• Journal of Distribution Science
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• v.14 no.4
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• pp.47-53
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• 2016

Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.445-450
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• 2001

The paper investigates the relationships between dynamic elastic modulus and static elastic modulus or compressive strength according to curing temperature, aging, and cement type. Based on this investigation, the new model equations are proposed. Impact echo method estimates the resonant frequency of specimens and uniaxial compression test measures the static elastic modulus and compressive strength. Type I and V cement concretes, which have the water-cement ratios of 0.40 and 0.50, are cured under the isothermal curing temperature of 10, 23, and 50 $^{\circ}C$. Cement type and aging have no large influence on the relationship between dynamic and static elastic modulus, but the ratio of dynamic and static elastic modulus comes close to 1 as temperature increases. Initial chord elastic modulus, which is calculated at lower strain level of stress-strain curve, has the similar value to dynamic elastic modulus. The relationship between dynamic elastic modulus and compressive strength has the same tendency as the relationship between dynamic and static elastic modulus. The proposed relationship equations between dynamic elastic modulus and static elastic modulus or compressive strength properly estimates the variation of relationships according to cement type, temperature, and aging.

• Steel and Composite Structures
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• v.9 no.5
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• pp.473-497
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• 2009

For the spatially coupled free vibration analysis of composite box beams resting on elastic foundation under the axial force, the exact solutions are presented by using the power series method based on the homogeneous form of simultaneous ordinary differential equations. The general vibrational theory for the composite box beam with arbitrary lamination is developed by introducing Vlasov°Øs assumption. Next, the equations of motion and force-displacement relationships are derived from the energy principle and explicit expressions for displacement parameters are presented based on power series expansions of displacement components. Finally, the dynamic stiffness matrix is calculated using force-displacement relationships. In addition, the finite element model based on the classical Hermitian interpolation polynomial is presented. To show the performances of the proposed dynamic stiffness matrix of composite box beam, the numerical solutions are presented and compared with the finite element solutions using the Hermitian beam elements and the results from other researchers. Particularly, the effects of the fiber orientation, the axial force, the elastic foundation, and the boundary condition on the vibrational behavior of composite box beam are investigated parametrically. Also the emphasis is given in showing the phenomenon of vibration mode change.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.504-513
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• 2013

Communication in delay tolerant networks (DTNs) relies on message transport by mobile nodes, and a correct understanding of the node mobility characteristics is therefore crucial to the design of an efficient DTN routing protocol. However, previous work has mainly focused on uncovering all behaviors of node movement, which is not conducive to accurately detecting the specific movement characteristics of a different node. In this paper, we seek to address this problem based on a consideration of social relationships. We first consider social ties from both static and dynamic perspectives. For a static perspective, in addition to certain accidental events, social relations are considered for a long time granularity and tend to be stable over time. For a dynamic perspective, social relations are analyzed in a relatively short time granularity and are likely to change over time. Based on these perspectives, we adopted different efficient approaches to dividing node pairs into two classes, i.e., familiar and unfamiliar pairs. A threshold approach is used for static social ties whereas a density-based aggregation method is used for dynamic social relationships. Extensive experimental results show that both familiar and unfamiliar node pairs have the same inter-contact time distribution, which closely follows a power-law decay up to a certain point, beyond which it begins to exponentially decay. The results also demonstrate that the inter-contact time distribution of familiar pairs decays faster than that of unfamiliar pairs, whether from a static or dynamic perspective. In addition, we also analyze the reason for the difference between the inter-contact time distributions of both unfamiliar and familiar pairs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.192-206
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• 2021

The pharmaceutical industry is an industry that provides medicines related to the health and life of the people. The pharmaceutical industry is a traditional regulation industry with the characteristics of R&D(Research and Development), purchasing, manufacturing, distribution and consumption under strict government management. Until now, pharmaceutical companies have continued to make efforts to maintain competitiveness through patent management, new product development, and marketing. However, industries are rapidly changing, including rising costs for developing new products and expanding generic markets. As these changes and uncertainties in the management environment increase, efforts are required to improve the competitiveness of the pharmaceutical industry from a new perspective. In this study, we intend to examine the impact of SCM(Supply Chain Management) dynamic capability of pharmaceutical companies on corporate performance through partnerships to respond to market changes and uncertainties. It was determined that the agility, visibility and flexibility that constitutes the SCM dynamic capabilities would affect the performance of pharmaceutical companies. In this study, the importance of SCM dynamic capabilities and cooperative relationships was identified through surveys by SCM managers of pharmaceutical companies. Consequently, in the pharmaceutical industry, which is a regulatory industry, we have identified that SCM dynamic capabilities and cooperative relationships with partner companies have a significant impact on corporate performance.

• The Journal of Economics, Marketing and Management
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• v.12 no.4
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• pp.51-64
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• 2024

Recent studies have introduced that digital transformation positively impacts firm performance. However, research on the relationship between organizational capabilities or attitudes as antecedents or situational variables for successfully driving digital transformation remains limited. Therefore, this study aims to systematically analyze how dynamic digital capabilities and the mutual relationships between organizational members' digital acceptance influence firm performance throughout the process of driving and achieving digital transformation. Research design, data, and methodology: This study developed the concepts and measurement items for each variable based on prior research. A survey was conducted with 258 companies participating in mini clusters within industrial complexes across the county. The data was analyzed using a structural equation model with the AMOS software package. Results: Based on existing literature, hypotheses were formulated regarding the causal relationships among variables, and analysis was conducted. The results indicate that digital transformation and employees' technological acceptance play a mediating role in the relationship between dynamic digital capabilities and firm performance. Specifically, the organization's dynamic digital capabilities enhance both digital transformation and technological acceptance. Moreover, digital transformation leads to higher firm performance when technological acceptance is high. Conclusions: This study has shown the importance of enhancing dynamic digital capabilities as a prerequisite for driving digital transformation and highlighted the significance of organizational members' perceptions and attitudes toward information technology. Particularly, through detailed causal analysis among the specific items of each variable, insights were gained for both academic and practical applications.

• Water for future
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• v.29 no.2
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• pp.143-151
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• 1996

The dynamic responses in the subsurface outflow, surface saturation area, soil moisture storage are established by numerical experiments with Richards equation. In addition to this, the dynamical relationship between surface saturation area and subsurface outflow, and between surface saturation area and soil moisture storage are also determined by varying the hillslope shape, soil type, and boundary condition. The simulation results indicate that the dynamical relationships between surface saturation area and subsurface outflow, and between surface saturation area and soil moisture storage are approximated by the steadystate relationships. And the dynamic responses of subsurface outflow and surface saturation area are characterized by the double peaks although the rainfall pattern is asimple pulse input. As a result of numerical simulation, the physical mechanism for the occurrence of the double peaks is explained using the concept of variable source area.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.203-215
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• 2022

Bayesian Networks are multivariate probabilistic factor graphs that are used to assess underlying factor relationships. From January 2005 to December 2018, the study examines how Dynamic Bayesian Networks can be utilized to estimate portfolio risk and return as well as determine inter-factor relationships among reversal profit-generating components in Pakistan's emerging market (PSX). The goal of this article is to uncover the factors that cause reversal profits in the Pakistani stock market. In visual form, Bayesian networks can generate causal and inferential probabilistic relationships. Investors might update their stock return values in the network simultaneously with fresh market information, resulting in a dynamic shift in portfolio risk distribution across the networks. The findings show that investments in low net profit margin, low investment, and high volatility-based designed portfolios yield the biggest dynamical reversal profits. The main triggering aspects related to generation reversal profits in the Pakistan market, in the long run, are net profit margin, market risk premium, investment, size, and volatility factor. Investors should invest in and build portfolios with small companies that have a low price-to-earnings ratio, small earnings per share, and minimal volatility, according to the most likely explanation.

• Transactions of Materials Processing
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• v.9 no.1
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• pp.72-79
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• 2000

Dynamic recrystallization (DRX), which may occur during hot deformation, is important for the microsturctural evolution of 304 stainless steel. Especially, the current interest in modelling hot rolling demands quantitative relationships among the thermomechanical process variables, such as strain, temperature, strain rate, and etc. Thus, this paper individually presents the relationships for flow stress and volume fraction of DRX as a function of processing variables using torsion tests. The hot torsion tests of 304 stainless steel were performed at the temperature range of 900~110$0^{\circ}C$ and the strain rate range of 5x10-2~5s-1 to study the high temperature softening behavior. For the exact prediction of flow stress, the equation was divided into two regions, the work hardening (WH) and dynamic recovery (DRV) region and the DRX region. Especially, The flow stress of DRX region could be expressed by using the volume fraction of DRX (XDRX). Since XDRX was consisted of the critical strain($\varepsilon$c) for initiation of dynamic recrystallization (DRX) and the strain for maximum softening rate ($\varepsilon$*), that were related with the evolution of microstructure. The calculated results predicted the flow stress and the microstructure of the alloy at any deformation conditions well.