774
Views
11
CrossRef citations to date
0
Altmetric
Research Articles

Exploration of domestic water demand attitudes using qualitative and quantitative social research methods

, , &
Pages 307-314 | Received 20 May 2015, Accepted 20 Nov 2015, Published online: 01 Feb 2016
 

Abstract

The sustainable evolution of the urban water system requires the recognition of uncertainty embedded in both climate and human behaviour. A challenge that water managers and policy makers need to tackle, is to understand the way the society’s water demand behaviour is affected. The inaccuracy between attitudes and behaviours and the cognitive association of water use to living standards, hinders the projection of society’s response to management’s measures. Thus, it is necessary to identify leverage points, where water demand management policies should aim their efforts. This work presents two parts of a social research held in Athens: quantitative questionnaire gathering information regarding the domestic water demand attitudes and behaviours; and a series of qualitative interviews aimed at exploring in-depth, the domestic water use attitudes, and behaviours. This work presents the design and results of both methods and the combination of the quantitative results with insights from the qualitative work.

Notes

1. In 2012, the NGO MEDSOS conducted an online survey in 11 major cities of Greece, without however publishing results for the Athenian households.

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 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 239.00 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.