• Journal of the Korean association of regional geographers
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• v.11 no.1
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• pp.54-70
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• 2005

The purpose of this study is to clarify motives, itinerary and general patterns associated with the traveling of the upper class in the Chosun Dynasty based on twenty travel accounts of Mt. Chungryang. In addition, previous studies were referred to in order to compare these trips to Mt. Chungryang with those which were undertaken to Mt. Kumgang so as to identify the unique characteristics of those involved with the trips to Mt. Chungryang and of these trips in themselves. Through this process, unique characteristics, such as the travelers' academic backgrounds and place of origin, as well as how these travelers' relationship with their teachers influenced the motivation for these trips were uncovered, as were the processes through which travel schedules and companions were selected. Moreover, the researcher identified similarities and differences between the travel of Mt. Chungryang and Mt. Kumgang in terms of the travelers' motivation for the trip, the transportation methods they employed, and the kind of accommodation they sought. Moreover while similarities were also uncovered with regards to the travel practices of the literati class during this time, differences emerged in terms of their travel dates and schedules.

• Journal of the Korean Society for Railway
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• v.14 no.5
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• pp.470-476
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• 2011

This study proposed the intervention ARIMA model as a way to forecast the KTX passenger demand. The second phase of the Gyeongbu high-speed rail project and the financial crisis in 2008 were analyzed in order to determine the effect of time series on the opening of a new line and economic impact. As a result, the financial crisis showed that there is no statistically significant impact, but the second phase of the Gyeongbu high-speed rail project showed that the weekday trips increased about 17,000 trips/day and the weekend trips increased about 26,000 trips/day. This study is meaningful in that the intervention explained the phenomena affecting the time series of KTX trip and analyzed the impact on intervention of time series quantitatively. The developed model can be used to forecast the outline of the overall KTX demand and to validate the KTX O/D forecasting demand.

• STI Policy Review
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• v.7 no.2
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• pp.60-84
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• 2016

What impact does the sharing economy have on existing businesses? This paper empirically examines how Uber transformed the taxi industry in New York City. Using a regression model controlling various potential influencing factors, we find no direct evidence that daily trips or revenue per taxi driver decreased since Uber entered the taxi industry. However, a closer investigation into other dimensions of taxi trips reveals that taxi drivers were forced to change their way of doing businesses to retain existing daily trips and revenue. Since Uber crowded out yellow taxis from the central area of Manhattan, yellow taxis responded by serving customers outside of the Manhattan borough. From enlarging their geographical coverage and serving customers that were previously ignored, yellow taxis were able to retain their previous level of taxi trips and market share. We also find that yellow taxis responded by improving their service quality to better serve customers' needs. Our result suggests that incumbents actively responded to Uber's entry and provided substantial benefit to consumers. Combined with the incumbent's response, the sharing economy transformed the existing market in a welfare-enhancing way. This paper provides managerial and policy implication on how incumbents affected by the disruptions of the sharing economy should respond. Even though it might be yet premature to examine the impact of Uber, results suggest that incumbents have effectively defended against Uber's entry so far. We conclude that the sharing economy and the existing economy can create positive value in our society through well-intentioned competition, complementing each other's weaknesses and strengths.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.87-97
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• 2008

The traditional trip-based modeling approach has assumed that a trip is generated for a purpose. However, the approach has not considered trips as a set of connected trips nor has it considered trip chaining. The purpose of this study is to identify general characteristics of trip chaining, and to explore relationships between trip purposes and trip chains using multivariate regression models. The data for this study come from the 2006 Seoul household travel diary survey. It is found that simple trip chains are dominant phenomena, and socio-economic characteristics such as occupation, income, age, and gender are closely related to types of trip chains. People aged less than 20, females, or high-income people are more likely to have a higher number of home-based trip chains. In addition, commute and school trips for workers and students respectively tend to be strongly associated with simple trip chains, while shopping and leisure trips for housewives tend to be related to simple trip chains.

• Journal of KIBIM
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• v.6 no.2
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• pp.19-28
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• 2016

Social costs analysis seeks to reveal the environmental effects of transportation policy. It delivers a sense of the effects of the public's daily travel and the costs that are or would be incurred from individual trips. Moreover, the accumulated total number of trips will uncover the effects of travel on society. This article shows the quantitative analysis of the economic outcomes of travel using social costs estimation methods. In order to support urban planning tasks, this research implemented analysis tool for social costs estimation by travel behavior. For a case study, a jave based application which can convert people's trip data into social costs is developed. the application used for simulating student-housing effects by estimating social costs changes. The analysis included the attributes, building scale and locational changes of the student housing as well as transforms of the students' trips.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3167-3179
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• 2024

In abnormal states of nuclear power plants (NPPs), operators undertake mitigation actions to restore a normal state and prevent reactor trips. However, in abnormal states, the NPP condition fluctuates rapidly, which can lead to human error. If human error occurs, the condition of an NPP can deteriorate, leading to reactor trips. Sudden shutdowns, such as reactor trips, can result in the failure of numerous NPP facilities and economic losses. This study develops a remaining trip time (RTT) prediction system as part of an operator support system to reduce possible human errors and improve the safety of NPPs. The RTT prediction system consists of an algorithm that utilizes artificial intelligence (AI) and explainable AI (XAI) methods, such as autoencoders, light gradient-boosting machines, and Shapley additive explanations. AI methods provide diagnostic information about the abnormal states that occur and predict the remaining time until a reactor trip occurs. The XAI method improves the reliability of AI by providing a rationale for RTT prediction results and information on the main variables of the status of NPPs. The RTT prediction system includes an interface that can effectively provide the results of the system.

• Journal of the Korean Geographical Society
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• v.42 no.6
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• pp.914-929
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• 2007

This study analyzes the accessibility patterns for commuting trips in Seoul Metropolitan Area using National Census Data between 1990 and 2000. the results show that the accessibility increased between 1990 and 1995, while it decreased between 1995 and 2000, due to the raised commuting time. Seoul, Kangju, Yeuju, Yangpyoung, Gapyoung show relatively high accessibility. The GINI parameters tell that the regional balance for commuting accessibility were worsen between 1990 and 1995, compared to that between 1995 and 2000. The accessibility patterns for commuting to Seoul were also analyzed and the result shows that the accessibility reduced between 1995 and 2000. Kwachun, Kwangju, Sungnum are found to have very high accessibility to Seoul, which is close to Soeoul with high percentage of incoming commuting trips. These results indicate that even continuous transport infrastructure supplies were not enough to solve the congestion problems for commuting trips in Seoul Metropolitan Area because of the induced traffic and traffic congestion.

• 주류산업
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• v.19 no.1
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• pp.51-61
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• 1999

• 주류산업
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• v.20 no.3
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• pp.66-73
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• 2000

• Journal of the Korean Geographical Society
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• v.42
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• pp.113-151
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• 1990