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Digital technologies and the circular economy: charting a shared journey toward sustainable development

Sep 2026 · International Journal of Productivity and Performance Management · Vol 75, pp. 199-239 · 0 citations · 104 references

TL;DR

The study demonstrates that artificial intelligence (AI) is developing intelligent devices and processes that analyse large datasets to identify patterns, verify and report on organisational activity, enabling real-time decision-making, thus highlighting significant gaps in the literature.

Abstract

The research aims to identify the practical benefits of implementing Digital Technologies (DTs) and the Circular Economy (CE) for Sustainable Development (SD) by enabling informed decision-making. The research consists of 148 articles, including quantitative (61), qualitative (52) and literature review studies (35), covering various fields such as ecology, supply chain management, marketing and circular business models, sourced from WOS, Scopus and Direct Science. Science-mapping techniques have been employed to analyse citations in published articles, measure their impact and identify leading and emerging trends in the literature. The study demonstrates that artificial intelligence (AI) is developing intelligent devices and processes that analyse large datasets to identify patterns, verify and report on organisational activity, enabling real-time decision-making. Furthermore, companies that excel in CE principles – a system focused on minimising waste and making the most of resources – are more likely to engage with Industry 4.0, which refers to the integration of DTs such as the Internet of Things (IoT), automation and data exchange in manufacturing. This subsequently results in improved financial outcomes and more rational decision-making. In addition, the research highlights limited connections within Industry 5.0 – an industry phase emphasising collaboration between humans and machines – with a particular focus on CE and SD. This research provides a unique overview in exploring DTs and CE across environmental performance, financial metrics, accounting relationships and the impact of computer-based analysis on decision-making, thus highlighting significant gaps in the literature. Moreover, this study offers practitioners interesting insights to improve financial outcomes, resource use, DT and CE adoption and decision-making processes.

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