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Online tourist behavior of the net generation: an empirical analysis in Taiwan based on the AISAS model

Online tourist behavior of the net generation: an empirical analysis in Taiwan based on the AISAS model

Xue, Lin-Lin, Shen, Ching-Cheng, Morrison, Alastair M. ORCID: 0000-0002-0754-1083 and Kuo, Li-Wen (2021) Online tourist behavior of the net generation: an empirical analysis in Taiwan based on the AISAS model. Sustainability, 13 (5):2781. ISSN 2071-1050 (doi:https://doi.org/10.3390/su13052781)

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Abstract

This study was intended to investigate the online behavior of Taiwan’s Net Generation (born between 1977 and 1997) based on Dentsu’s AISAS (Attention-Interest-Search-Action-Share) model. A conceptual framework and several hypotheses were developed and tested. A questionnaire survey was conducted in Taiwan in 2018 with 338 valid responses being received. The data were analyzed through linear regression analysis with learning and growth set as the dependent variable. Information search was the key action variable and especially during travel. Attention and interest had significant indirect influences on actions, which impacted sharing, learning, and growth. Learning and growth and action increased sharing. Post-travel sharing stimulated attention and was a catalyst for another cycle of AISAS. This research intended to fill a gap in the literature by examining the relationships among stages in the online purchase and consumption of travel products and services.

Item Type: Article
Uncontrolled Keywords: Net generation; learning and growth; AISAS model; Engel-Kollat-Blackwell (EKB) consumer decision model; information search before travel; information search during travel; sharing
Subjects: G Geography. Anthropology. Recreation > GV Recreation Leisure
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Department of Marketing, Events & Tourism
Related URLs:
Last Modified: 05 Oct 2021 15:58
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/33804

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