Global R&D Location Strategy of Multinational Enterprises: an Agent-Based Simulation Modeling Approach

Abstract

The global research and development (R&D) location strategy of multinational enterprises (MNEs) is examined using agent-based simulation (ABS) modeling. This study focuses on the positioning strategy of MNEs to understand the impact of their R&D location strategy. In ABS modeling, agents search for knowledge owners or universities in the global host market using Hotelling’s location model algorithm. We measure the result of increasing the number of entry agents from 2 to 121. Three types of equilibria are found in our agent-based simulation model: pure equilibrium, saturated equilibrium, and quasi-saturated equilibrium. Core locations attract MNEs, while peripheral countries in the global market are the least preferred. As a result, peripheral countries experience a paucity of foreign R&D investments. Even though emerging economies absorb foreign direct investment (FDI) inflows from MNEs, least-less developed countries (LLDC) may experience a dearth in FDI. Thus, the optimal location strategy of MNEs leads to economic disparities between the core and peripheral countries. This study suggests the need for developing official assistance to attract FDI inflows to LLDCs so that peripheral countries emerge as attractive global market destinations for MNEs.