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Data-Driven Information Resource Optimization for Cultural Tourism

Fuji Lan et al.

Information Resources Management Journal2026https://doi.org/10.4018/irmj.401115article
AJG 1ABDC C
Weight
0.50

What the paper says

Against the backdrop of global smart tourism, traditional cultural tourism faces limitations: disconnected technologies, lack of data-driven personalization, and no real-time regulation. This study proposed an artificial intelligence (AI)-driven framework integrating digital intellectual property, augmented reality, and location-based entertainment (LBE), with three innovations: a closed-loop AI model for multi-dimensional information resource collection/classification/processing/visualization/monitoring, a discrete AI model resolving AR-LBE compatibility, and an embedded real-time monitoring module. Post-optimization errors (E, OUT) drop to ≤4% (vs. 5.51%-14.80% pre-optimization). Core variables (cultural tourism resources, consumer willingness, technical degree) are independent (Q<1%). LBE/digital intellectual property models outperform traditional ones in satisfaction; top 30 Chinese scenic spots widely adopt them. The experimental group's score is 15-20 points higher. This framework upgrades cultural tourism tech and provides real-time decision tools.

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https://doi.org/https://doi.org/10.4018/irmj.401115

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@article{fuji2026,
  title        = {{Data-Driven Information Resource Optimization for Cultural Tourism}},
  author       = {Fuji Lan et al.},
  journal      = {Information Resources Management Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/irmj.401115},
}

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Data-Driven Information Resource Optimization for Cultural Tourism

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.