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Mapping barriers and challenges to digitalization in a circular economic model

Grant number: 20/14462-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): March 01, 2021
Effective date (End): February 28, 2022
Field of knowledge:Engineering - Production Engineering
Principal researcher:Janaina Mascarenhas Hornos da Costa
Grantee:Ana Caroline Vieira Lobo
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil


The Circular Economy economic model, which can be translated into strategies to reduce, reuse and recycle resources, has stood out as an alternative to traditional production and consumption practices. It has potential to unite and direct governmental, academic and corporate efforts, because it is associated with both reductions in environmental impacts and new value propositions for companies. Recent studies have indicated that digital technologies incorporation can support companies in the transition from the usual to the circular model. Digitalization benefits circular strategies, such as life product extension and reverse logistics, and it enables new sustainable businesses, such as product sharing systems and industrial symbiosis. However, there are problems in this process that need to be solved. The state of the art regarding the barriers and challenges to the digitalization of circular systems, as well the solutions that have been tried, has not yet been characterized. This information is relevant for both the evolution of academic research and market players interested in enabling circular business. Thus the objective of this research is to systematize the published results on the use of digital technologies in circular strategies, identifying barriers to their implementation and solution proposals. Adopted methodology will be the systematic literature review, adapted for management area studies. Evaluating results method will be the content analysis, considering an inductive approach. MAXQDA qualitative research support software will be used in the coding, analysis and synthesis of the data.

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