How do scientific innovations spread within and across scientific communities? In this paper, we propose a general account of the diffusion of scientific innovations. This account acknowledges that novel ideas must be elaborated on and conceptually translated before they can be adopted and applied to field-specific problems. We motivate our account by examining an exemplary case of knowledge diffusion, namely, the early spread of theories of rational decision-making. These theories were grounded in a set of novel mathematical tools and concepts (...) that originated in John von Neumann and Oskar Morgenstern's Theory of Games and Economic Behavior and subsequently spread widely across the social and behavioral sciences. Introducing a network-based diffusion measure, we trace the spread of those tools and concepts into distinct research areas. We furthermore present an analytically tractable typology for classifying publications according to their roles in the diffusion process. The proposed framework allows for a systematic examination of the conditions under which scientific innovations spread within and across preexisting and newly emerging scientific communities. (shrink)

Network analysis is increasingly appreciated as a methodology in the social sciences. In recent years, it is also receiving attention among historians of science. History of economics is no exception in that researchers have begun to use network analysis to study a variety of topics, including collaborations and interactions in scientific communities, the spread of economic theories within and across fields, or the formation of new specialties in the discipline of economics. Against this backdrop, a debate is emerging about how (...) network analysis can help address questions that are pertinent to the history of economics. With this paper, we want to push this debate one step forward by offering and discussing five reasons why network analysis should have a future in the history of economics. (shrink)

In the wake of Stalin's death, many Soviet scientists saw the opportunity to promote their methods as tools for the engineering of economic prosperity in the socialist state. The mathematician Leonid Kantorovich (1912–1986) was a key activist in academic politics that led to the increasing acceptance of what emerged as a new scientific persona in the Soviet Union. Rather than thinking of his work in terms of success or failure, we propose to see his career as exemplifying a distinct form (...) of scholarship, as a partisan technocrat, characteristic of the Soviet system of knowledge production. Confronting the class of orthodox economists, many factors were at work, including Kantorovich's cautious character and his allies in the Academy of Sciences. Drawing on archival and oral sources, we demonstrate how Kantorovich, throughout his career, negotiated the relations between mathematics and economics, reinterpreted political and ideological frames, and reshaped the balance of power in the Soviet academic landscape. (shrink)

Economic methodologists most often study the relations between models and reality while focusing on the issues of the model's epistemic relevance in terms of its relation to the ‘real world’ and representing the real world in a model. We complement the discussion by bringing the model's constructive mechanisms or self-implementing technologies in play. By this, we mean the elements of the economic model that are aimed at ‘implementing’ it by envisaging the ways to change the reality in order to bring (...) it more in line with the model. We are thus concerned mainly not with the ways to change the model to ‘fit’ the reality, but rather with the model's own armature that is supposed to transform the world along theoretical lines. The case we study is Arrow–Debreu–McKenzie general equilibrium model. In particular, we show the following: gradient methods and stability could be regarded as constructive mechanisms of general equilibrium modeling in the context of market socialism debates; the obsession of general eq.. (shrink)