功能可见性
知识管理
过程(计算)
计算机科学
数据科学
数据收集
资源(消歧)
扎根理论
过程管理
定性研究
业务
社会学
人机交互
社会科学
计算机网络
操作系统
作者
Cristina Trocin,Ingrid Våge Hovland,Patrick Mikalef,Christian Dremel
标识
DOI:10.1016/j.techfore.2021.121081
摘要
Artificial Intelligence (AI) is fuelling a new breed of digital innovation in Human Resource Management (HRM) by creating new opportunities for complying with General Data Protection Regulation (GDPR) during data collection and analysis, decreasing biases, and offering targeted recommendations. However, AI is also posing challenges to organisations and key assumptions about digital innovation processes and outcomes, making it unclear how to combine AI affordances with actors, goals, and tasks. We conducted a qualitative multiple-case study in Scandinavian organisations offering HR services. Grounded theory guided our data collection and analysis. Input-Process-Output framework and affordance theory supported the analysis of specific information processing constraints and enablers. We developed a framework to explain how AI affordances enable digital innovation and address the calls about definitional boundaries between innovation processes and outcomes. We showed how AI affordances are actualised and how this leads to reontologising decision-making and providing data driven legitimisation. Our study contributes to digital innovation research by elucidating AI affordances and their actualisation in organisations. We conclude with the implications to theory and practice, limitations, and suggestions for future research.
科研通智能强力驱动
Strongly Powered by AbleSci AI