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A Study on the Smart Tourism Awareness through Bigdata Analysis

The Journal of Industrial Distribution & Business / The Journal of Industrial Distribution & Business, (E)2233-5382
2020, v.11 no.5, pp.45-52
https://doi.org/https://doi.org/10.13106/jidb.2020.vol11.no5.45
LEE, Song-Yi
LEE, Hwan-Soo
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Abstract

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.

keywords
Smart tourism, Awareness, Big data, Text-mining, News

Reference

1.

Arturo, M. R., José, M. P., & Migueal, A. G. C. (2011). Otium: A web based planner for tourism and leisure. Expert Systems with Applications, 38(8), 10085-10093.

2.

Buhalis, D. (1988). Strategic use of information technologies in the tourism industry. Tourism Management, 19(15), 409-121.

3.

Cho, S. H. (2019). The effect of mobile tourism app characteristics on perceived value, satisfaction and behavioral intention. International Journal of Industrial Distribution & Business, 10(9), 45-52.

4.

Choi, E. H. (2017). Case Study and Implications of Smart Tourism in Korea. KIET Industrial Economic Review, 228, 49-57.

5.

Del Vecchio, P., Mele, G., Ndou, V., & Secundo, G. (2018). Creating value from social big data: Implications for smart tourism destinations. Information Processing & Management, 54(5), 847-860.

6.

Economou, M., & MEintani, E. (2011). Promising Beginning? Evaluating Museum Mobile Phone Apps. Paper presented at Rethinking Technology in Museums 2011.

7.

Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3), 179-188.

8.

Guttentag, D. A. (2010). Virtual reality: Applications and implications for tourism. Tourism Management, 31(5), 637-651.

9.

Huang, C. D., Goo, J., Nam, K., & Yoo, C. W. (2017). Smart tourism technologies in travel planning: The role of exploration and exploitation. Information & Management, 54(6), 757-770.

10.

Jovicic, D. Z. (2019). From the traditional understanding of tourism destination to the smart tourism destination. Current Issues in Tourism, 22(3), 276-282.

11.

Koo, C. M., Baron, C. P., Gretzel, U., Yuan, Y., & Lamsfus, C. (2014). Smart tourism ecosystem workshop. Paper presented at ENTER 2014.

12.

Koo, C. M., Kim, J. H., & Chung N. H. (2014). Theorization and utilization of smart tourism ecosystems. Information Systems Review, 16(3), 69-87.

13.

Koo, C., Shin, S., Gretzel, U., Hunter, W. C., & Chung, N. (2016). Conceptualization of smart tourism destination competitiveness. Asia Pacific Journal of Information Systems, 26(4), 561-576.

14.

Koo. C. M., Shin, S.H., Kim, K. H., Kim, C. W., & Chung, N. H. (2013). Smart Tourism of the Korea: A case study. Paper presented at PACIS 2013.

15.

Lee, S., & Jing, D. (2015). Use Intentions of Mobile Tour Apps through Expansion of the Technology Acceptance Model. Journal of Distribution Science, 13(10), 135-142.

16.

Li, Q. Z., & Lee, J. H. (2017). The influential relations on sharing economy and consumer traits. International Jornal of Industrial Distribution & Business, 8(6), 75-86.

17.

Li, Y., Hu, C., Huang, C., & Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58, 293-300.

18.

Lopes, R. O., Malik, O. A., Kumpoh, A. A. Z. A., Keasberry, C., Hong, O. W., Lee, S. C. W., & Liu, Y. (2019, September). Exploring Digital Architectural Heritage in Brunei Darussalam: Towards Heritage Safeguarding, Smart Tourism, and Interactive Education. Paper presented at the 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM) (pp. 383-390). IEEE.

19.

Maehara, C., Yatsugi, K., Kim, D. W., & Ushiama, T. (2012). An Exhibit Recommendation System Based on Semantic Networks for Museum. Studies in Computational Intelligence, 376, 131-141.

20.

Mak, A. H. N., Lumbers, M., Eves, A., & Chang, R. C. Y. (2013). An application of the repertory grid method and generalised Procrustes analysis to investigate the motivational factors of tourist food consumption. International Journal of Hospitality Management, 35, 327-338.

21.

Pradhan, M. K., Oh, J., & Lee, H. (2018). Understanding travelers’ behavior for sustainable smart tourism: A technology readiness perspective. Sustainability, 10(11), 4259.

22.

Purnomo, S., Rahayu, E. S., Riani, A. L., Suminah, S., & Udin, U. (2020). Empowerment Model for Sustainable Tourism Village in an Emerging Country. The Journal of Asian Finance, Economics and Business, 7(2), 261-270.

23.

Scott, N., Baggio, R., & Cooper, C. (2008). Network analysis and tourism: From theory to practice. Bristol, United Kingdom: Channel View Publications.

24.

Tan, G. W. H., Lee, V. H., Lin, B., & Ooi, K. B. (2017). Mobile applications in tourism: the future of the tourism industry. Industrial Management & Data Systems, 117(3), 560-581.

25.

Yoo, C., Kwon, S., Na, H., & Chang, B. (2017). Factors affecting the adoption of gamified smart tourism applications: An integrative approach. Sustainability, 9(12), 2162.

26.

Wang, D., Park, S. W., & Fesenmaier, D. R. (2012). The role of smartphones in mediating the touristic experience. Journal of Travel Research, 51(4), 371-387.

The Journal of Industrial Distribution & Business