{"title":"Past, present and future of AI in marketing and knowledge management","authors":"Reza Marvi, Pantea Foroudi, Maria Teresa Cuomo","doi":"10.1108/jkm-07-2023-0634","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This paper aims to explore the intersection of artificial intelligence (AI) and marketing within the context of knowledge management (KM). It investigates how AI technologies facilitate data-driven decision-making, enhance business communication, improve customer personalization, optimize marketing campaigns and boost overall marketing effectiveness.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>This study uses a quantitative and systematic approach, integrating citation analysis, text mining and co-citation analysis to examine foundational research areas and the evolution of AI in marketing. This comprehensive analysis addresses the current gap in empirical investigations of AI’s influence on marketing and its future developments.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>This study identifies three main perspectives that have shaped the foundation of AI in marketing: proxy, tool and ensemble views. It develops a managerially relevant conceptual framework that outlines future research directions and expands the boundaries of AI and marketing literature within the KM landscape.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This research proposes a conceptual model that integrates AI and marketing within the KM context, offering new research trajectories. This study provides a holistic view of how AI can enhance knowledge sharing, strategic planning and decision-making in marketing.</p><!--/ Abstract__block -->","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"22 1","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Knowledge Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/jkm-07-2023-0634","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
This paper aims to explore the intersection of artificial intelligence (AI) and marketing within the context of knowledge management (KM). It investigates how AI technologies facilitate data-driven decision-making, enhance business communication, improve customer personalization, optimize marketing campaigns and boost overall marketing effectiveness.
Design/methodology/approach
This study uses a quantitative and systematic approach, integrating citation analysis, text mining and co-citation analysis to examine foundational research areas and the evolution of AI in marketing. This comprehensive analysis addresses the current gap in empirical investigations of AI’s influence on marketing and its future developments.
Findings
This study identifies three main perspectives that have shaped the foundation of AI in marketing: proxy, tool and ensemble views. It develops a managerially relevant conceptual framework that outlines future research directions and expands the boundaries of AI and marketing literature within the KM landscape.
Originality/value
This research proposes a conceptual model that integrates AI and marketing within the KM context, offering new research trajectories. This study provides a holistic view of how AI can enhance knowledge sharing, strategic planning and decision-making in marketing.
期刊介绍:
Knowledge Management covers all the key issues in its field including:
■Developing an appropriate culture and communication strategy ■Integrating learning and knowledge infrastructure
■Knowledge management and the learning organization
■Information organization and retrieval technologies for improving the quality of knowledge
■Linking knowledge management to performance initiatives ■Retaining knowledge - human and intellectual capital
■Using information technology to develop knowledge management ■Knowledge management and innovation
■Measuring the value of knowledge already within an organization ■What lies beyond knowledge management?