Smart technologies are critical for businesses to develop these dynamic connections, as technologies enable them to network with others and exchange resources seamlessly. This fact makes it possible to modify the tasks performed by employees of tourism organizations that are in contact with consumers/tourists.

Smart Tourism is regarded as a new paradigm in the tourism industry. The purpose of this article is to present the first bibliometric study of Smart Tourism to help understanding the means of smart tourism by applying a co-word analysis. Co-word analysis is a content analysis technique which uses a pattern of co-occurrence of pair of items such as words, nouns or phrases in a corpus of texts to identify the relationships between ideas and the main themes within the subject areas. Smart tourism has been an issue in tourism industry these days. Some scholars are trying to define the ‘smart tourism’ as a different meaning from the ‘mobile tourism’ that is still commonly used. Practically, the term ‘smart’ is getting popular in tourism industry, since the advent of smartphones. Though the term ‘smart’ has not been defined clearly, it is still used even in academia. To examine the intellectual structureof Smart Tourism, this study used keywords in articles from the academic database in KCI (Korea Citation Index) from 2010 to February, 2014. This study used both quantitative and qualitative measures. Quantitative data are used to put very related concepts together, while qualitative indicators are used to measure the impact of the detected themes. In addition, the study presented bibliometric maps to show the networks between the main concepts treated by the Smart Tourism domains. The maps provide insights into the structure of the Smart Tourism with visualizing the division of the field into several subfields. For a method of the study, the main 10 keywords-‘smartphone’, ‘SNS’, ‘ubiquitous’, ‘service quality’, ‘LBS’, ‘AR’,…and so on.- related to Smart Tourism extracted from policy and trend reports of governmental offices(i.e. Mistry of Culture, Sport and Tourism), company of government(i.e. Korea Tourism Organization), and research institutes(Samsung Economic Research Institute, Korea Culture & Tourism Institute). Using 10 main keywords, we collected 185 articles related to the smart tourism filed.Then within 185 articles, there are 1,347author keywords extracted.After thenormalization of 1,347 keywords, 366 author keywords were selected for data analysis.A co-occurrence matrix and an affinity matrix were generated based on Pearson’s correlation coefficients to create a clustering of the words using hierarchical clustering analysis. To visualize these intellectual structures, this study carried out a network analysis with NodeXL to which a data algorithm in R was applied. These findings appear to indicate the potential usefulness of bibliometric studies in uncovering the different research fields’ intellectual structure and evolution. This evolution providesan opportunity to anticipate interesting developments in Smart Tourism field with respect to key topics of the field as well as predicting which topics are less likely to assume a central role in Tourism IT inthe near future.The study benefits researchers and practitionersby offering guidelines to the process of selecting research topics and of formulating policy regarding smart tourism.

Purpose: In the 4th industrial revolution, services that incorporate various smart technologies in the tourism sector have begun to gain popularity. Accordingly, academic discussions on smart tourism have also started to become active in various fields. Despite recent research, the definition of smart tourism is still ambiguous, and it is not easy to differentiate its scope or characteristics from traditional tourism concepts. Thus, this study aims to analyze the perception of smart tourism exposed online to identify the current point of smart tourism in Korea and present the research direction for conceptualizing smart tourism suitable for the domestic situation. Research design, data, and methodology: This study analyzes the perception of smart tourism exposed online based on 20,198 news data from portal sites over the past six years. Data on words used with smart tourism were collected from the leading portal sites Naver, Daum, and Google. Text mining techniques were applied to identify the social awareness status of smart tourism. Network analysis was used to visualize the results between words related to smart tourism, and CONCOR analysis was conducted to derive clusters formed by words having similarity. Results: As a result of keyword analysis, the frequency of words related to the development and construction of smart tourism areas was high. The analysis of the centrality of the connection between words showed that the frequency of keywords was similar, and that the words “smartphones” and “China” had relatively high connection centrality. The results of network analysis and CONCOR indicated that words were formed into eight groups including related technologies, promotion, globalization, service introduction, innovation, regional society, activation, and utilization guide. The overall results of data analysis showed that the development of smart tourism cities was a noticeable issue. Conclusions: This study is meaningful in that it clearly reflects the differences in the perception of smart tourism between online and research trends despite various efforts to develop smart tourism in Korea. In addition, this study highlights the need to understand smart tourism concepts and enhance academic discussions. It is expected that such academic discussions will contribute to improving the competitiveness of smart tourism research in Korea.