, and diversifying the cohort of gatekeepers.

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Structure and evolution of global cluster networks: evidence from the aerospace industry

Cited by 61 publications

References 62 publications

Segregated Systems of Human Brain Networks

Segregated Systems of Human Brain Networks

Modeling the impact of entrepreneurial attitude on self-employment intention among engineering students in Ethiopia

Industrial Clusters as Drivers of Sustainable Regional Economic Development? An Analysis of an Automotive Cluster from the Perspective of Firms’ Role

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