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A behavioral analysis of web sharers and browsers in Hong Kong using targeted association rule mining

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  • Rong, Jia
  • Vu, Huy Quan
  • Law, Rob
  • Li, Gang

Abstract

With the widespread use of Internet technology, electronic word-of-mouth [eWOM] communication through online reviews of products and services has a strong influence on consumer behavior and preferences. Although prior research efforts have attempted to investigate the behavior of users regarding the sharing of personal experiences and browsing the experiences of others online, it remains a challenge for business managers to incorporate eWOM effects into their business planning and decision-making processes effectively. Applying a newly proposed association rule mining technique, this study investigates eWOM in the context of the tourism industry using an outbound domestic tourism data set that was recently collected in Hong Kong. The complete profiles and the relations of online experience sharers and travel website browsers are explored. The empirical results are useful in helping tourism managers to define new target customers and to plan more effective marketing strategies.

Suggested Citation

  • Rong, Jia & Vu, Huy Quan & Law, Rob & Li, Gang, 2012. "A behavioral analysis of web sharers and browsers in Hong Kong using targeted association rule mining," Tourism Management, Elsevier, vol. 33(4), pages 731-740.
    • Handle: RePEc:eee:touman:v:33:y:2012:i:4:p:731-740
    DOI: 10.1016/j.tourman.2011.08.006
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    References listed on IDEAS

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    Cited by:

    1. Li, Gang & Law, Rob & Vu, Huy Quan & Rong, Jia, 2013. "Discovering the hotel selection preferences of Hong Kong inbound travelers using the Choquet Integral," Tourism Management, Elsevier, vol. 36(C), pages 321-330.
    2. Tao Liu & Ying Zhang & Huan Zhang & Xiping Yang, 2021. "A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    3. Abbasi, Amir Zaib & Tsiotsou, Rodoula H. & Hussain, Khalil & Rather, Raouf Ahmad & Ting, Ding Hooi, 2023. "Investigating the impact of social media images’ value, consumer engagement, and involvement on eWOM of a tourism destination: A transmittal mediation approach," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    4. Đorđević Aleksandar & Zečević Bojan & Hristov Stančić Branislava, 2016. "Importance of Various Service Types in Hotels - Empirical Analysis," Economic Themes, Sciendo, vol. 54(3), pages 403-423, September.
    5. Zajadacz Alina & Minkwitz Aleksandra, 2020. "Using Social Media Data to Plan for Tourism," Quaestiones Geographicae, Sciendo, vol. 39(3), pages 125-138, September.
    6. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.
    7. Wu, Mao-Ying & Wall, Geoffrey & Pearce, Philip L., 2014. "Shopping experiences: International tourists in Beijing's Silk Market," Tourism Management, Elsevier, vol. 41(C), pages 96-106.
    8. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
    9. Tosporn Arreeras & Mikiharu Arimura & Takumi Asada & Saharat Arreeras, 2019. "Association Rule Mining Tourist-Attractive Destinations for the Sustainable Development of a Large Tourism Area in Hokkaido Using Wi-Fi Tracking Data," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    10. Kim, Hyunwoo & Hong, Suckwon & Kwon, Ohjin & Lee, Changyong, 2017. "Concentric diversification based on technological capabilities: Link analysis of products and technologies," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 246-257.
    11. Versichele, Mathias & de Groote, Liesbeth & Claeys Bouuaert, Manuel & Neutens, Tijs & Moerman, Ingrid & Van de Weghe, Nico, 2014. "Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium," Tourism Management, Elsevier, vol. 44(C), pages 67-81.
    12. Yadegaridehkordi, Elaheh & Nilashi, Mehrbakhsh & Nizam Bin Md Nasir, Mohd Hairul & Momtazi, Saeedeh & Samad, Sarminah & Supriyanto, Eko & Ghabban, Fahad, 2021. "Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques," Technology in Society, Elsevier, vol. 65(C).

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