• The Journal of Information Systems
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• v.32 no.3
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• pp.19-39
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• 2023

Purpose This study aims to identify user experience factors that can enhance both metaverse utilization and satisfaction based on the honeycomb model. For this we presented two research questions: first, what are the experience factors of metaverse users? Second, do metaverse user experience factors impact satisfaction? Design/methodology/approach To address these questions, a mixed-methodology approach is employed, including text mining techniques to analyze online reviews and quantitative econometric analysis to reveal the relationship between user experience factors and satisfaction. A total of 69,880 reviews and ratings data were collected. Findings The analysis revealed eight metaverse user experience factors: entertainment, operability, virtual reality, immersion, economic activity, visual performance, avatar, and sociality, all of which were found to have a positive impact on user satisfaction.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.207-218
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• 2010

The purpose of the study is to predict the shipping business during the period of 2011 using the ARIMA-type models. This include the ARIMA and Intervention-ARIMA models. The multivariate cause-effect econometric model is not employed for not assuring a higher degree of forecasting accuracy than the univariate variable model. Such a cause-effect econometric model also fails in adjusting itself for the post-sample. This article introduces the four ARIMA models and six Intervention-ARIMA models. The monthly data cover the period January 2000 through October 2010. The out-of-sample forecasting performance is compared between the ARIMA-type models and the random walk model. Forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. The root mean squared percent errors of all the ARIMA-type models are somewhat higher than normally expected. Furthermore, the random walk model outperforms all the ARIMA-type models. This reveals that the BDI is just a random walk phenomenon and it's meaningless to predict the BDI using various econometric techniques. The ARIMA-type models show that the shipping market is expected to be bearish in 2011. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.79-87
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• 2011

This study was conducted to identify the relationship between urban heat island effect and forest, analyzing electricity consumption model and temperature change model. Electricity consumption model was adopted to clarify a role of forests in alleviating the heat island effect at the national scale, while temperature change model was adopted to clarify a role of forests in mitigating urban heat island effect on metropolis with using econometric analysis. The analysis results from both models clearly show a negative correlation between the urban forests within living areas and heat island effect. In particular, when urban forests within living area per person increases by $1m^2$, the average municipal electricity consumption decreases by 0.02MWh and the summer daytime temperature for metropolitan cities decreases by $1.15^{\circ}C$.

• ETRI Journal
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• v.7 no.3
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• pp.35-41
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• 1985

The objective of this study is to estimate the price elasticity of demand for telephone use in Korea. This paper provides a comprehensive review of the existing empirical study and establishes the econometric demand estimation model applicable to Korean telephone service. By this model, the price elasticities of demand in local and toll uses are estimated and their implications are discussed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.139-147
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• 2020

This paper aims to explore the relationship between the quality of the audit and the level of stock return co-movement in the context of the Vietnamese emerging market. The empirical study is designed based on the quatitative method and deductive approach. The panel dataset includes 256 listed firms from different industries,with 1115 firm-year observations on Ho Chi Minh City Stock Exchange for the period from 2014 to 2018. In the research, we built the econometric regression model, using stock return synchronicity and audit quality as the dependent and independent variable, respectively. Some control variables are also added to the econometric regression models as they are well-documented in prior research to have an effect on stock price synchronicity. To improve the accuracy of the regression coefficients, beside the Ordinary Least Squares, we employ the Random Effects Model and the Fixed Effects Model for better statistical analysis of panel data set. The results show that the quality of the audit is positively correlated to stock price synchronicity. This finding suggests that stock returns of companies with higher quality of the audit are more synchronous with the market. Results for other control variables also support our reasoning for the main findings.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.491-493
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• 2003

Load foretasting model used generally such as times series and econometric regression model often doesn't reflect the load characteristics of small remote islands. Therefore, in this paper load demand forecast is peformed using EGARCH-M non-linear forecasting model.

• The Journal of Fisheries Business Administration
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• v.29 no.2
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• pp.97-110
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• 1998

This paper tries to estimate Korea's import demand function for fisheries using cointegration analysis. The estimation function consists of one dependent variable-import quantity of fisheries(FTIW) and two independent variables-relative price(RP) between importable and domestic products and real income(GDP). As it has been empirically found out that almost all of time series of macro-variables such as GDP, price index are nonstationary, existing studies which ignore this fact need to be reexamined. Conventional econometric method can not analyze nonstationary time series in level. To perform the analysis, time series should be differenciated until stationarity is guaranteed. Unfortunately, the difference method removes the long run element of data, and so leads to difficulties of interpretation. But according to new developed econometric theory, cointegration approach could solve these problems. Therefore this paper proceeds the estimation on the basis of cointegration analysis, because the quartly variables from 1988 to 1997 used in the model is found out to be nonstationary. The estimation results show that all of the variables are statistically significant. Therefore Korea's import demand for fisheries has been strongly affected by the variation of real income and the relative price.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.95-99
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• 1985

In this paper, Bayesian analysiss of the general linear econometric model is carried out by using a multinomal prior for the vector of unknown regression coefficents and a half-normal prior for the standard deviation of the disturbances.

• Asian Journal of Innovation and Policy
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• v.6 no.3
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• pp.313-331
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• 2017

This paper exhibits the concept of Triple Helix model to explain and link university-industry-government (Triple Helix) connections to national innovation systems theory. The driver of this paper is to test the dynamics of Triple Helix concept under national innovation system in the Association of South East Asian Countries (ASEAN)-5 economies. Panel econometric analysis with cross-sectional dependence (CD) test is applied to investigate the relationship amongst Triple Helix variables. The empirical analysis employs innovation indicators of five founding ASEAN countries namely Malaysia, Indonesia, Singapore, the Philippines and Thailand for the period of 2000-2015 from an existing WDI and WCY database. Econometric results support the two research questions of this study; firstly, there is a significant relationship between innovation outcome and its key drivers under Triple Helix context of National Innovation System in ASEAN-5 economies; secondly, the extent of the relationship among government R&D expenditure with high-tech productions are positive and significant while new ideas coming from universities as scientific publications and high-tech production have positive relationship but not significant yet in ASEAN-5 countries. Overall labor productivity is positive and significant with innovation outcomes in ASEAN-5.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.