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Cognitive analytics enabled responsible artificial intelligence for business model innovation: A multilayer perceptron neural networks estimation

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  • معلومة اضافية
    • بيانات النشر:
      Elsevier
    • الموضوع:
      2024
    • Collection:
      University of the Arts London: UAL Research Online
    • نبذة مختصرة :
      Cognitive analytics employs and analyses complex and heterogeneous data sources generating deeper insights that mimic the natural intelligence of the human brain. Cognitive analytics-enabled Artificial Intelligence (AI) that promotes Business Model Innovation (BMI) for the efficiency of the healthcare system is a nascent and undertheorized domain. Within the healthcare management systems, stakeholders’ engagement with AI, particularly with responsible AI, to optimize BMI and improve business performance is bounded by several caveats. Using the Technology Acceptance Model (TAM) and Social Network Theory (SNT) as our conceptual foci, we empirically examine through the Multilayer Perceptron Neural Network the extent to which responsible AI leads to Business Model Innovation (BMI) through the stakeholders’ engagement. Our contributions are novel which demonstrate that cognitive analytics-enabled responsible AI is central to innovation, and healthcare stakeholders exhibit a robust propensity to reorientate and innovate their existing BMI to achieve improved business performance. It has significant implications for innovation, AI and cognitive analytics literature.
    • File Description:
      text
    • Relation:
      https://ualresearchonline.arts.ac.uk/id/eprint/22210/8/Cognitive%20Analytics_Manuscript_09062024.pdf; Kanungo, Rama Prasad and Gupta, Suraksha and Liu, Rui (2024) Cognitive analytics enabled responsible artificial intelligence for business model innovation: A multilayer perceptron neural networks estimation. Journal of Business Research, 182. ISSN 0148-2963; https://doi.org/10.1016/j.jbusres.2024.114788
    • الرقم المعرف:
      10.1016/j.jbusres.2024.114788
    • Rights:
      cc_by_nc_nd
    • الرقم المعرف:
      edsbas.FD9B833F