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Artificial intelligence applications in e-commerce: A bibliometric study from 1995 to 2023 using merged data sources
No full textPurpose: The aim of this study is to conduct a comprehensive review of scientific articles concerning artificial intelligence (AI) applications in electronic commerce through bibliometric analysis.
Theoretical Framework: The current study utilized both the SCOPUS and Web of Science (WoS) databases to enrich the analysis with a wider selection of papers in the field, incorporating an examination of the most cited documents.
Design/Methodology/Approach: The dataset for analysis was selected according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, integrating data from Scopus and WoS through R software, specifically using the biblioshiny library. It includes 8372 papers published from 1995 to 2023. This study's data analysis used two approaches: descriptive analysis to examine the data quantitatively and scientific mapping to explore the intellectual and social structures within the dataset.
Findings: The results reveal significant trends in the application of artificial intelligence in e-commerce, highlighting the rapid growth of interest in this area over the last decade. China emerges as the country with the highest number of citations, with ZHANG Y identified as the most relevant author and HU M as the most cited author. Furthermore, the study identifies prevalent keywords used by the authors, including sentiment analysis and recommendation systems.
Research, Practical & Social Implications: This study underscores the transformative potential of AI in enhancing e-commerce practices, offering insights for both academic researchers and industry professionals by providing valuable perspectives on current trends and contributions.
Originality/Value: The value of the study lies in its comprehensive bibliometric approach, which integrates two major databases to explore AI's applications in e-commerce. This deviation from previous reviews, which often rely on a single database, provides a deeper understanding of the current landscape and future directions in this field.Objetivo: O objetivo deste estudo é realizar uma revisão abrangente de artigos científicos sobre as aplicações de inteligência artificial (IA) no comércio eletrônico por meio de análise bibliométrica.
Referencial teórico: O estudo atual utilizou tanto as bases de dados SCOPUS quanto Web of Science (WoS) para enriquecer a análise com uma seleção mais ampla de artigos no campo, incorporando um exame dos documentos mais citados.
Desenho/metodologia/abordagem: O conjunto de dados para análise foi selecionado de acordo com o framework PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando dados do Scopus e WoS por meio do software R, especificamente utilizando a biblioteca biblioshiny, e inclui 8372 artigos publicados de 1995 a 2023. A análise de dados deste estudo utilizou duas abordagens: análise descritiva para examinar os dados quantitativamente e mapeamento científico para explorar as estruturas intelectuais e sociais dentro do conjunto de dados.
Resultados: Os resultados revelam tendências significativas na aplicação da inteligência artificial no comércio eletrônico, destacando o rápido crescimento do interesse nesta área ao longo da última década. A China emerge como o país com o maior número de citações, com ZHANG Y identificado como o autor mais relevante e HU M como o autor mais citado. Além disso, o estudo identifica palavras-chave prevalentes usadas pelos autores, incluindo análise de sentimento e sistemas de recomendação.
Pesquisa, implicações práticas e sociais: Este estudo destaca o potencial transformador da IA em aprimorar práticas de comércio eletrônico, oferecendo insights tanto para pesquisadores acadêmicos quanto profissionais da indústria, fornecendo perspectivas valiosas sobre tendências atuais e contribuições.
Originalidade/valor: O valor do estudo reside em sua abordagem bibliométrica abrangente, que integra duas bases de dados principais para explorar as aplicações da IA no comércio eletrônico. Esta divergência das revisões anteriores, que frequentemente se baseiam em uma única base de dados, proporciona uma compreensão mais profunda do cenário atual e das direções futuras neste campo.Propósito: El objetivo de este estudio es realizar una revisión exhaustiva de artículos científicos sobre las aplicaciones de la inteligencia artificial (IA) en el comercio electrónico a través de análisis bibliométrico.
Marco teórico: El estudio actual utilizó tanto las bases de datos SCOPUS como Web of Science (WoS) para enriquecer el análisis con una selección más amplia de artículos en el campo, incorporando un examen de los documentos más citados.
Metodología: El conjunto de datos para el análisis fue seleccionado de acuerdo con el marco PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando datos de Scopus y WoS a través del software R, específicamente utilizando la biblioteca biblioshiny, e incluye 8372 artículos publicados desde 1995 hasta 2023. El análisis de datos de este estudio utilizó dos enfoques: análisis descriptivo para examinar los datos cuantitativamente y mapeo científico para explorar las estructuras intelectuales y sociales dentro del conjunto de datos.
Conclusiones: Los resultados revelan tendencias significativas en la aplicación de la inteligencia artificial en el comercio electrónico, destacando el rápido crecimiento del interés en esta área durante la última década. China emerge como el país con el mayor número de citas, con ZHANG Y identificado como el autor más relevante y HU M como el autor más citado. Además, el estudio identifica palabras clave prevalentes utilizadas por los autores, incluyendo análisis de sentimientos y sistemas de recomendación.
Implicaciones de la Investigación: Este estudio subraya el potencial transformador de la IA en mejorar las prácticas de comercio electrónico, ofreciendo ideas tanto para investigadores académicos como profesionales de la industria, proporcionando perspectivas valiosas sobre tendencias actuales y contribuciones.
Originalidad/valor: El valor del estudio radica en su enfoque bibliométrico exhaustivo, que integra dos bases de datos principales para explorar las aplicaciones de la IA en el comercio electrónico. Esta desviación de revisiones anteriores, que a menudo se basan en una sola base de datos, proporciona una comprensión más profunda del panorama actual y las direcciones futuras en este campo
APLICACIONES DE INTELIGENCIA ARTIFICIAL EN EL COMERCIO ELECTRÓNICO: UN ESTUDIO BIBLIOMÉTRICO DE 1995 A 2023 UTILIZANDO FUENTES DE DATOS FUSIONADAS
Get PDFPurpose: The aim of this study is to conduct a comprehensive review of scientific articles concerning artificial intelligence (AI) applications in electronic commerce through bibliometric analysis.
Theoretical Framework: The current study utilized both the SCOPUS and Web of Science (WoS) databases to enrich the analysis with a wider selection of papers in the field, incorporating an examination of the most cited documents.
Design/Methodology/Approach: The dataset for analysis was selected according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, integrating data from Scopus and WoS through R software, specifically using the biblioshiny library. It includes 8372 papers published from 1995 to 2023. This study's data analysis used two approaches: descriptive analysis to examine the data quantitatively and scientific mapping to explore the intellectual and social structures within the dataset.
Findings: The results reveal significant trends in the application of artificial intelligence in e-commerce, highlighting the rapid growth of interest in this area over the last decade. China emerges as the country with the highest number of citations, with ZHANG Y identified as the most relevant author and HU M as the most cited author. Furthermore, the study identifies prevalent keywords used by the authors, including sentiment analysis and recommendation systems.
Research, Practical & Social Implications: This study underscores the transformative potential of AI in enhancing e-commerce practices, offering insights for both academic researchers and industry professionals by providing valuable perspectives on current trends and contributions.
Originality/Value: The value of the study lies in its comprehensive bibliometric approach, which integrates two major databases to explore AI's applications in e-commerce. This deviation from previous reviews, which often rely on a single database, provides a deeper understanding of the current landscape and future directions in this field.Propósito: El objetivo de este estudio es realizar una revisión exhaustiva de artículos científicos sobre las aplicaciones de la inteligencia artificial (IA) en el comercio electrónico a través de análisis bibliométrico.
Marco teórico: El estudio actual utilizó tanto las bases de datos SCOPUS como Web of Science (WoS) para enriquecer el análisis con una selección más amplia de artículos en el campo, incorporando un examen de los documentos más citados.
Metodología: El conjunto de datos para el análisis fue seleccionado de acuerdo con el marco PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando datos de Scopus y WoS a través del software R, específicamente utilizando la biblioteca biblioshiny, e incluye 8372 artículos publicados desde 1995 hasta 2023. El análisis de datos de este estudio utilizó dos enfoques: análisis descriptivo para examinar los datos cuantitativamente y mapeo científico para explorar las estructuras intelectuales y sociales dentro del conjunto de datos.
Conclusiones: Los resultados revelan tendencias significativas en la aplicación de la inteligencia artificial en el comercio electrónico, destacando el rápido crecimiento del interés en esta área durante la última década. China emerge como el país con el mayor número de citas, con ZHANG Y identificado como el autor más relevante y HU M como el autor más citado. Además, el estudio identifica palabras clave prevalentes utilizadas por los autores, incluyendo análisis de sentimientos y sistemas de recomendación.
Implicaciones de la Investigación: Este estudio subraya el potencial transformador de la IA en mejorar las prácticas de comercio electrónico, ofreciendo ideas tanto para investigadores académicos como profesionales de la industria, proporcionando perspectivas valiosas sobre tendencias actuales y contribuciones.
Originalidad/valor: El valor del estudio radica en su enfoque bibliométrico exhaustivo, que integra dos bases de datos principales para explorar las aplicaciones de la IA en el comercio electrónico. Esta desviación de revisiones anteriores, que a menudo se basan en una sola base de datos, proporciona una comprensión más profunda del panorama actual y las direcciones futuras en este campo.Objetivo: O objetivo deste estudo é realizar uma revisão abrangente de artigos científicos sobre as aplicações de inteligência artificial (IA) no comércio eletrônico por meio de análise bibliométrica.
Referencial teórico: O estudo atual utilizou tanto as bases de dados SCOPUS quanto Web of Science (WoS) para enriquecer a análise com uma seleção mais ampla de artigos no campo, incorporando um exame dos documentos mais citados.
Desenho/metodologia/abordagem: O conjunto de dados para análise foi selecionado de acordo com o framework PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), integrando dados do Scopus e WoS por meio do software R, especificamente utilizando a biblioteca biblioshiny, e inclui 8372 artigos publicados de 1995 a 2023. A análise de dados deste estudo utilizou duas abordagens: análise descritiva para examinar os dados quantitativamente e mapeamento científico para explorar as estruturas intelectuais e sociais dentro do conjunto de dados.
Resultados: Os resultados revelam tendências significativas na aplicação da inteligência artificial no comércio eletrônico, destacando o rápido crescimento do interesse nesta área ao longo da última década. A China emerge como o país com o maior número de citações, com ZHANG Y identificado como o autor mais relevante e HU M como o autor mais citado. Além disso, o estudo identifica palavras-chave prevalentes usadas pelos autores, incluindo análise de sentimento e sistemas de recomendação.
Pesquisa, implicações práticas e sociais: Este estudo destaca o potencial transformador da IA em aprimorar práticas de comércio eletrônico, oferecendo insights tanto para pesquisadores acadêmicos quanto profissionais da indústria, fornecendo perspectivas valiosas sobre tendências atuais e contribuições.
Originalidade/valor: O valor do estudo reside em sua abordagem bibliométrica abrangente, que integra duas bases de dados principais para explorar as aplicações da IA no comércio eletrônico. Esta divergência das revisões anteriores, que frequentemente se baseiam em uma única base de dados, proporciona uma compreensão mais profunda do cenário atual e das direções futuras neste campo
Explainable machine learning models applied to predicting customer churn for e-commerce
Get PDFPrecise identification of customer churn is crucial for e-commerce companies due to the high costs associated with acquiring new customers. In this sector, where revenues are affected by customer churn, the challenge is intensified by the diversity of product choices offered on various marketplaces. Customers can easily switch from one platform to another, emphasizing the need for accurate churn classification to anticipate revenue fluctuations in e-commerce. In this context, this study proposes seven machine learning classification models to predict customer churn, including decision tree (DT), random forest (RF), support vector machine (SVM), logistic regression (LR), naïve Bayes (NB), k-nearest neighbors (K-NN), and artificial neural network (ANN). The performances of the models were evaluated using confusion matrix, accuracy, precision, recall, and F1-score. The results indicated that the ANN model achieves the highest accuracy at 92.09%, closely followed by RF at 91.21%. In contrast, the NB model performed the least favorably with an accuracy of 75.04%. Two explainable artificial intelligence (XAI) methods, shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), were used to explain the models. SHAP provided global explanations for both ANN and RF models through Kernel SHAP and Tree SHAP. LIME, offering local explanations, was applied only to the ANN model which gave better accuracy
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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