• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.279-293
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• 2023

This study investigates network effects to measure how strongly the early adopters affect the brand choice of the potential consumer. By using the Gumbel-Hougaard (GH) copula, this study checks the magnitude of network effects varied from country to country. To consider consumer heterogeneity and network effects in the growth market, this study proposes the multi-brand Gamma/Shifted-Gompertz (m-G/SG) model based on the GH copula. Out of eighteen Western European cellular phone market data and South Korea smartphone data sets, the m-G/SG model provides an improvement in the estimation accuracy over the Libai, Muller, and Peres model. The results show that network effects enhance (i) the polarization of brand choice probabilities as time elapses; (ii) the dominance of the more preferred and the earlier entered brand; and (iii) the deceleration of category-level diffusion. Potential followers can analyze their relationship with earlier entrants through the m-G/SG model and also establish an optimal market entry strategy.

• Asia pacific journal of information systems
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• 제16권3호
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• pp.229-241
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• 2006

In this paper, we develop three stage non-cooperative game models to analyze the alliance strategies of companies in internet markets where network effects are present. Regardless of its market share, an internet company's strategic alliance appears to be a superior strategy. The analysis also identifies profit sharing structures in the internet market where a smaller and unknown company is enforced to split its own profits with a larger and well-known company. It is shown that the amount of profit sharing grows as the size of network effects becomes larger.

• 산업경영시스템학회지
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• 제46권4호
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• pp.53-62
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• 2023

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1474-1479
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• 2004

In this paper, the design of the network system using the CAN and the analysis of effects of time delay in the system are presented. A conventional implementation technique induces many problems because of the amount and complexity of wiring and maintenance problems. The network system reduces these problems, but it cause another problem; time delay. Time delay in a sampling time does not have much effects on the system, but time delay over the sampling time changes the control frequency and ended up makes the system unstable. It is verified that time delay between each parts has different effects on the entire system. The results from this paper will be a base for studying algorithms to reduce effects of time delay in the system using the CAN.

• ETRI Journal
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• 제39권6호
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• pp.841-850
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• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.

• Journal of Ginseng Research
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• 제48권4호
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• pp.373-383
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• 2024

Background: Network pharmacology has emerged as a powerful tool to understand the therapeutic effects and mechanisms of natural products. However, there is a lack of comprehensive evaluations of network-based approaches for natural products on identifying therapeutic effects and key mechanisms. Purpose: We systematically explore the capabilities of network-based approaches on natural products, using Panax ginseng as a case study. P. ginseng is a widely used herb with a variety of therapeutic benefits, but its active ingredients and mechanisms of action on chronic diseases are not yet fully understood. Methods: Our study compiled and constructed a network focusing on P. ginseng by collecting and integrating data on ingredients, protein targets, and known indications. We then evaluated the performance of different network-based methods for summarizing known and unknown disease associations. The predicted results were validated in the hepatic stellate cell model. Results: We find that our multiscale interaction-based approach achieved an AUROC of 0.697 and an AUPR of 0.026, which outperforms other network-based approaches. As a case study, we further tested the ability of multiscale interactome-based approaches to identify active ingredients and their plausible mechanisms for breast cancer and liver cirrhosis. We also validated the beneficial effects of unreported and top-predicted ingredients, in cases of liver cirrhosis and gastrointestinal neoplasms. Conclusion: our study provides a promising framework to systematically explore the therapeutic effects and key mechanisms of natural products, and highlights the potential of network-based approaches in natural product research.

• 한국정보시스템학회지:정보시스템연구
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• 제24권4호
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• pp.21-42
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• 2015

Purpose The high-technology market shows characteristics of a highly interdependent network market in both supply-side and demand-side, compared to other markets. Particularly, for convergence products, connectivity with related elements, as well as characteristics of innovation itself, is relatively important to the extent that they combine functions provided by several devices into a single device. Therefore, this study aims to identify whether network externality exists in value and adoption of a convergence product and discover a source of network externality, if any. Design/methodology/approach: Through a preceding research analysis and a literature review, 'social influence' and 'network size' have been drawn as direct network elements. On the other hand, general (comprehensive) concept compatibilities including 'intra-technology compatibility', 'inter-technology compatibility' and 'complementary-technology compatibility' are regarded as indirect network elements. Findings: Major findings are as followed;- First, it is shown that the factors influencing on perceived value of a convergence products are 'social influence' and 'network size' as the direct network elements and 'complementary-compatibility' among indirect network elements. Second, it is also found that 'intra-technology compatibility', 'inter-technology compatibility', 'complementary-compatibility' and 'perceived value' have significant effects on adoption of a convergence product. Particularly, it is known that 'complementary-compatibility' is an important source of network externality as it plays a decisive role in value judgment and has significant effects on perceived value. It is worthwhile to notice that this study comprehensively explains effects of network on high-tech products by structuring comparability as a multi-dimensional concept, as well as direct network elements.

• International journal of advanced smart convergence
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• 제6권2호
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• pp.34-50
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• 2017

This study delved into the effects of labor union members' social media utilization for the formation of labor union social capital. Specifically, this study aimed to identify the effects of labor union-related social media use and participation on the labor union's social capital formation through quantitative and qualitative research. It set up trust, network, and participation as social capital components and as dependent variables. Network, in particular, was divided into bonding and bridging aspect. There is the correlation between labor union-related social media use and the formation of labor union social capital. As participation in the group type social media operated by a labor union becomes more active, evaluation on labor union social capital throughout trust, network, and participation is higher. Especially, the correlation between bonding network and bridging network was high. This proves that a labor union's bond enhancement does not result in the labor union's selfishness, but it can build a cooperative system with an external network.

• 유통과학연구
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• 제20권10호
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• pp.51-60
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• 2022

Purpose: The aim of this research is to study 1) the effects of internal factors (technological capability and entrepreneurial orientation) that affect Thailand's hotel business network capability. 2) the effects of external factors (government policy and trust relationship) that affect Thailand's hotel business network capability. 3) the impact of network capability on the firm performance. 4) the moderating effect of absorptive capacity between network capability and firm performance. Research design, data and methodology: The test model collected data from a mail survey of 164 hotel businesses in Thailand. The correlation and multiple regression were adopted to analyze and test the proposed hypotheses. Results: Interestingly, technological capability, entrepreneurship orientation, and trust relationship have a direct impact on network capability. However, network capability still does not have a significant relationship with firm performance in all dimensions. Surprisingly, the absorptive capacity does not have a moderating effect on the relationship of network capability on firm performance of hotel businesses in Thailand. Conclusions: This research found that the hotel business should focus on analyzing the external and internal environment as it affects network building, which will guide the creation of strategies for further increasing hotel distribution channels and competitive advantage.

• 대한본초학회지
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• 제38권1호
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• pp.45-53
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• 2023

Objectives : Network pharmacology-based research is one of useful tool to predict the possible efficacy and molecular mechanisms of natural materials with multi compounds-multi targeting effects. In this study, we investigated the functional underlying mechanisms of Astragalus membranaceus Bunge (AM) on its anti-obesity effects using a network pharmacology analysis. Methods : The constituents of AM were collected from public databases and its target genes were gathered from PubChem database. The target genes of AM were compared with the gene set of obesity to find the correlation. Then, the network was constructed by Cytoscape 3.9.1. and functional enrichment analysis was conducted to predict the most relevant pathway of AM. Results : The result showed that AM network contained the 707 nodes and 6867 edges, and 525 intersecting genes were exhibited between AM and obesity gene set, indicating that high correlation with the effects of AM on obesity. Based on GO biological process and KEGG Pathway, 'Response to lipid', 'Cellular response to lipid', 'Lipid metabolic process', 'Regulation of chemokine production', 'Regulation of lipase activity', 'Chemokine signaling pathway', 'Regulation of lipolysis in adipocytes' and 'PPAR signaling pathway' were predicted as functional pathways of AM on obesity. Conclusions : AM showed high relevance with the lipid metabolism related with the chemokine production and lipolysis pathways. This study could be a basis that AM has promising effects on obesity via network pharmacology analysis.