TY - JOUR
T1 - Assessing Data Analytics Capabilities in Retail Organizations
T2 - Insights into Mining, Predictive Analytics and Machine Learning
AU - Pariona-Luque, Rosario
AU - Pacheco, Alex
AU - Vegas-Gallo, Edwin
AU - Castanho, Rui Alexandre
AU - Lema, Fabian
AU - Pacheco-Pumaleque, Liz
AU - Añaños-Bedriñana, Marco
AU - Marin, Wilson
AU - Felix-Poicon, Edwin
AU - Loures, Ana
N1 - Publisher Copyright:
© 2024, World Scientific and Engineering Academy and Society. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Nowadays, implementing data analytics is necessary to improve the collection, evaluation, analysis, and organization of data that allow the discovery of patterns, correlations, and trends that improve knowledge management, development of strategies, and decision-making in the organization. Therefore, this study aims to provide an accurate and detailed assessment of the current state of data analytics in the retail sector, identifying specific areas of improvement to strengthen knowledge management in organizations. The research is applied with a quantitative approach and non-experimental design at a descriptive and propositional level. The survey technique was used, and as a data collection instrument, a questionnaire addressed to 351 employees of companies in the retail sector concerning the variable data analysis with the dimensions of data extraction, predictive analysis, and machine learning and the variable management of the knowledge with the dimensions knowledge creation and knowledge storage. The results show that 52.99% of collaborators indicate that the level of data extraction is terrible, 57.83% indicate that the level of predictive analysis is wrong, and 54.99% express that the level of machine learning is average, which contributes to the implementation of innovative resources and solutions that promote the inclusion of a high-tech approach to address information management problems and contribution to the development of knowledge in an institution.
AB - Nowadays, implementing data analytics is necessary to improve the collection, evaluation, analysis, and organization of data that allow the discovery of patterns, correlations, and trends that improve knowledge management, development of strategies, and decision-making in the organization. Therefore, this study aims to provide an accurate and detailed assessment of the current state of data analytics in the retail sector, identifying specific areas of improvement to strengthen knowledge management in organizations. The research is applied with a quantitative approach and non-experimental design at a descriptive and propositional level. The survey technique was used, and as a data collection instrument, a questionnaire addressed to 351 employees of companies in the retail sector concerning the variable data analysis with the dimensions of data extraction, predictive analysis, and machine learning and the variable management of the knowledge with the dimensions knowledge creation and knowledge storage. The results show that 52.99% of collaborators indicate that the level of data extraction is terrible, 57.83% indicate that the level of predictive analysis is wrong, and 54.99% express that the level of machine learning is average, which contributes to the implementation of innovative resources and solutions that promote the inclusion of a high-tech approach to address information management problems and contribution to the development of knowledge in an institution.
KW - Data analytics
KW - Data extraction
KW - knowledge creation
KW - knowledge management
KW - machine learning
KW - predictive analytics
KW - storage of knowledge
UR - http://www.scopus.com/inward/record.url?scp=85202906900&partnerID=8YFLogxK
U2 - 10.37394/23207.2024.21.126
DO - 10.37394/23207.2024.21.126
M3 - Artículo
AN - SCOPUS:85202906900
SN - 1109-9526
VL - 21
SP - 1546
EP - 1556
JO - WSEAS Transactions on Business and Economics
JF - WSEAS Transactions on Business and Economics
ER -