Abstract
Here we turn to mechanisms of knowledge transfer in the Haze, initially within a paradigm before expanding to cross-paradigm exchanges. Before we do, the reader is reminded of one aspect of the following analysis. The use of theoretical tools to describe the interactions which lead scientists to new ideas or combinations of knowledge can make them appear routine, even as arranged occurrences. This strategy is helpful in reducing complexity to a manageable level.
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Here we turn to mechanisms of knowledge transfer in the Haze, initially within a paradigm before expanding to cross-paradigm exchanges. Before we do, the reader is reminded of one aspect of the following analysis. The use of theoretical tools to describe the interactions which lead scientists to new ideas or combinations of knowledge can make them appear routine, even as arranged occurrences. This strategy is helpful in reducing complexity to a manageable level. However, it also obscures the random and stochastic nature of these interactions. In general, it is not possible to plan them and often it is not evident until after the fact that such an exchange “triggered” the recognition of a new connection (Graßhoff 2008). This obscurity is the cause of the insurmountable complexity of the Haze; it is dependent on what we, at this point, can only classify as accidental occurrences. The more experience we gather with scientific breakthroughs, the better we can generalize them, however, they remain unique incidents resulting from a vast number of interdependent events. The story of one breakthrough holds hints about how another breakthrough will unfold, but cannot explain it fully. The physical and mathematical understanding of how and why the Haze condenses in one particular situation is contained in the breakthrough itself; the ability to understand how the pieces fit together requires the breakthrough to already have happened. If we wish to influence these processes, however, we may be able to increase the probability of such beneficial circumstances.
The narrative in Parts I and II illustrated several interactions between Haber and Nernst (and the resulting scientific progress) with only limited attention to the social setting. In the case of ammonia synthesis, the setting was simple: a small number of actors (or alters), manageable geographical distances, and adequate avenues of communication. In consideration of the development of scientific thought, it has been informative to consider the breakthrough without a theoretical social aspect (Rudwick 1985, pp. 411–435). Many scientific breakthroughs occur in arenas for discovery of limited social scope, making this perspective a common one. Can a reliance on case studies, or anecdotes, lead to conclusions similar to those of studies involving statistically significant numbers of actors encompassing an array of experiences (Lalli et al. 2021)?
Successful scientific advances are a result of direct epistemic transfers of information between theory and experiment or from social interactions which achieve the same outcome (Rudwick 1985, pp. 6–15). However, scientists operate in an environment that also allows for social interactions which are not of this type. What are the consequences of the different kinds of exchanges? Considering the nature of a scientist’s social network, we include living adherents to the accepted body of theoretical and experimental knowledge making up the content of the paradigm.Footnote 1 These are members of the scientific social setting who are able to personally engage in meaningful transfers of information. In order to incorporate the paradigm itself into the social setting, we can also include deceased colleagues who have made contributions to the body of knowledge (Rutherford 1938, p. 74), (Fangerau 2010, p. 131). Transfers facilitated by a scientist between dead colleagues (directly between theory and experiment) are epistemic transfers. Examples from ammonia synthesis include the way in which Nernst contrived and applied his version of the third law or how Haber was able to combine the empirical studies of the catalyst with the strict physicochemical equilibrium determination. Social interactions between living colleagues, however, can have varying outcomes. An example of a non-epistemic knowledge transfer is Nernst’s behavior at the meeting of the Bunsen Society in Hamburg (Part II, Sect. 11.1.4)
For a closer examination, let us consider some social network theory applied to the case study of ammonia synthesis. These theoretical tools will help us differentiate between specific types of knowledge transfer to sharpen the boundaries of what is and what is not part of science—even in the limit of small groups of actors. As we will see, some elements of the macrodynamics associated with the scientific endeavor do not result in the identification of any new scientific value because they are not part of science at all.
In scientific settings, potentially creative isolates may be at work at the edge of their social networks. (The influence of social settings has been linked to innovation and creativity, stemming particularly from loosely bound adherents to a group (isolates) (Ibarra and Andrews 1993; Perry-Smith and Shalley 2003).) However, what amounts to “social isolation” in science does not only apply to one’s current social setting. It also applies to the paradigm. Were he talented enough and supplied with proper knowledge of physical chemistry and catalysis, Fritz Haber could have completed his scientific experiments on ammonia synthesis in complete physical isolation. He could have worked in a cave without access to experience or external input from living colleagues. In other words, to achieve his breakthrough, it was possible for Haber to rely purely on information available before he began his work. He needed an apparatus, but this is the realm of engineering (in Part II, the contributions of his technical assistants are outlined), which allows only the production of experimental data. As it turned out, the interaction with Walther Nernst at the meeting of the Bunsen Society in Hamburg was not just accelerative (as it would have been in the idealized case of a “discovery in a cave”), it was needed to extend the limits of both Haber’s and Nernst’s understanding of physical chemistry as neither was in command of the complete set of physicochemical knowledge available at the beginning of the research. “Neither of the initial alternatives,” writes Rudwick in the case of the Devonian Controversy, “…had a monopoly in the requirements for victory…(Rudwick 1985, p. 405).” An incomplete knowledge base is often the case and scientists require interaction with one another, or the chance to capitalize on “the utility of people,” in order to successfully incorporate creative elements into their work (Becker 1984; Kanter 1988; Kasperson 1978), (Csikszentmihályi 1996, chapter 6, pp. 294–296), (Obstfeld 2017; Perry-Smith and Shalley 2003). The reliance on actual human exchanges illustrates the complexity of the real-life social setting of a scientist (Rudwick 1985, p. 456). In practical situations, the mere transfer of concepts between theory and experiment is unlikely to be successful on its own, because one person will not be in possession of a complete set of knowledge.
In real scientific work, there is much trial and error, conjecture, and opining about what the right answer might be. New ideas are continuously advocated and then accepted or rejected, both with and without apt consideration (Stigler 1982). These decisions are based on two strategies of cooperation. One is that “the certain path to feeling creative is to find a constituency more ignorant than you and poised to benefit from your idea (Burt 2004).” Burt, I think, was making a theoretical point about the power of bridging a “structural hole (Burt 1992, 2004).” A different dynamic can also play out. I once heard a senior colleague say something to the effect of: the way to be successful in science is to collaborate with people who are smarter than you and learn from them. It is the same dynamic of knowledge transfer but depends on who is giving and who is receiving—it is easy to see which party will tend to be more critical and which more deferential. Eventually, everyone will have their turn at each end. However, the decision-making process has no effect on what the correct answer actually is.
What, then, is the mechanism of transfer?
Borrowing the term from social network theory for the purposes of our examination, the answer is brokerage. Put simply, the concept of brokerage refers to behavior that links individuals from different groups via the closure of an open triad (in other words, it bridges a structural hole). Brokerage is also possible through the act of bringing individuals together who know each other but had not yet thought to collaborate in the manner proposed or enabled by the broker. Such activity may presuppose the existence of special (social) skills, self-motivation, the ability to motivate others, or the establishment of trust (Burt 2004; Fligstein 2001; Obstfeld et al. 2014; Padgett and Ansell 1993), (Obstfeld 2017, chapter 1), (Sgourev 2013, 2015). It also provides a connection between micro- and macrodynamics (Sgourev 2015), (Rudwick 1985, p. 14). The interesting cases are those acts of brokerage that result in combinations of knowledge leading to something new (a thing or idea), possibly triggering a non-linear effect. Strictly speaking, brokerage is a social interaction with many outcomes, some of which could have the effect of an epistemic transfer. Successful scientific advancement depends on the linking of theory and experiment (epistemic transfer) by means of a novel pathway along with relevant social interactions that amend gaps in an individual’s knowledge (Rudwick 1985, p. 405).
There are three kinds of brokerage. The most basic is conduit brokerage in which “the broker provides value to one group by providing them with needed resources derived from another group. The potential for providing value through conduit brokerage is a function of the differences between the parties connected by the broker (Obstfeld et al. 2014).” The more valuable the information, or token, the higher the syntactic boundaries (common lexicon) and semantic boundaries (requires translation) become (Carlile 2004), (Obstfeld 2017, pp. 33–34). The next type of brokerage, tertius iungens, or “the third who joins,” includes knowledge transfer but goes beyond conduit activity and “is most opportune when the broker detects opportunities to connect complementary, rather than redundant, alter [individual] attributes such as resources and abilities. At the same time, iungens brokerage connecting those with differing ties or attributes brings with it the corresponding challenge of coordinating dissimilar backgrounds and interests (Obstfeld et al. 2014).” However, successful knowledge transformation can lead groups or individuals to change their position and embrace new and innovative strategies (Obstfeld 2017, p. 56). These two types of exchanges can facilitate an epistemic transfer and drive the dynamic that advances science. While tertius iungens brokerage harbors the potential to combine knowledge into substantial advances, there is also the risk of the “action problem.” This complication arises when useful combinations of knowledge are possessed by groups which are uncoordinated and, therefore, cannot act in concert. The heterogeneity promises greater potential benefits for those involved, but also a higher risk of failure (Obstfeld et al. 2014). The inverse of the action problem is the “idea problem,” in which dense networks have the ability to react but may lack the ideas with which they can produce novel value (Granovetter 1973; Obstfeld 2005). This situation is in play in any interdisciplinary pursuit without brokerage. Science itself would function for some time without significant knowledge transfer, but eventually conduit or tertius iungens activity is required because no one scientist can independently achieve all necessary epistemic transfers.
There is a also a third type of brokerage called tertius gaudens (Burt 1992), or “the third who rejoices (when the other two parties are in conflict).” “Tertius gaudens strategies involve the restriction of alter-alter activity by either keeping certain alters apart or actively cultivating alter-alter tension in a given interaction…(Obstfeld et al. 2014).” The broker employing this practice “profits by maintaining separation between alters [players, individuals]…(Obstfeld 2005).” This type of social interaction, which is also present in a scientist’s social environment, is not and does not facilitate an epistemic transfer and is without permanent effect on scientific progress (the interpretation of experimental results in the context of a theory). It is, however, found in two endeavors that are tightly intertwined with the social dynamic of science: engineering and politics (in an academic setting or with respect to funding decisions). Both these pursuits have subjective aspects so that tertius gaudens microdynamics, whether intentional or not, can alter the perceived best and, therefore, chosen outcome. In science, the result leads to social artifacts such as research strategies, selection of methods, accepted solutions, and funding decisions.
In the conclusion of Part II, the importance of “microcomplexities” between 1903 and 1908 were discussed as they emerged within the arena for discovery of ammonia synthesis. There is a gap between microprocesses and observed macro-scale characteristics which may be closed by appropriate aspects of brokerage (Kanter 1988; Obstfeld 2005; Sgourev 2015). Due to this gap, science can appear from the macro-level to contain subjective social elements resulting from political dynamics and engineering decisions. That is, science appears to behave like any other field (engineering, politics, art, business, sports, etc.), especially if tertius gaudens microdynamics are considered. At the micro-level, however, tertius gaudens (and some conduit and tertius iungens) brokerage activity does not result in an epistemic transfer and makes no contribution to scientific advancement. The solution to a scientific investigation is determined by the paradigm and it is only a question of time until the twists and turns of normal science (perhaps created by various social interactions or erroneous conclusions or results) lead to the correct answer. The solution itself, and the value of this solution, is path-independent because a theory is not impacted by our wants and needs (Polanyi 1962, p. 4). The only permanent result of tertius gaudens brokerage in changing a scientific outcome is to delay it for so long that a paradigm shift renders it irrelevant or, I suppose, that the world comes to an end.
For an example, we again consider the meeting of the Bunsen Society in Hamburg in 1907. Assuming the role of a tertius gaudens broker, Walther Nernst attempted to convince the assembled scientists that the equilibrium of ammonia was such that industrial upscaling was unlikely—and this after he had already entered into a contractual agreement with Grießheim-Elektron the year before to commercially develop this same process. Nernst’s actions, after consideration of the experimental and theoretical numbers at his disposal, make it likely that he suspected from the earliest stages that industrial upscaling was actually worth pursuing. However, from a scientific perspective, this conclusion is immaterial: either the rules of physical chemistry allow for the industrial synthesis of ammonia using current technological capabilities or they do not. At most, any “success” Nernst could have had as a tertius gaudens broker would have been to detract others so that he could benefit financially or receive recognition for being the first to complete the synthesis on a laboratory scale. It is certainly possible that he had such motivations; Nernst was a business man and did not shy away from vanity. Rudwick also discusses the career acumen and financial means of the actors in the Devonian Controversy and comes to the conclusion that they had no effect on the outcome (Rudwick 1985, pp. 438–445).
The instances of conduit, tertius iungens, and tertius gaudens brokerage employed during the scientific development and early-stage industrialization of ammonia synthesis are shown in Fig. 18.1. Both Haber and Nernst pursued a combined conduit-iungens strategy of brokerage when bridging the gap between theory and their technical assistants in the realm of experiment and later, between science and industry (Obstfeld et al. 2014). One good example of the evolution of their approach is illustrated by the vessel in which ammonia was synthesized. Between 1905 and 1908, the synthesis was performed in a pressure oven with a catalyst to establish a precise temperature and pressure at which small amounts of nitrogen, hydrogen, and ammonia were in equilibrium (Part II, Chap. 11). The results, obtained by Haber, Nernst, and their assistants, were only a verification of physicochemical principles established by linking theoretical and laboratory considerations. In 1909, Haber and his assistant Robert Le Rossignol translated this information into a more industrial language by building their final laboratory apparatus, which included all of the aspects needed for industrialization (continuous ammonia production, heat exchange) but still at a laboratory scale (Part II, Fig. 12.1). The translation continued as Carl Bosch and Alwin Mittasch, with considerable effort and setbacks, upscaled the machinery and catalyst according to the principles established by Haber (Part I, Chap. 7). Only after those challenges had been overcome, could industrialization be completed with the factory at Leuna in 1913. In this final phase, Haber was absent.
Another, purely scientific, brokerage dynamic is found in the interaction between Fritz Haber and Walther Nernst themselves between 1903 and 1908. Here, they also brokered between theory and experiment with a combined strategy, albeit in ways more explicitly dependent on their backgrounds. Nernst brokered mainly from theory to experiment, while Haber maintained a balance, moving at times in either direction. One notable aspect is that some of this brokerage involved a two-step bridging of the structural holes (Fig. 18.2a). Theoretical knowledge sometimes moved from Nernst to Haber and then from Haber to experiment, or laboratory experience moved in the opposite direction. From another perspective, Haber and Nernst simultaneously occupied positions in both theory and experiment. The historical record does not allow for a full reconstruction of the state of physical knowledge of each man, but their specific behavior indicates their interaction may also be characterized via the pathway of knowledge transfer called the structural fold, shown in Fig. 18.2b (Vedres and Stark 2010). In addition, Fig. 18.2 shows Friedrich Jost as an independent contributor to research on ammonia synthesis after 1907 (Part II, Chap. 11).
It is also worth mentioning that brokerage can be used in the development of new talent for the next generation (Sgourev 2015), a pursuit to which Haber and Nernst were committed throughout their careers.
The analysis of Haber and Nernst’s brokerage roles gives theoretical underpinning to the two scientists’ abilities to shift between experiment and the mathematically demanding theory of physical chemistry. In Part II, I assigned great importance to this movement as a determining factor in Haber’s breakthrough. Their positions, in some ways peripheral with ties to outside groups, are described as “structurally contradictory,” “anomalous,” or “stylistically incoherent” (Padgett and Ansell 1993; Sgourev 2015). Haber was the more anomalous of the two. His theory work may not have been as bold as Nernst’s, but he was more than a proficient theorist. It was Haber’s experimental expertise—or perhaps his attention to experimental detail—that gave him the decisive advantage over Nernst when he correctly incorporated the effect of the catalyst into his work. As he himself put it: “…a combination of experimental success with thermodynamic considerations was needed (Haber 1920, p. 326).” Haber’s experience from his early career in the experimental domain gave him a novel perspective when he transitioned to theory, as did the ability to develop conceptual tools not available to the common scientist (Padgett and McLean 2006).
Nernst, through his relationship with Grießheim-Elektron, had a further intermediary, or structurally anomalous position, this time between science and industry. It is a position Haber would later assume with BASF and demonstrates the potential of bridging this kind of divide. Such brokerage activity may cause investments to be made in scientific research in a speculative way, or at the “low end” of the market, and may effect the speed with which a scientific discovery is industrialized, or who reaps the financial rewards. However, while these anomalous positions may be crucial in the transformation of scientific value into commercial market value, the resulting activity does not alter the scientific value itself.
The result of successful brokerage is not only knowledge transfer and coordination, but also the creation of a tie where a structural hole used to be (with respect to an epistemic transfer I used the term pathway). These ties can be strong or weak (or perceived to be such) and bind an alter, or actor, into a social network (Granovetter 1973; Ibarra and Andrews 1993; Perry-Smith and Shalley 2003). The strength of the ties, as well as to whom the alter is connected, help to indicate a central or peripheral position. Pioneers or pathfinders, whom we focus on here, often are (or perceive themselves to be) marginal. The classic conundrum is that innovative players at the periphery are free to act as they wish, but have limited influence. Influential players who are well-connected, on the other hand, are less free to act. Having weak ties is vital to being innovative, but there is a limit, after which an increasing number of weak ties becomes detrimental (Granovetter 1973; Kerckhoff and Back 1965), (Becker 1984, pp. 233–246), (Sgourev 2013, 2015). An alter’s position is, furthermore, dynamic (Rudwick 1985, p. 420). Initially, “weak [boundary-spanning] ties are better than strong ties for creativity and…a peripheral position with many connections outside of the network is likely to be associated with more creative insights and potentially groundbreaking advancements” because “exposure to a new process of working or a new approach to a problem may serve as a seed that causes one to pursue previously unexplored directions…” However, success and exposure will lead to a new equilibrium and “eventually, the person will become so central in the network that he or she will become too entrenched or immersed, ultimately constraining creativity (Perry-Smith and Shalley 2003).”Footnote 2 Returning to the social network of a scientist, a setting in which access to knowledge of current trends is not necessary for success and where disregard for external public or professional opinion may have no consequence, we can see how the problem may be overcome of remaining innovative while occupying a central position. A scientist’s social setting consists of colleagues and paradigm (the body of theoretical and experimental knowledge), and being “central” or “peripheral” can be with respect to either. A senior scientist can be well-connected (in, say, a political sense) to colleagues in the field of specialization but remain an isolate with respect to the paradigm; the ties to dead colleagues remains weak. This researcher is free to innovate and has the influence to publicize any results. Such a position is often assured via the power of job security (tenure) and research freedom, equating to the ability to take risks. It is also possible that a scientist, senior or junior, has many weak ties to living colleagues but chooses to stick closely to the chosen paradigm. It is unlikely this researcher will be innovative. In a unique situation, a researcher may be peripheral with respect to both living and dead colleagues. If the novel, creative work of this researcher proves correct according to the “objective” truth within the paradigm, the results will eventually gain acceptance.Footnote 3 While weak ties to living colleagues can be beneficial in science for identifying and articulating knowledge, they may also be limited; weak ties are not necessarily decisive for diffusion of knowledge through social contacts because the published scientific literature (especially renowned journals) can replace them. However, the number of ties can effect the speed at which the information disseminates. Strong ties to living colleagues are the key to amassing political clout, which may be needed for subjective decisions, such as setting research agendas or establishing scientific consensus (and are especially important if the choices are poor).
Part II, Chap. 10 describes how this social structure played into Haber’s rationale for taking up the challenge of ammonia synthesis. Politically, he was a central player with job security, at least after he became a professor in Karlsruhe. However, as he had one foot in both theory and experiment, he had weak ties to both these sets of knowledge compared to many of his colleagues who had one main area of expertise. He was in a position to be innovative and to take a risk. As for Nernst, he had stronger ties to theory than Haber, but weaker ties to experiment. While also an advantageous position, in this case, Haber had a more beneficial mixture.
The discussion thus far has covered the transfer of knowledge within a paradigm, that is, during times of normal science. However, the example of ammonia synthesis shows transfers of knowledge between paradigms can also be decisive for a scientific breakthrough. Let us recall the aforementioned example of Haber facilitating the knowledge transfer between the paradigm of empirical chemistry (the qualitative behavior of the catalyst) and the quantitative mathematical theory of physical chemistry, at times with the help of Nernst. Another example can be found during the early stages of industrialization at BASF: the transfer of knowledge between Alwin Mittasch, who led purely empirical investigations to identify a suitable industrial catalyst, and Carl Bosch who was upscaling Haber’s laboratory apparatus while remaining within the conditions dictated by physical chemistry. This brokerage dynamic is actually more complicated in that Bosch formed the link directly to engineering while Haber remained involved in the upscaling as the direct link to physical chemistry. We still see this activity today in scientific research. Investigations of catalyst materials, for example, involve multiple independent fields such as empirical chemistry and materials science, optics, the wave theory of light, semiconductor theory, thermodynamics, ab initio density functional theoretical calculations (quantum mechanics), classical electrodynamics, and relativistic electrodynamics (Greiner et al. 2018). The exploitation of these weak ties is reflected in publications with long author lists representing many institutes. The discussion of cross-paradigmatic work is concluded in Chap. 21.
One final, seemingly simple factor central to successful brokerage is that capable individuals need a reason to engage in knowledge transfer. They need motivation to interact, access to one another, and a working atmosphere that encourages and facilitates trust and collaboration (i.e. a research facility) (Brooks 1994; Pavitt 1990), (Csikszentmihályi 1996, chapter 6), (Burt 2004; Fligstein 2001; Obstfeld et al. 2014; Sgourev 2015). These factors seem so obviously important but are often neglected in practice. Silicon Valley, for example, has put much effort into cultivating and maintaining such an atmosphere (Part I, Chap. 8). In science especially, where value can be difficult to assess, sources of motivation can be ephemeral. Whether it be the pursuit of an aesthetic theory, a professorship, “the need to know,” or the thrill of discovery, there are many genuine sources of motivation in science. These must be strengthened and proliferated because the structure of academic research can lend itself to attempts at gaudens brokerage—a choice that at best slows, but can also damage the scientific endeavor.
Notes
- 1.
Today scientists are often adherents to multiple paradigms spanning the investigation of different components of complex systems (see Chap. 21).
- 2.
Fleck argued that this move from the periphery toward the center is accompanied by a of loss of ability to think outside of the paradigm (Fleck 1980, pp. 109, 121–124). While this assertion may be true in some cases, it is not a general characteristic of becoming more incorporated into a scientific community. However, the situations in which one can comfortably express one’s self freely may become rare.
- 3.
The question of whether this researcher will receive due credit is another matter.
References
Becker, H. S. 1984. Art worlds. University of California Press.
Brooks, H. 1994. The relationship between science and technology. Research Policy 23: 477–486
Burt, R. S. 1992. Structural holes: The social structure of competition. Cambridge: Harvard University Press.
Burt, R. 2004. Structural holes and good ideas. American Journal of Sociology 110: 349–399.
Carlile, P. R. 2004. Transferring, translating, and transforming: An integrative framework for managing knowledge across boundaries. Organization Science 15: 499–616.
Csikszentmihályi, M. 1996. Flow and the psychology of discovery and invention. New York: HarperCollins.
Fangerau, H. 2010. Spinning the scientific web: Jaques Loeb (1859–1924) und sein Programm einer internationalen biomedizinischen Grundlagenforschung. Berlin: Akademie Verlag.
Fleck, L. 1980. Entstehung und Entwicklung einer wissenschaftlichen Tatsache: Einführung in die Lehre vom Denkstil und Denkkollektiv. Frankfurt am Main: Suhrkamp Verlag.
Fligstein, N. 2001. Social skill and the theory of fields. Sociological Theory, 105–125.
Granovetter, M. S. 1973. The strength of weak ties. American Journal of Sociology 78: 1360–1380.
Graßhoff, G. 2008. Gesprch mit Dr. J. Bednorz. In Innovation–Begriffe und Thesen, ed. G. Graßhoff and R. Schwinges, 133–147. Zürich: vdf Hochschulverlag.
Greiner, M. T., T. E. Jones, S. Beeg, L. Zwiener, M. Scherzer, F. Girgsdies, S. Piccinin, M. Armbrüster, A. Knop-Gericke, and R. Schlögl. 2018. Free-atom-like d states in single-atom alloy catalysts. Nature Chemistry 10: 1008–1015.
Haber, F. 1920. Nobel prize lecture. In English: https://www.nobelprize.org/nobel_prizes/chemistry/laureates/1918/haber-lecture.pdf, In German: https://www.nobelprize.org/nobel_prizes/chemistry/laureates/1918/haber-lecture_ty.html.
Ibarra, H. and S. B. Andrews. 1993. Power, social influence, and sense making: Effects of network centrality and proximity on employee perceptions. Administrative Science Quarterly 38: 277–303.
Kanter, R. M. 1988. When a thousand flowers bloom: Structural, collective, and social conditions for innovation in organization. Research in Organizational Behavior 10: 169–211.
Kasperson, C. J. 1978. Psychology of the scientist: XXXVIL scientific creativity: A relationship with information channels. Psychological Reports 42: 691–694.
Kerckhoff, A. C. and K. W. Back. 1965. Sociometric patterns in hysterical contagion. Sociometry 28: 2–15.
Lalli, R., R. Howey, and D. Wintergrün. 2021. The dynamics of collaboration networks and the history of general relativity, 1925–1970. Scientometrics 122: 1129–1170.
Obstfeld, D. 2005. Social networks, Tertius Iungens orientation, and involvement in innovation. Administrative Science Quarterly 50: 100–130.
Obstfeld, D. 2017. Getting new things done. Stanford: Stanford Business Books.
Obstfeld, D., S. P. Borgatti, and J. Davis. 2014. Brokerage as a process: Decoupling third party action from social network structure. In Research in the sociology of organizations: Contemporary perspectives on organizational social networks, ed. D. J. Brass, S. P. Borgatti, D. S. Halgin, G. Labianca, and A. Mehra, vol. 4, 135–159. Bingley: Emerald Group Publishing Limited.
Padgett, J. F. and C. K. Ansell. 1993. Robust action and the rise of the Medici, 1400–1434. American Journal of Sociology 98: 1259–1319.
Padgett, J. F. and P. D. McLean. 2006. Organizational invention and elite transformation: The birth of partnership systems in renaissance florence. American Journal of Sociology 111: 1463–1568.
Pavitt, K. 1990. What makes basic research economically useful? Research Policy 20: 109–119.
Perry-Smith, J. E. and C. E. Shalley. 2003. The social side of creativity: A static and dynamic social network perspective. Academy of Management Review 28: 89–106.
Polanyi, M. 1962. Personal knowledge. Chicago: The University of Chicago Press.
Rudwick, M. J. S. 1985. The Great Devonian controversy. Chicago: The University of Chicago Press.
Rutherford, E. 1938. Forty years of physics. In Background to modern science, ed. J. Needham and W. Pagel. Cambridge: Cambridge University Press.
Sgourev, S. V. 2013. How Paris gave rise to cubism (and Picasso): Ambiguity and fragmentation in radical innovation. Organization Science 24: 1601–1617.
Sgourev, S. V. 2015. Brokerage as catalysis: How Diaghilev’s Ballets Russes escalated modernism. Organization Studies 36: 343–361.
Stigler, G. J. 1982. The process and progress of economics. Nobel Prize Lecture.
Vedres, B. and D. Stark. 2010. Structural folds: Generative disruption in overlapping groups. American Journal of Sociology 115: 1150–1190.
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Johnson, B. (2022). Dynamic of The Haze. In: Making Ammonia. Springer, Cham. https://doi.org/10.1007/978-3-030-85532-1_18
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