{"title":"电子商务领域的人工智能文献计量分析:过去十年的趋势与进展","authors":"Samira Frioui, Amel Graa","doi":"10.24818/mer/2024.01-01","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) techniques are commonly used in e-commerce, but there is little bibliometric analysis in this field. Using a bibliometric approach, it conducted a comprehensive study over the past decade to assess the research landscape, progress, and emerging trends in the field of artificial intelligence in e-commerce. Data was collected from related literature in the Scopus database from 2014 to the first half of 2023. VOSviewer and R studio were used to perform the bibliometric analysis of AI in e-commerce. The author status, nations, affiliations, annual publications, keywords, and journals were all evaluated in this way. The oldest relevant article was published in 1994, and article reviews were the most common form of document among the 669 manuscripts. Furthermore, the most popular research areas in this topic are business, management, and accounting. Additionally, the most productive journal is Proceedings of the International Conference on Electronic Business (ICEB). Moreover, the UK is the country that has published the most articles, and in terms of co-authorship, it has the strongest overall link. Finally, the keyword co-occurrence network indicates that the most important keywords are machine learning, e-commerce, recommender systems, fraud detection, decision-making systems, data mining, and online retailing.","PeriodicalId":223559,"journal":{"name":"MANAGEMENT AND ECONOMICS REVIEW","volume":"57 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bibliometric Analysis of Artificial Intelligence in the Scope of E-Commerce: Trends and Progress over the Last Decade\",\"authors\":\"Samira Frioui, Amel Graa\",\"doi\":\"10.24818/mer/2024.01-01\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial intelligence (AI) techniques are commonly used in e-commerce, but there is little bibliometric analysis in this field. Using a bibliometric approach, it conducted a comprehensive study over the past decade to assess the research landscape, progress, and emerging trends in the field of artificial intelligence in e-commerce. Data was collected from related literature in the Scopus database from 2014 to the first half of 2023. VOSviewer and R studio were used to perform the bibliometric analysis of AI in e-commerce. The author status, nations, affiliations, annual publications, keywords, and journals were all evaluated in this way. The oldest relevant article was published in 1994, and article reviews were the most common form of document among the 669 manuscripts. Furthermore, the most popular research areas in this topic are business, management, and accounting. Additionally, the most productive journal is Proceedings of the International Conference on Electronic Business (ICEB). Moreover, the UK is the country that has published the most articles, and in terms of co-authorship, it has the strongest overall link. Finally, the keyword co-occurrence network indicates that the most important keywords are machine learning, e-commerce, recommender systems, fraud detection, decision-making systems, data mining, and online retailing.\",\"PeriodicalId\":223559,\"journal\":{\"name\":\"MANAGEMENT AND ECONOMICS REVIEW\",\"volume\":\"57 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MANAGEMENT AND ECONOMICS REVIEW\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24818/mer/2024.01-01\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MANAGEMENT AND ECONOMICS REVIEW","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24818/mer/2024.01-01","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
人工智能(AI)技术在电子商务中得到了普遍应用,但这一领域的文献计量分析却很少。本研究采用文献计量学方法,对过去十年进行了全面研究,以评估电子商务中人工智能领域的研究状况、进展和新兴趋势。数据收集自 Scopus 数据库中 2014 年至 2023 年上半年的相关文献。使用 VOSviewer 和 R studio 对电子商务中的人工智能进行文献计量分析。作者身份、国家、所属单位、年度出版物、关键词和期刊都是通过这种方式进行评估的。最早的相关文章发表于 1994 年,文章评论是 669 篇手稿中最常见的文献形式。此外,该主题最受欢迎的研究领域是商业、管理和会计。此外,产量最高的期刊是《国际电子商务会议论文集》(ICEB)。此外,英国是发表文章最多的国家,在共同作者方面,英国的整体联系最强。最后,关键词共现网络表明,最重要的关键词是机器学习、电子商务、推荐系统、欺诈检测、决策系统、数据挖掘和在线零售。
Bibliometric Analysis of Artificial Intelligence in the Scope of E-Commerce: Trends and Progress over the Last Decade
Artificial intelligence (AI) techniques are commonly used in e-commerce, but there is little bibliometric analysis in this field. Using a bibliometric approach, it conducted a comprehensive study over the past decade to assess the research landscape, progress, and emerging trends in the field of artificial intelligence in e-commerce. Data was collected from related literature in the Scopus database from 2014 to the first half of 2023. VOSviewer and R studio were used to perform the bibliometric analysis of AI in e-commerce. The author status, nations, affiliations, annual publications, keywords, and journals were all evaluated in this way. The oldest relevant article was published in 1994, and article reviews were the most common form of document among the 669 manuscripts. Furthermore, the most popular research areas in this topic are business, management, and accounting. Additionally, the most productive journal is Proceedings of the International Conference on Electronic Business (ICEB). Moreover, the UK is the country that has published the most articles, and in terms of co-authorship, it has the strongest overall link. Finally, the keyword co-occurrence network indicates that the most important keywords are machine learning, e-commerce, recommender systems, fraud detection, decision-making systems, data mining, and online retailing.