AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover

Tachia Chin, Muhammad Waleed Ayub Ghouri, Jiyang Jin () and Muhammet Deveci
Additional contact information
Tachia Chin: Zhejiang University of Technology
Muhammad Waleed Ayub Ghouri: Zhejiang University of Technology
Jiyang Jin: Dhurakij Pundit University
Muhammet Deveci: National Defence University

Palgrave Communications, 2024, vol. 11, issue 1, 1-13

Abstract: Abstract Due to the extraordinary capacity of artificial intelligence (AI) to process rich information from various sources, an increasing number of enterprises are using AI for the development of ecosystem-based business models (EBMs) that require better orchestration of multiple stakeholders for a dynamic, sustainable balance among people, plant, and profit. However, given the nascency of relevant issues, there exists scarce empirical evidence. To fill this gap, this research follows the affordance perspective, considering AI technology as an object and the EBM as a use context, thereby exploring how and whether AI technologies afford the orchestration of EBMs. Based on data from Chinese A-share listed companies between the period from 2014 to 2021, our findings show an inverted U-shape quadratic relationship between AI and EBM, moderated by knowledge spillover. Our results enhance the understanding of the role of AI in configuring EBMs, thus providing novel insights into the mechanisms between AI and a specific business practice with societal concerns (i.e., EBM).

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41599-024-03003-7 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03003-7

Ordering information: This journal article can be ordered from
https://www.nature.com/palcomms/about

DOI: 10.1057/s41599-024-03003-7

Access Statistics for this article

More articles in Palgrave Communications from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().