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  • 标题:Exploring Factors Influencing Organizational Adoption of Artificial Intelligence (AI) in Corporate Social Responsibility (CSR) Initiatives
  • 本地全文:下载
  • 作者:Vaibhav Pai ; Shalini Chandra
  • 期刊名称:Pacific Asia Journal of the Association for Information Systems
  • 印刷版ISSN:1943-7544
  • 出版年度:2022
  • 卷号:14
  • 期号:5
  • 页码:1-34
  • DOI:10.17705/1pais.14504
  • 语种:English
  • 出版社:Association for Information Systems
  • 摘要:Globalization has resulted in social, economic, political, commercial,and technological integration. A social problem needs a global collaborative viewto find a solution. Wide-ranging partnerships are essential to achievedevelopmental goals, with public and private partners pooling their resources andcompetencies. The private sector contributes by engaging in corporate socialresponsibility (CSR) initiatives. These initiatives can significantly impact byleveraging emerging technologies such as Artificial Intelligence (AI). While manysupport AI, some believe that AI is a threat to humanity. With mixed attitudestowards AI, its adoption in CSR is somewhat limited. This research leverages theTechnology-Organization-Environment (TOE) framework to explore factorsinfluencing AI adoption intention from an organizational perspective.Method: The factors were identified from a thorough literature review and mappedwith Carroll's CSR framework. The theorized model was tested via a sampleresponse of 124 Indian firms.Results: The findings of this research share insight into the influence of the ninetechnological, organizational, and environmental factors and dives deeper throughthe post-hoc analysis of the variations due to the size of the firm, public or privateorientation, and industry sector.Conclusions: Along with the contributions to literature and theory, this researchstudy has several significant contributions to firms, AI products, service companies,AI strategists, and application developers.
  • 关键词:Artificial Intelligence;Corporate Social Responsibility;TOEFramework;Carroll's Pyramid of CSR;Structural Equation Modelling
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