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  • 标题:Research Framework for Determining How Artificial Intelligence Enables Information Technology Service Management for Business Model Resilience
  • 本地全文:下载
  • 作者:Hongyi Mao ; Tao Zhang ; Qing Tang
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2021
  • 卷号:13
  • 期号:20
  • 页码:11496
  • DOI:10.3390/su132011496
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:Information technology service management (ITSM) driven by artificial intelligence (AI), i.e., AITSM, is likely to change business models and enterprise operations substantially, setting off a wave of enterprise AI transformation. Empowerment from AI has brought new vitality and challenges to ITSM capabilities, and enterprises must start thinking about how the capability of AITSM can be reactivated to shape the resilience of business models and meet survival needs in complex and ever-changing environments. To systematically achieve the development of enterprise business model resilience under AITSM, this study combines the actual situation of ITSM and enterprise AI transformation practice and then deconstruct it into three sub-research questions along the primary line of driver identification–model construction–paradigm optimization. We retrieve high-quality literature in the field of information systems from common databases and discuss the topics of AITSM and business model resilience. This study finds that future research should focus on forming an accurate description of the resilience demand of business models in the current era, and thus, better explain the value cocreation process between AITSM and business units. In addition, future research should emphasize the dynamic and strategic nature of business model resilience to study the continuous optimization of business models with the help of AITSM.
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