Exploring circular economy in the United Kingdom based on LinkedIn data from company profiles

This work explores the landscape of Circular Economy within the business domain through an innovative approach to topic modelling applied to 1396 LinkedIn company profiles in the UK. We explore thematic structures within a dataset curated through the LinkedIn search engine prompt for companies related to the Circular Economy. Leveraging Latent Dirichlet Allocation models, we identify topics that encapsulate the essence of circular and sustainable business practices. Our findings unveil key thematic clusters, including "Waste Management and Environmental Impact," highlighting companies at the forefront of waste reduction and eco-conscious industry practices. Another significant cluster, "Sustainable Solutions and Customer-Centric Approach," delves into businesses seamlessly integrating sustainability across product design and customer interactions. Lastly, "Green Technology and Community Building" sheds light on companies excelling in green technology and actively contributing to environmentally responsible global networks. Topic modelling is employed as a powerful tool for unravelling complex business narratives and fostering a holistic approach to sustainable practices.

Authors

Institutions

Publication Details

Journal
Journal of Cleaner Production
Published
2025-03-22
DOI
https://doi.org/10.1016/j.jclepro.2025.145355
Citations
5
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
11.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring circular economy in the United Kingdom based on LinkedIn data from company profiles

G. P. Tsironis, Rylan Cox, Konstantinos Salonitis, Mark Jolly et al.
5 citations
Journal of Cleaner Production
Sustainable Supply Chain Management
11.13
article

Exploring circular economy in the United Kingdom based on LinkedIn data from company profiles

G. P. Tsironis, Rylan Cox, Konstantinos Salonitis, Mark Jolly, Konstantinos P. Tsagarakis
article en
5 citations

Abstract

This work explores the landscape of Circular Economy within the business domain through an innovative approach to topic modelling applied to 1396 LinkedIn company profiles in the UK. We explore thematic structures within a dataset curated through the LinkedIn search engine prompt for companies related to the Circular Economy. Leveraging Latent Dirichlet Allocation models, we identify topics that encapsulate the essence of circular and sustainable business practices. Our findings unveil key thematic clusters, including "Waste Management and Environmental Impact," highlighting companies at the forefront of waste reduction and eco-conscious industry practices. Another significant cluster, "Sustainable Solutions and Customer-Centric Approach," delves into businesses seamlessly integrating sustainability across product design and customer interactions. Lastly, "Green Technology and Community Building" sheds light on companies excelling in green technology and actively contributing to environmentally responsible global networks. Topic modelling is employed as a powerful tool for unravelling complex business narratives and fostering a holistic approach to sustainable practices.

Journal of Cleaner ProductionVol. 503
Democritus University of Thrace (GR), Technical University of Crete (GR), Cranfield University (GB)
Decent work and economic growth
Openalex Percentile: Top 2%
Sustainable Supply Chain Management
11.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.