From the organization to the division of cognitive labor

Politics, Philosophy and Economics

Volumn 8, Issue 1, 2009, Pages 101-129

  D'Agostino, Fred ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

Complexity; Epistasis; Interdependency; Kuhn; Modularity; NK fitness landscapes; Path dependency; Risk spreading

Indexed keywords

EID: 58449109159     PISSN: 1470594X     EISSN: 17413060     Source Type: Journal    
DOI: 10.1177/1470594X08098873     Document Type: Article

References (101)

1. Phillip Kitcher, 'The Division of Cognitive Labor', Journal of Philosophy 87 (1990): 5-22;
2. See also Phillip Kitcher, The Advancement of Science: Science without Legend, Objectivity without Illusions (New York: Oxford University Press, 1993)
3. and Phillip Kitcher, Science, Truth, and Democracy (Oxford: Oxford University Press, 2001).
4. Compare Steve Fuller, Social Epistemology (Bloomington: Indiana University Press, 1988).
5. Kitcher, The Advancement of Science, p. 303.
6. Fred D'Agostino, '"Demographic" Factors in Revolutionary Science: The Wave Model', Methodology and Science 26 (1993): 41-52.
7. See also Fred D'Agostino, Free Public Reason (New York: Oxford University Press, 1996)
8. and Fred D'Agostino, 'Kuhn's Risk-Spreading Argument', Episteme 1 (2005): 201-9.
9. D'Agostino, 'Kuhn's Risk-Spreading Argument'; Alexander Rueger, 'Risk and Diversification in Theory Choice', Synthese 109 (1996): 263-80.
10. Thomas Kuhn, The Structure of Scientific Revolutions (Chicago, IL: University of Chicago Press, 1970), p. 186.
11. Fred D'Agostino, 'Pluralism and Liberalism', in Handbook of Political Theory, edited by Gerald F. Gaus and Chandran Kukathas (Thousand Oaks, CA: Sage, 2004).
12. Rachel Laudan and Larry Laudan, 'Dominance and the Disunity of Method', Philosophy of Science 56 (1989): 221-33.
13. Fred D'Agostino, 'Incommensurability and Commensuration: Lessons from (and to) Ethico-Political Theory', Studies in the History and Philosophy of Science 31 (2000): 429-47.
14. See also D'Agostino, 'Kuhn's Risk-Spreading Argument'.
15. Chun Wei Choo, The Knowing Organization: How Organizations Use Information to Construct Meaning, Create Knowledge, and Make Decisions (Oxford: Oxford University Press, 1998), p. xvii.
16. Fred D'Agostino, Rituals of Cosmopolitanism. Sites of Cosmopolitanism: Citizenship, Aesthetics, Culture (Brisbane: Griffith University Centre for Public Culture and Ideas, 2005).
17. D'Agostino, 'Kuhn's Risk-Spreading Argument'.
18. Friedrich A. Hayek, Law, Legislation and Liberty (Chicago, IL: University of Chicago Press, 1973-76).
19. Imre Lakatos, 'Falsification and the Methodology of Scientific Research Programmes', in Criticism and the Growth of Knowledge, edited by Imre Lakatos and Alan Musgrave (Cambridge: Cambridge University Press, 1970).
20. Fred D'Agostino, 'Naturalizing the Essential Tension', Synthese 162 (2008): 302.
21. Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations (London: Routledge, 1893 [1776]), Book I, Ch. 1.
22. Karl Marx, Capital (London: Lawrence and Wishart, 1954 [1867]), Vol. I, Ch. 14.
23. They include Carliss Baldwin and Kim Clark, Design Rules, Volume 1: The Power of Modularity (Cambridge, MA: MIT Press, 2000);
24. Stefano Brusoni and Andrea Prencipe, 'The Division of Labor and the Division of Knowledge'. Paper presented at Dynamics of Industry and Innovation: Organizations, Networks and Knowledge, Copenhagen Business School, 27-29 June 2005;
25. Giovanni Dosi, 'Technological Paradigms and Technological Trajectories', Research Policy 11 (1982): 147-62;
26. Sendil Ethiraj and Daniel Levinthal, 'Modularity and Innovation in Complex Systems', Management Science 50 (2004): 159-73;
27. Koen Frenken, Innovation, Evolution and Complexity Theory (Cheltenham and Northampton, MA: Edward Elgar, 2006);
28. Raghu Garud, Arun Kumaraswamy and Richard N. Laglois, Managing in the Modular Age: Architectures, Networks and Organizations (Oxford: Blackwell, 2003);
29. Stuart A. Kauffman, The Origins of Order: Self Organization and Selection in Evolution (New York: Oxford University Press, 1993);
30. Luigi Marengo and Giovanni Dosi, 'Division of Labor, Organizational Coordination and Market Mechanisms in Collective Problem Solving', Journal of Economic Behavior and Organization 58 (2005): 303-26;
31. Luigi Marengo, Giovanni Dosi, Paolo Legrenzi and Conrado Pasquali, 'The Structure of Problem-Solving Knowledge and the Structure of Organizations', Industrial and Corporate Change 9 (2000): 757-88;
32. Ron Sanchez and Joseph T. Mahoney, 'Modularity, Flexibility, and Knowledge Management in Product and Organization Design', Strategic Management Journal 17 (1996): 63-76;
33. Eric Von Hippel, 'Task Partitioning: An Innovation Process Variable', Research Policy 19 (.1990): 407-18. (Kauffman is important and widely cited by others, but, it should be noted, he writes as a biologist.)
34. Allen Newell and Herbert A. Simon, Human Problem Solving (Englewood Cliffs, NJ: Prentice Hall, 1972);
35. Herbert A. Simon, The Sciences of the Artificial (Cambridge, MA: MIT Press, 1969).
36. Isaiah Berlin, Four Essays on Liberty (London: Oxford University Press, 1969);
37. John Gray, Post-Liberalism: Studies in Political Thought (London: Routledge, 1993).
38. Fred D'Agostino, 'Ethical Pluralism and the Role of Opposition in Democratic Polities', Monist 73 (1990): 437-63.
39. See also Fred D'Agostino, 'Some Modes of Public Justification', Australasian Journal of Philosophy 69 (1991): 390-414;
40. D'Agostino, Free Public Reason;
41. Fred D'Agostino, 'The Legacies of John Rawls', Journal of Moral Philosophy 1 (2004): 351-67;
42. D'Agostino, 'Pluralism and Liberalism.'.
43. Compare D'Agostino, Free Public Reason, Section 26.
44. This disputes some remarks by Gerald F. Gaus, Value and Justification (Cambridge: Cambridge University Press, 1990).
45. Marengo and Dosi, 'Division of Labor, Organizational Coordination and Market Mechanisms in Collective Problem Solving', p. 309.
46. Fred D'Agostino, Incommensurability and Commensuration: The Common Denominator (Aldershot: Ashgate, 2003).
47. Frenken, Innovation, Evolution and Complexity Theory, p. 8 (emphasis added).
48. It is worth noting that such complex relations among evaluative standards are recognized, or at least asserted, by ethical 'particularists' such as Jonathon Dancy. See Jonathon Dancy, Moral Reasons (Oxford: Blackwell, 1993). Indeed, Dancy's particularism is grounded precisely in such complexity, not that, to my knowledge, he puts it that way himself.
49. Ethiraj and Levinthal, 'Modularity and Innovation, in Complex Systems', p. 161 (emphasis added).
50. Kauffman, The Origins of Order;
51. Lee Altenberg, 'NK Fitness Landscapes', in The Handbook of Evolutionary Computation, edited by Thomas Back, David B. Fogel and Zbigniew Machalewicz (Oxford: Oxford University Press, 1997).
52. John W. Payne, James R. Bettman and David Schkade, 'Measuring Constructed Preferences: Towards a Building Code', Journal of Risk and Uncertainty 19 (1999): 243 ff.
53. Frenken, Innovation, Evolution and Complexity Theory, pp. 33-4.
54. Paolo Saviotti and J.S. Metcalfe, 'A Theoretical Approach to the Construction of Technological Output Indicators', Research Policy 14 (1984): 141-51.
55. R.A. Fisher, The Genetical Theory of Natural Selection (Oxford: Oxford University Press, 1930).
56. Marengo et al., 'The Structure of Problem-Solving Knowledge and the Structure of Organizations', p. 760 (emphasis added).
57. It is important to note that our analysis presupposes that we have commensurated the standards. Difficulties searching a complex landscape are, of course, as I have pointed out and will reiterate, made more difficult when the landscape itself is constructed 'as we go', as, of course, it almost always is. The difficulties we are examining here, however, do not depend on this point. Even a fully constructed evaluative landscape will be difficult to search for the best option when that landscape is rugged.
58. Frenken, Innovation, Evolution and Complexity Theory, p. 15.
59. Frenken's fifth point is striking and will bear further consideration. It seems, on the face of it, to suggest that there may, in fact, be little point in wasting resources searching a very rugged fitness landscape, since there will be little reward, in the form of improved outcomes, to be gained. See note 40 below.
60. I will comment later (note 44 below) on a possibility that the attentive reader may have already noticed, namely, that the permutations of technical changes may not exhaust those of the underlying standards against which overall service value is understood.
61. All the difficulties of searching a pre-existing NK evaluative landscape are only compounded, of course, when we have to construct it as we go - develop variants on existing options and commensurate standards of evaluation which have not already been 'priced out' with respect to one another.
62. Frenken, Innovation, Evolution and Complexity Theory, p. 14.
63. It is worth remarking, of course, that the key features of a rugged evaluative landscape (many mediocre local optima) might ground a case for Simonian 'satisficing'. Why bother to expend resources in searching a space where a local peak is not likely to differ very much from any other local peak. Find a peak and stay there might be rather good advice. For an interesting discussion, see ibid., pp. 25 ff.
64. Ibid., p. 20.
65. Marengo and Dosi, 'Division of Labor, Organizational Coordination and Market Mechanisms in Collective Problem. Solving', p. 309 (emphasis added).
66. Frenken, Innovation, Evolution and Complexity Theory, p. 21. In this case it is crucial, though I have not seen it commented on, that the very notion of a global optimum makes sense only in relation to the system as a whole and only as an option, which is composite. I will return to this point.
67. Ibid. Even relative to the qualifications I will review later, this approach encounters a potential difficulty which has not, to my knowledge, been discussed in the literature. The difficulty arises because or to the extent that the technically achievable subdivision of the object of enquiry does not map properly onto the decomposition of the evaluative space. The suggestion is that it cannot be guaranteed that the ways in which it is possible to decompose the object of enquiry will line up in the right sort of way with the ways in which it is possible to partition the values interdependencies. (I am not sure how this relates to what, according to Frenken, Innovation, Evolution and Complexity Theory, p. 34, Saviotti calls the 'imaging pattern between technical and service characteristics'.)
68. See Paolo Saviotti, Technological Evolution, Variety and the Economy (Cheltenham and Brookfield, MA: Edward Elgar, 1996), p. 66.
69. See note 37 above.
70. Baldwin and Clark, Design Rules, Volume 1.
71. Ibid., p. 50.
72. Ibid.
73. Marengo and Dosi, 'Division of Labor, Organizational Coordination and Market Mechanisms in Collective Problem. Solving', p. 309.
74. Ibid., p. 310.
75. Readers familiar with social choice theory will hear the resonance of this description with the cycling that can arise in situations in which multiple points of view need to be reconciled with one another to identify a socially best choice. Compare Dennis C. Mueller, Public Choice II (Cambridge: Cambridge University Press, 1989).
76. Baldwin and Clark, Design Rules, Volume 1, p. 50.
77. Garud et al., Managing in the Modular Age, p. 2.
78. Terry Connolly and Ken Koput, 'Naturalistic Decision Making and the New Organizational Context', in. Organizational Decision Making, edited by Zur Shapira (Cambridge: Cambridge University Press, 2002), p. 288.
79. See, in particular, Baldwin and Clark, Design Rules, Volume 1;
80. Ethiraj and Levinthal, 'Modularity and Innovation in Complex Systems'; Garud et al., Managing in the Modular Age;
81. Sanchez and Mahoney, 'Modularity, Flexibility, and Knowledge Management in Product and Organization Design'.
82. Sanchez and Mahoney, 'Modularity, Flexibility, and Knowledge Management in Product and Organization Design', p. 65.
83. Compare Ethiraj and Levinthal, 'Modularity and Innovation in Complex Systems', p. 161 and Baldwin and Clark, Design Rules, Volume 1, p. 14.
84. It is not a trivial matter to partition a system into subsystems. I consider this issue later. It is also appropriate to recall my earlier discussion of the potential mismatch between feasible partitions of the technical characteristics of the object of enquiry and partitions of the service characteristics by which that object is to be judged. See notes 37 and 44 above. Especially when the evaluative space is constructed as we go, enquirers are not working directly with service, but rather, with technical characteristics. Any sensible partitioning of the task is probably therefore going to be made on a technical basis.
85. I have adopted a way of describing these decisions and the design rules to which they lead, despite the way in which they are commonly portrayed, as decisions which enforce partitions on technical characteristics, rather than service characteristics. This only adds to my anxieties about the potential for a mismatch. There is no reason to believe, a priori, that technically feasible subdivisions will track evaluatively modular partitions.
86. Brian Loasby, Choice, Complexity and Ignorance (Cambridge: Cambridge University Press, 1976), pp. 77-8.
87. Baldwin and Clark, Design Rules, Volume 1, pp. 68-9.
88. Ethiraj and Levinthal, 'Modularity and Innovation in Complex Systems', p. 162 (emphasis added).
89. Baldwin and Clark, Design Rules, Volume 1, p. 70.
90. Ethiraj and Levinthal, 'Modularity and Innovation in Complex Systems', p. 169-70.
91. Marengo et al., 'The Structure of Problem-Solving Knowledge and the Structure of Organizations', p. 777.
92. (In D'Agostino, Incommensurability and Commensuration, pp. 137-8, I described what was, in effect, a federalist model for enquiry of a similar kind.)
93. Brian Loasby, 'Decision Premises, Decision Cycles and Decomposition', Industrial and Corporate Change 9 (2000): 722.
94. Kuhn, The Structure of Scientific Revolutions, p. 186.
95. I do not here insist on another kind of diversity, for example the kind Kuhn wrote of in which, because of differences in weighting contributory evaluative standards, different teams might have a different sense of what was needed, to be 'best overall'. Perhaps, as I suggested earlier, there is unanimity among the teams only when an option is 'dominant' in the sense that I recommended earlier and elsewhere.
96. Marengo et al., 'The Structure of Problem-Solving Knowledge and the Structure of Organizations', pp. 779-80.
97. For relevant discussion, see Garud et al, Managing in the Modular Age, p. 4.
98. Giovanni Dosi, 'Opportunities, Incentives, and the Collective Patterns in Technological Change', Economic Journal 107 (1997): 1531.
99. Marengo et al., 'The Structure of Problem-Solving Knowledge and the Structure of Organizations', p. 757.
100. Pierre Bourdieu, 'The Specificity of the Scientific Field and the Social Conditions of the Progress of Reason', in The Science Studies Reader, edited by Mario Biagiolo (New York and London: Routledge, 1998 [1975]), p. 39.
101. Michael Polanyi, 'The Republic of Science', Minerva .1 (1962): 55.