scholarly journals Japanese Network Economy-ERGM analysis of the “Big Six”

2021 ◽  
Vol 4 (2) ◽  
pp. p44
Author(s):  
Marton Gosztonyi
Keyword(s):  
Graph Model ◽  
Japanese Economy ◽  
Exponential Random Graph Model ◽  
Random Graph Model ◽  
Corporate Groups ◽  
Model Method ◽  
Exponential Random Graph ◽  
Economic Practice ◽  
Big Six

The paper analyses the network of relationships between large companies that defines the Japaneseeconomy using ERGM (Exponential Random Graph Model) method. The Japanese economy, becauseof the presence of keiretsu groups and other corporate groups, is an excellent example of what canhappen to a country’s economy if large corporations and financial institutions in the market operate ina closely interconnected, highly centralized and dependent network. This is an important issue, becausethis economic practice is happening globally right now. Therefore, the interpretation of the Japanesenetwork and the analysis of its economic performance also reflect the long-term negative and positiveeffects of this trend.

scholarly journals Symptom and Age Homophilies in SARS-CoV-2 Transmission Networks during the Early Phase of the Pandemic in Japan

Biology ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 499
Author(s):  
Ali Andalibi ◽  
Naoru Koizumi ◽  
Meng-Hao Li ◽  
Abu Bakkar Siddique
Keyword(s):  
Early Stage ◽  
Graph Model ◽  
Initial Response ◽  
Contact Tracing ◽  
Pcr Analysis ◽  
Exponential Random Graph Model ◽  
Transmission Networks ◽  
Random Graph Model ◽  
Healthcare Settings ◽  
Exponential Random Graph

Kanagawa and Hokkaido were affected by COVID-19 in the early stage of the pandemic. Japan’s initial response included contact tracing and PCR analysis on anyone who was suspected of having been exposed to SARS-CoV-2. In this retrospective study, we analyzed publicly available COVID-19 registry data from Kanagawa and Hokkaido (n = 4392). Exponential random graph model (ERGM) network analysis was performed to examine demographic and symptomological homophilies. Age, symptomatic, and asymptomatic status homophilies were seen in both prefectures. Symptom homophilies suggest that nuanced genetic differences in the virus may affect its epithelial cell type range and can result in the diversity of symptoms seen in individuals infected by SARS-CoV-2. Environmental variables such as temperature and humidity may also play a role in the overall pathogenesis of the virus. A higher level of asymptomatic transmission was observed in Kanagawa. Moreover, patients who contracted the virus through secondary or tertiary contacts were shown to be asymptomatic more frequently than those who contracted it from primary cases. Additionally, most of the transmissions stopped at the primary and secondary levels. As expected, significant viral transmission was seen in healthcare settings.

scholarly journals The drivers of regulatory networking: policy learning between homophily and convergence

2018 ◽  
Vol 39 (3) ◽  
pp. 443-464 ◽  
Author(s):  
Francesca P. Vantaggiato
Keyword(s):  
Regulatory Networks ◽  
Graph Model ◽  
Exponential Random Graph Model ◽  
Random Graph Model ◽  
Market Structures ◽  
Exponential Random Graph ◽  
Policy Frameworks ◽  
Regulatory Coordination ◽  
Regular Network ◽  
The Eu

AbstractThe literature on transnational regulatory networks identified interdependence as their main rationale, downplaying domestic factors. Typically, relevant contributions use the word “network” only metaphorically. Yet, informal ties between regulators constitute networked structures of collaboration, which can be measured and explained. Regulators choose their frequent, regular network partners. What explains those choices? This article develops an Exponential Random Graph Model of the network of European national energy regulators to identify the drivers of informal regulatory networking. The results show that regulators tend to network with peers who regulate similarly organised market structures. Geography and European policy frameworks also play a role. Overall, the British regulator is significantly more active and influential than its peers, and a divide emerges between regulators from EU-15 and others. Therefore, formal frameworks of cooperation (i.e. a European Agency) were probably necessary to foster regulatory coordination across the EU.

scholarly journals A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model

2019 ◽  
Vol 7 (1) ◽  
pp. 20-51 ◽  
Author(s):  
Philip Leifeld ◽  
Skyler J. Cranmer
Keyword(s):  
Network Analysis ◽  
Random Graph ◽  
Graph Model ◽  
Real Data ◽  
The Other ◽  
Exponential Random Graph Model ◽  
Empirical Comparison ◽  
Random Graph Model ◽  
Exponential Random Graph ◽  
Longitudinal Network Analysis

AbstractThe temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several theoretical differences the analyst might consider and find that with some specifications, the two models behave very similarly, while each model out-predicts the other one the more the specific assumptions of the respective model are met.

Data-Driven Dynamic Network Modeling for Analyzing the Evolution of Product Competitions

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Jian Xie ◽  
Youyi Bi ◽  
Zhenghui Sha ◽  
Mingxian Wang ◽  
Yan Fu ◽  
...  
Keyword(s):  
Survey Data ◽  
Random Graph ◽  
Network Modeling ◽  
Dynamic Network ◽  
Graph Model ◽  
Exponential Random Graph Model ◽  
Random Graph Model ◽  
Exponential Random Graph ◽  
Dynamic Network Modeling ◽  
The Impact

Abstract Understanding the impact of engineering design on product competitions is imperative for product designers to better address customer needs and develop more competitive products. In this paper, we propose a dynamic network-based approach for modeling and analyzing the evolution of product competitions using multi-year buyer survey data. The product co-consideration network, formed based on the likelihood of two products being co-considered from survey data, is treated as a proxy of products’ competition relations in a market. The separate temporal exponential random graph model (STERGM) is employed as the dynamic network modeling technique to model the evolution of network as two separate processes: link formation and link dissolution. We use China’s automotive market as a case study to illustrate the implementation of the proposed approach and the benefits of dynamic network models compared to the static network modeling approach based on an exponential random graph model (ERGM). The results show that since STERGM takes preexisting competition relations into account, it provides a pathway to gain insights into why a product may maintain or lose its competitiveness over time. These driving factors include both product attributes (e.g., fuel consumption) as well as current market structures (e.g., the centralization effect). With the proposed dynamic network-based approach, the insights gained from this paper can help designers better interpret the temporal changes of product competition relations to support product design decisions.

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