*Result*: Exploring the sustainable packaging sector through European companies' LinkedIn profiles with unsupervised machine learning.

Title:
Exploring the sustainable packaging sector through European companies' LinkedIn profiles with unsupervised machine learning.
Authors:
Tsironis G; School of Production Engineering and Management, Technical University of Crete, Chania, Greece., Krauter V; Institute of Packaging and Resource Management, Department Applied Life Sciences, University of Applied Sciences, Vienna, Austria., Tsagarakis KP; School of Production Engineering and Management, Technical University of Crete, Chania, Greece. Electronic address: ktsagarakis@tuc.gr.
Source:
Journal of environmental management [J Environ Manage] 2026 Feb 01; Vol. 399, pp. 128589. Date of Electronic Publication: 2026 Jan 14.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Academic Press Country of Publication: England NLM ID: 0401664 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-8630 (Electronic) Linking ISSN: 03014797 NLM ISO Abbreviation: J Environ Manage Subsets: MEDLINE
Imprint Name(s):
Original Publication: London ; New York, Academic Press.
MeSH Terms:
Product Packaging* , Unsupervised Machine Learning*, Europe ; Machine Learning
Contributed Indexing:
Keywords: LinkedIn; Machine learning; Packaging; Sustainability; Topic modelling
Entry Date(s):
Date Created: 20260115 Date Completed: 20260129 Latest Revision: 20260129
Update Code:
20260130
DOI:
10.1016/j.jenvman.2026.128589
PMID:
41539251
Database:
MEDLINE

*Further Information*

*The rapidly increasing demand for goods and services has led to increased use of packaging for products. Production and consumption practices are critical for environmental preservation as they directly impact pollutants, emissions, and waste generation. This study investigates 516 LinkedIn profiles of entities registered as "companies" that include the term "Sustainable Packaging" in any section of their profiles and whose location filter is set to "Europe". Two unsupervised machine learning approaches, HDBSCAN and Latent Dirichlet Allocation (LDA), are employed to analyse a dataset of company descriptions focusing on the sustainable packaging sector. The first topic emphasizes sustainability across various business operations and product development aspects. The second topic shares many core terms with the first, such as "packaging," "sustainable," and "product," indicating a general thematic overlap. However, it highlights how companies leverage sustainability as a key component of their brand identity, particularly in markets like cosmetics and organic products.
(Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.)*

*Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.*