Hasan, Rajibul and Abdunurova, Assem and Wang, Wenwen and Zheng, Jiawei and Shams, S.M. Riad
(2020)
Using deep learning to investigate digital behavior in culinary tourism.
Journal of Place Management and Development, 14 (1).
pp. 43-65.
ISSN 1753-8335
Abstract
Purpose – The purpose of this study is to gather insights into digital consumer behaviour related to Chinese
restaurents by examining visual contents on Tripadvisor platform.
Design/methodology/approach – Using the deep learning approach, this research assessed consumer-posted online content of dining experiences by implementing image analysis and clustering. Text mining
using word cloud analysis revealed the most frequently repeated keywords.
Findings – First, 4,000 photos of nine Chinese restaurants posted on Tripadvisor’s website were analyzed
using image recognition via Inception V3 and Google’s deep learning network; this revealed 12 hierarchical
image clusters. Then, an open-questionnaire survey of 125 Chinese respondents investigated consumers’
information needs before visiting a restaurant and after purchasing behavior (motives to share).
Practical implications – This study contributes to culinary marketing development by introducing a
new analysis methodology and demonstrating its application by exploring a wide range of keywords and
visual images published on the internet.
Originality/value – This research extends and contributes to the literature regarding visual user-generated content in culinary tourism.
| Item Type: |
Article
|
| Keywords: |
Deep learning; Text mining; Image analysis; Culinary tourism;
Digital consumer behavior; Online contents; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
15939 |
| Identification Number: |
https://doi.org/10.1108/JPMD-03-2020-0022 |
| Depositing User: |
Rajibul Hasan
|
| Date Deposited: |
11 May 2022 10:30 |
| Journal or Publication Title: |
Journal of Place Management and Development |
| Publisher: |
Emerald |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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