Abstract
This article examines contingencies and constraints in problem-solving processes underlying technological change and industry evolution. It shows how learning through practice can help drive technical change but, when this is impeded, the ability to make use of models and engage in experimental learning becomes even more pertinent for explaining variation in the rate and direction of technical change. The article explores HIV as an example of vaccine innovation, and vaccines as an example of medical innovation. I find the absence of these two variables (ability to learn directly in humans, and ability to learn vicariously through animal models) not only make up a large part of how I would characterize “difficulty” in the HIV R&D process, but they also seem to go a long way toward explaining why 33 other diseases have—or have not—had vaccines developed for them. Implications for theory and policy are discussed.
Highlights
Why have we been able to put a man on the moon but not improve the plight of those in the ghetto? That question, posed nearly 40 years ago, remains as troubling today as it was (Nelson, 2011)
This article explores how R&D and its technologies can lead to highly uneven effects on practice and how the cognitive and organizational conditions of knowledge growth can give rise to strikingly heterogeneous innovation outcomes. It examines contingencies and constraints in the problem-solving processes underlying technological change. The nature of these problem-solving processes, and the ability to incorporate them into organizational routines, have profound effects on industrial dynamics
The presence of such bodies of knowledge is important for industrial organization because it serves to increase the endogeneity of science, as well as redefine the productivity of the technological paradigm
Summary
Why have we been able to put a man on the moon but not improve the plight of those in the ghetto? That question, posed nearly 40 years ago, remains as troubling today as it was (Nelson, 2011). This article explores how R&D and its technologies can lead to highly uneven effects on practice and how the cognitive and organizational conditions of knowledge growth can give rise to strikingly heterogeneous innovation outcomes. It examines contingencies and constraints in the problem-solving processes underlying technological change. What sets medicine apart from most other sectors of economic activity is that it is research intensive, or that is it is widely appreciated as being so, but that safety plays a paramount role Defective technology in this domain can be harmful or lethal. I discuss the extent to which variation in vaccines against other diseases can be explained using these two variables (Section 6)
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