• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.6
• /
• pp.87-95
• /
• 1999

We propose a simulation model of 3-dimensional MPEG data over Asynchronous transfer Mode(ATM) networks. The model is based on a slice level and is named to Projected Vector Autoregressive(PVAR) model. The PVAR model is modeled using the Autoregressive(AR) model in order to meet the autocorrelation condition and fit the histogram, and maps real data by a projection function. For the projection function, we use the Cumulative Distribution Probability Function (CDPF), and the procedure is performed at each slice level. Our proposed model shows good performance in meeting the autocorrelation condition and fitting the histogram, and is found important in analyzing the performance of networks. In addiotion, we apply a smoothing method by which a periodic mean value. In general. the Quality of Service(QoS) depends on the Cell Loss Rate(CLR), which is related to the cell loss and a maximum delay in a buffer. Hence the proposed smoothing method can be used to improve the QoS.

• Journal of Distribution Science
• /
• v.18 no.3
• /
• pp.25-36
• /
• 2020

Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

• Asia-Pacific Journal of Business
• /
• v.15 no.1
• /
• pp.225-237
• /
• 2024

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.1
• /
• pp.5-13
• /
• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.

• Journal of Korea Trade
• /
• v.27 no.3
• /
• pp.103-118
• /
• 2023

Purpose - This study aims to examine the dynamic relationship between the variables impacted by the Regional Comprehensive Economic Partnership (RCEP) and the level of intra-industry trade among member states, with the ultimate objective of deducing the short- and long-term effects of RCEP on trade. Design/methodology - This study focuses on tariffs, GDP growth rates, and the proportion of regional FDI to total FDI as research variables, and employs a panel vector autoregression model and GMM-style estimator to investigate the dynamic relationship between RCEP and intra-industry trade among member countries. Findings - The study finds that the level of intra-industry trade between member states is positively impacted by both tariffs and intra-regional FDI. The impulse response graph shows that tariffs and FDI within the region can promote intra-industry trade among member countries, with a quick response. However, the contribution rates of tariffs and intra-regional FDI are not particularly high at approximately 1.5% and 1.4%, respectively. In contrast, the contribution rate of GDP growth can reach around 8.5%. This implies that the influence of economic growth rate on intra-regional trade in industries is not only long-term but also more powerful than that of tariffs and intra-regional FDI. Originality/value - The originality of this study lies in providing a new approach to investigating the potential impact of RCEP while avoiding the limitations associated with the GTAP model. Additionally, this study addresses existing gaps within the research, further contributing to the research merit of the study.