• Title/Summary/Keyword: ERGM(Exponential Random Graph Model)

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A Study on the ERGM on Innopolis Start-ups Networks: Focusing on Daedeok Innopolis (연구소기업 네트워크의 ERGM 분석 연구: 대덕연구개발특구를 중심으로)

  • Jang-Won Koo;Jae-Bin Lim
    • Industry Promotion Research
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    • v.9 no.2
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    • pp.45-58
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    • 2024
  • This study modelled the social network structure characteristics between Innopolis Start-ups located in Daejeon and Innopolis Start-ups' customers scattered across the country as a tendency of regional clustering among homogeneous technologies, and the observed values were included within the 95% confidence interval of the ERGM(Exponential Random Graph Model) analysis model. If both the research institute and the customer company are located in Yuseong-gu, Daejeon, the probability of being connected is about 13 times higher than if they are located in other administrative districts, and there is a strong tendency of connection between firms with the same technology with a negative value of assortment and homogeneity (0.1904), especially among the six technology sectors, with a P value of 0.035. There was a negative value (-0.0035) among firms not located in Yuseong-gu, with less clustering tendency. This confirms that Yuseong-gu, Daejeon, where the Daedeok Innopolis is located, is forming the centre of an innovation cluster.

Statistical ERGM analysis for consulting company network data (직장 네트워크 데이터에 대한 통계적 ERGM 분석)

  • Park, Yejin;Um, Jungmin;Hong, Subeen;Han, Yujin;Kim, Jaehee
    • The Korean Journal of Applied Statistics
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    • v.35 no.4
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    • pp.527-541
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    • 2022
  • A company is a social group of many individuals that work together to obtain better results, and it is an organization that pursues common goals such as profit. As a result, forming networks among members, as well as individual communication abilities, is critical. The purpose of this research was to determine what factors influence the creation of employee advice relationships. Using the ERGM(Exponential Random Graph Model) approach, we looked at the network data of 44 individuals from consulting firms with offices in the United States and Europe. The significance of structural network factors like connectivity was first discovered. Second, the gender factor had the most significant main influence on the likelihood of adopting each other's advice. Third, geographical homogeneity resulted in higher link probabilities than major impacts of gender. This research looked at ways to make a company's network more efficient and active.

Analysis of promising countries for export using parametric and non-parametric methods based on ERGM: Focusing on the case of information communication and home appliance industries (ERGM 기반의 모수적 및 비모수적 방법을 활용한 수출 유망국가 분석: 정보통신 및 가전 산업 사례를 중심으로)

  • Jun, Seung-pyo;Seo, Jinny;Yoo, Jae-Young
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.175-196
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    • 2022
  • Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.

Cosponsorship networks in the 17th National Assembly of Republic of Korea (17대 국회의 공동법안발의에 관한 네트워크 분석)

  • Park, Chanmoo;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.30 no.3
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    • pp.403-415
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    • 2017
  • In this paper, we investigate cosponsorship networks found in the 17th National Assembly of Republic of Korea. New legislation should be sponsored by at least 10 legislators including one main sponsor. Cosponsorship networks can be constructed, using directional links from cosponsors of legislation to its main sponsor; subsequently, these networks indicate the social relationships among the legislators. We apply Exponential Random Graph Model (ERGM) for valued networks to capture structural properties and the covariate effects of networks. We find the effect of the same party has the greatest influence on the composition of the network. Mutuality also plays an important role in the cosponsorship network; in addition, the effect of the number of elections won by a legislator has a small but significant influence.