Asia pacific journal of information systems

The Korea Society of Management Information Systems (한국경영정보학회)
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Exploring the Movements of Chinese Free Independent Travelers in the U.S.: A Social Network Analysis Approach

  • Lin Li (School of Management, Kyung Hee University) ;
  • Yoonjae Nam (Department of Culture, Tourism & Content, Kyung Hee University) ;
  • Sung-Byung Yang (School of Management, Kyung Hee University)
  • Received : 2019.03.15
  • Accepted : 2019.08.27
  • Published : 2019.09.30
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Abstract

In a new age of smart tourism, free independent travelers (FITs) choose their travel routes in a more diversified and less predictable way with the aid of smart services. This paper focuses on the movements of Chinese outbound FITs in the U.S. in the year of 2018. 110 places to visit (destinations) extracted from 122 travel routes recommendations on Qyer.com, a major online travel community in China, are analyzed with social network analysis (SNA). Based on the results of SNA, employing degree centrality, eigenvector centrality, betweenness centrality, network visualization, and cluster diagram methods, some preferred cities and natural attractions outside city centers (i.e., New York City (NYC), Los Angeles, San Francisco, Washington D.C., and Niagara Falls) are identified. Moreover, it is found that NYC in the East and Los Angeles in the West play a major role in the movements of Chinese FITs. This study contributes to the body of knowledge on tourist destination movements and provides valuable implications for smart service development in the tourism and hospitality industry.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A5B8059804).

References

  1. Alt, R., Demirkan, H., Ehmke, J. F., Moen, A., and Winter, A. (2019). Smart services: The move to customer orientation. Electronic Markets, 29(1), 1-6. https://doi.org/10.1007/s12525-019-00338-x
  2. Arlt, W. G. (2019). 180 million Chinese outbound trips in 2019. Retrieved from https://china-outbound.com/editorial-2019-forecast/ Accessed on 24 June 2019.
  3. Barnett, G. A., Danowski, J. A., and Richards, W. D. (1993). Communication networks and network analysis: A current assessment. Progress in Communication Science, 12, 1-19.
  4. Barnett, G. A., Lee, M., Jiang, K., and Park, H. W. (2016). The flow of international students from a macro perspective: A network analysis. Compare: A Journal of Comparative and International Education, 46(4), 533-559. https://doi.org/10.1080/03057925.2015.1015965
  5. Borgatti, S. P., and Halgin, D. S. (2011). Analyzing affiliation networks. The Sage Handbook of Social Network Analysis, 1, 417-433.
  6. Brandt, T., Bendler, J., and Neumann, D. (2017). Social media analytics and value creation in urban smart tourism ecosystems. Information & Management, 54(6), 703-713. https://doi.org/10.1016/j.im.2017.01.004
  7. Breiger, R. L., Boorman, S. A., and Arabie, P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12(3), 328-383. https://doi.org/10.1016/0022-2496(75)90028-0
  8. China Travel News (2015). New York City the top US destination for Chinese visitors. Retrieved from https://www.chinatravelnews.com/article/93999/ Accessed on 23 January 2019.
  9. Chung, H. C., Chung, N., and Nam, Y. (2017). A social network analysis of tourist movement patterns in blogs: Korean backpackers in Europe. Sustainability, 9(12), 2251.
  10. Cohen, E. (1972). Toward a sociology of international tourism. Social Research, 39(1), 164-182.
  11. Esser, J. (2019). AI in travel booking and management - How smart travel assistants disrupt travel distribution. Retrieved from https://www.rolandberger.com/nl/Point-of-View/Smart-Travel-Assistants-%E2%80%93-The-new-gateway-for-travel.html/ Accessed on 7 March 2019.
  12. Gallarza, M. G., Saura, I. G., and García, H. C. (2002). Destination image: Towards a conceptual framework. Annals of Tourism Research, 29(1), 56-78. https://doi.org/10.1016/S0160-7383(01)00031-7
  13. Gherasim, D. (2012). Rural tourism in Romania. Economy Transdisciplinarity Cognition, 15(1), 279.
  14. Gretzel, U., Sigala, M., Xiang, Z., and Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3), 179-188. https://doi.org/10.1007/s12525-015-0196-8
  15. Gulliver, B. R. (2016). Travellers are still unsure about booking trips on their smartphones. Retrieved from https://www.economist.com/gulliver/2016/09/20/travellers-are-still-unsure-about-booking-trips-on-their-smartphones/Accessed on 25 June 2019.
  16. Hunter, W. C., Chung, N., Gretzel, U., and Koo, C. (2015). Constructivist research in smart tourism. Asia Pacific Journal of Information Systems, 25(1), 105-120. https://doi.org/10.14329/apjis.2015.25.1.105
  17. Hwang, Y. H., Gretzel, U., and Fesenmaier, D. R. (2006). Multicity trip patterns: Tourists to the United States. Annals of Tourism Research, 33(4), 1057-1078. https://doi.org/10.1016/j.annals.2006.04.004
  18. Jones, T. (2015) Chinese tourism boom extends to Grand Canyon. Retrieved from https://explorethecanyon.com/chinese-tourism-boom-extends-to-grand-canyon/Accessed on 6 March 2019.
  19. Kabadayi, S., Ali, F., Choi, H., Joosten, H., and Lu, C. (2019). Smart service experience in hospitality and tourism services: A conceptualization and future research agenda. Journal of Service Management. Online Publication.
  20. Khan, S. F., and Ismail, M. Y. (2018). An investigation into the challenges and opportunities associated with the application of Internet of Things (IoT) in the agricultural sector-A review. Journal of Computer Science, 14(2), 132-143. https://doi.org/10.3844/jcssp.2018.132.143
  21. Kogan, N., and Lee, K. J. (2014). Exploratory research on success factors and challenges of Smart City Projects. Asia Pacific Journal of Information Systems, 24(2), 141-189. https://doi.org/10.14329/apjis.2014.24.2.141
  22. Koo, C., Shin, S., Gretzel, U., Hunter, W. C., and Chung, N. (2016). Conceptualization of smart tourism destination competitiveness. Asia Pacific Journal of Information Systems, 26(4), 561-576. https://doi.org/10.14329/apjis.2016.26.4.561
  23. Krackhardt, D. (1987) QAP partialling as a test of spuriousness. Social Networks, 9(2), 171-186. https://doi.org/10.1016/0378-8733(87)90012-8
  24. Law, L. (2019). 15 Best places to visit in the United States. Retrieved from https://www.planetware.com/usa/best-places-to-visit-in-the-united-states-us-ny-21.htm/Accessed on 5 March 2019.
  25. Lee, H., Chung, N., and Nam, Y. (2018). Do online information sources really make tourists visit more diverse places? Based on the social networking analysis. Information Processing & Management. Online Published.
  26. Lee, Y. (2019). Why are so many South Korean travel agencies closing? Retrieved from https://skift.com/2019/01/14/why-are-so-many-south-korean-travel-agencies-closing/Accessed on 21 June 2019.
  27. Lee, Y., and Kim, I. (2018). Change and stability in shopping tourist destination networks: The case of Seoul in Korea. Journal of Destination Marketing & Management. Online Published.
  28. Leung, X. Y., Wang, F., Wu, B., Bai, B., Stahura, K. A., and Xie, Z. (2012). A social network analysis of overseas tourist movement patterns in Beijing: The impact of the Olympic Games. International Journal of Tourism Research, 2012(14), 469-484. https://doi.org/10.1002/jtr.876
  29. Lewis, C. (2017). How China surged ahead in mobile - and what the West can learn. Retrieved from https://www.marketingweek.com/2017/01/31/china-mobile-commerce/ Accessed on 21 June 2019.
  30. Li, L., Lee, K. Y., and Yang, S. B. (2018). Exploring the effect of heuristic factors on the popularity of user-curated 'Best places to visit' recommendations in an online travel community. Information Processing & Management. Online Published.
  31. Li, X., Meng, F., and Uysal, M. (2008). Spatial pattern of tourist flows among the Asia-Pacific countries: An examination over a decade. Asia Pacific Journal of Tourism Research, 13(3), 229-243. https://doi.org/10.1080/10941660802280323
  32. Mansfeld, Y. (1990). Spatial patterns of International tourist flows: towards a theoretical framework. Progress in Human Geography, 14(3), 372-390. https://doi.org/10.1177/030913259001400303
  33. McKercher, B., and Lew, A. A. (2004). Tourist flows and the spatial distribution of tourists. A Companion to Tourism, 36-48.
  34. Middleton, V. T., and Hawkins, R. (1998). Sustainable tourism: A marketing perspective. Routledge.
  35. Morrison, A. M., Hsieh, S., and T O'Leary, J. (1994). A comparison of the travel arrangements of international travelers from France, Germany and the UK. Tourism Management, 15(6), 451-463. https://doi.org/10.1016/0261-5177(94)90066-3
  36. Nam, Y. (2015). Institutional network structure of corporate stakeholders regarding global corporate social responsibility issues. Quality & Quantity, 49(3), 1063-1080. https://doi.org/10.1007/s11135-014-0035-6
  37. Nam, Y., and Barnett, G. A. (2011). Globalization of technology: Network analysis of global patents and trademarks. Technological Forecasting and Social Change, 78(8), 1471-1485. https://doi.org/10.1016/j.techfore.2011.06.005
  38. Nam, Y., Barnett, G. A., and Kim, D. (2014). Corporate hyperlink network relationships in global corporate social responsibility system. Quality & Quantity, 48(3), 1225-1242.
  39. Otte, E., and Rousseau, R. (2002). Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441-453. https://doi.org/10.1177/016555150202800601
  40. Pearce, P. L. (1990). The Backpacker Phenomenon: Preliminary Answers to Basic Questions. Department of Tourism, James Cook University of North Queensland: Douglas, Australia.
  41. Piro, G., Cianci, I., Grieco, L. A., Boggia, G., and Camarda, P. (2014). Information centric services in smart cities. Journal of Systems and Software, 88, 169-188. https://doi.org/10.1016/j.jss.2013.10.029
  42. Rogers, E. M., and Kincaid, D. L. (1981). Communication networks: Toward a new paradigm for research. The Free Press: NY, USA.
  43. Scott, J. (2000). Social Network Analysis: A Handbook, 2nd ed. Sage: Thousand Oaks, CA, USA.
  44. Shih, H. Y. (2006). Network characteristics of drive tourism destinations: An application of network analysis in tourism. Tourism Management, 27(5), 1029-1039. https://doi.org/10.1016/j.tourman.2005.08.002
  45. U.S. Travel Association (2015). Fact sheet: International inbound travel to the U.S. Retrieved from https://www.ustravel.org/system/files/Media%20Root/Document/Research_Fact-Sheet_International-Inbound.pdf/ Accessed on 2 February 2019.
  46. Vogt, J. W. (1976). Wandering: Youth and travel behavior. Annals of Tourism Research, 4(1), 25-41. https://doi.org/10.1016/0160-7383(76)90051-7
  47. Walter, C. K., and Tong, H. M. (1977). A local study of consumer vacation travel decisions. Journal of Travel Research, 15(4), 30-34. https://doi.org/10.1177/004728757701500406
  48. Wasserman, S., and Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.
  49. Xinhua (2018). Los Angeles welcomes record 1.1 million Chinese visitors in 2017. Retrieved from http://www.chinadaily.com.cn/a/201801/11/WS5a56d97ba3102e5b17374304.html/Accessed on 23 December 2018.
  50. Yang, O. L. W., Hui-Min, G. U., and Ryan, C. (2009). Itinerary planning and structured travel: preferences by outbound Chinese holidaymakers. Anatolia, 20(1), 119-133. https://doi.org/10.1080/13032917.2009.10518899
  51. Yoshioka, W. (2018). Hawaii tourism authority: chasing Chinese millennials. Retrieved from http://www.hawaiipublicradio.org/post/hawaii-tourism-authority-chasing-chinese-millennials/ Accessed on 22 December 2018.
  52. Zhou, W. (2017). Over 1m Chinese tourists to visit NY in 2018. Retrieved from http://www.chinadaily.com.cn/world/2017xivisitsfinlandandus/2017-04/08/content_28841394.htm Accessed on 5 February 2019.