Journal of Business Research, Journal Year: 2024, Volume and Issue: 182, P. 114764 - 114764
Published: June 14, 2024
Language: Английский
Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 200, P. 123189 - 123189
Published: Jan. 11, 2024
This study explores the interlink between AI capabilities and circular business models (CBMs) through a literature review. Extant reveals that can act as efficiency catalyst, empowering firms to implement CBM. However, journey harness for CBM is fraught with challenges grapple lack of sophisticated processes routines tap into AI's potential. The fragmented leaves void in understanding barriers development pathways contexts. Bridging this gap, adopting perspective, review intricately brings together four pivotal capabilities: integrated intelligence capability, process automation augmentation infrastructure platform ecosystem orchestration capability drivers AI-enabled These are vital navigating multi-level utilizing key contribution synthesis an framework, which not only summarizes results but also sets stage future explorations dynamic field.
Language: Английский
Citations
22
Review of Managerial Science, Journal Year: 2024, Volume and Issue: unknown
Published: April 18, 2024
Abstract This study intends to scrutinize the role of Artificial Intelligence (AI) in Product-Service Innovation (PSI). The literature on AI enabled PSI, other related innovation business models, product-service systems, and servitization has grown significantly since 2018; therefore, there is a need structure systematic manner add what been studied thus far. Product-service used represent relevance achieving models dealing with outcomes including artificial intelligence. bibliographic coupling analyze 159 articles emerging from fields computer sciences, engineering, social decision management. review depicts structures comprising five (5) clusters, namely, (1) technology adoption transformational barriers, which barriers faced during AI-enabled technologies following transformation; (2) data-driven capabilities innovation, highlights data-based supported through innovation; (3) digitally model explained how occurs; (4) smart design changes sustainability, reveals working product service environments different transformations based sustainability; sectorial application, industry examples. Each cluster comprehensively analyzed its contents, central themes, theories, methodologies, help identify gaps support suggestions for future research directions.
Language: Английский
Citations
21
Frontiers in Artificial Intelligence, Journal Year: 2024, Volume and Issue: 6
Published: Jan. 15, 2024
The functions of human resource management (HRM) have changed radically in the past 20 years due to market and technological forces, becoming more cross-functional data-driven. In age AI, role HRM professionals organizations continues evolve. Artificial intelligence (AI) is transforming many practices throughout creating system process efficiencies, performing advanced data analysis, contributing value creation organization. A growing body evidence highlights benefits AI brings field HRM. Despite increased interest AI-HRM scholarship, focus on human-AI interaction at work AI-based technologies for limited fragmented. Moreover, lack considerations tech design deployment can hamper digital transformation efforts. This paper provides a contemporary forward-looking perspective strategic human-centric plays within as becomes integrated workplace. Spanning three distinct phases integration (technocratic, integrated, fully-embedded), it examines technical, human, ethical challenges each phase suggestions how overcome them using approach. Our importance evolving AI-driven organization roadmap bring humans machines closer together
Language: Английский
Citations
20
Journal of Innovation & Knowledge, Journal Year: 2024, Volume and Issue: 9(2), P. 100481 - 100481
Published: March 23, 2024
Knowledge creation is the foundation for indigenous innovation in manufacturing enterprises; however, effects of digital transformation on knowledge are still not well understood. Nonaka put forward model creation, which includes four processes: socialization, externalization, combination, and internalization, known as famous SECI model. Based model, this study analyzes processes, using panel data from Chinese listed enterprises 2007 to 2020. The provides several novel findings. First, positively affects all with combination capability being particularly notable. Second, digitalization inputs externalization insignificant but exert a negative impact socialization internalization. Third, heterogeneity analysis reveals that facilitating effect more significant state-owned large enterprises. Moreover, it primarily acts "cherry top," significantly benefiting already have strong capabilities. A low level technology development region where an enterprise located will inhibit role promoting socialization. Furthermore, culture regional environments play positive moderating roles. This contributes further understanding how enterprises' activities.
Language: Английский
Citations
20
Journal of Business Research, Journal Year: 2024, Volume and Issue: 182, P. 114764 - 114764
Published: June 14, 2024
Language: Английский
Citations
20