• Title/Summary/Keyword: Tourist Demand

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Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

The Direction for Complex Natural Park Development According to Demand Analysis of Tourists (관광객 요구분석에 따른 복합자연공원 개발방향 연구)

  • Cho, Ui-Young
    • The Journal of the Korea Contents Association
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    • v.6 no.11
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    • pp.85-94
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    • 2006
  • This study was conducted to suggest new development model for national & public parks by applying fascinating theme to the existing standardized development of those park. For this purpose, YeonIn Mountain Provincial Park was chosen as object of this research, which is located in GaPyeong, Kyonggi Province. The results from analysis of demand for tourism trend and development were as follows. Most of visitors(87%) come from the metropolitan area and their age are between the ages of 20 and 30. And the visitors' preference for accommodation is the independent villa style. For commercial facility, the strong expansion for food and beverage facilities and stores was needed. The future facilities and activities which they want to experience and e are health-recreation facility and ecological experience based on nature. From these results, It might conclude that we have to develop the qualified nature park with various theme focused on experience and recreation, and that we do preserve the environment.

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Forecasting of Foreign Tourism demand in Kyeongju (경주지역 외국인 관광수요 예측)

  • Son, Eun Ho;Park, Duk Byeong
    • Journal of Agricultural Extension & Community Development
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    • v.20 no.2
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    • pp.511-533
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    • 2013
  • The study used a seasonal ARIMA model to forecast the number of tourists to Kyeongju foreign in a uni-variable time series. Time series monthly data for the investigation were collected ranging from 1995 to 2010. A total of 192 observations were used for data analysis. The date showed that a big difference existed between on-season and off-season of the number of foreign tourists in Kyeongju. In the forecast multiplicative seasonal ARIMA(1,1,0) $(4,0,0)_{12}$ model was found the most appropriate model. Results show that the number of tourists was 694 thousands in 2011, 715 thousands in 2012, 725 thousands in 2013, 738 thousands in 2014, and 884 thousands in 2015. It was suggested that the grasping of the Kyeongju forecast model was very important in respect of how experts in tourism development, policy makers or planners would establish marketing strategies to allocate services in Kyeongju as a tourist destination and provide tourism facilities efficiently.

A study on demand forecasting for Jeju-bound tourists by travel purpose using seasonal ARIMA-Intervention model (계절형 ARIMA-Intervention 모형을 이용한 여행목적 별 제주 관광객 수 예측에 관한 연구)

  • Song, Junmo
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.3
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    • pp.725-732
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    • 2016
  • This study analyzes the number of Jeju-bound tourists according to travellers' purposes. We classify the travellers' purposes into three categories: "Rest and Sightseeing", "Leisure and Sport", and "Conference and Business". To see an impact of MERS outbreak occurred in May 2015 on the number of tourists, we fit seasonal ARIMA-Intervention model to the monthly arrivals data from January 2005 to March 2016. The estimation results show that the number of tourists for "Leisure and Sport" and "Conference and Business" were significantly affected by MERS outbreak whereas arrivals for "Rest and Sightseeing" were little influenced. Using the fitted models, we predict the number of Jeju-bound tourists.

Management System for Parking Free Space based on Open CV (Open CV를 기반으로 한 주차 여유 공간 관리 시스템)

  • Nam, Eun-Joo;An, Deouk-Kyi;Seo, You-Jin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.1
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    • pp.69-75
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    • 2020
  • This paper introduces the parking guide service developed to address the inconvenience of parking in areas where demand for parking spaces is high, such as busy streets and tourist attractions. Due to difficulties in measuring and developing the actual parking lot while driving the car, we created a temporary parking lot and created Arduino RC Car to replace the actual car. Video processing based on Open CV allows users to identify the entire parking lot, parking space, and completed parking space, and track moving cars, and this information has been developed to enable users to see through the application. The application allows the user to book the desired parking space and introduce a way-finding algorithm to guide them through the optimal path to the selected parking compartment.

Comparing the Spatial Mobility of Residents and Tourists by using Geotagged Tweets (지오트윗을 이용한 거주자와 방문자의 공간 이동성 연구)

  • Cho, Jaehee;Seo, Il-Jung
    • Journal of Information Technology Services
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    • v.15 no.3
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    • pp.211-221
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    • 2016
  • The human spatial mobility information is in high demand in various businesses; however, there are only few studies on human mobility because spatio-temporal data is insufficient and difficult to collect. Now with the spread of smartphones and the advent of social networking services, the spatio-temporal data began to occur on a large scale, and the data is available to the public. In this work, we compared the movement behavior of residents and tourists by using geo-tagged tweets which contain location information. We chose Seoul to be the target area for analysis. Various creative concepts and analytical methods are used: grid map concept, cells visited concept, reverse geocoding concept, average activity index, spatial mobility index, and determination of residents and visitors based on the number of days in residence. Conducting a series of analysis, we found significant differences of the movement behavior between local residents and tourists. We also discovered differences in visiting activity according to residential countries and used applications. We expect that findings of this research can provide useful information on tourist development and urban development.

Indicators of the Destination Competitiveness of Rural Tourism Township in Korea (관광목적지로서의 농촌관광마을의 경쟁력 평가지표 개발)

  • Yoon, Jun-Sang;Kim, So-Yun;Park, Duk-Byeong
    • Journal of Agricultural Extension & Community Development
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    • v.22 no.2
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    • pp.135-144
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    • 2015
  • Competitiveness has been associated in the tourism literature as a crucial factor for the success of tourist destinations. This study is to develop indicators that measure destination competitiveness of rural tourism townships in Korea. It was conducted via a Delphi technique and the analytical hierarchy process method. After four rounds of discussions, the panel members reached consensus on a set of 27 indicators with three dimensions which are attractor (resource, infrastructure, and tourism products), assistance (tourism business assistance and value-added processing assistance), and planning and management (planning for development, capacity for management). This set of destination competitiveness indicators can serve as a starting point for devising a set of indicators at the local level in order to be useful rural tourism sector manager and administrators. The selected indicators are measurable, demand driven and practical to show the real performance in rural destination.

A study on the exchange Kaesong area sightseeing train movement by the inter-Korean Railway Connection (남북철도 연결에 따른 개성지역 관광열차 운행에 대한 연구)

  • Park, Hong-Soon
    • Proceedings of the KSR Conference
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    • 2004.06a
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    • pp.570-575
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    • 2004
  • This paper deals with the exchange of tourists and the operation of sightseeing train encouraged by the inter-Korean cross-border railway project. First of all, how the inter-Korean cross-border railway project has developed will be discussed. After this, the present tourism state, facilities, the state of railways and roads of North Korea, and major tourist attraction around the Kyonguisun will be shown. And then, several aspects on the agreements between the Korean National Railroad (KORAIL) and North Korean railroad system will be summarized. And, finally, the economic effect of the line including the operation schedule of the Kyonguisun sightseeing train, the demand forecast, the computation of railway fare, and profit sharing will be depicted.

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A Study on the Ecotourism Policy Direction of Saemangeum.Gunsan Free Economic Zone (새만금.군산경제자유구역의 생태관광 방향)

  • Lim, Hyung-Baek;Choi, Hung-Kyu;Lee, Seong-Woo
    • Hwankyungkyoyuk
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    • v.22 no.4
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    • pp.53-65
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    • 2009
  • Saemangeum is the largest reclaimed land in Korea. Saemangeum is the large scale project responding to the economic demand of globalization, and a government initiated new development business with a vision of global Free Economic Zone(FEZ). Jeollabuk-province conducted a international competition to establish a global-scale, creative development plan and grow the Saemangeum as an international destination of economy, and a world-wide brand. SGFEZ has much to offer in terms of tourists attractions and breathtaking scenery. And tourism is one of the important industry in SGFEZ. Many tourist facilities will be construct in SGFEZ. Environment is the important issue in many field of study. Recent days, green growth come into the spotlight in Korea. But even as SGFEZ prepares for its future global tourists attraction, so much of the tourism policy directions remains unconsidered. The objective of this study was to suggest tourism policy direction, especially concentrated on ecology tourism policy direction of Saemangeum Gunsan Free Economic Zone(SGFEZ).

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Estimating volatility of American tourist demand with a pleasure purpose in Korea inbound tourism market (방한 미국여행객의 국제 수요변동성 분석)

  • Kim, Kee-Hong
    • International Commerce and Information Review
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    • v.10 no.1
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    • pp.395-414
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    • 2008
  • The objective of this study is to introduce the concepts and theories of conditional heteroscedastic volatility models and the news impact curves and apply them to the Korea inbound tourism market. Three volatility models were introduced and used to estimate the conditional volatility of monthly arrivals of inbound tourists into Korea and news impact curves according to the three models. Results of this study are as follows. As the proportion of American tourists occupied a large amount of Korea inbound tourism market, the markets' forecasting is very important. The news impact curves which used EGARCH model (1,1) and TGARCH model(1,1), with data on these tourists to Korea showed an asymmetry effect of volatility. It was common that bad news means that it was estimated more sensitively than good news. From these results, we will notice that American tourists who visited Korea only for tourism are affected by good news. The result suggests that the Korea government and tourism industry should pay more attention to changes in the tourism environment following bad news because conditional volatility increases more when a negative shock occurs than when a positive shock occurs.

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