Showing papers by "David J. Teece published in 2021"

Innovating Big Tech Firms and Competition Policy: Favoring Dynamic Over Static Competition

Abstract: This paper gives a fresh account of competition in the digital economy. Economic analysis in the field of industrial organization remains largely focused on a sophisticated version of the Schumpeter-Arrow debate, which is unresolved and largely irrelevant. We posit the need to look at competition anew. Static models of monopoly firms and markets in equilibrium are often used to characterize Big Tech firms’ size and scope. We suggest that this characterization is inappropriate because the growth and diversification of many digital firms lead to a situation of broad-spectrum competition that cuts across markets. Current market positions do not reflect monopoly power but are vulnerable to the competitive pressure of disequilibrating forces arising from the use of data-driven operating models, astute resource orchestration, and the exercise of dynamic capabilities. A few strategic errors by management in handling internal transitions and/or external challenges and big tech firms could be competitively impaired. The implications of a more dynamic understanding of the competition process in the digital economy are explored. We consider how big data and entrepreneurial management impacts firm performance. We also explore the nature of different types of rents (Schumpeterian, Ricardian, and monopoly rents) and suggest a modified long-term consumer welfare standard for competition policy. We formulate preliminary tests and predictors to assess dynamic competition. Our perspective advances a policy stance that favors innovation.

Profiting from enabling technologies

Abstract: How to profit from innovation has been an important question for both innovation scholars and practitioners over the years. It is certainly a relevant question for all types of technological innova...

Innovating Big Tech firms and competition policy: favoring dynamic over static competition

Abstract: This paper gives a fresh account of competition in the digital economy. Economic analysis in the field of industrial organization remains largely focused on a sophisticated version of the Schumpeter-Arrow debate, which is unresolved and largely irrelevant. We posit the need to look at competition anew. Static models of monopoly firms and markets in equilibrium are often used to characterize Big Tech firms’ size and scope. We suggest that this characterization is inappropriate because the growth and diversification of many digital firms lead to a situation of broad-spectrum competition that cuts across markets. Current market positions do not reflect monopoly power but are vulnerable to the competitive pressure of disequilibrating forces arising from the use of data-driven operating models, astute resource orchestration, and the exercise of dynamic capabilities. A few strategic errors by management in handling internal transitions and/or external challenges and big tech firms could be competitively impaired. The implications of a more dynamic understanding of the competition process in the digital economy are explored. We consider how big data and entrepreneurial management impacts firm performance. We also explore the nature of different types of rents (Schumpeterian, Ricardian, and monopoly rents) and suggest a modified long-term consumer welfare standard for competition policy. We formulate preliminary tests and predictors to assess dynamic competition. Our perspective advances a policy stance that favors innovation.

Innovation, governance, and capabilities: implications for competition policyA Tribute to Nobel Laureate Oliver Williamson by his Colleague and Mentee David J. Teece

Abstract: Oliver Williamson’s contributions to many subfields of economics are salutary. However, he was recognized by the Nobel Laureate Committee primarily for his work on the boundaries (scale and scope) of the firm. This tribute endeavors to marry Williamson’s transaction cost economics with a capabilities framework to obtain new insights into how the scope and scale of technology companies influence their competitive performance in today’s digital economy. The role of big data and learning are highlighted. Strong implications for competition policy, and for management, emerge from the fusion of the two frameworks. Such fusion yields a more granular view of management and policy issues but requires the policy analyst to understand not just industrial economics but also the technology management literature which also has useful insights for competition policy and regulatory professionals.

Technological Leadership and 5G Patent Portfolios: Guiding Strategic Policy and Licensing Decisions:

Abstract: Whether it’s mobile phones or autonomous cars or telemedicine, a well-functioning robust 5G ecosystem will require licensing executives to have a deep understanding of the need for timely licensing...

Capability-Based Theories of Multinational Enterprise Growth

Abstract: In this chapter we argue that traditional approaches to modeling the growth of the multinational enterprise (MNE) that focus on costs and efficiencies are too narrow to adequately and comprehensively address the foundations of MNE growth trajectories. Today’s global realities and the changing view of the MNE require a more focused and explicit capability-based perspective. In particular, we posit that contemporary theories of the MNE require frameworks and explanations that should simultaneously account for the uncertainties that firms face in their external environment and the complexities of often competing internal, organizational alternatives. To develop our reasoning in support of capability-based thinking, we discuss the changing nature on the international business (IB) landscape, the evolving views on the nature of the MNE, and present the core building blocks of capability-based thinking in managing MNE growth. We conclude the chapter by offering some thoughts on how capability-based thinking could be applied in future scholarly efforts.

Resolving Bargaining Range Indeterminacy in Patent Damages After VirnetX

Abstract: Recent US federal court rulings have provided new guidance on the use of economic models of bargaining in estimating reasonable royalty damages in patent cases. After reviewing relevant case law and providing an overview of the bargaining range approach, we describe one analytic method (the Rubinstein Bargaining Model) for developing a quantitative starting point with which to divide a bargaining range and explain how it can be tied, at least in part, to the facts and circumstances of the parties around the time of the Hypothetical Negotiation. We also describe how this approach can be used in conjunction with an analysis of other quantitative and qualitative factors related to the bargaining power of the parties, to help estimate reasonable royalty damages.