Evidence map›Paper›PMID 36570019›Full record

ArticleSustainable cities and society2021

Tourism research after the COVID-19 outbreak: Insights for more sustainable, local and smart cities.

Luis-Alberto Casado-Aranda, Juan Sánchez-Fernández, Ana-Belén Bastidas-Manzano

Abstract read
In one paragraph

Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Do Greener Urban Streets Provide Better Emotional Experiences? An Experimental Study on Chinese Tourists.International journal of environmental research and public health · 2022
    Trial
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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

3 authors.

Luis-Alberto Casado-ArandaDepartment of Marketing and Market Research, University of Granada, Campus Universitario Cartuja, 18011, Granada, Spain.
Juan Sánchez-FernándezDepartment of Marketing and Market Research, University of Granada, Campus Universitario Cartuja, 18011, Granada, Spain.
Ana-Belén Bastidas-ManzanoDepartment of Tourism and Marketing, Madrid Open University, Vía de Servicio A-6, 15, 28400 Collado Villalba, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents the results of a bibliometric analysis of academic research dealing with COVID-19 in the area of city destination development from 1 December 2019 to 31 March 2021. Particularly, by means of SciMAT software, it identifies, quantifies, and visually displays the main research clusters, thematic structure and emerging trends that city and tourism planners will face in the new normal. The search revealed that social media and smart tourism are the themes with the greatest potential; sustainable cities, local destination development, changes in tourist behavior, and tourists' risk perception are underdeveloped streams with enormous relevance and growth in the new normal. Research on the effects of COVID-19 on citizen health and its economic impact on the tourism industry and cities are intersectional and highly developed topics, although of little relevance. The current study also identifies the challenges of destination research for planners and proposes future research directions. Consequently, this paper contributes to the existing literature on COVID-19 and sustainable cities, as it develops a critical examination of the extant research and points out the research gaps that must be filled by future studies.

Indexed as

COVID-19Co-word analysisLocal developmentSmart citiesSustainable citiesTourism industry

Identifiers

PMID36570019
PMCPMC9760270

What OpenQuestion holds

Textmetadata
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.