Rethinking the national defense R&D innovation system for latecomer: Defense R&D governance matrix
Jun Gon Lee and
Min Jae Park
Technological Forecasting and Social Change, 2019, vol. 146, issue C, 1-11
The purpose of this study is to present defense R&D governance model for governance analysis and decision making in defense R&D programs. In particular, by utilizing the MIT Sloan IT governance matrix and through Delphi surveys of a group of defense R&D experts, an efficient governance model of national R&D and weapon systems acquisition area is deducted and at the same time policy implications and directions of defense R&D and weapon systems decision making processes for technology-pursuing countries are presented. This study contributes to the decision making of R&D and weapon systems acquisition programs that utilize defense R&D governance, by allowing many corporations trying to enter emerging economies to understand those countries' defense R&D governance models. This study emphasizes that the governance with the most optimal combination of the Decision types (R&D Principles, R&D Architecture, R&D Infrastructure, Business Application Needs, R&D Investment) and the Archetypes (National R&D Committee Monarchy, Defense Agency Monarchy, Federal, Defense Industries Monarchy) must be reflected on national defense R&D programs and weapons systems acquisition procedures, in accordance with the scale and budget of a given program. This can be applied through various means to benefit national defense R&D and weapons system-related projects in different countries.
Keywords: Defense R&D; R&D governance; Latecomer; National Innovation System; Decision-making process (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:146:y:2019:i:c:p:1-11
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Haili He ().