• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.79-94
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• 2005

This study examines which factors affect on Job-Satisfaction of Tour Guide in Korea, perceiving that Job-Satisfaction of Tour Guide affects customer satisfaction, and outcomes of business. In the tourism industry, Tour Guides are one of the most important factors influencing customer satisfaction, because they are one of the key front- line players. Ultimately, the purpose of this study is to present the importance of efficient management for human resources through investigating Job-Satisfaction of Tour Guide. To active purpose of this study, both literatures and empirical research based on Japanese, and Chinese Tour Guides in Korea were adopted and conducted. In conclusion, in order to improve psychological and behavioral outcomes of the Tour Guides, job satisfaction factors have to be improved in many ways and also travel managers should consider them.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.171-177
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• 2020

This study investigates e-service quality of online travel agency and influence on relationship quality and Reuse. The individual Chinese tourists with experiences using online travel agencies were chosen for the study. The survey was carried out at Jeju International Airport, which is the most frequently used by Chinese tourists visiting Korea. Data were collected for 7 days from July 15, 2019 to July 21, 2019. A total of 320 tourists were attended in this research and finally 300 samples were used for empirical analysis. The result of the study showed that e-service quality of online travel agencies all factors(convenience, individuality, accuracy and price attractiveness) influences on relationship quality all factors(satisfaction, trust) and the factor 'accuracy' was analyzed as the biggest among them. Moreover satisfaction and trust factors of all sub-factors of relationship quality influences on reuse. In the future, we intend to provide basic marketing data for Chinese tourists using online travel agencies to officials and practitioners. Particularly, focusing on the tourism behaviors of individual Chinese tourists, we are going to propose effective business cooperation plans and strategic alternatives with online travel agencies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.5808-5815
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• 2012

Through Tourism Information System, we can know, how much we feel importance of travel information and how to they spending, research when they need to go to travel according to we have to realize about anticipation/planning phase and on-site phase are different exactly. This purpose is how to get a basic data when we support with tourist about information of festival in travel and also how to give satisfaction for tourist and how many tourist wants to join the travels in addition, it is possible to we can develop all of things about travel informations. This is a result of research. First, all of the tourists participate the FESTIVAL, even though they didn't get any informations about travel. The second, information of festival in travel has different feeling between importance of participate in festival and performance after experience.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.213-224
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• 1998

Theoretically and practically, it is very important to understand the way which tourist satisfaction is operated. The purpose of this study is to identify interaction among the determinants of tourist satisfacton process. A model of tourist satisfactioin process is developed based based on the confirmation / disconfirmation which is originated from consumer behavior literature. Three elements of the model include 'expectation','performance', and 'discrepancy between expectation and performance'. 340 questionnaires were delivered to find Everland visitors' perceptions of the determinants of tourist satisfaction. LISREL 8.14 was used to analyze the interaction among the determinants. The results are as follows : 1) 'expectation' has indirect effect on tourist satisfaction while 'performance' and 'discrepancy' has direct effect on the tourist satisfaction, 2) two precedent variables such as 'expectation' and 'performance' have indirect effect on the satisfaction through 'discrepancy',3) among the three determinants it is found that 'performance' is the most effective determinant of tourist satifaction, and 4) the model which was composed from the aspect of 'travel cost' was more effective to describing tourist satisfacton rather that from the aspect of 'service quality'.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.207-218
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• 2023

Jeju Island is a major area generates origin-destination trips, accounting for about 90 % of domestic air transportation, and popular tourist destination visited by more than 10 million domestic and foreign tourists annually. Travel behavior patterns of tourists in Jeju Island have great meaning for not only Jeju Island, but also the inland aviation, tourism, mobility industry. This study presented passenger travel behavior in Jeju Island based on a survey including foreign visitors and residents as well as domestic visitors. In particular, the survey was conducted in early 2020 prior to the COVID-19 pandemic, it is expected to be a major preliminary study for changes in tourist travel and air travel in Jeju Island before and after COVID-19.

• Knowledge Management Research
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• v.24 no.1
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• pp.99-126
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• 2023

As cultural background contributes members of society to recognize and behave in a specific direction, customers with different cultural backgrounds show various reactions even when they are provided with the same service. Previous studies have used the Hofstede cultural dimension to understand how hotel visitors' satisfaction varies with the provided service as per their cultural background. However existing research only considered the cultural background of the guests, and there are not many studies focused on the types of travel. Therefore, in this study, the travel types of hotel visitors are classified into business travel visitors and leisure tourism visitors, and analyzed the effect of Hofstede's cultural dimension on hotel selection attributes according to the styles of travel. In this study, we collected information on six cultural dimensions of Hofstede, and from TripAdvisor, a representative tourism platform, 204,261 optional attribute ratings for hotels in New York to investigate the satisfaction of hotel selection attributes. In conclusion, it is expected that this study will be able to identify which service attributes the customers of various cultures who visit hotels put emphasis in advance, and therefore provide suitable service accordingly.

• Journal of Families and Better Life
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• v.5 no.2
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• pp.11-27
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• 1987

This study examined job satisfaction levels between employed single women and employed married women. The specific objectives of this study were; (1) to investigate differences in the level of job satisfaction between employed single women and employed married women; (2)to investigate the factors which influence the level of job satisfaction; (3)to investigate the relationship between job satisfaction and life satisfaction. the data used in this study included 441 working women from 290 (65.8 %) single women and 151 (34.2%) married women. Statistical analyses were conducted using frequencies, percentiles, mean , t-test , ANOVA, pearson's correlation and a stepwise multiple regression. The major findings were ; (1) at the P<.005 level, there was a significant difference in the job Satisfaction Index (JSI) between employed single and married women by using the t-test ; (2) Occupation, type of organization , job experiences, travel time from home to work. unionization, age, and health status were significantly related to the JSI by using the one-way ANOVA; (3) Thee was an interaction effect between income and marital status on the JSI, and between education and marital status on the JSI; (4) Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between employed single and married women; (5) There was a positive relationship between the JSI and Life Satisfaction Index(r=.41)

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.62-71
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• 2017

In order to attract foreign tourists, it is important to understand what factors on domestic tour spots are critically considered and how they are evaluated after visit. However, most of the researches on tour business have collected information from tourists through survey on a small number of tourists, which leads to inaccurate and biased conclusion. In this paper, we suggest a data-driven methodology to figure out tourists' satisfaction factors and estimate sentiment scores on them. To do so, we collected review comments data from popular web site. Latent dirichlet allocation is employed to extract key factors and elastic net is used to estimate sentiment scores. Then, an aggregated evaluation score is generated by combining the factors and the sentiment scores per topics. Our proposed method can be used to recommend travel schedules with themes and discover new spots.