• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.237-243
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• 2008

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• Journal of the Korean Institute of Landscape Architecture
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• v.17 no.3
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• pp.9-20
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• 1990

The objective of this study is to test the applicability of the Information processing model suggested by Kaplan to the preferences of Korean people as well as to investigate the preference patterns of Korean people and the influencing factors on Korean preferences for the landscape. Photo - questionnaire survey was conducted twice to collect the data concerning the landscape preferences. The samples of the first survey were selected from the citizens of Seoul and the students of Seoul National University. The first survey focused on the preference patterns of Korean people while the emphasis of the second survey was given to the test of information processing model and the influencing factors on the preferences of Korean people. The samples of second survey were also selected from the students of Seoul National University. The photos in the photo - questionnaire for the first survey included the scenes representing both three landscape styles(Korean, Japanese and Western styles)and three landscape qualities such as the layout of space, the use of landscape plants and the use of stones and rocks. For the second survey, four informational factors such as complexity, coherence, legibility and mystery were selected for inclusion in the photos of photo - questionnaire. Respondents for both survey were asked to respond their preferences on the five - point Likers scale. The results of the study suggested that four informational factors influence significantly the preferences of Korean students. The study indicated that both the citizens of Seoul and the students of Seoul National University prefer water and vegetation to rock among the contents of landscape. Among the landscape styles, Japanese landscape style was most preferred and Western landscape style was more preferred than Korean traditional landscape style. In addition to informational factors, it was found that the contents of landscape and landscape style were also major influencing factors on the landscape preferences. The socio - economic backgrounds of respondents such as age, foreign travel experience, income, residency before the age 14, familiarity and respondent's experties in landscape architecture seemed to Influence the landscape preferences.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.17 no.1
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• pp.69-84
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• 2006

Recently, Cruise travel Industry becomes a major market in the SIT tour. this perspective, the primary purpose of this study was to investigate relationship between influencing factors of the Selection Attributes of Cruise Tour. This research aims to provide information to establish customer-oriented marketing strategies in developing by cruise tour. The current study examined related literature finding out the number of the factors to meet future users preference and expectations. Based on examined factors, the study investigated the same dimensions in Korea future cruise industry. The data collected outgoing tourists of travel service company. The Survey instrument consisted of asking respondents a number of questions regarding their intention, preferences, and expectations toward future cruise travel. The result of study showed that a certain number of factors were statistically significant on the future users cruise travel intention. It shows that there was significant difference related to the using purpose and the usage attitude. It can be conducted from the results that respondents expected a certain number of factors when the cruise travel launched in korea.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.327-331
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• 2023

This paper proposes a tourist destination recommendation application that combines a chatbot and a recommendation system. The data to be entered into the chatbot was through big data on social media. Through TEXTOM, a total of 22,701 data were collected over a one-year period from January 2022 to January 2023. Non-terms that interfere with analysis were removed through the data purification process. Using refined data, network visualization and CONCOR analysis were used to identify the information users want to obtain about travel to Jeju Island, and categories for each cluster were organized. The content was intuitively organized so that even those who approached it for the first time could easily use it, reducing the difficulty of operating the application. In this paper, users can select their own preferences and receive information. In addition, a tool called a chatbot allows users to focus more on the process of acquiring information by gaining a sense of reality while operating the application. This suggests an application that can reach the purpose of the curator by affecting the user's desire to visit tourist attractions.

• The Journal of Information Technology and Database
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• v.7 no.1
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• pp.42-53
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• 2000

The major goal of this research is to develop an optimal route search algorithm for an intelligent route guidance system, one sub-area of ITS. ITS stands for intelligent Transportation System. ITS offers a fundamental solution to various issues concerning transportation and it will eventually help comfortable and swift moves of drivers by receiving and transmitting information on humans, roads and automobiles. Genetic algorithm, and fuzzy logic are utilized in order to implement the proposed algorithm. Using genetic algorithm, the proposed algorithm searches shortest routes in terms of travel time in consideration of stochastic traffic volume, diverse turn constraints, etc. Then using fuzzy logic, it selects driver-preference optimal route among the candidate routes searched by GA, taking into account various driver's preferences such as difficulty degree of driving and surrounding scenery of road, etc. In order to evaluate this algorithm, a virtual road-traffic network DB with various road attributes is simulated, where the suggested algorithm promptly produces the best route for a driver with reference to his or her preferences.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.159-185
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• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.108-113
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• 2024

The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

• International Commerce and Information Review
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• v.19 no.1
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• pp.213-234
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• 2017

This study analyzed valid samples of 707 units collected by conducting paper and online surveys on the Korean, the Chinese, the American, and the Japanese. The result showed that a significant causal relationship exists between power distance and pull motivation as well as collectivism and push motivation, which led to a conclusion that developing travel packages that can strengthen bonding of fraternal societies through various events and attractions is effective for respondents from Asian countries. On the other hand, Americans turned out to prefer practical plans, which could provide individual's needs and preferences, for example, a self-healing package. This study, using a simple survey, may have a limitation in that it does not allow the participants to express their opinions. However, the study is meaningful that it made a theoretical contribution utilizing Hofstede's cultural dimensions index, two types of motivation, and theories of customer satisfaction and revisit intention. It also has a practical implication in that it proposes the most optimal and applicable overseas travel marketing strategy by comparing cultural traits of each country.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.93-115
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• 2017

The ability of smartphones to facilitate various services like mobile banking, e-commerce and mobile payments has made them part of consumers' lives. Conjoint analysis (CA) is a marketing research approach used to assess how consumers' preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in marketing research. The purpose of this study is to utilise CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers' smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.