• Journal of the Korean Geographical Society
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• v.47 no.4
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• pp.522-540
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• 2012

The main aim of the paper is to identify the position or status of Korean economic geography in changing global economic geography by reviewing papers published in Korean geographical journals since the mid-1950s. Since the late 20th century as economic geography has developed significantly with the introduction of new research issues, methodologies, and theory and concepts, economic geography in Korea also has gone through rapid development in terms of both quantitative and qualitative perspectives. The paper attempts to analyze trends in Korean economic geography by reviewing agricultural, industrial, commercial geographies, and others since the mid-1950s. The review of economic geography in Korea would be based on four periods classified by research issues and approaches; foundation (~1950s), positioning (1960s and 1970s), jump and rush (1980s and mid-1990s), and transitional period (late 1990s~). Agricultural geography in Korea has decreased due to increases of the interests in industrial geography since the 1980s. In particular, since the late 1990s industrial geography has undergone a significant transition in accordance with the emergence of new theories of institutional perspectives, centering around issues on value chains, innovative cluster, cooperative and competitive networks, foreign direct investment, flexible specialization and venture ecology. Along with this, there has been changes in the interest of commercial geography in Korea from researches on periodical markets, the structure of store formats, and distributions by commodity, to researches on producer services and retailer's locational behaviors and commercial supremacy according to the emergence of new store formats. Since the late 1990s, many researches and discussions associated with the new economic geography began to emerge in Korea. Various research issues are focused on analyzing changes of local, regional and global economic spaces and their processes in relation to institutional perspectives, knowledge and innovation, production chain and innovative networks, industrial clusters and RIS, and geographies of service. Although economic geography in Korea has developed significantly both in quantitative and qualitative perspectives, we pointed out that it has still limited in some specific scope and issues. Therefore, it is likely to imply that its scope and issues should be diversified with new perspectives and approaches.

• 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.