Analytical Techniques for Understanding and Enhancing Consumer Sustainability Behaviour

This research explores the factors influencing Generation Z and Millennial consumers’ engagement with sustainable fashion, particularly within collaborative consumption models. By applying machine learning techniques, the study segments consumers based on their sustainability behaviors and identifies key drivers and barriers, such as cost, quality, and environmental awareness. Clustering methods are also employed to uncover patterns in consumer preferences and brand attributes, enhancing market segmentation. Additionally, robust optimization techniques are used to improve the reliability of predictive models. The ultimate goal is to provide brands with insights to better align their marketing efforts with environmentally conscious values and foster a broader shift toward sustainability.

Faculty Supervisor:

Amir Ardestani-Jaafari

Student:

Partner:

SKEMA Business School

Discipline:

Business

Sector:

Sustainability & the Environment; Other

University:

The University of British Columbia - Okanagan

Program: