Title: Predicting future new technology trade relations among regional comprehensive economic partnership member countries - based on a link prediction method

Authors: Xinli Qi; Changping Zhao; Yu Gong; Zhenghui Yuan; Yangyan Shi

Addresses: College of Transportation Engineering, Dalian Maritime University, Dalian, 116026, China ' Business School, Changshu Institute of Technology, Changshu, 215500, China ' Southampton Business School, University of Southampton, Southampton, SO17 1BJ, UK ' Research Center for Belt and Road Financial and Economic Development Center, Xiamen National Accounting Institute, Xiamen, 361000, China ' Department of Management, Macquarie Business School, Macquarie University, 2109, Australia

Abstract: Based on 2009-2018 technical trade data, this article uses link prediction methods to explore RCEP's potential technological innovation cooperation and trade relationship rules from the perspective of physical topology networks and national node attributes, and to predict the possible RCEP technical trade links that may be established in the future. The research results show that: 1) the number of national trading partners in a node country has a positive impact on the potential links of its technology trade; 2) countries with technology trade cooperation will be more likely to conduct technology transactions in the future; 3) there will be more technology trade between RCEP and EU countries in the future; 4) ASEAN countries and enterprises have weak capacity to establish new technological trade relations. Priority should be given to expanding technology trade with other RCEP enterprises to enhance ASEAN's international technology trading capacity.

Keywords: RCEP; international technology trade; technological innovation cooperation; social network; link prediction.

DOI: 10.1504/IJTM.2023.132603

International Journal of Technology Management, 2023 Vol.93 No.1/2, pp.133 - 164

Received: 15 Sep 2021
Received in revised form: 16 Jun 2022
Accepted: 27 Jul 2022
Published online: 30 Jul 2023 *

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