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What is Outside-In and Inside-Out Strategy

Handbook of Research on Green, Circular, and Digital Economies as Tools for Recovery and Sustainability
A conceptual approach leverages the theory spillover of knowledge from Foreign Direct Investments, multinational corporations, and state-owned enterprises into local companies through spin-offs initiatives Domiciling investing in identified knowledge domains to local firms, including small and medium enterprises and local institutes of research and learnings to facilitate innovation and growth.
Published in Chapter:
Developing a National Innovation System in Small States: A Case for Brunei Darussalam's Economic Development – A Catalyst for Digitalization Catch-Up and Economic Growth
Amirul Shahnoel Noeh (Universiti Brunei Darussalam, Brunei), Pg Siti Rozaidah Pg Idris (Universiti Brunei Darussalam, Brunei), and Muhammad Anshari (Universiti Brunei Darussalam, Brunei)
DOI: 10.4018/978-1-7998-9664-7.ch006
Abstract
This study shares some empirical insights for adopting a national innovation system (NIS) to catalyze capacity building in small states with relatively low technology-based research and development resources. These countries may have to start further back than other nations; however, this chapter maintains that with the right NIS, latecomers can have the advantage of catching up economically. This study explores Brunei Darussalam's journey to catalyze innovation for sustainable economic growth, particularly digitalization and deep tech. The study found that establishing a national innovation ecosystem could be effective with national consensus and acceptance behind the approach. It emphasizes building critical infrastructures, institutions, and governance to promote efficient knowledge flow, talent development, digital literacy, and overall absorptive capacity. Because Brunei is a small state, coordinating and facilitating cohesive linkages among its key stakeholders can strategically mobilize change. As Brunei Darussalam embarks on such a trajectory, it must determine a relevant model.
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