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Future research directions of generative AI in marketing and logistics

  • Eugene Cheng Xi Aw
  • , Ali Anjomshoae
  • , Constantin Blome
  • , Tat Huei Cham
  • , Hing Kai Chan
  • , Jacqueline Eastman
  • , Arpan Kumar Kar
  • , Chung Wha (Chloe) Ki
  • , Lai Ying Leong
  • , Subhadeep Mandal
  • , Anubhav Mishra
  • , Keng Boon Ooi
  • , Ramakrishnan Raman
  • , Nripendra P. Rana
  • , Garry Wei-Han Tan*
  • *Corresponding author for this work

Research output: Journal PublicationArticlepeer-review

Abstract

Purpose – Generative AI has revolutionized business operations radically, including marketing and logistics. In order to explore the transformative impact of generative AI on these two domains, this article discusses the opportunities, challenges and research agendas in the specific areas of consumer buying behavior, business-to-business marketing, retail marketing, marketing communication, supply chain management, transportation management, and logistic management. Design/methodology/approach – Building upon an expert-oriented approach, this article examines the current body of literature and practices revolving around the intersection of generative AI and marketing/logistic-related domains. Findings – The contributors recognize the significant impact of generative AI to reshape marketing and logistic areas, including creating designs, handling customer inquiries and sales processes, optimizing customer experience, and planning and allocating logistic resources. On the other hand, some concerns are highlighted including jeopardizing brand value, resulting in the loss of human touch, discriminating customers, and incurring financial challenges. Originality/value – This article presents a pioneering approach to understanding the application of generative AI in the field of marketing and logistics. Furthermore, the article charts the research roadmap for future investigations, which includes changes in consumer decision-making under the influence of generative AI, diffusion and ethical consideration of generative AI, and human–generative AI collaboration.

Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalAsia Pacific Journal of Marketing and Logistics
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Free Keywords

  • Artificial intelligence
  • Consumer behavior
  • Generative AI
  • Logistics
  • Machine learning
  • Marketing
  • Supply chain management

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Marketing

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