Examine the enablers of generative artificial intelligence adoption in supply chain: a mixed method study

被引:0
|
作者
Sharma, Ashish Jagdish [1 ]
Rathore, Bhawana [2 ]
机构
[1] Indian Inst Management Sambalpur, Informat Syst Management, Basantpur, India
[2] Indian Inst Management Sambalpur, Operat Management Area, Basantpur, India
关键词
Generative artificial intelligence; AHP; Latent Dirichlet Allocation; FUZZY DELPHI METHOD; AI; ETHICS; IDENTIFICATION; BARRIERS; SYSTEM;
D O I
10.1080/12460125.2024.2410030
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Generative Artificial Intelligence (Gen-AI) is a burgeoning subfield of artificial intelligence that focuses on creating new content which is poised to revolutionise different industries by 2028. This study aims first to identify key enablers for the successful integration of Gen-AI into the supply chain with the help of Delphi and AHP techniques. Then, we screened these enablers categories and identified seven key enabler categories using the Delphi method. We computed the weights of those categories and ranked them on the basis of their weights with Ethical and Fair AI Practices and Public Trust and Societal Impact among the most significant. Second, this study categorised the tweet into positive, neutral, and negative sentiments using sentiment analysis and identified fifteen topics from secondary data. The research concludes with actionable strategies for practitioners and outlines the significance of ethical and trust-related enablers in the adoption of Gen-AI in the supply chain.
引用
收藏
页数:33
相关论文
共 50 条
  • [41] Enablers of blockchain adoption on supply chain with dynamic capability perspectives with ISM-MICMAC analysis
    Kuei, Shang-Ching
    Chen, Mu-Chen
    ANNALS OF OPERATIONS RESEARCH, 2023,
  • [42] Enablers to Implement Circular Initiatives in the Supply Chain: A Grey DEMATEL Method
    Khan, Shahbaz
    Haleem, Abid
    Khan, Mohd Imran
    GLOBAL BUSINESS REVIEW, 2024, 25 (01) : 68 - 84
  • [43] Empowering co-creation of services with artificial intelligence: an empirical analysis to examine adoption intention
    Behera, Rajat Kumar
    Bala, Pradip Kumar
    Rana, Nripendra P.
    Irani, Zahir
    MARKETING INTELLIGENCE & PLANNING, 2024, 42 (06) : 941 - 975
  • [44] The Impact of Generative Artificial Intelligence on Education: A Comparative Study
    Elmourabit, Zohair
    Retbi, Asmaa
    El Faddouli, Nour-Eddine
    PROCEEDINGS OF THE 23RD EUROPEAN CONFERENCE ON E-LEARNING, ECEL 2024, 2024, 23/1 : 470 - 476
  • [45] Collaborative Working and Critical Thinking: Adoption of Generative Artificial Intelligence Tools in Higher Education
    Ruiz-Rojas, Lena Ivannova
    Salvador-Ullauri, Luis
    Acosta-Vargas, Patricia
    SUSTAINABILITY, 2024, 16 (13)
  • [46] From familiarity to acceptance: The impact of Generative Artificial Intelligence on consumer adoption of retail chatbots
    Arce-Urriza, Marta
    Chocarro, Raquel
    Cortinas, Monica
    Marcos-Matas, Gustavo
    JOURNAL OF RETAILING AND CONSUMER SERVICES, 2025, 84
  • [47] Exploring the use, adoption, and ethics of generative artificial intelligence in the public relations and communication professions
    Duckett, Jana
    Westrick, Nicole M.
    COMMUNICATION TEACHER, 2025, 39 (01) : 33 - 41
  • [48] Prioritizing factors for generative artificial intelligence-based innovation adoption in hospitality industry
    AL-Khatib, Ayman Wael
    MANAGEMENT DECISION, 2024,
  • [49] An Empirical Evaluation of a Generative Artificial Intelligence Technology Adoption Model from Entrepreneurs' Perspectives
    Gupta, Varun
    SYSTEMS, 2024, 12 (03):
  • [50] A critical analysis of the integration of blockchain and artificial intelligence for supply chain
    Charles, Vincent
    Emrouznejad, Ali
    Gherman, Tatiana
    ANNALS OF OPERATIONS RESEARCH, 2023, 327 (01) : 7 - 47