Policy simulation of firms’ cooperation in innovation

Abstract

This study utilizes results from an agent-based simulation model to conduct public policy simulation of firms' networking and cooperation in innovation. The simulation game investigates the differences in sector responses to internal and external changes, including cross-sector spillovers, when applying three different policy strategies to promote cooperation in innovation. The public policy strategies include clustering to develop certain industries, incentives to encourage cooperative R&D and spin-off policies to foster entrepreneurship among R&D personnel. These policies are compared with the no-policy alternative evolving from the initial state serving as a benchmark to verify the gains (or loses) in the number of firms cooperating and networking. Firms' behavior is defined according to empirical findings from analysis of determinants of firms' participation in cooperation in innovation with other organizations using the Korean Innovation Survey. The analysis based on manufacturing sector data shows that firms' decision to cooperate with partners is primarily affected positively by firm's size and the share of employees involved in R&D activities. Then, each cooperative partnership is affected by a different set of determinants. The agent-based models are found to have a great potential to be used in decision support systems for policy makers. The findings indicate possible appropriate policy strategies to be applied depending on the target industries. We have applied few examples and showed how the results may be interpreted. Guidelines are provided on how to generalize the model to include a number of extensions that can serve as an optimal direction for future research in this area.

Agent-based model: A method worthy of promotion in Library and Information Science

“…Potluri et al [22] simulated the economic behaviour under the premise of ‘data localisation’, regarded data producers and consumers as agents that can make decisions independently, and analysed the interaction under different states for policy-makers’ reference. Heshmati and Lenz-Cesar [23] discussed various factors affecting innovation cooperation, and simulated innovation incentive policies of enterprise cooperation. This article believes that ABMs have great potential in the support system of decision-makers.…”

Life Cycle Management of Infrastructures

“…This implies that the ABM creates an abstraction model of the real world based on a network of agents that demonstrates synergies and interaction behaviors between them in the system. The ABM may potentially help to overcome the underlying limitations in the current LCM tools and make it possible to assess system behavior and effectiveness of an innovation or a sets of strategies (Berman et al 2004;Heshmati and Lenz-Cesar 2015).…”