• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.180-191
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• 2020

This study analyzes factors that affect average daily travel time budgets, using the Time Use Survey data from 1999 to 2014 in Seoul. We first developed multivariate regression models for travel time from each year, considering demographic and socio-economic variables as well as non-home activity time. The model results showed that household and personal characteristics and non-home activities significantly affect travel time, and their effects are different over time. In addition, we developed seemingly unrelated regression (SUR) models for time allocation for non-home activity and travel, considering their correlations, and explanatory variables were compared over time. Overall, demographic and socio-economic variables significantly affect travel time as well as non-home activity time.

• Knowledge Management Research
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• v.23 no.2
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• pp.211-228
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• 2022

As social media marketing becomes prevalent, it is necessary to understand the administrative role of managers in promoting user engagement. However, little is known about how community managers enhance user engagement in social media. In this research, we study how managers can boost online user participation, including clicking likes and writing comments. Using the SUR (Seemingly Unrelated Regression) model, we find out that the active participation of managers increases user engagement of both passive (likes) and active (comments) ones. In addition, we find that the number of emotional words included in posts has a positive effect on the passive engagement whereas it negatively affects the active engagement. Lastly, the congruency between posts and comments positively affects users' passive engagement. This study contributes to prior literature related to online community management and text analyses. Furthermore, our findings offer managerial insights for practitioners and social media managers to further facilitate user engagement.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.53-76
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• 2010

This paper attempts to estimate and compare environmental Kuznets curves (EKC) for$CO_2$ emissions of five regions constituting South Korea. For this, panel data of $CO_2$ emission for these regions are constucted for the period 1990 - 2007. Close inter-dependency among these five regions is considered by using a seemingly unrelated regression (SUR) model. In addition to real per-capita income, price index of energy sources and population dens ity are included as control variables. Results of estimates show the robust existence of EKC's in all these regions. EKC turning points of five regions range between 13.7 and 21.6 million Korean Won, showing a large variation. This difference among regions should be conisidered for the effective implementation of policies targeting the reduction of $CO_2$ emmission. In addition, the increase of energy price is found help reduce the $CO_2$ emmision while the rise of population density seems to lead to the increase of $CO_2$ emission.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.4
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• pp.62-72
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• 2015

Nowadays the issue of aging society has received considerable critical attention, especially in transportation planning and demand forecasting. This study identified the factors related to travel time budget for elderly by purpose using seemingly unrelated regression model (SUR model). The SUR model is suitable when error terms of each equation are assumed to be correlated across the equations in terms of travel time budget which is constant in 2 hours per day commonly. The results showed that elderly's travel time budget was affected by individual, household, urban facility and transportation service. The leisure travel comprised a large proportion of total travel time and had a positive relationship with elderly, sports, religious facilities. Moreover, the elderly who had low income or unemployed person had low frequency of social activity such as leisure, shopping and business. This study can provide a comprehensive implications of forecasting the future travel demand and analyzing the travel behavior.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.159-172
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• 2023

This study aims to empirically investigate the relative effects of business-to-business (vs. business-to-consumer) business model innovation (BMI) on innovation performance. The research examines the impact of three key components of BMI: 1. value creation, 2. value proposition, and 3. value capture, on innovation performance. The 2022 Entrepreneurship Survey data by the Korean Entrepreneurship Foundation was used to analyze 2,879 companies. An exploratory data analysis (EDA) including various categories such as industry, firm, CEO, and technology chracteristics was conducted to show the latest startup status in Korea. The results show that value creation of B2B (vs. B2C) firms has a more positive and significant impact on innovation performance. Whereas, value proposition of B2C (vs. B2B) firms was found to have a more positive and significant effect on innovation performance. Interestingly, value capture did not show any effects for either type of firms. Additionally, the study employed seemingly unrelated regression (SUR) analysis for robustness checks. These findings provide important insights about the relative effects of B2B-BMI (vs. B2C-BMI).

• KDI Journal of Economic Policy
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• v.44 no.4
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• pp.79-108
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• 2022

This study examines the impact of sentiment shock, which is defined as a stochastic innovation to the Housing Market Confidence Index (HMCI) that is orthogonal to past housing price changes, on aggregate housing price changes and housing price volatility. This paper documents empirical evidence that sentiment shock has a statistically significant relationship with Korea's aggregate housing price changes. Specifically, the key findings show that an increase in sentiment shock predicts a rise in the aggregate housing price and a drop in its volatility at the national level. For the Seoul Metropolitan Region (SMR), this study also suggests that sentiment shock is positively associated with one-month-ahead aggregate housing price changes, whereas an increase in sentiment volatility tends to increase housing price volatility as well. In addition, the out-of-sample forecasting exercises conducted here reveal that the prediction model endowed with sentiment shock and sentiment volatility outperforms other competing prediction models.

• Ocean policy research
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• v.34 no.2
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• pp.1-28
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• 2019

The purpose of this study is to analyze the substitution among production factors of Korean distant water longline fisheries in IATTC waters. In the analysis, the translog function which have one output variable of total cost and input variables of labor, fuel, fishing gear, and capital was established and it was transformed into simultaneous equations by each cost. Then, variables of equations were estimated by SUR (seemingly unrelated regression) model. Since distant water longline fisheries is a fishing type with high fuel usage, substitution of fuel with other factors was mainly analyzed. Results showed a substitute relation between fuel and labor as well as fuel and fishing gear, while a complementary relation between fuel and capital. In addition, it was analyzed that magnitude of fuel elasticity with other factors would be inelastic.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.194-202
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• 2006

Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.121-135
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• 2022

The purpose of this study is to explore the convergence sector of the spatial information industry based on the business transaction data of spatial information companies and to predict the market size of the industry using the Seemingly Unrelated Regression(SUR) model. The convergence part of spatial information industry, which cannot be identified in the Spatial Data Industry Survey, was analyzed by exploring keywords related to spatial information using the business DB of Korea Enterprise Data (2010-2019). The convergence of spatial information businesses mainly appeared in the business relationship between the value chain between Seoul and Gyeonggi Province. The convergence business has the largest sales in the value chain 2 (utilization, service) & 3 (convergence), and also the convergence in the value chain 1 (production, construction) & 2, 2 & 3 stages has doubled in 2019 compared to 2010. In 2019, the total sales of the spatial information industry based on the Statistical Korea were announced at about 8 trillion won, but in this study, the total sales of the spatial information industry were estimated at 28 trillion won considering convergence activities. Finally, when scenario 1 (0.38% population growth, 2020-2024) and 0.07% (2026-2030) were applied using the SUR model to predict the expected market size of the industry, sales decreased by -0.37% to 0.069% in 2025 and 2030 by respectively. When scenario 2 (average wage growth 1.2%) was applied during the same period, sales in the industry increased by 2.326% to 12.185%. In other words, the sales in the spatial information industry depends on Labor, Total Factor Productivity, and Capital Productivity so it is necessary to additional research on policy development and alternatives of enhancing each productivity.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.797-806
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• 2021

As the number of scaled-up ranches increased and agile responses to market changes became possible, decision-making by Hanwoo cattle farms also began to affect short-term shipments. Considering the changing environment of the Hanwoo supply market and the response speed of producers, it is necessary quickly to grasp the forecast ahead of time and to respond accordingly in an effort to stabilize supply and demand in the Hanwoo market. In this study, short-term forecasting model centered on the supply of Hanwoo was established. The analysis conducted here indicates that the slaughter of Hanwoo males increases by 0.248 as the number of beef cattle raised over 29 months of age in the previous month increases by one, and 0.764 Hanwoo females were slaughtered under average conditions for every Hanwoo male slaughtered. With regard to time, the slaughtering of Hanwoo was higher in January and August, which are months known for holiday food preparation activities for the New Year and Chuseok in Korea, respectively. Simulations indicated that errors were within 10% in all simulations performed through the Hanwoo supply model. Accordingly, it is considered that the estimation results from the supply model devised in this study are reliable and that the model has good structural stability.