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Technology licensing is an important means for companies to extract more value from their intellectual assets. We build a model that helps understand how licensing activity should be organized within large corporations. More specifically, we compare decentralization—where the business unit using the technology makes licensing decisions—to centralized licensing. The business unit has superior information about licensing opportunities but may not have the appropriate incentives because its rewards depend on product market performance. If licensing is decentralized, the business unit forgoes valuable licensing opportunities because the rewards for licensing are (optimally) weaker than those for product market profits. This distortion is stronger when production-based incentives, especially private benefits, of business unit managers are more powerful, making centralization more attractive. Surprisingly, we find that interdependency across business units may result in more, not less, decentralization. Furthermore, even though centralization results in less information, centralized licensing deals are larger. Our model conforms to the existing evidence that reports heterogeneity across firms in both licensing propensity and organization of licensing. This paper was accepted by Bruno Cassiman, business strategy.
Organization design, Centralization, Licensing; Markets for technology; Organization design, Markets for technology; Innovation; Licensing, Licensing, Strategic organization design, Markets for technology, Technology licensing, jel: jel:L22, jel: jel:L2, jel: jel:L24, jel: jel:O32
Organization design, Centralization, Licensing; Markets for technology; Organization design, Markets for technology; Innovation; Licensing, Licensing, Strategic organization design, Markets for technology, Technology licensing, jel: jel:L22, jel: jel:L2, jel: jel:L24, jel: jel:O32
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 70 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |