| Title |
Assessing the Role of Big Data and the Internet of Things on the Transition to Circular Economy: Part I An extension of the ReSOLVE framework proposal through a literature |
| ID_Doc |
17072 |
| Authors |
Nobre, GC; Tavares, E |
| Title |
Assessing the Role of Big Data and the Internet of Things on the Transition to Circular Economy: Part I An extension of the ReSOLVE framework proposal through a literature |
| Year |
2020 |
| Published |
Johnson Matthey Technology Review, 64, 1 |
| DOI |
10.1595/205651319X15643932870488 |
| Abstract |
The debate about circular economy (CE) is increasingly present in the strategic agenda of organisations around the world, being driven by government agencies and general population pressures, or by organisations' own vision for a sustainable future. This is due in part to the increasing possibility of turning original theoretical CE proposals into real economically viable initiatives, now possible with modern technology applications such as big data and the internet of things (IoT). Information technology (IT) professionals have been called upon to incorporate technology projects into their strategic plans to support their organisations' transition to CE, but a structured framework with the necessary IT capabilities still lacks. This study focuses on taking the first step towards this path, by extending the technology attributes present on the existing Ellen MacArthur Foundation (EMF) Regenerate, Share, Optimise, Loop, Virtualise and Exchange (ReSOLVE) framework. The research was conducted based on an extensive literature review through 226 articles retrieved from Scopus (R) and Web of Science (TM) databases, which were triangulated, validated and complemented with content analysis using the 'R' statistical tool, grey literature research and inputs from specialists. Part I describes the introduction and methods used in this study. |
| Author Keywords |
|
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000541122300004 |
| WoS Category |
Chemistry, Physical |
| Research Area |
Chemistry |
| PDF |
https://doi.org/10.1595/205651319x15643932870488
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