scholarly journals Knowledge Exchange and Intermodal Logistics Network Integration: Social Network Embeddedness Perspective

2012 ◽  
Vol 10 (2) ◽  
pp. 3-19
Author(s):  
Eon-Seong Lee
MIS Quarterly ◽  
2017 ◽  
Vol 41 (4) ◽  
pp. 1035-1058 ◽  
Author(s):  
Ni Huang ◽  
◽  
Yili Hong ◽  
Gordon Burtch ◽  
◽  
...  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joelle Rodway ◽  
Stephen MacGregor ◽  
Alan Daly ◽  
Yi-Hwa Liou ◽  
Susan Yonezawa ◽  
...  

PurposeThe purpose of this paper is two-fold: (1) to offer a conceptual understanding of knowledge brokering from a sociometric point-of-view; and (2) to provide an empirical example of this conceptualization in an education context.Design/methodology/approachWe use social network theory and analysis tools to explore knowledge exchange patterns among a group of teachers, instructional coaches and administrators who are collectively seeking to build increased capacity for effective mathematics instruction. We propose the concept of network activity to measure direct and indirect knowledge brokerage through the use of degree and betweenness centrality measures. Further, we propose network utility—measured by tie multiplexity—as a second key component of effective knowledge brokering.FindingsOur findings suggest significant increases in both direct and indirect knowledge brokering activity across the network over time. Teachers, in particular, emerge as key knowledge brokers within this networked learning community. Importantly, there is also an increase in the number of resources exchanged through network relationships over time; the most active knowledge brokers in this social ecosystem are those individuals who are exchanging multiple forms of knowledge.Originality/valueThis study focuses on knowledge brokering as it presents itself in the relational patterns among educators within a social ecosystem. While it could be that formal organizational roles may encapsulate knowledge brokering across physical structures with an education system (e.g. between schools and central offices), these individuals are not necessarily the people who are most effectively brokering knowledge across actors within the broader social network.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Lizhao Yan ◽  
Yi Wen ◽  
Kok Lay Teo ◽  
Jian Liu ◽  
Fei Xu

In this paper, we construct a regional logistics model from a macroperspective. First, based on the gravity model, the index of logistics attraction between cities is established as the weight of the model, and hence the regional logistics weighted model is constructed. Next, we use the social network analysis method to analyze its structure and make specific recommendations for the construction of logistics networks. Finally, we analyze the model’s response to random attacks and deliberate attacks. From our study, it is found that when the failure nodes or edges reach a certain percentage, the regional logistics network will collapse on a large scale. Therefore, it is important to optimization the threshold of the regional logistics network. This clearly provides a new perspective for the study of the regional logistics networks.


2016 ◽  
Vol 55 (7) ◽  
pp. 1957-1969 ◽  
Author(s):  
Yi-Kuei Lin ◽  
Cheng-Fu Huang ◽  
Yi-Chieh Liao ◽  
Chih-Ching Yeh

2019 ◽  
Author(s):  
Meghan L. Meyer ◽  
Eleanor Collier

AbstractWe often interact with multiple people at a time and consider their various points-of-view to facilitate smooth social interaction. Yet, how our brains track multiple mental states at once, and whether skill in this domain links to navigating real-world social interactions, remains underspecified. To fill this gap, we developed a novel social working memory paradigm in which participants manage two- or four-people’s mental states in working memory, as well as control trials in which they alphabetize two- or four-people’s names in working memory. In Study 1, we found that the dorsomedial subsystem of the default network shows relative increases in activity with more mental states managed in working memory. In contrast, this subsystem shows relative decreases in activity with more non-mental state information (the number of names alphabetized) managed in working memory. In Study 2, only individual differences in managing mental states in working memory, specifically on trials that posed the greatest mental state load to working memory, correlated with social network integration. Collectively, these findings add further support to the hypothesis that social working memory relies on partially distinct brain systems and may be a key ingredient to success in a social world.


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