Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance
By Patrick Mikalef, Manjul Gupta. Information Manager (The), 2021
1,189 citations recorded by the source corpus.
Abstract Artificial intelligence (AI) has been heralded by many as the next source of business value. Grounded on the resource-based theory of the firm and on recent work on AI at the organizational context, this study (1) identifies the AI-specific resources that jointly create an AI capability and provides a definition, (2) develops an instrument to capture the AI capability of the firms, and (3) examines the relationship between an AI capability and organizational creativity and performance. Findings empirically support the suggested theoretical framework and corresponding instrument and provide evidence that an AI capability results in increased organizational creativity and performance.
Subfields: Management Information Systems, Sociology and Political Science, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/8d9f4b3f299b8f93e2b73dfd25f6d7420471c83f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
In Sociology and Political Science
In Strategy and Management
Citations in the corpus
- Innovative Finance, Technological Adaptation and SMEs Sustainability: The Mediating Role of Government Support during COVID-19 Pandemic (2021, background): “Resources include the firm’s business strategy and client base [30,31], external social capital such as collaborations [32,33], and reputational resources such as trust and brand image [34].”
- Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review (2022, background): “We understand AI as “the ability of a system to identify, interpret, make inferences, and learn from data to achieve predetermined organizational and societal goals” (Mikalef & Gupta, 2021).”
- GPT-3 and InstructGPT: technological dystopianism, utopianism, and “Contextual” perspectives in AI ethics and industry (2022, background): “For example, key human roles include AI trainers who teach AI systems how they should perform and AI sustainers who ensure that systems are properly functioning, and unanticipated consequences are addressed [44].”