5th International Conference on Recycling and Reuse (R&R 2024), İstanbul, Türkiye, 5 - 06 Temmuz 2024
Examining and comprehending the
elements that impact waste recycling behaviour is crucial for enhancing domestic
waste management separation practices. The recycling of used products
represents a vital improvement in sustainability for households and related locations.
Domestic waste separation relies on residents, whose behaviour in waste
separation significantly influences the outcome of waste management efforts,
whether successful or unsuccessful for the related country. While domestic
waste separation is common in numerous countries, its adoption remains
uncommon in Turkey. Even though there is limited research on household
recycling behaviour in metropolitan cities such as
Istanbul, gaining insight into these factors can pave the way for more
efficient recycling programs. To this end, this paper investigates the
factors altering the behaviour of individuals in the separation of domestic
waste in a system for the collection of recyclable waste in Istanbul, Türkiye.
The waste recycling behaviour study data was collected by Istanbul
Municipality with a detailed questionnaire (face to face) to 50000
people (2023). Correspondence analysis, also known as reciprocal averaging,
is a valuable multivariate statistical technique in data science used to
visualize and understand relationships between categories. It involves
creating a graph to display the relationships between two or more data
points, providing a clear visual representation of the data. With this aim, Correspondence
analysis with Euclid Distance was used to examine household domestic
recycling behaviours, visualize the current behavioural direction with the
help of two-dimensional maps, and display the cluster structures constructed.
As a result, district-based waste separation behaviours have been determined,
and it is aimed to reveal the structures of these reasonings with district
characteristics.
Keywords: Waste management; Recycling; Recycling behaviour; Correspondence analysis |