ArticleHeliyon2024
Enhancing tourism management through big data: Design and implementation of an integrated information system.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in the tourism business: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Research on intelligent decision support platform for tourism enterprises based on multi-source heterogeneous data fusion.Scientific reports · 2025Article
Corrections and comments
- Retraction · 2025-10-03Computer-Aided Content or Computer-Generated Content · Concerns/Issues about Authorship/Affiliation · Concerns/Issues about Referencing/Attributions · Investigation by Journal/Publisher · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many sectors, particularly traveling, have been profoundly affected by the fast development of big data technologies. This article provides a detailed examination of the development and execution of a Tourism Management Information System (TMIS) that utilizes big data analytics to improve operational effectiveness, gain insights into tourist behavior, and encourage sustainable tourism practices. The system combines data from several sources, including booking systems, social media platforms, and tracking devices, and addresses issues related to data privacy, quality, and integration. The TMIS utilizes statistical information to provide tailored tourist experiences, enhance resource allocation, and aid in long-term planning. The study emphasizes the significance of strong data management, which involves assuring the precision of data and its immediate significance. Additionally, this article examines the potential of big data in promoting a strong and creative tourism industry. It highlights the importance of future studies in exploring sustainable uses of big data and the incorporation of novel technologies, such as artificial intelligence, to improve personalized experiences. The present research highlights the significant and positive influence of big data on the management of tourism. It offers a structured approach for implementing big data in practice and sets the stage for long-term and sustainable growth in the tourism sector.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.