Guest editorial: Artificial intelligence for B2B marketing: Challenges and opportunities

被引:35
作者
Dwivedi, Yogesh K. [1 ,2 ]
Wang, Yichuan [3 ]
机构
[1] Swansea Univ, Emerging Markets Res Ctr EMaRC, Sch Management, Room 323,Bay Campus, Swansea SA1 8EN, Wales
[2] Pune & Symbiosis Int, Symbiosis Inst Business Management, Dept Management, Pune, Maharashtra, India
[3] Univ Sheffield, Sheffield Univ Management Sch, Sheffield S10 1FL, England
关键词
Artificial intelligence; B2B marketing; Customer experience; AI chatbot; Supply chain management; Knowledge creation; Adoption of AI; B2B marketing strategy; Innovation; DECISION-MAKING; BIG DATA; AI; ANALYTICS; KNOWLEDGE; PERFORMANCE; INNOVATION; FRAMEWORK;
D O I
10.1016/j.indmarman.2022.06.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
A growing body of evidence indicates that implementing artificial intelligence (AI) at scale can improve market performance in B2B settings by accelerating decision-making process. Despite its popularity in the B2B sector, there have been few academic studies about this phenomenon in the context of industrial markets. Currently, AI research focuses predominantly on the marketing aspect of consumers, but in fact industrial data is rarely analyzed to address the issues regarding organizational behavior, product innovation, supply chain management, and B2B customer relationship management. The special issue presents 16 papers that explore why do B2B companies seek to use AI for marketing purposes, how AI can be used to foster innovation and use supply chain networks, how AI can enhance B2B customer experience and customer relationship management, and how AI can be used to develop dynamic capabilities on B2B marketing. These research articles provide insights into various industrial contexts and have applied both qualitative and quantitative approaches to identify AI applications for value creation.
引用
收藏
页码:109 / 113
页数:5
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共 39 条
  • [1] How to Build an AI Climate-Driven Service Analytics Capability for Innovation and Performance in Industrial Markets?
    Akter, Shahriar
    Wamba, Samuel Fosso
    Mariani, Marcello
    Hani, Umme
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 97 : 258 - 273
  • [3] Ethical framework for Artificial Intelligence and Digital technologies
    Ashok, Mona
    Madan, Rohit
    Joha, Anton
    Sivarajah, Uthayasankar
    [J]. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2022, 62
  • [4] SMEs and artificial intelligence (AI): Antecedents and consequences of AI-based B2B practices
    Baabdullah, Abdullah M.
    Alalwan, Ali Abdallah
    Slade, Emma Louise
    Raman, Ramakrishnan
    Khatatneh, Khalaf Fakhri
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 98 : 255 - 270
  • [5] An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance
    Bag, Surajit
    Gupta, Shivam
    Kumar, Ajay
    Sivarajah, Uthayasankar
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 92 : 178 - 189
  • [6] The effect of AI-based CRM on organization performance and competitive advantage: An empirical analysis in the B2B context
    Chatterjee, Sheshadri
    Rana, Nripendra P.
    Tamilmani, Kuttimani
    Sharma, Anuj
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 97 : 205 - 219
  • [7] Artificial intelligence in information systems research: A systematic literature review and research agenda
    Collins, Christopher
    Dennehy, Denis
    Conboy, Kieran
    Mikalef, Patrick
    [J]. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2021, 60
  • [8] What is it about humanity that we can't give away to intelligent machines? A European perspective
    Coombs, Crispin
    Stacey, Patrick
    Kawalek, Peter
    Simeonova, Boyka
    Becker, Joerg
    Bergener, Katrin
    Carvalho, Joao Alvaro
    Fantinato, Marcelo
    Garmann-Johnsen, Niels F.
    Grimme, Christian
    Stein, Armin
    Trautmann, Heike
    [J]. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2021, 58
  • [9] How artificial intelligence will change the future of marketing
    Davenport, Thomas
    Guha, Abhijit
    Grewal, Dhruv
    Bressgott, Timna
    [J]. JOURNAL OF THE ACADEMY OF MARKETING SCIENCE, 2020, 48 (01) : 24 - 42
  • [10] Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach
    De Caigny, Arno
    Coussement, Kristof
    Verbeke, Wouter
    Idbenjra, Khaoula
    Phan, Minh
    [J]. INDUSTRIAL MARKETING MANAGEMENT, 2021, 99 : 28 - 39