Complexity and industrial networks

1. Complexity and industrial networks Preliminary notions

2. Systems and aggregates System: “…the properties of the components depend on the systemic context within which the components are located” Juarrero, p. 109 “The root idea of system is of integration into orderly whole that functions as an organic unity” Rescher (1979), cited in Juarrero, p.109 Aggregate: “…the properties of parts do not change depending on whether or not they are part of the aggregate” Juarrero, p. 109

3. Reading complexity as a theory of constraints

4. BZ reaction: rules and constraints of self-organisation in autocatalytic sets

5. Autocatalytic Set Catalyst: • any object that accelerates a reaction (in biology an enzyme) • example of positive feedback or non linear behaviour • catalysis leads systems away from equilibrium Autocatalytic set (Kauffman, 1995; Ingber, 2000; Juarrero, 1999, Prigogine, 1989, McKelvey, 2000): • example • closure • autocatalytic set creates macro-correlation • autopoiesis (Maturana 1980, Grobstein 1973) • emergence of higher level order • Interlevel causality: bottom-up and top-down (“the previously unknown”, Kant, The Critique of judgement”)

6. A B E C D A B C D E A BZ reaction A  X B + X  Y + Q X  P Y + 2X  3X

7. What are catalytic sets made of?

8. Constraints as relational properties Context-free constraints (CFCs) • Affect equiprobability not independence of events • In BZ CFCs set the probabilities of occurrence of the different channels of reactions • In language CFCs affect the probability of occurrence of any single letter, e.g. in English as and es more likely than xs and zs • CFCs bear no relationship with time and space

9. Constraints as relational properties First order Context sensitive constraints (CSCs) • Takes aggregate’s components away from independence • Makes probability of occurrence of event B dependent upon prior occurrence of event A; probability of B becomes a function of space and time. CSCs introduce idiosyncratic development, that is history • In BZ CSCs cause the appearance of chemical waves due to action of catalysts that close around certain channels and create the condition of interdependence between contiguous molecules; • I-tuplets in language

10. Constraints as relational properties First order CSC • CSCs make complexity possible and literally create the system. The emergence of self-organised systems is the manifestation of the closure (autocatalysis) of CSC. • CSCs work bottom-up • CSCs respect the principle of locality “By correlating and coordinating previously aggregated parts into a more complex, differentiated systematic whole, contextual constraints enlarge the variety of states the system as a whole can access” Juarrero, p138

11. Constraints as relational properties Second order CSC • The autocatalytic network emerges as an overall constraint for the single elements • Second order constraints define the system’s boundary and, by reducing the components’ degrees of freedom, they define the system’s trajectory (path of development). Stated in another way the behaviour of the single components depends on the collective coherence defined by the catalytic closure • 2nd order CSCs work top-down (whole to part) • Do 2nd order CSCs obey the principle of locality?

12. Krugman’s big question “...Suppose that we really lived in the constant returns world tat much economic theory still assumes. Then it would be hard to understand why the economy is not characterised by ‘backyard capitalism’, in which each household or small group produces most items for itself” Fujita, Venables, Krugman: The spatial economy, p.2

13. Krugman’s hypothesis “...The dramatic spatial unevenness of the real economy is surely the result not of inherent differences among locations but of some set of cumulative processes, necessarily involving some form of increasing returns, whereby geographic concentration can be self-reinforcing” Fujita, Venables, Krugman: The spatial economy, p.2

14. Autocatalytic processes in networks of SMEs • Question: what are the constraints that set in motion self-sustaining (autocatalytic) processes that generate networks? • Objectives of research: identify • context free constraints • context sensitive constraints • catalytic processes • catalytic closure and coevolutive properties

15. Autocatalytic processes in networks of SMEs context free constraints geographic and/or historical conditions that affect diversity and concentration of agents context sensitive constraints “two prisoners’ dilemma”: cooperation or defection policy are context sensitive (depend on previous outcomes); the interplay between context sensitive and context free constraints isolate communities of ‘cooperators’ catalytic processes increasing returns mechanisms, market externalities, multiplier effects catalytic closure and coevolutive properties Self-referencing of catalytic processes (autocatalytic set or mutualism)generate coevolution in dissipative systems. Diversity in system determines coevolutive rate of change

16. $ $ $ $ 2$ 2$   $ 2$ 3$ 3$    $ 3$ The base multiplier

17. Y = X + aX + a2X + … + anX Aggregate income of region Fraction of X reused within cluster Second wave of transactions triggered by export Income from export An example of catalytic set: the base multiplier  X/(1-a) Y: income of region; X: income from external transaction (export); a: multiplier

18. å/ _ Y = (1+ (1- 4X)1/2/2  1/4 å (1- å)/ An example of catalytic set: the base multiplier Y Y = X/(1- å) 10 6 2 X 0 1.0 2.0 3.0 Source: Krugman, 1999, “The spatial Economy” p 29

19. Base multiplier and economies of scale Base multiplier Economies of scale

20. Interpretations of the base multiplier • Base and non-base activities • Pred’s interpretation:  =  (size of local market) • Krugman’s elaboration: Pred’s hypothesis hides complex dynamics and specifically non linear cumulative process around an S-curve • The multiplier as an autocatalytic set: economies of variety, modularity and deconstruction

21. The autocatalytic set of economies of diversity Base multiplier Architectural and disruptive innovation Vertical disintegration Reuse of knowledge Acceleration of microcoevolutive rate Economies of diversity Modularisation of production Niche separation effects predominate over population selection effects Disparity and variety increase

22. “… diversity probably begets diversity; hence diversity may help beget growth” Kauffman, “At home in the universe”, p. 292

23. Variety Number of distinct species in a group or Number of technological options based on a technological trajectory (dominant design) Disparity Number of categories necessary to classify all species or Number of technological trajectories A definition of diversity (Jay Gould)

24. An example of variety and diversity

25. Organisation by firm as diversity reducing • Monolithic network • Integrated aggregate • Rational allocation of scarce resources • Closed system: optimised design of NK and minimisation of CS links • Firm as a coordination and resources allocation mechanism in presence of information asymmetry (Evans & Wurster, 1999; Malone and Laubacher, 1998) and stable environment • Specialisation strategy: • variety increasing and disparity decreasing (Kogut, 2000) • sustaining, radical and component innovation (Christensen 1997, Clark &Henderson, 1990) • Exploration and exploitation of opportunities within single technological trajectory (Dosi 1982; Nelson & Winter 1982) and dominant production paradigm

26. Organisation by firm as diversity reducing • Monolithic network • Integrated aggregate • Rational allocation of scarce resources • Closed system: optimised design of NK and minimisation of CS links • Firm as a coordination and resources allocation mechanism in presence of information asymmetry (Evans & Wurster, 199?, Malone and Laubacher, 199?) and stable environment • Specialisation strategy: • variety increasing and disparity decreasing (Kogut, 2000) • sustaining, radical and component innovation (Christensen 1997, Clark &Henderson) • Exploration and exploitation of opportunities within single technological trajectory (Dosi, Nelson & Winter) and dominant production paradigm

27. Organisation by network as diversity increasing • Distributed system • Redundancy • Emergent allocation of resources • Parallel modularity: interface and knowledge • open system: NK and CS self-adjust • Network as an emergent uncertainty shedding mechanism • Diversification strategy: • Disparity increasing and disparity/variety trade off • Locus of diversity of organisations • Locus of organisation of diversity (Grabher, 1997) • Exploration and exploitation of diversity • Incremental, architectural and disruptive innovation

28. Organisation by network as diversity increasing • Distributed system • Redundancy • Emergent allocation of resources • Parallel modularity: interface and knowledge • open system: NK and CS self-adjust • Network as an emergent uncertainty shedding mechanism • Diversification strategy: • Disparity increasing and disparity/variety trade off • Locus of diversity of organisations • Locus of organisation of diversity (Grabher, 199?) • Exploration and exploitation of diversity • Incremental, architectural and disruptive innovation

29. Readings Axelrod R, 1984, “The evolution of co-operation”, New Basic Books, London Christensen, C.M, (1997), “The innovator’s dilemma”, Harvard Business School Press Evans, Wurster (1999) “Blown to bits”, Harvard Business School Press Fujita M, Venables A, Krugman P, 1999, “The spatial economy: cities, regions and international trade”, MIT Press, Cambridge, Mass Grabher G. and Stark, D. (1997), “Organising diversity: evolutionary theory, network analysis and postsocialism”, Regional Studies, Vol. 31.5, pp. 533-544 Ingber, D.E. (2000), “The origin of cellular life”, Bioessays, 22 Ingber, D.E. (1998), “The architecture of life”, Scientific American, N. 278 Juarrero, A. (1999), “Dynamics in action”, MIT Press Kauffman, S. (1995), “At home in the universe”, Oxford Krugman, (1996), “The self-organizing economy”, Blackwell Malone, T.M. & Laubacher, R.J. (1998) “The Dawn of the E-Lance Economy”, Harvard Business Review, September-October Nelson, R.R., Winter, S.G. (1982) An Evolutionary Theory of Economic Change, Harvard University Press Nicolis G, Prigogine I, (1989), “Exploring complexity: an introduction”, Freeman, New York Gibbons M, Metcalfe J, 1986, “Technology, variety and competition” In: Prigogine, I., and Sanglier, M., “Laws of nature and human conduct”, Academie Royal Belgique, Brussels Stirling, A. (1998), “On the economics and analysis of diversity”, Electronic Papers Working Series N.28, Brighton, SPRU