Evidence map›Paper›PMID 35275909›Full record

ArticlePloS one2022

Optimization of tourism routes in Lushunkou District based on ArcGIS.

Qian Pei, Li Wang, Peng Du, Zhaolan Wang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
3.1field-weighted citation impact, top 10% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Qian PeiSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.ORCID 0000-0002-3003-9278
Li WangSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Peng DuSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Zhaolan WangSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Liaoning Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advancements and developments in China's tourism industry, various autonomous forms of tourism have been gaining prominence. As such, to facilitate tourists and provide them with maximum experience while economizing on time and cost is essential. One approach toward achieving this is the optimization of tourism routes. However, so far the studies on this approach have focused primarily on inland tourist sites and have lacked a geographic perspective. Therefore, this study undertook the tourism resource data of Lushunkou District of 2020, used the ArcGIS accessibility evaluation model to analyze tourism resources, and finally used the Vehicle Routing Problem of network analysis technology to optimize the tourism route of Lushunkou District and obtain the general overall intellectual framework and technical methods for tourism route optimization. The results showed that the ArcGIS accessibility evaluation model could be used to integrate resources in the tourism area before using the Vehicle Routing Problem to optimize the analysis of tourism routes, thereby enabling the separation of different types of tourism. These divisions were based on the Vehicle Routing Problem to optimize routes for one-day and two-day tours. A new method and model for optimization for tourism routes was constructed to provide a basis and reference for the optimization of tourism routes in similar cities. The observations and results of the present study can facilitate the government in developing the tourism industry and maximizing the benefits obtained from them. Further, travel agencies and tourists will have the provision of designing optimum tourism routes.

Indexed as

TourismTravelCitiesIndustry

Identifiers

PMID35275909
PMCPMC8916684
OpenAlexW4221069955

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.