The Living Thing / Notebooks : Innovation

See also Intellectual Property.

I am especially interested in modeling how technology changes the rules of the game, as opposed to marginally changes some parameters; not, say residual stochastic shocks (in the “Real Business Cycle” models), or as the slope of a marginal cost of production curve (in textbook microeconomics). That is, technological innovation that leads to a qualitative, rather than incremental, change in the state of play —- respecting that a lot of marginal changes might in fact lead to major qualitative changes.

In recognition of that emphasis, I briefly called this entry “disruptive technology” instead of mere “innovation”, but then I felt like a TED speaker and woke up sweating in the night to change it.

To consider

This is at the very limit of modelability, surely?. The introduction of a new technology has many components, from social uptake, to supply chains, to the discovery process. The unexpected interactions with the other technologies out there. The internal combustion engine changed more than just transit times. The computer network altered more than just mail delivery times.

The cascade of effects from any one alteration is, it is likely, unknowable in advance, but might have some regularities, or at least some kind of underlying set of distributions as a stochastic process - some kind of branching process perhaps? Fixation processes, by analogy with evolutionary theory?

“Product space” model

Due originally to Hidalgo and Hausmann, and made purportedly more rigorous by Caldarelli et al.

Considers products and nations in a bipartite graph, and does various network statistics upon it.

Attempts to be predictive about the “natural level” of a country’s GDP.

(c.f. Felix Reed-Tsochas’ affinity for such graphs, har har) Note that there is an implicit third part in the graph, to whit “capabilities”, which represent infrastructure to manufacture products.

Frank Schweitzer et al have a similar notion of inter-firm R&D networks which may be related? See references.

Hype cycle

Should mention this, despite nonverifiability etc.

Marginal returns on research

Moore’s law versus Eroom’s law governing trends in marginal research productivity. What does the paucity of new drugs mean?

Eroom's law, via John D Cook

Declining marginal productivity in drug research, from the Scanelli et al paper.

Other interesting things to look at


Anderies, J. M.(2003) Economic development, demographics, and renewable resources: a dynamical systems approach. Environment and Development Economics, 8, 219–246. DOI.
Antonelli, C., & Ferraris, G. (2011) Innovation as an Emerging System Property: An Agent Based Simulation Model. Journal of Artificial Societies and Social Simulation, 14(2), 1.
Arthur, W. B.(1989) Competing Technologies, Increasing Returns, and Lock-In by Historical Events. The Economic Journal, 99(394), 116–131. DOI.
Battiston, F., Cristelli, M., Tacchella, A., & Pietronero, L. (2014) How metrics for economic complexity are affected by noise. Complexity Economics, 1(1), 1–22. DOI.
Beinhocker, E. D.(2007) Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. . Harvard Business Press
Beinhocker, E. D.(2011) Evolution as computation: integrating self-organization with generalized Darwinism. Journal of Institutional Economics, 7(Special Issue 03), 393–423. DOI.
Caldarelli, G., Cristelli, M., Gabrielli, A., Pietronero, L., Scala, A., & Tacchella, A. (2012) A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy. PLoS ONE, 7(10), e47278. DOI.
Cristelli, M., Tacchella, A., Gabrielli, A., Pietronero, L., Scala, A., & Caldarelli, G. (2012) Competitors’ communities and taxonomy of products according to export fluxes. The European Physical Journal Special Topics, 212(1), 115–120. DOI.
Cristelli, M., Tacchella, A., & Pietronero, L. (2015) The Heterogeneous Dynamics of Economic Complexity. PLoS ONE, 10(2), e0117174. DOI.
David, P. A.(1985) Clio and the Economics of QWERTY. The American Economic Review, 75(2), 332–337.
Derex, M., Beugin, M.-P., Godelle, B., & Raymond, M. (2013) Experimental evidence for the influence of group size on cultural complexity. Nature, 503(7476), 389–391. DOI.
Filimonov, V., Bicchetti, D., Maystre, N., & Sornette, D. (2014) Quantification of the high level of endogeneity and of structural regime shifts in commodity markets. Journal of International Money and Finance, 42, 174–192. DOI.
Filimonov, V., & Sornette, D. (2012) Quantifying reflexivity in financial markets: Toward a prediction of flash crashes. Physical Review E, 85(5), 56108. DOI.
Filimonov, V., & Sornette, D. (2013) A stable and robust calibration scheme of the log-periodic power law model. Physica A: Statistical Mechanics and Its Applications, 392(17), 3698–3707. DOI.
Frenken, K. (2006a) Innovation, Evolution and Complexity Theory. . Edward Elgar Publishing
Frenken, K. (2006b) Technological innovation and complexity theory. Economics of Innovation and New Technology, 15(2), 137–155. DOI.
Garas, A., Tomasello, M. V., & Schweitzer, F. (2014) Selection rules in alliance formation: strategic decisions or abundance of choice?. arXiv:1403.3298 [Physics].
Gerlach, M., & Altmann, E. G.(2013) Stochastic Model for the Vocabulary Growth in Natural Languages. Physical Review X, 3(2), 21006. DOI.
Gisler, M., & Sornette, D. (2008) Exuberant Innovations: The Apollo Program. Society, 46(1), 55–68. DOI.
Goldenberg, J., Libai, B., Louzoun, Y., Mazursky, D., & Solomon, S. (2004) Inevitably reborn: The reawakening of extinct innovations. Technological Forecasting and Social Change, 71(9), 881–896. DOI.
Grebel, T. (2009) Technological change: A microeconomic approach to the creation of knowledge. Structural Change and Economic Dynamics, 20(4), 301–312. DOI.
Hua, L., & Wang, W. (2014) The impact of network structure on innovation efficiency: An agent-based study in the context of innovation networks. Complexity, n/a-n/a. DOI.
Iribarren, J. L., & Moro, E. (2011) Branching dynamics of viral information spreading. Physical Review E, 84(4), 46116. DOI.
Kali, R., Reyes, J., McGee, J., & Shirrell, S. (2013) Growth networks. Journal of Development Economics, 101, 216–227. DOI.
König, M. D., Battiston, S., Napoletano, M., & Schweitzer, F. (2011) Recombinant knowledge and the evolution of innovation networks. Journal of Economic Behavior & Organization, 79(3), 145–164. DOI.
König, M. D., Battiston, S., Napoletano, M., & Schweitzer, F. (2012) The efficiency and stability of R&D networks. Games and Economic Behavior, 75(2), 694–713. DOI.
Lane, D. A., & Maxfield, R. R.(2005) Ontological uncertainty and innovation. Journal of Evolutionary Economics, 15, 3–50. DOI.
Moussaïd, M., Kämmer, J. E., Analytis, P. P., & Neth, H. (2013) Social Influence and the Collective Dynamics of Opinion Formation. PLoS ONE, 8(11), e78433. DOI.
Nowak, M. A., & Krakauer, Da. C. (1999) The evolution of language. Proceedings of the National Academy of Sciences of the United States of America, 96(14), 8028.
Ormerod, P., & Bentley, R. A.(2010) Modelling Creative Innovation. Cultural Science, 3(1).
Rahmandad, H., & Sterman, J. D.(2008) Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models. Management Science, 54, 998–1014. DOI.
Saavedra, S., Reed-Tsochas, F., & Uzzi, B. (2011) Common Organizing Mechanisms in Ecological and Socio-economic Networks. In F. Reed-Tsochas & N. Johnson (Eds.), Complex Systems and Interdisciplinary Sciences (London.). World Scientific Publishing
Saichev, A. I., Sornette, D., & Filimonov, V. (2009) Most Efficient Homogeneous Volatility Estimators (SSRN Scholarly Paper No. ID 1596036). . Rochester, NY: Social Science Research Network
Scannell, J. W., Blanckley, A., Boldon, H., & Warrington, B. (2012) Diagnosing the decline in pharmaceutical R&D efficiency. Nature Reviews Drug Discovery, 11(3), 191–200. DOI.
Schweitzer, F., Fagiolo, G., Sornette, D., Vega-Redondo, F., Vespignani, A., & White, D. R.(2009) Economic Networks: The New Challenges. Science, 325(5939), 422–425. DOI.
Solé, R. V., Corominas-Murtra, B., Valverde, S., & Steels, L. (2010) Language networks: Their structure, function, and evolution. Complexity, 15, 20–26. DOI.
Solé, R. V., Valverde, S., Casals, M. R., Kauffman, S. A., Farmer, D., & Eldredge, N. (2013) The evolutionary ecology of technological innovations. Complexity, 18(4), 15–27. DOI.
Sood, V., Mathieu, M., Shreim, A., Grassberger, P., & Paczuski, M. (2010) Interacting branching process as a simple model of innovation. Physical Review Letters, 105(17), 178701. DOI.
Stadler, B. M. R., Stadler, P. F., Wagner, G. P., & Fontana, W. (2001) The Topology of the Possible: Formal Spaces Underlying Patterns of Evolutionary Change. Journal of Theoretical Biology, 213(2), 241–274. DOI.
Sutton, J. (2001) Technology and Market Structure: Theory and History. . The MIT Press
Tacchella, A., Cristelli, M., Caldarelli, G., Gabrielli, A., & Pietronero, L. (2012) A New Metrics for Countries’ Fitness and Products’ Complexity. Scientific Reports, 2. DOI.
Tacchella, A., Cristelli, M., Caldarelli, G., Gabrielli, A., & Pietronero, L. (2013) Economic complexity: Conceptual grounding of a new metrics for global competitiveness. Journal of Economic Dynamics and Control, 37(8), 1683–1691. DOI.
Tainter, J. A.(1995) Sustainability of complex societies. Futures, 27, 397–407. DOI.
Thiel, P. A.(2014) Zero to one: notes on startups, or how to build the future. (First edition.). New York: Crown Business
Thorngate, W., Liu, J., & Chowdhury, W. (2011) The Competition for Attention and the Evolution of Science. Journal of Artificial Societies and Social Simulation, 14(4), 17.
Tomasello, M. V., Napoletano, M., Garas, A., & Schweitzer, F. (2013) The Rise and Fall of R&D Networks. arXiv:1304.3623 [Physics].
Tomasello, M. V., Perra, N., Tessone, C. J., Karsai, M., & Schweitzer, F. (2014) The role of endogenous and exogenous mechanisms in the formation of R&D networks. Scientific Reports, 4. DOI.
Tria, F., Loreto, V., Servedio, V. D. P., & Strogatz, S. H.(2013) The dynamics of correlated novelties. arXiv:1310.1953 [Physics], 4. DOI.
Valverde, S., Solé, R. V., Bedau, M. A., & Packard, N. H.(2007) Topology and evolution of technology innovation networks. Phys. Rev. E, 76(5), 56118. DOI.
Vespignani, A. (2009) Predicting the Behavior of Techno-Social Systems. Science, 325(5939), 425–428. DOI.
Zabell, S. L.(1992) Predicting the unpredictable. Synthese, 90(2), 205–232. DOI.
Zaccaria, A., Cristelli, M., Tacchella, A., & Pietronero, L. (2014) How the Taxonomy of Products Drives the Economic Development of Countries. arXiv:1408.2138 [Q-Fin].