The Next 'Deep' Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach

被引:1
|
作者
Charles, Vincent [1 ]
Rana, Nripendra P. [2 ]
Pappas, Ilias O. [3 ,4 ]
Kamphaug, Morten [5 ]
Siau, Keng [6 ]
Engo-Monsen, Kenth [7 ]
机构
[1] Queens Univ Belfast, Queens Business Sch, Belfast, North Ireland
[2] Qatar Univ, Coll Business & Econ, Doha, Qatar
[3] Univ Agder, Agder, Norway
[4] Norwegian Univ Sci & Technol, Trondheim, Norway
[5] Deloitte, Oslo, Norway
[6] City Univ Hong Kong, Hong Kong, Peoples R China
[7] Smart Innovat Norway, Halden, Norway
关键词
Artificial intelligence; Digital technologies; Data-driven decision-making; Marketing strategy; Consumer behaviour; DIGITAL TRANSFORMATION; TECHNOLOGIES;
D O I
10.1007/s10796-023-10462-x
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The existing body of literature indicates a growing interest in research pertaining to the influence of artificial intelligence (AI) on marketing strategies, processes, and practices. However, further studies are required to fully unravel its complete potential and the implications it holds for practical application. The aim of this special issue on "The Next 'Deep' Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach" is to explore the next frontiers and delve into the various facets of AI-driven marketing, shedding light on cutting-edge research and practical insights that can shape the future of the field. It also focuses on novel ways of using AI techniques to derive innovative insights that can streamline marketing processes and make businesses more effective. The papers herein contribute not only to the advancement of knowledge and understanding surrounding the utilisation of AI in marketing but also play a crucial role in establishing a renewed and revitalised research agenda.
引用
收藏
页码:851 / 856
页数:6
相关论文
共 50 条
  • [1] The Next ‘Deep’ Thing in X to Z Marketing: An Artificial Intelligence-Driven Approach
    Vincent Charles
    Nripendra P. Rana
    Ilias O. Pappas
    Morten Kamphaug
    Keng Siau
    Kenth Engø-Monsen
    Information Systems Frontiers, 2024, 26 : 851 - 856
  • [2] An Artificial Intelligence-Driven Deep Learning Model for Chest X-ray Image Segmentation
    Nillmani
    Sharma, Neeraj
    BIOMEDICAL ENGINEERING SCIENCE AND TECHNOLOGY, ICBEST 2023, 2024, 2003 : 107 - 116
  • [3] An Artificial Intelligence-Driven Deep Learning Model for Chest X-ray Image Segmentation
    Nillmani
    Sharma, Neeraj
    Communications in Computer and Information Science, 2024, 2003 CCIS : 107 - 116
  • [4] Artificial intelligence-driven biomedical genomics
    Guo, Kairui
    Wu, Mengjia
    Soo, Zelia
    Yang, Yue
    Zhang, Yi
    Zhang, Qian
    Lin, Hua
    Grosser, Mark
    Venter, Deon
    Zhang, Guangquan
    Lu, Jie
    KNOWLEDGE-BASED SYSTEMS, 2023, 279
  • [5] The next big thing - artificial intelligence
    Ahluwalia, Pal
    Miller, Toby
    SOCIAL IDENTITIES, 2023, 29 (01) : 1 - 4
  • [6] Artificial intelligence-driven tone recognition of Guzheng: A linear prediction approach
    Han, Mingjin
    DEMONSTRATIO MATHEMATICA, 2024, 57 (01)
  • [7] Artificial intelligence-driven approach for patient-focused drug development
    Karmalkar, Prathamesh
    Gurulingappa, Harsha
    Spies, Erica
    Flynn, Jennifer A.
    FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2023, 6
  • [8] Artificial intelligence-driven decision making and firm performance: a quantitative approach
    Giachino, Chiara
    Cepel, Martin
    Truant, Elisa
    Bargoni, Augusto
    MANAGEMENT DECISION, 2024,
  • [9] Causal Artificial Intelligence-Driven Approach for HVAC Preventive Maintenance Explanation
    Kliangkhlao, Mallika
    Haruehansapong, Kanjana
    Yeranee, Kirttayoth
    Sahoh, Bukhoree
    IEEE ACCESS, 2024, 12 : 121064 - 121076
  • [10] Artificial intelligence-driven cardiac amyloidosis screening
    Abdaem, Jacob
    Miller, Robert
    LANCET DIGITAL HEALTH, 2024, 6 (04): : e231 - e232