THE IMPACT OF INTER-ORGANISATIONAL NETWORK STRUCTURES ON RESEARCH OUTCOMES FOR ARTIFICIAL INTELLIGENCE TECHNOLOGIES

Abstract

The purpose of this study is to empirically explore the impact of inter-organizational network structures, such as alliances, on the research outcomes of artificial intelligence technologies during the adoption and diffusion phases of their lifecycle. The optimal inter-organizational network structure varies depending on the characteristics of the technology, industry, and product. Artificial intelligence (AI) technology has been rapidly put to practical use, especially in recent years, in a wide range of business domains due to improvements in hardware performance and the increasing collection and use of big data. In collecting and using big data, collaboration among multiple organizations can be more advantageous than activities by a single organization, and the relationships among organizations are thought to have an impact on the expansion of research results. Nevertheless, the optimal structure of inter-organizational relations is thought to be influenced by the characteristics of the industry and products that use artificial intelligence technology, so we collected actual cases and carried out an exploratory analysis. As a research method, we collected information about cooperation between organizations related to artificial intelligence from press releases and newspaper articles and analyzed the network structure among the organizations using social network analysis. The number of registered patents on artificial intelligence was used as an index of research results. As a result of the statistical analysis, the research results of organizations with weak network ties were higher, mainly in the basic technology area. On the other hand, in practical technology, there were some areas where strong network ties led to high research results.

Data:
Received: 31 Jan 2022
Revised: 16 Mar 2022
Accepted: 6 Apr 2022
Published: 20 Apr 2022