3,305
Views
22
CrossRef citations to date
0
Altmetric
Original Articles

A Socioecological Examination of Observing Littering Behavior

, &
Pages 235-253 | Published online: 07 Aug 2017
 

ABSTRACT

Despite evidence of the negative health, environmental, and economic impacts, littering continues to be a problem and therefore warrants ongoing research attention. Guided by a Behavioural Ecological Framework, this study observed individual-, social-, and environmental-level factors on littering behavior across three different parks in Saudi Arabia. A total of 362 individuals were observed over 12 days. Approximately half of all disposals were improper, with litter left on the ground. The most commonly littered object was nuts (29.4%). The findings revealed that environmental factors had a significant impact, including the amount of existing litter, beautification efforts, and distance to rubbish bins, and that the only significant individual factor to have any impact on individual littering behavior was group size. Implications for litter prevention are discussed. Future research opportunities are outlined.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the authorship and/or publication of this article.

Funding

The authors received no financial support for the research and/or authorship of this article.

Additional information

Funding

The authors received no financial support for the research and/or authorship of this article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 688.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.