a capability theory of production: learning in time,...
TRANSCRIPT
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DIME Workshop on “Production theory” Process, Technology, and Organisation: Towards a useful Theory of Production
LEM | Scuola Superiore Sant'Anna, Pisa
A capability theory of production: learning in time, complementarities and proximities
Antonio Andreoni1 University of Cambridge
Abstract By integrating structural approaches to production with capability theories, the paper outlines a capability theory of production. The black box of the production process has been opened by describing it as a particular network of interrelated tasks through which transformations of materials are performed according to different patterns of capabilities coordination, and subject to certain scale and time conditions. Capabilities are structurally constrained, although an entire spectrum of virtual organizational and technological arrangements is possible. These possibilities are generated by multiple relationships of complementarity and similarity among structural components –i.e. materials in transformation, productive agents and network of tasks – both at the firm and inter-firm level. Discovering these possibilities is the very essence of a fully endogenous process of learning – i.e. structural learning in historical time. Complementarities are essential focusing devices in the continuous process of reconfiguration of the analytical map of production relationships. In this process of change, problems of capability compatibility and coordination arise both at the firm/industry and inter-firm/industry level. Different forms of production organization have historically emerged and reappeared in response to these coordination problems. Production organizations develop in historical time as a result of exogenous circumstances as well as endogenous dynamics according to patterns of specialization and diversification. In today’s global division of labour and knowledge, the need for coordinating closely complementary but dissimilar activities has found a response in the network-form of production organization. The effectiveness of these networks in coordinating production and innovation activities is determined by the degree of proximity among the agents embedded in the network and, thus, among their capabilities. As a matter of fact, the analysis of the internal structure of production and its change is essential for investigating the structural dynamics of economic systems and for developing a political economy of capability building. Keywords: Production Theory; Economics of Capabilities; Complementarities; Structural Learning; Network form of production organization; Proximity; Political Economy of Capability Building.
1 PhD Candidate, Department of Land Economy, University of Cambridge. Email: [email protected]
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Introduction Knowledge embodied in machines, human beings, institutional and organizational
structures is the most ‘powerful engine of production’ and the main driver of structural
change. However, the complex way in which knowledge enters production activating and
allowing processes of transformation of inputs into outputs is still not fully understood.
Cross-sector processes of knowledge diffusion, capabilities development through
learning in time are equally still not reconciled in a comprehensive theoretical
framework. Although many analytical efforts have been made, the ‘black box’ of
production still remains closed to economists limiting in many circumstances their ability
to propose effective policies for qualitative transformation of a country’s productive
structure – i.e. its development.
Today’s conventional production theory explains production processes as
relationships between combinations of productive factors – i.e. input quantities – and
certain quantities of outputs. By assuming that producers 'know-how' certain inputs may
be combined and transformed to obtain certain outputs, production functions do not make
any explicit reference to the capabilities needed to perform the real process of production.
Thus, in standard production theory there is no production process strictly speaking, and
knowing how to perform tasks and how to coordinate and activate different capabilities in
time, scale and among different agents are not problematic issues. The capability theory
of the firm, on the contrary, is based upon the recognition that the knowledge of
productive possibilities – i.e. input combinations – has to be complemented by the
availability of those capabilities – i.e. know-how – that are required to perform the
process of production. Although often neglected, this theory is at the very root of various
recent approaches based on different concepts of capabilities – i.e. productive,
technological and organizational – considered at different levels of aggregation – i.e.
firm, inter-firm, regional and national. By recognizing the complex nature of knowledge,
its tacit components as well as the complexities connected to its creation, diffusion,
absorption, adoption and accumulation, these contributions have shown theoretically and
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empirically that the conventional understanding in economic theory of these dynamics is
very limited.
Starting from a critical analysis of these two different theoretical frameworks
(sections I and II), the paper argues that neither the production function approach nor the
capability theory of the firm alone are adequate in opening the black box of production as
well as in dealing with the emergent structures of the network form of production
organization. The main reason is that productive organizations of the network type
presuppose at the same time existing structural constraints, their evolution over time, and
a certain degree of open endedness as to what the actual organizational configuration will
be.
On this basis, the paper suggests that in order to reformulate the theory of
production in a 'useful' way we should focus on capabilities in a network-process
perspective. The analytical strategy suggested here is to complement the very common
functional focus characterizing capability approaches with a more definite structural
focus. Precisely, instead of concentrating the analysis in identifying capabilities
according to the functions and tasks they perform, the paper suggests a stylized
representation of the internal productive structure2 in which (i) the production process is
decomposed into elementary processes; (ii) interdependencies among structural
components –i.e. materials in transformation, productive agents and network of tasks –
are analysed; and (iii) structural change dynamics triggered by processes of learning in
historical time are given central stage. From a methodological standpoint, in order to
decompose the complex architecture of production as well as investigate learning
dynamics, the paper will maintain a separation between two fundamental level of
analysis3.
2 See Landesmann (1988) on the comparison between descriptive-analytical and optimizing approaches in production studies. 3 As suggested by Luigi Pasinetti in his ‘separation theorem’ (2007:255) ‘it is possible to disengage those investigations that concern the foundational bases of economic relations – to be detected at a strictly essential level of basic economic analysis – from those investigations that must be carried out at the level of the actual economic institutions, which at any time any economic system is landed with, or has chosen to adopt, or is trying to achieve”. See also Herbert Simon (1962) on techniques for decomposing the
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Firstly, the paper opens the black box of the production process by describing it
as a particular network of interrelated tasks through which transformations of materials
are performed according to different patterns of capabilities coordination, provided
certain scale and time constraints (section III). At this level of the analysis the attention
will be directed towards detecting the different potential patterns of complementarities
among capabilities, tasks and materials, as well as among the virtual capabilities and
capabilities in use embedded in different fund factors. Not only time as well as scale do
play a crucial role in combining different capabilities for performing a network of tasks,
but also do affect the process of learning in the social organization of production.
Through a historical analysis of different processes of structural learning at the firm as
well as industry and inter-industry level, the paper will show how the process of learning
results from a continuous process of structural adjustment and discovery of
complementarities in historical time. As a matter of fact, the learning process is
cumulative, path dependent although reversible and in certain circumstances exclusive,
that is, the acquisition of certain capabilities might impede the acquisition of others of
different kind. Finally, it will be highlighted how learning takes place in time through a
relational process of intended collective action pervasively affected by serendipity
dynamics and unintended consequences.
At the second level of the analysis, problems of capability compatibility and
coordination are considered (both at the firm/industry and inter-firm/industry level) by
stressing the historical emergence and reappearance of different forms of production
organization. (section IV). As capabilities are distributed among different agents – i.e.
individual and collective funds, and must remain so if they want to develop according to
the principle of the division of labour, firms need not only to know how to do certain
things – i.e. direct capabilities, but also how to get other things done for them – i.e.
indirect capabilities. As for the latter, firms may be able to get things done by gaining
control of other capabilities (coordination by direction), by establishing continuous
architecture of complexity and Scazzieri (1993:11-13) on the distinction between social and technical division of labour.
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relationships with others (coordination by inter-firm cooperation), or finally by market
transactions. Following the approach of G.B. Richardson, a coordination device will be
chosen simultaneously according to the degree of similarity and complementarities of
those activities that have to be performed. The historical analysis will suggest that the
emerging network form of production organization can be better identified as one of
producing in proximity. The paper concludes sketching out the kind of political economy
which would derive from a capability theory of production. A new political economy of
capability building would be focused on the following strategic issues: understanding the
structure of learning within the economy and across sectors; triggering processes of
knowledge flows, complementarities discovery and collective knowledge creation;
designing of ‘search networks’ for interacting agents; finally, identifying local industrial
policies for the creation/restoring of industrial commons.
I. Approaching production theories: in search for an analytical framework
The history of human societies is pervaded by extraordinary examples of the increasing
capabilities of individuals and collectivities, both as producers of wealth and consumers
of resources (Hicks, 1969; Rosenberg, 1976). Through continuous and cumulative
innovations, learning and processing of organizational and technological knowledge,
human beings have become increasingly capable of mastering their relationship with the
physical world. At the same time, the development of a sophisticated set of institutions –
i.e. social technologies – such as the market and the firm, has allowed human beings to
coordinate their social and economic relationships as well as to specialise in more
complex productive activities, both individually and collectively. In particular, the
adoption of the Smithian principle of the division of labour which allows shorter idle
periods of funds utilization, greater effectiveness in task execution and faster learning,
has been a fundamental step in the creation and improvement of specialist competences
because ‘knowledge grows by division’ (Loasby, 1999:50). Recognizing that structural
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change dynamics are strictly related to the evolution of organizational and technological
capabilities as well as to their effective utilization in ‘supporting’ networks of productive
tasks of material transformations, economists have attempted many different analytical
representation of production processes (Scazzieri, 1993).
The analysis of the internal structure of production combined with a strong
attention for the representation of the complex system of interrelated production
processes were at the centre of the Classical theory of production. In particular classical
economists focused on the limited availability of non-producible goods, the utilization
problem and the various constraints determined by the production scale and its time
structure (Landesmann, 1988). Four are the main components of the Classical theoretical
framework. Francois Quesnay’s first formulation of the concept of productive
interdependencies called attention to the ‘circular flow’ of wealth production and
reproduction; Adam Smith’s analysis of the internal structure of the pin factory revealed
the microeconomic advantages of the division of labour – i.e. network of productive
funds – and the macroeconomic conditions on which it is based – i.e. stock of circulating
capital flows; Charles Babbage’s focus ‘on the causes and consequences of large
factories’ led to the formulation of the law of multiples and, thus, to the discovery of
different patterns of proportional utilization and maintenance of indivisible funds; finally,
Karl Marx’s analysis of different arrangements of production processes highlighted the
main features of the modern factory system and, thus, the working of the so called
‘collective machine’ (Landesmann, 1986; Scazzieri, 1993)4.
During the post-classical period, the production functions model emerged as the
main approach in production studies. In standard economic theory, production functions
represent complete sets of feasible input combinations for a given output; in an
isomorphic way, utility functions establish a relationship between combinations of
consumption goods and the satisfaction that they provide – i.e. utility. Both production
and utility functions are designed to show in the universe of rational choice and
4 The relevance of the classical ‘production principles’ for the development of a useful theory of production will be more widely considered in the following sections.
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equilibrium allocations how the combinations chosen (respectively of inputs and
consumption goods) reflect relative prices. For conventional production theory does not
provide any analytical representation of the internal structure of production processes,
qualitative transformations generated by innovations and changes in the technology of
production remain completely unexplored. As a result, not only the network of tasks of
material transformations is relegated into a time-less black box, but also heroic
assumptions have to be made for what concern producers’ knowledge of the entire
spectrum of production possibilities as well as their availability of appropriate productive,
technological and organizational capabilities. On the contrary, as the literature on
localized technical change (Atkinson and Stiglitz, 1969; Antonelli 1995) has shown,
given the local and cumulative character of knowledge producers are only aware of a
limited number of factors composition laws – i.e. proximate production possibilities;
moreover, as shown in the capability literature, production ‘has to be undertaken by
human organizations embodying specifically appropriate experience and skills’
(Richardson, 1972:888)5.
A distinct theoretical framework in production studies stems from Wassily
Leontief ‘s (1947) pioneering input-output analysis and, more recently, from the fund-
flow model proposed by Nicholas Georgescu-Roegen (1969; 1970; 1971; 1986; 1990) on
which various contributions found their main inspiration (Scazzieri, 1983 and 1993;
Landesmann 1986; Morroni, 19926; Piacentini, 1995; Landesmann and Scazzieri 1996)7.
In the former contributions (as well as in Morroni, 1992) the focus is on the ‘different
patterns according to which the operations of fund factors are arranged over time’
(Scazzieri 1993:9); in the latter the productive process is represented as a particular
network of interrelated tasks through which a sequence of transformations of materials
5 It is beyond the scope of the present paper to provide a comprehensive discussion of the many contributions discussing the analytical and technical limitations of the production function models (see Robinson 1953-54; Pasinetti, 1959; Georgescu-Roegen 1969, 1970; Scazzieri, 1993; Sylos Labini 1995). 6 Morroni (1992, part III) is a unique attempt in operationalizing the fund-flow model of production. 7 See Mir-Artigues and Gonzales-Calvet (2007) for a review of these approaches.
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are performed according to different patterns of capabilities coordination in quantity, time
and among productive agents.
Finally, a very influential attempt to cope with the fundamental limitations of
more conventional production models can be found in the capability theory of the firm,
an approach emerged at the intersection of various research areas, namely organizational
and innovation studies (Penrose 1959; Simon, 1969 Richardson 1972; Teece, 1980;
Langlois, 1992; Teece et al., 1997; Loasby 1999; Morroni, 2005), institutional and
evolutionary economics (Nelson and Winter, 1982; Lundvall, 1992; Dosi et al. 2000), as
well as empirical works in development economics (Bell 1982; Lall 1992; Bell and Pavitt
1995). On the one hand, given their specific (although quasi-exclusive) focus on the
capability dimension of production, these approaches are able to provide an in depth
analysis of the nature of the firm, the representation of different forms of knowledge,
important learning and technological dynamics (see section II); on the other hand,
however, capability approaches do not attempt to provide a comprehensive analytical
framework for understanding production processes, especially from the point of view of
the economics of structural change. Specifically, capability approaches find their limits in
their lack of understanding of production processes as systems of interdependent
processes, in the analysis of compositional changes and structural dynamics and, finally,
in detecting the structural constraints and patterns of complementarity by which
production and learning are pervasively affected (see section III).
The next sections will try to integrate structural approaches to production theory
with capability theories with the aim of outlining a capability theory of production. The
increasing interest for technological upgrading, learning, knowledge diffusion, structural
change and diversification make this attempt relevant. As a matter of fact, if we recognize
how development is mainly ‘a process that links micro learning dynamics, economy-wide
accumulation of technological capabilities and industrial development’ (Cimoli, Dosi and
Stiglitz 2009:543), increasing our understanding of production as a ‘network-process’
represents a crucial step both in a positive and normative perspective.
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II. The Economics of Capabilities
In the Coasian theory of the firm (Coase, 1937) ‘production costs determine the technical
(substitution) choices [while] transaction costs determine which stages of the productive
process are assigned to the institution of the price system and which to the institution of
the firm’ (Langlois 1998: 186; see also Langlois 1992). Thus the firm emerges as the
more convenient way (lowest cost option) for obtaining control over the relevant cluster
of capabilities needed for undertaking the production process.
On the other hand, as theorized by Edith Penrose (1959), creating a firm may not
simply be a way of reducing transaction costs but it may be the highest value option for
the creation and development of capabilities8. Penrose's (1959:149) definition of the firm
as ‘a pool of resources the utilization of which is organized in an administrative
framework’ constitutes the original root of the capability theory of the firm. The firm is a
collection of physical and human resources which may be deployed in a variety of ways
to provide a variety of productive services. Refuting the conventional assimilation of
inputs and factors of production, Penrose introduced a fundamental distinction between
productive resources which are homogeneous and productive services which are
heterogeneous. In her interpretation of the growth of the firm, this distinction is
functional to recognize how ‘the services yielded by resources are a function of the way
in which they are used – exactly the same resource when used for different purposes or in
different ways and in combination with different types or amounts of other resources
provides a different service or set of services’ (Penrose 1959: 25)9. The growth process,
in the Penrosian framework, is realized through the recognition and exploitation by the
firm of ‘productive opportunities’, specifically of ‘all of the productive possibilities that
its entrepreneurs see and can take advantage of’ (Penrose, 1959:31). As Best (1999:108)
pointed out ‘productive opportunities links the firm to the customer in an interactive
relationship in which new product concepts are developed. The advances in productive 8 As Alfred Chandler's (1977) analysis of the growth of US firms demonstrates, an increase in transaction costs may be well justified if it allows an enhancement of capabilities and knowledge. 9 This intuition will be developed in the next section by discussing the issue of degree of utilization of the capabilities in use, provided certain funds of capabilities.
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services can extend the firm’s productive opportunities by enlarging the members’
capacity to recognize and respond to new product concept possibilities in the
environment’10.
Penrose’s terminology (productive resources and services) was successfully
replaced by George B. Richardson (1972:888) who introduced to economics the term
capabilities. Maintaining the same distinction between resources and services,
Richardson describes industries and their firm as entities in which a large number of
activities are undertaken through the adoption of an appropriate cluster of capabilities.
‘It is convenient to think of industry as carrying out an indefinitely large number of activities, activities
related to the discovery and estimation of future wants, to research, development, and design, to the
execution and co-ordination of processes of physical transformation, the marketing of goods, and so on.
And we have to recognize that these activities have to be carried out by organizations with appropriate
capabilities, or, in other words, with appropriate knowledge, experience, and skills.’11
Capabilities are associated with clusters of relatively persistent ‘capacities to act’
(Cartwright, 1984). Thus they are know-how, both direct and indirect, that cannot be
deduced from (and reduced to) knowledge that. Moreover, since a capacity is not an act,
capabilities are particular dispositions to bring that act about as a result of intended
action. Capabilities may be characterized by different degrees of effectiveness and their
development is cumulative (but also path dependent) in the sense that ‘the acquisition of
certain kinds of know-how facilitates the acquisition of further knowledge of the same
kind, and impedes the acquisition of knowledge of incompatible kinds’ (Loasby
1999:58). The know-how emerge and accumulate through a continuous process of trial
and error, interpretations and falsifications, on the basis of an experimental and pragmatic
approach to the solutions of problems. However, the true fact that every human being
cannot be capable of performing alone all the activities necessary for the satisfaction of
10 Andreoni (2010) discusses the process of circular and cumulative causation through which consumer and producers capabilities co-evolve through historical time. 11 In contrast, Richardson (1972:887) critically asses the formal theory of the firm for being ‘little more than an application of the logic of choice to a particular set of problems’.
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his/her needs implies that human societies have to solve a fundamental problem of the
coordination of capabilities and activities. In other words, we need not only to know how
to do certain things – i.e. direct capabilities – but also how to get other things done for us
– indirect capabilities. These latter capabilities are of two kinds: we may be able to get
things done by gaining control of other capabilities or by obtaining access to them12.
Capabilities are embedded in physical agents – i.e. machines and workers – as
well as organizational configurations and institutional arrangements. According to the
loci where they reside as well as the degree of aggregation considered – i.e. individual
agent, collective agent (e.g. organizations) or systemic (e.g. regional, national level) –
different capability concepts have been proposed. Many of them have been emerging
throughout the 1980s, putting the bases for a new Economics of Capabilities.
At the systemic level, Moses Abramovitz (1986) famously introduced the concept
of social capabilities to define those ‘tenacious societal characteristics’ that influence the
responses of people to economic opportunity. In the development of the catching up
hypothesis, Abramovitz equates social capabilities to managerial and technical
competences, but more crucially to a set of political, commercial, industrial, and financial
institutions. This systemic concept of capabilities have been also re-proposed in various
contributions on regional/national technological capabilities or innovation systems (see
for example Lall 1992; Lundvall, 1992).
At the individual level, a particular subset of human capabilities, that is, ‘the
ability to make independent technological choices, to adapt and improve upon chosen
techniques and products and eventually to generate new technology endogenously’
(Stewart 1981:80) were immediately recognized as fundamental factors in the expansion
12 As Marshall (1920) noted, evolution through the division of labour tends to favour both greater specialization (increasing capabilities) and closer integration (an increasing number of institutional devices to coordinate capabilities and activities). This idea was complemented by the famous aphorism by A.Young (1928) according to which ‘the division of labour depends upon the extent of the market, but the extent of the market depends upon the division of labour’. This means that ‘an increase in the market triggers further specialization which is a process that simultaneously increases the size of the market for specialist skills and activities’ (Best 1999:107). Thus, the division of labour is the fundamental premise for a process of division of knowledge and more effectively increasing capabilities. The development of new knowledge inspires a novel division of labour in a cumulative sequence that leads to the fundamental process of increasing returns (Marshall 1920; Young 1928).
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of individual freedoms. On the one hand, Sen’s seminal work Capabilities and
Commodities (1985) focused on the link between the actual exercise of certain human
capabilities and the recognition of a set of individual entitlements13. What is central, here,
is that entitlements define the boundaries of the space of practicable capabilities, that is of
those productive/technical capacities people can exercise, given a certain socio-
institutional context and historical time. The need to identify the set of feasible operations
in production processes given a set of existing 'work capacities' or capabilities was also
initially stressed in the time-structure theory of production proposed by Landesmann
(1986) and Scazzieri (1993).
On the other hand, drawing from the Penrosian resource-based approach and on
previous contributions14, Bell and Pavitt (1995) propose the concept of technological
capabilities. The latter includes all those resources needed to generate and manage
technological change (including skills, knowledge and experience, and organizational
systems). Specifically, technological capabilities refer to the firm's abilities to undertake
in-house improvements across different technological functions, such as process and
production organization, products, equipment and investments. In the ‘technological
capability matrix’ proposed by Sanjaya Lall (1992:167; see below), firm-level
technological capabilities are categorized by technical functions (investment, production
and linkage capabilities) and their accumulation is actualized through the capacity of
performing more and more complex activities (from simple routine, to adaptive
duplicative activities, up to innovative risky activities)15.
13 A recent contribution (von Tunzelman and Wang, 2007) attempts a reformulation of Sen’s model of consumer capabilities for addressing the problem of capabilities utilization in production processes. Here, particular emphasis is given to the emergence of ‘dynamic interactive capabilities’. 14 Martin Bell (1982) distinguished two kinds of a firm’s fundamental resources: those needed to ‘operate’ existing production systems – i.e. productive capabilities – and those needed to ‘change’ production systems – i.e. technological capabilities. This contribution, together with the first empirical works developed by Sanjaya Lall (1982, 1987) and many scholars affiliated with the ‘Katz Programme’ in Latin America introduced the concept of technological capabilities. 15 The development of these capabilities is recognized to be both an outcome of an endogenous process of capabilities building within the firm and the response to exogenous stimuli, such as those arising from FDI made by transnational corporations into the global value chain (Archibugi and Pietrobelli 2003).
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Those capabilities ‘needed to generate and manage technical change’ – i.e.
technological capabilities – very often ‘differ substantially from those needed to operate
existing technical systems’. The latter, that is, the ‘resources used to produce industrial
goods at given level of efficiency and given input combinations’ have been identified as
productive capabilities (Bell and Pavitt, 1995:78).
Table 1: Illustrative matrix of technological capabilities
Source: Lall (1992:167)
More recent contributions have refined and expanded the technological
capabilities approach by explicitly addressing the more organizational and managerial
dimensions of the firm. The first concept introduced is the one of dynamic capabilities,
that is, ‘firm’s ability to integrate, build and reconfigure internal and external
competencies to address rapidly changing environments’ (Teece et al., 1997: 516). This
set of capabilities is crucial in explaining differences in firms' competitive advantages, as
refers to the specific capacity of the firm to balance continuity – i.e. execution of
invariant processes – with change – i.e. transformation of capabilities, provided a certain
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exogenous shock16. The second concept – i.e. organizational capabilities, arises from
evolutionary approaches which stem from the seminal work by Nelson and Winter An
Evolutionary Theory of Economic Change (1982, chapters 3-5). Here, as stressed by Foss
(2003), an attempt is made towards integrating the Simonian’s (1957) bounded rationality
notion and the Polanyi’s (1958) notion of tacit knowledge in a unifying framework.
Organizational capabilities account for a particular form of know-how, that is the
one which enables organizations to perform their ‘basic characteristic output actions –
particularly, the creation of a tangible product or the provision of a service, and the
development of new products and services’ (Dosi et al. 2000:1). Here, for organizations
‘to be capable of some thing is to have a generally reliable capacity to bring that thing
about as a result of intended action’ (Dosi et al., 2000:2). To the opposite of
organizational routines, which are characterized by a high degree of tacitness,
automaticity and repetitiveness, capabilities are developed and deployed by organizations
as a result of intentional and conscious decisions. However, as routines constitute one of
the building blocks of organizational capabilities as well as individual skills contribute to
the emergence of organizational routines, these two functional features of organizations –
i.e organizational capabilities and routines – remain strongly intertwined. Here, the
central point is to understand contextually to what extent a capability became routinized
and or a routine emerge as a distinct capability.
At this point, a general distinction is attempted: if technological capabilities
mainly refer to a form of know-how related to ‘how to handle the structure of nature’;
organizational capabilities specifically refer to the distinctive, collective and only
partially continuous ways to ‘handle the structure of the organization’. A theoretical as
well as empirical analysis of these different classes of capabilities is a fundamental step
in understanding how organizations develop, transform or disappear, learn and unlearn.
Although these approaches widely inform and potentially contribute to the construction
of a ‘useful’ theory of production, their main aim is to understand how single agents or
organizations, endowed with certain clusters of capabilities, can act as problem-solving
16 See also Kogut and Zander (1992) on the similar concept of ‘combinative capabilities’.
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entities. In this sense they are characterized by a functional focus more than a truly
structural focus. The latter, however, is a crucial passage for understanding production as
a process. For example, those contributions in which more immaterial forms of
knowledge are stressed, do not fully recognize how production interdependencies and
material/scale/time constraints may both affect the utilization of capabilities and enable
the process of organizational coordination and/or reconfiguration of capabilities and task
combinatorics. Moreover the emergence of new forms of productive organizations
require a more detailed analysis of production processes which comprises and connects
micro-dynamics at the firm level, inter-intra industries interactions at the meso level and,
finally, division of labour and division of knowledge at the level of global production
networks. For these reasons, by adopting a ‘network-process’ perspective in which each
production organizations are described as ‘pools of fund complementarities’, the next
section will attempt to embed different concepts of capabilities in a structural theory of
production.
III. The production process: structural components, complementarities and learning in
historical time
Approaching production from the point of view of structural economics implies an
analytical focus on the following set of both quantitative and qualitatively coordination
problems: (i) how to synchronize the network of interrelated tasks; (ii) how to arrange
materials in transformation; (iii) how to organize and activate the network of productive
agents – i.e. funds of capabilities and flow agents17. Interdependencies among these
coordination problems are pervasive. Thus, the analytical space is one of structural
components in a multilayered network. As a second step (section IV), different forms of
17 Richardson (1972:885) stresses how ‘the habit of working with models which assume a fixed list of goods may have the unfortunate result of causing us to think of coordination merely in terms of the balancing of quantities of inputs and outputs and thus leave the need for qualitative coordination out of account.
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production organization are introduced as structurally persistent coordination devices
(Landesmann and Scazzieri, 1996).
III.i Arranging structural components in time and scale: the network-process model A production process Pr (r = 1,…,k) can be represented as a particular network of
interrelated tasks through which a sequence of material transformations is performed
according to different patterns of capabilities coordination, provided certain scale and
time constraints.
Tasks refers to ‘what is sequentially and purposefully performed in a production
process’. Each task T j (j = 1, 2, …, J) can be decomposed in elementary operations or
clustered in groups of tasks.
Pr :
T
According to the set of capabilities and materials in transformation, tasks can be arranged
sequentially in various stages of fabrication (j = 1, 2, …, J), sometimes in a discrete way
others in a continuous way, that is, with or without interruptions. The latter distinction
reveals to be very relevant as soon as we consider how different forms of production
organization have historically developed different techniques for inventory and storage
capacities management (Marx, [1867]1972; Rosenberg 1994; Landesmann and Scazzieri
1996: chapter 8).
Materials refer to ‘what is transformed in the fabrication stages of a production
process’18. The relationship between materials and stages of fabrication can be
represented by a descriptive matrix M = [m ij ] in which any element refers to the material
i that has been transformed in the fabrication stage j.
18 In the case of ‘immaterial production’ – e.g. service activities – ‘materials in process cannot be identified, at least in the usual sense, and the production process generally takes the form of a close interaction among fund agents, in the course of which some of the characteristics of such agents (and sometimes their capabilities as well) may get transformed (Landesmann and Scazzieri, 1996:252-3).
T1 … Tj … TJ
…
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M =
At each fabrication stage, only some materials will be utilized and, thus, transformed.
This implies that for each production process we will observe a certain realized matrix
M* = [m ij ] whose internal structure represents all the materials in use in the stages of that
production process (Scazzieri, 1999). As for the time structure, the material
transformation processes can be visualized as a system of pipelines (Landesmann, 1986;
see also Morroni 1992).
Productive agents refer to those ‘flow agents and fund agents utilized in
performing a network of tasks for material transformation’. The distinction proposed by
Georgescu Roegen (1970) between fund and flow inputs, calls attention to the degree of
permanence of a productive agent in the entire production process. Flow agents – e.g.
fuel, chemical catalysts, electricity, fertilizers – are utilized in certain stages of material
transformation; however, flow agents do not materially constitute the final output of the
process as the materials in use do. Flow agents used in a certain production process can
be described through a matrix F = [f ij ] in which any element refers to the flow agent i
that has been consumed in the fabrication stage j. As for materials, for each production
process we will observe a certain realized matrix F* = [f ij ].
F =
m11 … mij … mnJ
f11 … f ij … fmJ
18
On the contrary, fund agents are both mechanical artifacts – e.g. machines, tools,
equipments – or human beings – e.g. workers, supervisors, engineers, managers. Each of
them can be represented as a fund of multiple and complementary capabilities19. By
activating some of them, each productive agent is able to perform a single task or a set of
similar tasks, that is, tasks which requires the utilization of the same set of
complementary capabilities. In some cases, fund agents own capabilities which allow
only to execute productive tasks at a given level of technology – i.e. productive
capabilities; in others, fund agents present those sets of capabilities needed for improving
or even re-inventing the way in which tasks are performed – i.e. technological
capabilities. As discussed (see section II), performing a production process requires the
coordination of different bundles of productive and technological capabilities embedded
in multiple fund agents. Here, the concept of organizational capabilities comes in to
identify the specific capacity of a production organization to coordinate different
productive and technological capabilities embedded in different fund agents. This
specific set of capabilities points to ‘the importance of the immaterial side of production,
that is, of the complex network of cognitive rules and practices, customs and social norms
from which production is made possible’ (Landesmann and Scazzieri, 1996:4)
As different production organizations are endowed with different organizational
capabilities, they can arrange the network of interrelated tasks of material transformation
– i.e. their cognitive map – in different ways. In other words, multiple cognitive maps of
production are possible given the fact that the same process can be performed according
to different tasks arrangements, by coordinating different fund agents, by utilizing
different sets of capabilities or, finally, by transforming different materials. This point
suggests that, the production process observed in a certain production organization is just
one realization of an entire spectrum of production possibilities, satisfied certain time and
scale constraints (see section III.iii).
19 Fund agents maintain their characteristics substantially unaltered during a production process, provided certain tolerance thresholds are not violated (Landesmann, 1986).
19
Having that in mind, we can distinguish between the bundle of capabilities owned
by a certain number of fund agents in a given productive organization – i.e. virtual
capabilities – and the capabilities utilized by the same productive organization in
performing a certain network of tasks – i.e. capabilities in use20. A way to represent the
bundle of capabilities and capabilities in use is to consider a matrix C = [cij ] in which any
element cij denotes the relationship between the capability i and the task T j performed at
the stage of fabrication j. As shown in Cartwright (1989), very often capabilities can be
expressed in a quantitative form, so we can assume that they are comparable in cardinal
space (Landesmann and Scazzieri 1996:197)21. As for the matrix of materials M* = [m ij ],
the internal structure of the matrix C* = [cij ] shows among the capabilities (vis-à-vis
materials) available those which have been in use in performing each task. A series of
specifications are needed.
C =
First of all, the distinction between the matrix of virtual capabilities C = [cij ] and
the one of capabilities in use C* = [cij ] stresses how the same production process Pr (r =
1,…,k) can be performed by using different bundles of fund agents, that is, different
combinations of capabilities. In other words, given a virtual capability space C = [cij ], the
production process Pr can be represented with different matrices C1* = [cij ] ≠ C2* = [cij ]
≠ … according to the different fund agents in use. However, even when two different
productive organizations perform the same process Pr by combining the same bundle of
20 As it has been stressed, this distinction leads to interpret the emergence of new productive structures within the space of virtual practices as ‘the outcome of a clustering process that brings about a rearrangement of the primitive elements of productive activity; [thus] structural change may be considered as a case of variation within a spectrum of virtual possibilities’ (Scazzieri 1999:230) 21 For a review of recent attempts in measuring technological capabilities at the country level see Archibugi and Coco, 2004.
c11 … cij … cqr
20
capabilities C* = [cij ], these capabilities can be employed in different proportions. For
example, two firms F1 and F2 can perform the same production process by using the same
two fund agents – i.e. workers w and machines m – but one of them is labour intensive
(the ratio w/m > 1) while the second one is capital intensive (the ratio w/m < 1).
C1*=
5w 7w 1m 1m
Thus, by comparing C1* with C2* we can discover specific features of the production
process Pr performed by F1 and F2 with different proportions of the same bundle of
capabilities. In particular, the two matrices express different relationships of
complementarity among funds of capabilities. In our case, the first stage T1 of the
production process Pr can be performed either by combining one machine with five
workers or three machines and one worker (see above). Given these relationships of
complementarity, the kind of combinations of fund agents that firm can select from the
virtual capabilities space C = [cij ] for performing Pr are limited. Moreover, scaling up the
production process not only requires the consideration of these relationships of
complementarity but also that a law of proportionality among all the structural
components of the process is satisfied (see below).
A second specification is related to the time structure of the production process in
relation to the capabilities in use. The matrix C* = [cij ] can be transformed in a matrix of
capabilities use – times Ω* = [ Ωij ] where the generic Ωij represents the use-time of the
capability cij in the production process Pr.
Ω* =
Ω11 … Ωij … Ωqr
C2* =
1w 2w 3m 3m
21
Given the case in which two different productive organizations perform the same process
Pr by combining the same bundle of capabilities C* = [c ij ], by comparing the matrices of
capabilities use – times Ω* we can discover if one time arrangement of Pr is more or less
time wasting than another. For example, the reconfiguration of the time structure of Pr
from one in line to one in parallel can reduce the amount of time waste of fund agents
across fabrication stages (see below).
Finally, the analysis of the matrix C = [cij ] suggests how a production process
may be qualitatively transformed even without equipping the productive organization
with new bundle of capabilities, but just re-arranging capabilities among the network of
tasks which have to be performed. Moreover, as a matter of fact, there are various way of
combining elementary operations into tasks or clustering tasks. Evidently, this depends
again on the capabilities embedded in funds agents, their degree of utilization, their
distribution among productive agents, their time arrangements as well as the kind of
materials in transformation utilized (see section III).
The fact that production processes are characterized by multiple
interdependencies among structural components (Buenstorf, 2005), can be visualized by
mapping in Venn diagrams the relationships between capabilities, tasks and materials22.
Consider the example of the production process Pr (r = 1,…,k) for the commodity A,
given the matrices C = [cij ] M = [mij ] and F = [f ij ]. Venn diagrams represent
respectively the spaces of capabilities C, tasks T and materials M available in a given
organization which produces the commodity A. Given the entire spectrum of possible
combinatorics contained in Venn diagrams, we can visualize the analytical map of
production relationships among C, T and M (see figure 1)23. The mapping from the
capability space C to the task space T – i.e. job specification programme – can be
determined following different criteria. For example different capabilities may be
22 For clarity, the flow agents are taken out of the picture. The choice to privilege the other three dimensions matrices C, T and M is related to the fact that commonly there are higher degrees of freedom in their combinatorics and the use of flow agents is strictly dependent on the utilization of fund agents. 23 The concept of ‘analytical map of the true [interpersonal] relations’ is proposed in Georgescu-Roegen (1976:205) as one possible realization of the ‘entire spectrum of peasant institutions’. See also Baranzini and Scazzieri (1990:252-255).
22
relatively more or less adequate for the execution of one task or cluster of tasks; in other
cases a reconfiguration of the job specification programme – i.e. different mapping C
T – allow to activate some capabilities or to achieve higher efficiency in the utilization of
capabilities in use.
C M
T
C = [cij ] Pr : M = [mij ] t
Figure 1: The analytical map of production relationships
Source: author
The network of relationships and interdependencies among the spaces C, T, M has
to be synchronized over time and according to specific scale requirements determined by
the existence of process indivisibilities as well as indivisible productive agents24. As for
the time structure, synchronization has to be pursued at three different levels – i.e.
coordination and utilization of fund capabilities, arrangement of interdependent tasks
over time, transformation of materials over time. The difficulty of matching the ‘time
sequencing requirements’ of these three dimensions makes perfect synchronization
24 For a comprehensive discussion of time and scale as structural dimensions of production see Landesmann, 1986; Morroni 1992; Scazzieri 1993; Landesmann and Scazzieri 1996.
C11
C23
C32
Cij
C41
T3
T2
T1
m11
m21
m32
T1 … Tj … TJ
…
23
impossible as well as justifies the co-existence of patterns of simultaneity or
sequentiality, for example in the utilization of capabilities funds. Thus, time gaps and
wastes are structurally determined and only partially reducible (Landesmann and
Scazzieri, 1996).
As for indivisibilities, processes are indivisible when they are not ‘indifferent to
size’. In biology as well as technology all individual processes ‘follow exactly the same
pattern: beyond a certain scale some collapse, others explode, or melt, or freeze. In a
word, they cease to work at all. Below another scale, they do not even exist’ (Georgescu
Roegen, 1976:288). The fact that processes are ‘scale-specific’, that is, are characterized
by upper and lower bounds, implies that activating smaller or larger scales of the same
process can be done only if a law of proportionality among the structural components of
the process is satisfied. In other words, a law of multiples must be satisfied (Babbage,
1832). At the level of the structural components, limitations both in the bundling and
unbundling of capabilities or in the size of flow agents – i.e. productive agents
indivisibilities – as well as in the decomposability of materials in transformation are
widely present. However, flow agents are more often divisible than funds of capabilities
such as ovens, machines, equipment, tools, containers.
The existence of indivisible funds of capabilities fundamentally arise from the fact
that for being a fund of capabilities fully utilized a specific scale of production of a
certain commodity A has to be achieved. Thus, the existence of invisibilities implies that
for lower scales of production of the same commodity A, funds of capabilities would be
underutilized. However, if funds of capabilities are not too specialized in the execution of
some tasks, scale constraints can be overcome by utilizing indivisible funds of
capabilities in producing other commodities B, C... . Processes of production of these
commodities has to be enough similar to the one executed for producing A, which means
they require the same bundle of capabilities. This example suggests how the job
programme C T as well as the internal structure of production organizations
historically emerged are very much scale dependent.
24
In sum, ‘constraints with respect to the time structuring and with respect to scale
are the two fundamental constraints on the internal organizational structure of a process
and these constraints are of course a function of the state of technological (or process)
knowledge’ (Landesmann and Scazzieri, 1996:206).
III.ii Complementarities and similarities: structural features of production processes Complementarities as well as similarities among structural components of a production
process are pervasive and can realize at the firm as well as at the inter-fim level. In
particular, funds of capabilities as well as ‘innovations hardly ever function in isolation’
(Rosenberg, 1979:26). Instead, their utilization and productivity critically depend on the
availability of complementary technologies or, more generally, of other productive agents
or materials25.
At the firm level, each fund agent involved in a production process can be
assigned to perform some elementary operations, one single task –i.e mono task – or a
cluster of similar tasks – i.e. multi task. In general, when the same fund agent executes
more than one task, these tasks must be not too dissimilar as fund agents are endowed
with only a limited set of complementary capabilities, exactly those which allows them to
perform that limited set of similar tasks. As a matter of fact, if a production process is a
network of similar tasks, fund agents can be arranged and utilized in many different ways
in the execution of tasks. Thus, in this case, the arrangement of tasks in the production
organization can be very flexible and each fund agent can be involved sequentially in all
the tasks of the process – i.e. high degree of fund agents substitutability. On the contrary,
if a production process is constituted by a network of dissimilar tasks, fund agents will
not be able to perform all the tasks. A production process composed by a network of
dissimilar tasks will be executed by specialized fund agents – i.e. low level of fund agents
substitutability. In other words, if tasks are very dissimilar and complex, fund agents have
to specialize in the execution of only one task, or even in performing elementary
25 See Rosenberg (1979:28) for an analysis of how ‘the social payoff of an innovation can rarely be identified in isolation’.
25
operations of most complex tasks. In this case, a number of processes of the same type
can be organized in series so that specialized fund agents can be utilized in performing
the task in which they are specialized without long time of inactivity. This arrangement
allows firms to reduce wastes of time as fund agents will shift over time from one
production process to another one.
In a production process constituted by a network of interdependent dissimilar
tasks, capabilities funds performing a specific task in one stage of fabrication are
combined with others performing other tasks in other stages of fabrication with a
relationship of complementarity rather than of substitutability. Of course, this
relationships of complementarity can be also present among the set of capabilities funds
which execute the same complex task at one stage of fabrication. Both inter-tasks
complementarities and intra task-complementarities are scale-dependent – e.g. at the intra
task level, each machine requires a fixed number α of workers and technicians to execute
a certain task. Thus, indivisibilities accounts for many forms of complementarity in
production processes. Finally, complementarities may also arise among different
production processes when the combined execution of tasks reduced the costs of each
production process – i.e. economies of scope. The reduction of costs usually depends
from a better coordination and utilization of indivisible capabilities funds. To
recapitulate, at the firm level, complementarities arise among indivisible fund agents,
intermediate stages of fabrication of a single production process, combination of various
production processes (Morroni, 1992; 2005).
At the inter-firm level, the classical paper ‘The Organization of Industry’ by G.B.
Richardson (1972) shows that various forms of inter-firm cooperation we observe in
reality arise from different patterns of similarity and complementarity among firm’s
activities. In the Richardsonian framework, the production of each final commodity is
broken down into various stages or activities, each of them executable by various firms.
‘Activities which require the same capability for their undertaking’ are called similar
activities (Richardson 1972:888). On the other hand, activities can be complementary
‘when they represent different phases of a process of production and require in some way
26
or another to be coordinated [...] both quantitatively and qualitatively’ (idem :889-890).
Coordination can be realized in three different ways by direction 'when the activities are
subject to a single control and fitted into one coherent plan' (see above), by cooperation
when 'two or more independent organizations agree to match their related plans in
advance' or finally through market transactions. At this stage of the analysis, where only
structural elements have been taken into consideration, we limit ourselves in stressing
how according to Richardson (1972:892) the main explanation behind complex and
interlocking clusters, groups and alliances of firms can be found in the need to coordinate
‘closely complementary but dissimilar activities’26. A typical example is the one of two
firms owning different technological capabilities which decide to cooperate for
performing dissimilar but closely complementary activities. This example leads towards a
fundamental intuition. On the one hand, as complementarities introduce qualitative and
quantitative interdependences both at the firm and inter-firms levels, they can be
considered as constraints. However, on the other hand, as complementarities
continuously force firms in re-configuring their production processes, in re-imagining
their organizational form, in developing new capabilities, in expanding their external
network, they can be considered as focusing devices for innovation. Thinking of
complementarities not only as constraints but also as focusing devices is a perspective
widely supported by the historical analysis of processes of structural learning.
III.iii Structural learning: complementarities as focusing devices The main trait of a capability theory of production, is that capabilities are structurally
constrained. At the same time, a pervasive element of virtuality characterizes this
framework. The virtual component has been introduced suggesting how the coordination
problems in the space of productive agents, materials and tasks can be solved in multiple,
although interdependent, ways. In other words, as stressed by Salais and Storper (1997),
26 The emergence of different forms of production organization, patterns of complementarities and diversification are analysed in section IV.
27
there are ‘worlds of production’ – i.e. a variety of production programmes. Thus, ‘worlds
of possibilities’ are open for transforming production and its outcome – i.e. process and
product innovations (Sabel and Zeitlin, 1997). This statement does not want to
underestimate the fact that these possibilities – i.e feasible organizational and
technological arrangements – have to be known to be exploited and that the existence of
indivisibilities, bottlenecks, technical imbalances, complementarities, materials
characteristics are pervasive constraints. On the contrary, it does stress how discovering
these possibilities, given certain structural constraints, is the very essence of a fully
endogenous process of learning. Complementarities, in particular, have historically
resulted in being crucial focusing devices in the process of choice and exploration of new
techniques (Sen, 1960; Rosenberg, 1969, 1976, 1979, 1982; Richardson, 1972).
Recognizing complementarities as focusing devices means to investigate how
'[c]omplex technologies create internal compulsions and pressures which, in turn,
initiate exploratory activity in particular directions' (Rosenberg, 1969:4). As shown by
Nathan Rosenberg’s work, historical episodes of technological change are invaluable
heuristics in identifying those ‘inducement mechanisms’ (Hirschman, 1958), ‘compulsive
sequences’ and causational chains through which a process of structural learning in
historical time realizes. Rosenberg (1969) identifies three main inducement mechanisms,
namely technical imbalances or bottlenecks, labour-saving/uncertainty-reducing
machines, substitutes or alternative sources of supply. Few examples can help at this
point.
In 1900 the machine tool industry was revolutionized by the introduction of high-
speed steel which allowed increasing the hardness of cutting tools. However, ‘it was
impossible to take advantage of higher cutting speeds with machine tools designed for the
older carbon steel cutting tools because they could not withstand the stresses and strains
or provide sufficiently high speeds in the other components of the machine tool’
(Rosenberg, 1969:7). As a consequence, structural transmissions, control elements and
other machine tool components had to be redesigned; this change ‘in turn, enlarged
considerably the scope of their practical operations and facilitated their introduction into
28
new uses’ (Rosenberg, 1969:8). This typical example of a technical imbalance leading to
changes in complementary processes as well as structural components, highlights how a
technical constraint can actually activate a process of exploration and searching in which
‘the size of the discovery need bear no systematic relationship to the size of the initial
stimulus’.
Not only technical, but also social processes can work as triggers for
technological change. In the Poverty of Philosophy Karl Marx observed how ‘after each
new strike of any importance, there appeared a new machine’ (n.d.:134; first source
Rosenberg, 1969). The threat of strikes introduces a critical element of uncertainty in the
supply of labour and strongly affects the delicate time structure of a production process.
Robert’s self-acting mule and the Jacquard punching machine in the nineteenth century;
the introduction by the British Government of the ‘American System of Manufacturing’
in the gun making industry in 1854; even the introduction of legal restrictions, are all
cases in which the invention or acquisition of a new machine is just the first step of a
subsequent endogenous process of structural learning (Rosenberg, 1969; see also Chang,
2002). For example, becoming a new machine available, productions which were
technically feasible but not economically convenient become possible. This possibility
may depend on increasing the scale of complementary machines or in the re-arrangement
of workers in the production unit. Moreover, as soon as the scale of production increases
‘a shifting succession of bottlenecks’ will emerge. Focusing on them, engineers will start
exploring new possible structural configuration of the production process, a tour which
may lead to discovering serendipitously ‘singleton techniques’ (Mokyr, 2002)27.
One of the possible ways to visualize the dynamics behind these historical
examples is to make use of the analytical map of production relationships28 proposed
27 Other examples can be found in analysing how complementary innovations such as refrigerators and railroads or steamships have affected the reduction of transportation costs, increased the degree of regional specialization, allowed increasing returns to scale. 28 These dynamics may be also analysed by adopting the virtual matrix of capabilities C = [cij ] and the matrix of capabilities in use C* = [cij ] (see above). Here, through the process of structural learning some relationships of complementarity among funds of capabilities will end, others will change although maintaining the same proportions among fund agents, others will be completely transformed.
29
above and to show how structural learning realize in two steps: (i) identifications of focal
points – e.g. technical imbalances, bottlenecks, scale constraints, material innovation,
new output requirements – and (ii) discover of new complementarities which act as
focusing devices for gradual improvements or radical innovations. Different examples
can be visualized in the analytical map of production relationships (see figure 2). Let’s
consider the following illustrative case. The acquisition of a new fund of capabilities c53 –
e.g. a new machine through technology transfer or a traditional machine transformed by
small improvements – can trigger a cascade process of production reconfiguration. The
task T2 has to be decomposed in the similar tasks T’2 and T’3; the obsolete fund of
capabilities c23 can be dismissed; the discovery of a new material m54 requires to execute
a new task T4 to be transformed; the scale of the capability c41 given the introduction of a
new indivisible fund of capabilities c53 has to be changed; a previously unutilized
capabilities fund c64 is activated as a new complementarity with the new material m54 has
been discovered.
C = [cij ] Pr: M = [mij ] C’ = [cij ] P’r: M’ = [mij ]
Figure 2: Structural learning: complementarities as focusing devices
Source: author
m11
m21
m32
C11
C23
C41
C64
C32
T1
T3
T2
T’ 2
T’ 3
T4
C53
m43
m54
T1 T2 T3
T1 T’ 2 T’ 3 T4
30
However, this cascade process of production reconfiguration cannot be thought as
an automatic one, as Rosenberg himself recognizes. In order to react to structural
feedback firms have to be equipped with a certain bundle of organizational and
technological capabilities. This point has been raised and historically documented in
Poni’s analysis of the silk industry. From his comparative study of the silk industry in
Lyon and Bologna we realize that, in order to activate a process of structural learning,
feedback must ‘end in the hands of the right persons [as feedback management] require
capabilities and knowledge of techniques which are not necessarily available in the right
moment, in the right sector, in the right hands’ (Poni, 2009:297; author’s translation). The
same condition has to be satisfied in the case of learning by using, a process which
occurs ‘only after certain new product are used’ (Rosenberg, 1982:122). Thus, as stressed
before, same technical imbalances can be either constraints or focusing devices for new
opportunities discovery according to the capacity of the productive organizations to see
and take advantage of them (Penrose, 1959:31).
In sum, what the concept of structural learning in historical time is aimed to
stress is that a continuous process of reconfiguration of the analytical map of production
relationships occurs at the firm and inter-firm level and that complementarities are
focusing devices for technological change. However, given the multilayered nature of
production, in complex production organizations multiple actors experience at the same
time various processes of structural learning in different directions and at different
speeds. For this reason, two aspects have to receive more attention, respectively the time-
speed and the collective dimensions of learning.
The first dimension is still widely unexplored. Learning in time can proceed at
different speeds according to the time required for reconfiguring the structure of
production, given a certain exogenous or endogenous factor, or according to the time
knowledge requires to flow – i.e. being disseminated and adsorbed – throughout the
production organization or at the inter-firm level. In other words, the problem is not only
‘how to learn to learn’ or ‘what to learn’ but also ‘how to learn faster’. As shown by
Dodgson (1991) the differential ability in learning quickly about technological
31
opportunities is a crucial determinant especially in those sectors – e.g. biotechnology –
characterized by an uncertain and generally fast process of transformation.
As for the second dimension, Lundvall (1992) introduced the concept of learning
by interacting as a critical feature of societies. Capabilities are collectively developed
through social interactions mainly by observing and imitating others’ actions as well as
by mirroring their attitudes. The organizational design as well as the underlying relational
structures can affect people’s disposition towards mutual learning and knowledge
discovery which can results from the same process of learning – e.g. small improvements,
process and product adjustments, etc. In the analysis of the bounded rationality problem,
Herbert Simon (1957) introduced the idea that individuals’ learning is socially
constructed or, in other words, that ‘[w]hat an individual learns in an organization is very
much dependent on what is already known to (or believe by) other members of the
organization and what kinds of information are present in the organizational
environment’ (Simon, 1991:125). Historically, learning by interacting realizes in various
ways from more co-operative to more competitive forms such as copying, foreign skilled
workers’ recruitment, technicians exchange, pooling of technology, organization of expos
and industrial espionage (Chang 2002; Poni 2009). One of the main drivers of today’s
network forms of production organization has to be found exactly in the many
opportunities of structural learning it provides.
IV. Forms of production organization: ‘producing in proximity’ through networks
Production processes and structural learning in historical time require the operation of a
complex organizational structure. The notion of forms of production organization
captures the different ways in which ‘coordination problems have been resolved in
particular circumstances, taking into account the state of technological knowledge, the
evolution of patterns of demand, natural resources and environmental constraints, etc.’
(Landesmann and Scazzieri, 1996:218). The emergence and disappearance of different
32
forms of production organization testify that the coordination of tasks, productive agents
and materials in transformation can follow different patterns according to specific
objectives and constraints (see above)29. Thus, the ‘virtual coordination patterns’
actualise as ‘real responses’ to specific historical and contextual circumstances. For
example, the job-shop model, adopted in the craft system, is a form of production
organization characterized by (i) multi-task productive agents performing interlocking
networks of similar tasks and (ii) a ‘stop and go’ process of material transformations.
These two features provide craft system with high flexibility and adaptability in solving
unexpected problems, although low capacity in satisfying increasing levels of demand.
The transition from the job-shop model to the putting-out or the factory forms is a
response to the considerable growth of demand for certain commodities and emerging
technical constraints. For example, the increasing complexity of tasks or the need for
higher speed at which material transformations follow one another30.
The differentiation of tasks and the increasing specialization of capabilities – i.e.
from multi- to mono- tasks – are the common features of the putting-out and the factory
form of manufacturing31. However, these models developed ‘different ways of dealing
with the interface between different stages of any given transformation process’
(Landesmann and Scazzieri, 1996:262). On the one hand, the putting-out model (also
known as Verlagssystem) is structured as a network of separate ‘specialized workshops’,
each of them performing a limited number of tasks related to a specific stage of
fabrication – i.e. craft differentiation. Very often the workshop (or the merchant)
executing the final stage of production is responsible for the coordination of the flexible
29 As stressed by Pasinetti (2007:271) ‘[The production paradigm cannot] abstract, as the models of exchange usually do, from historical specificities, since the kind of institutions that shape an industrial society, besides being far more complex, are inherently subject to changes induced by the evolving historical events, much more extensively than those that shaped the era of trade’. 30 For a detailed analysis of these forms of production organization see Scazzieri (1993) and Landesmann and Scazzieri (1996: chapter 8). 31 The analysis of different forms of production organization focuses on manufacturing activities, defined as processes of transformation of raw materials into useful products. However, it is possible to conduct the same analysis taking into consideration other sectors. For example, see Romagnoli’s essay (1996) in Landesmann and Scazzieri (1996) for an analysis of forms of production organization in agriculture.
33
linkages among network’s nodes. Sometimes, it is also involved in previous stages of
fabrication, for example by assuring the provision of raw materials (Hicks, 1969). On
the other hand, the factory model was developed as a concentrated form of production in
which complex tasks were subdivided in elementary operations performed by highly
specialized productive agents. Here, both workers and machines – i.e. indivisible funds of
capabilities – are coordinated in a way that guarantee their full and continuous utilization
in executing networks of dissimilar tasks (Landesmann, 1986:294). Moreover, thanks to
the precise coordination of tasks and materials in transformation over time, the factory
model allows to respond to customers’ request ‘just in time’. However, a just-in-time
network may consist of a mix of factory establishments and job-shop workshops (see
Scazzieri, 1993:90). The continuous improvements in the factory form of manufacturing
led to the development of the flexible manufacturing system as well as the achievement
of increasing coordination of materials in transformation over time.
The historical analysis of different forms of production organization permits to
identify among others two main stylized facts. First of all, forms of production
organization structurally persist for a certain period of time and, very often, old ones
compete with new ones for considerable periods in history. The reason is that transition is
costly and require adaptation and reconfiguration of production through structural
learning (Landesmann, 1988:173; Rosenberg, 1976). Moreover, as each form of
production organization is a response to specific socio-technical circumstances, old ones
can reappear. Examples are today’s re-emergence of ‘modern craftsmen’ (Sennett, 2008)
adopting the job-shop form of production organization32 as well as the increasing
pervasiveness of global production networks, a model which share many features with
the putting-out system developed in early modern Europe (Dyker and von Tunzelman,
2002). Secondly, historical examples show that production can be coordinated by
adopting various devices, namely (i) by market transactions; (ii) by directing and
controlling production activities within a single organization; or (iii) by collaborative
32 See also Andreoni and Pelligra (2009) for an analysis of various forms of relational credit adopted for financing modern micro-enterprises and craftsmen.
34
arrangements of varying degrees of intensity, between organizations which are formally
independent.
The classification of production activities along the dimensions of similarity and
complementary proposed by Richardson (1960; 1972) contributes in explaining (i)
patterns of diversification within a single organization, and (ii) patterns of specialization
in interlocking networks of production organizations. Diversification in similar
production activities do not require any investment in building or acquiring new
capabilities. Instead it allows to fully exploit firm’s technological and organizational
capabilities. For example, indivisible funds can be more efficiently utilized and, thus,
both economies of scale and scope achieved. In this case, activities will be directed and
coordinated within the firm which has an incentive in diversifying in those similar
activities for which it owns all the necessary capabilities. On the contrary, diversification
in closely complementary but dissimilar activities, such as producing ‘a particular car
with a particular brake and a particular brake lining’ in the same firm, require
investments for building or acquiring new bundles of capabilities and, very often, a
complete reconfiguration of the job programme C T. In this second case, then,
coordination ‘cannot be left entirely to direction within firms because the activities are
dissimilar, and cannot be left to market forces in that it requires […] the matching, both
qualitative and quantitative, of individual enterprise plans’ (Richardson, 1972:891-892).
The coordination device adopted in the case of closely complementary but dissimilar
activities will be the network form of production organization33. This network will be
composed by independent and highly specialized production organizations, each of them
performing in a coordinated way a set of closely complementary but dissimilar
activities34.
Relationships among productive nodes in producers’ networks generally realize in
multiple dimensions – i.e. not only capabilities, but also materials and flow agents – as
33 See Powell (1990) for a classical analysis of network forms of organization. 34 With this respect Silver (1984) argues that ‘in developing countries, or in developed economies when innovation renders the market’s existing capabilities obsolete, a firm may have to integrate into many dissimilar activities in order to generate all the complementary activities it needs’ (Langlois, 1992:108)
35
well as at multiple levels – i.e. regional, national or global. The dimension of connection
among two (or more) nodes in a network is not irrelevant – e.g. being part of a capability
vis-à-vis a material network. Actually, it introduces an important qualitative distinction.
The fact that firms in a region are strongly interconnected with global producers does not
guarantee that they are also networking in the most strategic dimensions. A capability
theory of production stresses how the most relevant dimensions are those related to
capabilities. As a matter of fact, ‘it is knowledge stocks within firms and knowledge
flows to them, between them and within them which underlie change in the types of
goods they produce and the methods they use to produce them’ (Bell and Albu,
1999:1722). In his Principles of Economics, Alfred Marshall (1920) suggested that every
firm builds up an external organization as a means not only for developing a special
market and establishing preferential relationships with costumers, but also for acquiring
that kind of knowledge that cannot be attained by anonymous contracting35. In the
network form of production, the transfer and pooling of technology, drawings, tools,
personnel are the main triggers of structural learning dynamics and, thus, the most
strategic dimensions of connection36.
However, the effective functioning of network forms of production organization
is very much determined by the degree of proximity among the different production
organizations embedded in the network (Bellet et al., 1993; Boschma, 2005). Here, the
concept of proximity should be declined in a plural way in order to stress its
multidimensional and multilevel nature.
As for the former aspect – i.e multidimensionality – proximity does not refer only
to a condition of geographical distance. In fact, geographical proximity is neither a
necessary nor a sufficient condition; in some circumstances it can be even
counterproductive by discouraging geographical openness and the activation of 35 The creation of these continuing relationships is based not only on the establishment of forms of cooperation between different firms, as well as among customers and firms, but also on the same competitive dynamics that are achieved through market transactions. As Richardson (1972:896) eloquently states: 'firms form partners for the dance but, when the music stops, they can change them. In these circumstances competition is still at work even if it has changed its mode of operation'. 36 See Lomi and Pattison (2006) for an empirical study of organization of production across multiple networks.
36
diversified connections. Others dimensions of 'ap-proximation' – i.e. cognitive,
organizational, social and institutional – among producers in a network may affect the
‘transfer of complementary pieces of knowledge’ (Boschma, 2005:71). On the other
hand, the presence of complementary pieces of knowledge and, thus, the possibility to
take advantage of them by networking implies the existence of differences and distances
in capabilities endowments. For two (or more) nodes of a producers’network ap-
proximate, their differences and distances must not exclude the possibility of
connecting/being compatible in at least one technological or productive capability
dimension. Thus, proximity is a concept which refers to the structural compatibility of
two (or more) different production organizations embedded in a network. Given the space
of capabilities C1 = [cij ] and C2 = [cij ] of two different production organization F1 and F2,
their proximity Φ is a function of the number of feasible connections among the fund
agents’ capabilities respectively owned by F1 and F2.
Φ : C1 = [cij ] C2 = [cij ]
The mapping between F1 and F2 can be extended to consider the entire set of nodes
embedded in a network form of production organization. By recurring to adjacency
matrices, we can analytically develop a matrix of proximity Φ. Here, each element
indicates according to a binary codification if fund of capabilities of one firm are
compatible with those of the others. For example, it will show if the machine owned by
F2 achieves the standard of precision or scale which are necessary for complementing in
production those machines owned by F1.
Below a certain level of proximity Φ < Φ, it is very unlikely that the two firms
will adopt a network form of production organization. An example would help here. Let
us consider a high-tech manufacturing firm F1 interested in splittering its production by
outsourcing the production of a set of components of the commodity A to another
manufacturing firm F2. To be sold in international markets the commodity A has to
satisfy certain properties and quality tests. In order to achieve these output standards, F1
37
has to be sure that the productive and technological capabilities through which it
performs part of the production process are compatible with those capabilities in use in
the firm F2. For example, as stressed above, F1 has to be sure that machines, workers etc.
owned by F2 are able to perform the production of certain components on time and
according to the required scale standards. Thus, outsourcing is not simply a problem of
cost reductions but mainly one of structural compatibility of capabilities in production.
This explains why, very often, producing in proximity requires investments in
transferring of tools, machines, mutual personnel training, drawings exchange, effective
knowledge transfer etc. At the end, all these strategies are meant to connecting and
making compatible different productive organization endowed with different capabilities
and to make possible the discovery and exploitation of complementarities among them.
For this reason, producing in proximity is a process which necessitates a continuous
investment in those skills which are needed for undergoing processes of structural
learning in network forms of production organization. To sum up, the concept of
producing in proximity refers to the fundamental dimension of structural compatibility
among producers in a network. By doing that, this concept highlights the need to consider
in a problematic way the bundle of relationships which realizes in multilayered networks
of producers – i.e. global production networks.
As for the second aspect – i.e. multilevel proximity, as the network form of
production comprises both horizontal relationships among production organizations at the
regional level as well as vertical relationship at the global level, different degrees of
proximity will be experienced by organizations according to their type of relationships.
As a matter of fact, networks of producers at the regional and global level overlap and
interact in a multilayered network structure. For example, complex and interlocking
clusters such as the industrial district in Emilia Romagna or the Baden-Wurttemberg
region (Piore and Sabel, 1984; Lorenzoni and Ornati, 1988; Best 1990; Pyke and
Sengenberger, 1992: Quadrio Curzio and Fortis, 2002; Becattini, 2004) are regional cases
of network forms of production organization. At the global level, the creation of
international networks of sub-contractors characterized by a certain degree of stability is
38
another example of close cooperation in a network form among increasingly specialized
organizations. As the network alignment approach has recently documented, both
regional and more global networks are actually strongly interconnected in a system
'where the relationships are many-to-many rather than one-to-the-next' (Dyker and von
Tunzelman, 2002:2). From a normative perspective, the development of technological
and organizational capabilities can neither derive only from ‘in-house’ technological
efforts by the firms nor simply from developing local ‘cluster knowledge systems’ which
remain closed to global production/technological networks. The development of
capabilities requires a pragmatic integration of ‘locally and nationally emerging networks
with global network structures’ (Kim and von Tunzelman 1998:1; Mc Gowan et al.,
2004: chapter 3; Iammarino et al., 2008). This integration will be responsible for the
emergence of new forms of production organization and will trigger new processes of
structural learning.
Concluding remarks
By integrating structural approaches to production with capability theories, the paper
outlines a capability theory of production. The black box of the production process has
been opened by describing it as a particular network of interrelated tasks through which
transformations of materials are performed according to different patterns of capabilities
coordination, subject to certain scale and time constraints. Capabilities are structurally
constrained, although an entire spectrum of virtual organizational and technological
arrangements is possible. These possibilities are generated by multiple relationships of
complementarity and similarity among structural components –i.e. materials in
transformation, productive agents and network of tasks – both at the firm and inter-firm
level. Discovering these possibilities is the very essence of a fully endogenous process of
learning – i.e. structural learning in historical time. Complementarities are essential
39
focusing devices in the continuous process of reconfiguration of the analytical map of
production relationships. In this process of change, problems of capability compatibility
and coordination arise both at the firm/industry and inter-firm/industry level. Different
forms of production organization have historically emerged and reappeared in response to
these coordination problems. Production organizations develop in historical time as a
result of exogenous circumstances as well as endogenous dynamics according to patterns
of specialization and diversification. In today’s global division of labour and knowledge,
the need for coordinating closely complementary but dissimilar activities has found a
response in the network-form of production organization. The effectiveness of these
networks in coordinating production and innovation activities is determined by the degree
of proximity among the agents embedded in the network and, thus, among their
capabilities.
The analysis of the internal structure of production and its change is essential for
investigating the structural dynamics of economic systems as well as for developing a
‘political economy of capability building’ (Cimoli, Dosi and Stiglitz, 2009: chapters 1
and 20). Structural economic dynamics identifies ‘those economic transformations that
explicitly account for the relative persistence of certain elements or relationships of
economic structure while other elements or relationships are subject to change’
(Landesmann and Scazzieri, 1996:3)37. At the micro-meso level – i.e. firms and local
networks, structural learning determines which components and processes in productive
structures will change or persist over time, both qualitatively and quantitatively. As a
matter of fact, structural transformations at the micro-meso level profoundly affect
structural dynamics of the overall economic system – i.e. macro level. However, there is
also a chain of causation which goes from the macro to the meso-micro level. The
possibility to influence and direct micro-meso structural dynamics through selective
policies is mainly in governments’ hands. According to Chang’s definition (1994:60)
industrial policies are policies ‘aimed at particular industries (and firms as their
components) to achieve the outcomes that are perceived by the state to be efficient for the
37 See also Baranzini and Scazzieri (1990)
40
economy as a whole’. Historically and across countries, selective industrial policies have
been main drivers of technological and organizational capabilities building (Chang, 2002:
2009; Andreoni, 2010b). These micro-meso dynamics account for the extraordinary
processes of structural change experienced at different points in history by today’s
industrialized countries.
The usefulness of a theory of production critically depends on its contribution to
the development of a new political economy of capabilities building. The capability
theory of production proposed above suggests two main research directions. First of all, it
highlights the advantages of re-embedding production theory into a structural economic
framework as well as to look at capabilities as structurally constrained. The need for a
‘re-structuralization’ of the industrial policy debate has been raised in recent debates
(Chang e Lin 2009) and some contributions (Chang, 2009; Lin 2010; Lin and Monga,
2010). Secondly, a capability theory of production stresses the importance of triggering
processes of structural learning through complementarity discovery both at the sectoral
and at the ‘super-sectoral’ levels. Industrial policies for the coordination of
complementary as well as competing investments, can activate processes of structural
reconfiguration of catching up economies and orientate their integration into global
production networks. Moreover, given the increasing pervasiveness of the network form
of production organization, industrial policies should focus on ‘connecting problems’
such as facilitating effective knowledge flows in producers’ networks; promoting sectoral
intersections and linkages; supporting adjustment costs; restoring industrial commons. In
sum, useful theories of production are necessary for designing and justifying new
policies. The final aim of these policies for capability building and accumulation is to
facilitate the discovery of new ‘worlds of possibilities’ and, thus, the emergence of ‘new
worlds of production’.
41
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