Past, present and future of AI in marketing and knowledge management

IF 6.6 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Reza Marvi, Pantea Foroudi, Maria Teresa Cuomo
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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.

人工智能在营销和知识管理领域的过去、现在和未来
本文旨在探讨知识管理(KM)背景下人工智能(AI)与营销的交集。它研究了人工智能技术如何促进数据驱动的决策,增强业务沟通,改善客户个性化,优化营销活动和提高整体营销效果。本研究采用定量和系统的方法,整合引文分析、文本挖掘和共被引分析,考察基础研究领域和人工智能在营销中的演变。这一全面的分析解决了人工智能对营销及其未来发展的影响的实证调查中目前的差距。本研究确定了三种主要观点,它们塑造了人工智能在营销中的基础:代理、工具和集成观点。它开发了一个管理相关的概念框架,概述了未来的研究方向,并在KM领域内扩展了人工智能和营销文献的边界。原创性/价值本研究提出了一个在知识管理背景下整合人工智能和营销的概念模型,提供了新的研究轨迹。本研究提供了人工智能如何在市场营销中促进知识共享、战略规划和决策的整体观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
13.70
自引率
15.70%
发文量
99
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?
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