Evaluating Customer Perspectives on Sustainability Advertising in the Fashion Retail Sector Using Machine Learning

Luca Rossi (), Maria Giovina Pasca (), Gabriella Arcese () and Dario Barberini ()
Additional contact information
Luca Rossi: Niccolò Cusano University, Department of Economic, Psychological, Communication, Education and Motor Sciences
Maria Giovina Pasca: Niccolò Cusano University, Department of Economic, Psychological, Communication, Education and Motor Sciences
Gabriella Arcese: Niccolò Cusano University, Department of Economic, Psychological, Communication, Education and Motor Sciences
Dario Barberini: Niccolò Cusano University, Department of Economic, Psychological, Communication, Education and Motor Sciences

Chapter Chapter 24 in Human Resource Development for Sustainability and Social Responsibility, 2026, pp 339-352 from Springer

Abstract: Abstract This paper explores how sustainability-themed advertising influences consumer perceptions and purchase intentions in the fashion retail sector, specifically focusing on the Italian market. Using a mixed-method approach, the study integrates quantitative survey data, biometric facial recognition, and natural language processing (NLP) to assess the impact of advertising elements such as credibility, transparency, and emotional engagement. A sample of 120 Italian consumers viewed a sustainability-oriented promotional video and responded to structured questions and open-ended prompts while being recorded via webcam. Statistical analyses, including regression and machine learning models (Lasso, Random Forest), revealed that perceived credibility (β = 0.41, p

Keywords: Sustainability advertising; Consumer behavior; Machine Learning (ML); Emotional engagement; Fashion retail sector (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-032-09683-8_24

Ordering information: This item can be ordered from
http://www.springer.com/9783032096838

DOI: 10.1007/978-3-032-09683-8_24

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().