Artificial Intelligence in Organizations: New Opportunities for Phenomenon-Based Theorizing
By Georgvon Krogh. Academy of Management Discoveries, 2018
456 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/9083485d05b00e72377a6d2ea3ddbc6a97c746c1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Nripendra P. Rana
- Yogesh Kumar Dwivedi
- Kuttimani Tamilmani
- Arpan Kumar Kar
- Rohita Dwivedi
- Michael D. Williams
- Hatice Kizgin
- John S. Edwards
In Sociology and Political Science
- Nripendra P. Rana
- Yogesh Kumar Dwivedi
- Kuttimani Tamilmani
- Ali Abdallah Alalwan
- Rohita Dwivedi
- Yanqing Duan
- John S. Edwards
- Elvira R. Ismagilova
Citations in the corpus
- A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective (2021, unknown): “AI is increasingly incorporated at work to improve task execution and performance (Lee, Davari, Singh, & Pandhare, 2018; Von Krogh, 2018), and it is associated with computer-based systems and applications involving, among other things, machine learning (Chui, Manyika, & Miremadi, 2015), soft…”
- Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2019, background): “The layered nature of the potential disruptions in the introduction of AI in the public sector calls for a renewed research agenda, and new theorisation e ff orts (von Krogh, 2018).”
- Ethical framework for Artificial Intelligence and Digital technologies (2022, background): “…“assemblage of technological components” (Canhoto & Clear, 2020, p. 184) that perform cognitive functions associated with human minds, operate autonomously without human intervention, and learn and identify patterns to make decisions (Raisch & Krakowski, 2020; Sousa et al., 2019; von Krogh, 2018).”
- Algorithmic management in a work context (2021, background): “As von Krogh (2018) explains, both traditional and non-traditional work settings will be increasingly shaped by the “interaction of human and machine authority regimes” (p.406).”
- Organizational Decision-Making Structures in the Age of Artificial Intelligence (2019, background): “5 By synthesizing robust patterns from large data sets, AI— and, in particular, machine learning algorithms—enables the creation of new information and predictions from data (provided that the future can be fairly well predicted by existing data).”