Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data
Descripción del Articulo
The objective of the work was to enhance the competitiveness of e-commerce and to mitigate the disadvantages associated with it, such as the untimely delivery of purchased products. This was to be achieved through the implementation of a proposed methodology in the processes related to the ‘Last Mil...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2024 |
| Institución: | Universidad Peruana de Ciencias Aplicadas |
| Repositorio: | UPC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/676252 |
| Enlace del recurso: | http://hdl.handle.net/10757/676252 |
| Nivel de acceso: | acceso abierto |
| Materia: | Big data Covid-19 Lean logistics Light logistics Productivity SMEs |
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oai:repositorioacademico.upc.edu.pe:10757/676252 |
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| dc.title.es_PE.fl_str_mv |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| title |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| spellingShingle |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data Rojas-García, José Antonio Big data Covid-19 Lean logistics Light logistics Productivity SMEs |
| title_short |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| title_full |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| title_fullStr |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| title_full_unstemmed |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| title_sort |
Enhancement of the distribution process on light logistics SMEs in times post-pandemic Covid-19 with Ukraine-Russia conflict by lean logistics and big data |
| author |
Rojas-García, José Antonio |
| author_facet |
Rojas-García, José Antonio Elias-Giordano, Cynthia Nallusamy, S. Quiroz-Flores, Juan Carlos |
| author_role |
author |
| author2 |
Elias-Giordano, Cynthia Nallusamy, S. Quiroz-Flores, Juan Carlos |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Rojas-García, José Antonio Elias-Giordano, Cynthia Nallusamy, S. Quiroz-Flores, Juan Carlos |
| dc.subject.es_PE.fl_str_mv |
Big data Covid-19 Lean logistics Light logistics Productivity SMEs |
| topic |
Big data Covid-19 Lean logistics Light logistics Productivity SMEs |
| description |
The objective of the work was to enhance the competitiveness of e-commerce and to mitigate the disadvantages associated with it, such as the untimely delivery of purchased products. This was to be achieved through the implementation of a proposed methodology in the processes related to the ‘Last Mile’, leveraging Big Data and Lean Logistics to boost the productivity of light logistics SMEs (small and medium-sized enterprises). To identify the conditions impacting the distribution processes, a study was conducted on a population of 750 S MEs, utilizing a sample of 255 companies through stratified probabilistic sampling. The research spanned the years 2022 and 2023. The methodology advocated in this study combines Lean Logistics and Big Data to enhance the supply chain's efficiency and profitability for SMEs engaged in light logistics, amidst the post-pandemic landscape and the conflict between Ukraine and Russia. This methodology was structured into three stages: firstly, the organization of the customer shipment database; secondly, the cleaning of this database to pinpoint records scheduled for distribution; and thirdly, the assignment of delivery rates and probabilities using historical delivery outcomes. The findings suggested that the integration of Lean Logistics and Big Data offers a viable solution for improving the supply chain efficiency and profitability for light logistics SMEs during the post-pandemic period and amidst the Ukraine-Russia conflict. This research's originality is underscored by its novel approach of merging Lean Logistics and Big Data to fortify the supply chain efficiency and profitability for SMEs in light logistics, a synergy not previously identified in existing literature. |
| publishDate |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-10-28T02:15:05Z |
| dc.date.available.none.fl_str_mv |
2024-10-28T02:15:05Z |
| dc.date.issued.fl_str_mv |
2024-01-01 |
| dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.ssaho.2024.100945 |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10757/676252 |
| dc.identifier.eissn.none.fl_str_mv |
25902911 |
| dc.identifier.journal.es_PE.fl_str_mv |
Social Sciences and Humanities Open |
| dc.identifier.eid.none.fl_str_mv |
2-s2.0-85192889688 |
| dc.identifier.scopusid.none.fl_str_mv |
SCOPUS_ID:85192889688 |
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S2590291124001426 |
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0000 0001 2196 144X |
| identifier_str_mv |
10.1016/j.ssaho.2024.100945 25902911 Social Sciences and Humanities Open 2-s2.0-85192889688 SCOPUS_ID:85192889688 S2590291124001426 0000 0001 2196 144X |
| url |
http://hdl.handle.net/10757/676252 |
| dc.language.iso.es_PE.fl_str_mv |
eng |
| language |
eng |
| dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International |
| dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.format.es_PE.fl_str_mv |
application/pdf |
| dc.publisher.es_PE.fl_str_mv |
Elsevier Ltd |
| dc.source.none.fl_str_mv |
reponame:UPC-Institucional instname:Universidad Peruana de Ciencias Aplicadas instacron:UPC |
| instname_str |
Universidad Peruana de Ciencias Aplicadas |
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UPC |
| institution |
UPC |
| reponame_str |
UPC-Institucional |
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UPC-Institucional |
| dc.source.journaltitle.none.fl_str_mv |
Social Sciences and Humanities Open |
| dc.source.volume.none.fl_str_mv |
10 |
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To identify the conditions impacting the distribution processes, a study was conducted on a population of 750 S MEs, utilizing a sample of 255 companies through stratified probabilistic sampling. The research spanned the years 2022 and 2023. The methodology advocated in this study combines Lean Logistics and Big Data to enhance the supply chain's efficiency and profitability for SMEs engaged in light logistics, amidst the post-pandemic landscape and the conflict between Ukraine and Russia. This methodology was structured into three stages: firstly, the organization of the customer shipment database; secondly, the cleaning of this database to pinpoint records scheduled for distribution; and thirdly, the assignment of delivery rates and probabilities using historical delivery outcomes. The findings suggested that the integration of Lean Logistics and Big Data offers a viable solution for improving the supply chain efficiency and profitability for light logistics SMEs during the post-pandemic period and amidst the Ukraine-Russia conflict. 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13.890581 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).