Studying the Evolution of the ‘Circular Economy’ Concept using Topic Modelling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Circular Economy has gained immense popularity for its perceived capacity to operationalise sustainable development. However, a comprehensive long-term understanding of the concept, characterising its evolution in academic literature, has not yet been provided. As a first step, we apply unsupervised topic models on academic articles to identify patterns in concept evolution. We generate topics using LDA, and investigate topic prevalence over time. We determine the optimal number of topics for the model (k) through coherence scorings and evaluate the topic model results by expert judgement. Specifying k as 20, we find topics in the literature focussing on resources, business models, process modelling, conceptual research and policies. We identify a shift in the research focus of contemporary literature, moving away from the Chinese pre-dominance to a European perspective, alongwith a shift towards micro level interventions, e.g., circular design, business models, around 2014-2015.

Bibliographical metadata

Original languageEnglish
Title of host publicationIDEAL 2019: Intelligent Data Engineering and Automated Learning – IDEAL 2019
Subtitle of host publication20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part II
PublisherSpringer Nature
Pages259-270
Number of pages12
ISBN (Print)978-3-030-33616-5, 978-3-030-33617-2
Publication statusPublished - 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11872
ISSN (Print)0302-9743