Open Access

Application of experience economy and recommendation algorithm in tourism reuse of industrial wasteland

Yanbin Wu
Yanbin Wu
, 
Zheng Huo
Zheng Huo
, 
Wentao Xing
Wentao Xing
, 
Zhaoheng Ma
Zhaoheng Ma
 and 
Hooreya Mohamed Ahmed Aldeeb
Hooreya Mohamed Ahmed Aldeeb
   | Oct 29, 2021
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Published Online: Oct 29, 2021
Page range: 227 - 238
Received: Mar 22, 2021
Accepted: Jun 29, 2021
DOI: https://doi.org/10.2478/amns.2021.2.00039
Keywords
© 2021 Yanbin Wu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Sample UTP graph and adjacency matrixes: (a) UTP graph; (b) U-T matrix; (c) T-P matrix. UTP, user-tag-project.
Sample UTP graph and adjacency matrixes: (a) UTP graph; (b) U-T matrix; (c) T-P matrix. UTP, user-tag-project.

Fig. 2

Hit ratio changes for different α values: (a) TripAdvisor dataset and (b) CiteULike dataset. R-UTP, recommendation-user-tag-project.
Hit ratio changes for different α values: (a) TripAdvisor dataset and (b) CiteULike dataset. R-UTP, recommendation-user-tag-project.

Fig. 3

Recall ratio changes with |P|: (a) TripAdvisor dataset (α=0.3); (b) CiteULike dataset (α=0.4). R-UTP, recommendation-user-tag-project.
Recall ratio changes with |P|: (a) TripAdvisor dataset (α=0.3); (b) CiteULike dataset (α=0.4). R-UTP, recommendation-user-tag-project.

Fig. 4

Relationship between α and novelty: (a) TripAdvisor dataset; (b) CiteULike dataset.
Relationship between α and novelty: (a) TripAdvisor dataset; (b) CiteULike dataset.

Multiple linear regression.

Variable Unstandardised coefficient Standardised coefficient β t Sig
β Standard error
Tourism signs 0.180 0.045 0.213 3.163 0.000
Theme posters 0.054 0.056 0.060 0.861 0.197
Advertising 0.183 0.048 0.254 3.697 0.000
News coverage 0.051 0.060 0.062 0.852 0.397
Hotspot-based marketing 0.173 0.045 0.213 3.612 0.000
Website promotion –0.026 0.040 –0.049 –0.838 0.401
Sightseeing 0.003 0.049 0.005 0.003 0.997
Object display 0.015 0.051 0.022 0.312 0.744
Knowledge distribution 0.071 0.045 0.091 1.191 0.197
Interactive experience 0.189 0.049 0.201 3.510 0.001
Product purchases –0.026 0.047 –0.063 –0.547 0.689
Tour guides 0.016 0.058 0.019 0.276 0.897
Service staff numbers 0.033 0.061 0.046 0.568 0.546
Visitors –0.020 0.062 –0.023 –0.317 0.752
Landscape features 0.081 0.061 0.097 1.340 0.175
Infrastructure 0.027 0.058 0.035 0.452 0.675
Supporting facilities –0.034 0.048 –0.052 –0.703 0.483
Neighbouring attractions 0.181 0.046 0.223 3.299 0.000
Government support 0.084 0.047 0.125 0.918 0.071
Industry alliance 0.035 0.057 0.046 0.658 0.510
Tourism cooperation 0.008 0.060 0.011 0.133 0.895

Experience economy factor analysis.

Dimensions Variables Factor loading
1 2 3 4
Visual signs Tourism signs 0.839
Theme posters 0.716
Media Advertising 0.661
News coverage 0.643
Hotspot-based marketing 0.502
Website promotion 0.543
Service process Sightseeing 0.809
Object display 0.419
Knowledge distribution 0.511
Interactive experience 0.798
Product purchases 0.344
Personnel characteristics Tour guides 0.598
Service staff 0.661
Visitors 0.398
Spatial surroundings Landscape features 0.801
Infrastructure 0.702
Supporting facilities 0.698
Neighbouring attractions 0.809
External associations Government support 0.344
Industry alliance 0.399
Tourism cooperation 0.609
eISSN:
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Language:
English
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Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics
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