Models used to characterise blockchain features. A systematic literature review and bibliometric analysis

Rico-Peña, Juan Jesús, Arguedas-Sanz, Raquel y López-Martín, Carmen . (2023) Models used to characterise blockchain features. A systematic literature review and bibliometric analysis. Technovation, 123 (2023)

Ficheros (Some files may be inaccessible until you login with your e-spacio credentials)
Nombre Descripción Tipo MIME Size
Rico_Pena_Juan_Jesus_Models.pdf Rico_Pena_Juan Jesus Models.pdf application/pdf 9.00MB

Título Models used to characterise blockchain features. A systematic literature review and bibliometric analysis
Autor(es) Rico-Peña, Juan Jesús
Arguedas-Sanz, Raquel
López-Martín, Carmen
Materia(s) Economía
Abstract Blockchain has emerged as an innovative technology with potential to transform business management, through operational efficiency improvements. Nevertheless, several performance and vulnerability issues have been identified for the different typologies supporting the wide range of blockchain-based applications currently implemented in different domains. A variety of analytical and empirical models are being used to evaluate the issues associated with the different blockchain typologies, enabling systematic analyses of the corresponding efficiency impact, and technical or economic threats. A thorough systematic literature review of these models has been performed, followed by a detailed assessment on the way these models have been employed, and the target parameters and applications evaluated (336 research selected and analysed). We propose a co-classification of these models, allowing us to identify which ones are employed to a greater extent to address the different blockchain issues in scientific research. In a second step, a bibliometric analysis on the selected research is conducted, offering a complementary overview of the status of and trends in blockchain modelling, including the most prolific authors and leading contributing countries to the topic. The main outcome and contribution of the paper is the provision of a broad overview on how blockchain issues have been analytically tackled, through the synthesis and meta-analysis of the models used in the scientific literature since the inception of blockchain technology. The results have two main direct applications, firstly supporting novel vulnerability and performance analyses of existing blockchain applications by providing historical information on the models used so far, as well as the key parameters and typology of the blockchain-based applications evaluated. Secondly, in the implementation of new applications, by allowing the recognition of key issues identified that are associated with the different blockchain typologies and to determine the most suitable models to analyse the weaknesses and risks of the alternative designs under evaluation for these new implementations.
Palabras clave Blockchain
Markov chain
Directed graph
Machine learning
Game theory
Editor(es) Elsevier
Fecha 2023-05-01
Formato application/pdf
Identificador bibliuned:DptoEEC-FCEE-Articulos-Rarguedas-0001
http://e-spacio.uned.es/fez/view/bibliuned:DptoEEC-FCEE-Articulos-Rarguedas-0001
DOI - identifier https://doi.org/10.1016/j.technovation.2023.102711
ISSN - identifier 1879-2383
Nombre de la revista Technovation
Número de Volumen 123
Publicado en la Revista Technovation, 123 (2023)
Idioma eng
Versión de la publicación acceptedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales The published version of this article, first published in Technovation, is available online at the publisher's website: Elsevier, https://doi.org/10.1016/j.technovation.2023.102711
Notas adicionales La versión publicada de este artículo, publicado por primera vez en Technovation, está disponible en línea en el sitio web del editor: Elsevier, https://doi.org/10.1016/j.technovation.2023.102711

 
Versiones
Versión Tipo de filtro
Contador de citas: Google Scholar Search Google Scholar
Estadísticas de acceso: 107 Visitas, 18 Descargas  -  Estadísticas en detalle
Creado: Mon, 20 Nov 2023, 21:04:34 CET