Evidence map›Paper›PMID 35756132›Full record

ArticleHeliyon2022

Investigating the environmental externalities of tourism development: evidence from Tanzania.

Valensi Corbinian Kyara, Mohammad Mafizur Rahman, Rasheda Khanam

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Valensi Corbinian KyaraSchool of Business, University of Southern Queensland, West Street, Toowoomba, QLD, 4350, Australia.
Mohammad Mafizur RahmanSchool of Business, University of Southern Queensland, West Street, Toowoomba, QLD, 4350, Australia.
Rasheda KhanamSchool of Business, University of Southern Queensland, West Street, Toowoomba, QLD, 4350, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tourism growth is an important component for welfare improvement in the host destination, but it can be associated with environmental degradation. The aim of the current study is to assess the environmental impacts of tourism growth in Tanzania, using time series data for the period 1995-2017. It utilizes ecological footprints as a proxy for environmental damage, tourism receipt as an economic indicator, and primary energy consumption, urban population, and trade openness as control variables. The study employs Autoregressive Distributed Lag Bounds Testing, Vector Error Correction Model (VECM), and Granger causality test for analysis and the Wild Bootstrap approach to check the accuracy of the computed statistics. The VECM Granger causality test shows that in the case of Tanzania, international tourism revenue and trade openness compact environmental degradation, while urbanization and primary energy consumption accelerate it. Besides, while long run cointegration exists among the variables, the environmental Kuznets curve hypothesis was not ascertained in Tanzania. Therefore, Tanzania must adopt more proactive urban planning strategies to achieve sustainable urbanization thereby improving the quality of the environment. Additionally, it is important for Tanzania to make strategic use of trade and tourism receipts, such as investment on renewable energy, to lessen dependence on fossil fuels, and improve environmental sustainability. So, the study opens new policy perspectives with wide international relevancy as outlined in the policy implication section.

Indexed as

Environmental kuznets curve hypothesisEnvironmental qualityTanzaniaTourism developmentVector error correction

Identifiers

PMID35756132
PMCPMC9213710

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.