Chapter 2

Learning to Communicate in the Production ofCollective Knowledge

CRISTIANO ANTONELLIUniversity ofTurin

1. INTRODUCTION

Worldwide, the generation of technological innovations seems localized in afew technological districts characterized by a web of communicationchannels among innovators. Within technological districts technologicalknowledge acquires the features of a collective activity that is the result ofthe joint undertaking and the complementary efforts of a variety of learningagents connected by communication channels. The role of communication inthe production of technological knowledge is emerging as an important areafor empirical and theoretical research in the economics of innovation. Thedynamics of regional clustering of innovation activities within technologicaldistricts in fact seems to be shaped by the interplay among knowledgeexternalities, communication activities, and increasing returns (Antonelli1999,2001).The chapter is structured as follows. Section 2.2 provides a general

account of the notions of collective knowledge, technological districts andtechnological communication. Section 2.3 presents a simple model of thegeneration of collective knowledge within communication networks withspecial attention to understanding some dynamic implications. Theconclusion puts the results of the analysis in a more general perspective andstresses the policy implications.

M. P. Feldman et al. (eds.), Institutions and Systems in the Geography of Innovation© Springer Science+Business Media New York 2002

22 Institutions and Systems in the Geography ofInnovation

2. COLLECTIVE KNOWLEDGE ANDCOMMUNICATION

A general consensus has been established about the key role of knowledgeexternalities in the production of new knowledge. Technological knowledgeis no longer viewed strictly as an output but also as an input. The positiveeffects of knowledge externalities now balance the limitation of marketeconomies to generate the correct amount of technological knowledge due tolimited appropriability. Technological knowledge can be appropriated onlyto a limited extent because of its quasi-public characters based on localindivisibilities and non-rival use. Technological knowledge spills into the airand can be used by third parties. At the same time, however, it seems moreand more evident that specific efforts are necessary for technologicalknowledge, spilling in the air, to be identified, understood, and properly usedin a different locus from the one of original generation (Arora andGambardella 1990; Arrow 1969).Communication plays a central role in this specific context. Because of

the localized and embedded character of much technological knowledge,communication is necessary between users and producers to identify,qualify, explore, and assess the potential for knowledge externalities.Communication is instrumental to making potential knowledge externalitiesactually relevant for perspective users. While knowledge holders cannotprevent the dissipation of their knowledge, perspective users may be unableto make a good use of it (Lamberton 1971, 1996).This is especially true in a multitechnological context, where a variety of

coexisting and partly complementary knowledges are identified (seeDesrochers, Chapter 6, this volume). Knowledge in fact can be conceived asa folder containing a variety of specific and localized knowledges, each ofwhich has a specific context of application and relevance. Strongcomplementarities, however, exist among technological knowledges andhelp make the folder a single container. In a monotechnological context,direct competitors can make a rival use of proprietary knowledge and reduceits economic value for original holders. In a multitechnological one,perspective users instead are not direct competitors and external knowledgeis an intermediary input that, after proper recombination and creative use,becomes a component of the localized production process of newknowledge. Local cumulativity and indivisibility are clearly importantattributes of technological knowledge: new knowledge is built on previousknowledge, and indivisibility is relevant both diachronically between old andnew technologies as well as horizontally among a limited variety of newtechnological knowledges being introduced at each point in time (Nelson1987).

Learning to Communicate 23

The key role of the necessary interactions between users and producers ofnew knowledge, and specifically the essential contribution made bycommunications (that is, the active participation of both talkers andlisteners) in making technological externalities possible illustrates thecollective character of technological knowledge (Gibbons et al. 1994;Lundvall 1985; Von Hippel 1988). Technological knowledge is a collectiveactivity when potential knowledge externalities, because of the activeimplementation of communication activities, can be shared and become thesource of major increasing returns. Such a collective character, however, isactually workable only within a circumscribed regional and technologicalenvironment. The costs of communication and the fall in the positive effectsof knowledge externalities associated with dissipation (driven by theincrease of distance and heterogeneity among users and producers) limit thescope of fruitful interaction (Foray 1991; Freeman 1997).External technological knowledge does not fall from heaven like a

manna: it is an input, which can be quasi-internalized but only bearingspecific absorption and listening costs that depend on the variety of codesand the number of communication channels (Carter 1989; Cohen andLevinthal 1989; Griliches 1992). The costs of the production of knowledge,including such communication costs, are lower for firms that are able toestablish cooperative relations and access the pool of collective knowledgemade available. Appropriability also is affected. The opportunity costsengendered by the uncontrolled leakage of technological knowledge arelower when the mutuality and trust conditions in place within the group offirms are higher. For given innovation costs (including research, learning,and communication activities), a collective output can be easily identified. Itstands between the Arrovian private and social outputs and makes it possibleto reduce the social losses due to inappropriability (see Figure 1). Mostimportant, the collective output makes possible external increasing returns inthe production of knowledge: the larger the number of connected firms, thelarger the amount of knowledge generated.For effective communication to take place, however, systematic efforts

and a long time spell are required. First of all, for communication to takeplace at least two parties must be purposely involved: communication isinherently a collective activity. Second, the establishment of effectivecommunication links requires long time implementation and codification ofshared protocols and communication rules. Third, effective communicationrelies on immaterial infrastructures, which can be created over time and withreciprocal consensus. Finally, in the short term, the amount and importanceof the actual traffic of signals and information bits can vary greatly; in thelong term, however, communication takes place, and effective successfultransfer of information between parties takes place.

24 Institutions and Systems in the Geography ofInnovation

K Private good

Collective good

Public good

R&D&L

Figure J. The value of knowledge (K) as a private, collective, and public good

3. THE DYNAMICS OF COLLECTIVEKNOWLEDGE WITH COMMUNICATION

The key role of external knowledge qualifies the production of technologicalknowledge of each finn. Hence we can specify a localized technologicalknowledge (LTK) production function where together with traditionalresearch, development, and learning activities (R&D&L) conductedinternally within the finn j, external knowledge (EK) spilling from otherfinns, enters directly as an input. Because of limited cumulability and localindivisibility we assume that the amount of external knowledge each finnhas access to increase with the number of finns, albeit with a decreasingrate. Fonnally:

(1) LTKj =j «R&D&Lj, EKn-j)

where

EKn-j =m (N); with m'>O, but m"<O, for N=n-j

(1)

(2)

The cost equation associated with the generation of knowledge makes therole of communication clear. Let us assume a given distribution of agents inthe regional, technological, and economic spaces. According to the localizedtechnological knowledge approach, each agent differs from the others andhas some idiosyncratic features. Each agent undertakes some innovativeactivity and spills locally some technological externalities whoseaccessibility decays with distance. Each agent tries and takes advantage of

Learning to Communicate 25

the local externalities made available by the other firms engaging incommunication activities, which become more and more expensive asdistance increases. Distance here is measured in terms of the cumulateddifferences among agents with respect to the regional, technological, andeconomic spaces: the larger the number of firms, the larger their cumulateddistance index.Innovating firms bear the costs of research and learning inputs with a unit

cost p and of communication inputs. The former can be stylized as variablecosts, while the latter are fixed ones. While the former vary with theirquantity, the latter increase with the number of communication channels (C).Formally:

CT = (p R&D&L + c C). (3)

Following a well-established literature, we assume that in the short-termcommunication costs do not increase with the flow of external knowledgeshared: a communication channel, once established, can carry large andincreasing quantities of communication flows (Antonelli 1999; Arrow 1969).

LTKCT

K*

Short tenn Innovation andCommunication costs [CT]

Collective KnowledgeOutput [K]

q* q(quantity)

Figure 2. The short-teon equilibrium

In the short term this assumption has relevant consequences. Firms bearthe variable costs of internal research, development, and learning activitiesand the fixed costs of existing communication channels. A short-termequilibrium condition can be identified. Firms, in fact, maximize the amountof internal R&D&L expenses under the control of the total revenuestemming from innovating activities, for given levels of communicationchannels in place. The former includes some fixed communication costs, andthe latter the positive externalities spilling from the other connectedmembers of the network. The number of firms that belong to the network is,

26 Institutions and Systems in the Geography ofInnovation

in the short term, exogenous, and it is not under the control of the connectedones. In this context costs can be far below revenues, and extra profits can begained: connected firms take advantage of increasing returns (see Figure 2).In the long term, however, the situation can change: extra economic

profits and the scope of increasing returns may attract new firms. Learningto communicate and the entry of new agents within the network drive thesystem toward the long-term equilibrium.In such a framework the equilibrium size of each district will depend on

the tradeoff between the net positive effects generated by the addition ofeach agent to the group on the productivity of innovative activities, aftertaking into account the loss in terms of appropriability, and the negativeeffects of the additional communication costs. It is immediately clear that thelower the communication costs among agents and the better the quality ofcommunication channels, the larger is the number of firms and the larger thesize of the district, and, most important, the larger is the scope for increasingreturns available in the production of technological knowledge (see Figure3).

LTKCC

Communication costs in ageodesic network [CC]

Localized CollectiveKnowledge Output (K)

Communication costs [CC] in aStructured network

Figure 3. The long-term equilibrium

The shape of long-term communication costs becomes a central issue.Within a network the number of channels or links (C) increasesexponentially with the number of connected agents (N). Hence we have thatthe number of links is

C=N(N-l)/2 (4)

In a geodesic network where all agents are directly linked to each otherwith a dedicated communication channel and given unit communication

Learning to Communicate 27

costs, total communication costs increase with a more than proportionateeffect.The structure of the network, however, can change this result. In a

structured and organized network, where additional links can take advantageof interconnection with preexisting ones, incremental costs and economies ofdensity apply. In such networks in the long term we can assume that totalcommunication costs at the aggregate level increase with a proportionateeffect.Formally, we see that, at the aggregate level and in the long term for

given levels of R&D activities, firms will engage in technologicalcommunication (TC) and enter the connected system as long as profits aredriven to average levels (zero in perfect competition). Specifically, on therevenue side we account for the effects of the positive externalities on theproduction of new localized and collective technological knowledge (LTK),which becomes accessible and available. These effects can be thought to bepositive but with a diminishing impact as the number of firms and the relatedvariety of knowledge spillovers increase: complementarity is limited. On thecost side we find the communication and transaction costs (CC) that arenecessary respectively to establish communication links and to preventuncontrolled losses of appropriability and to account for the opportunitycosts associated with excess leakages. Because of the combined effect ofincreasing returns in communication and the exponential increase of linkswithin a network, we can assume that total communication costs increasewith a proportionate effect with respect to the number of agents (N) engagedin the process and their distribution in the space. Hence:

P (TC) is max for LTK(N) =CC(N) (5)

Firms can engage in technological communication and benefit fromexternal increasing returns until the maximum number of firms andmaximum levels of heterogeneity among firms are achieved.This result, however, can be properly appreciated only in a dynamic

context. Firms will benefit from external increasing returns as long as theequilibrium size is achieved. By the same token, firms will build newcommunication channels and establish additional communication flows aslong as the equilibrium size is achieved. In this context the effects of thereduction in appropriability are more than compensated by the access toexternal increasing returns. Until such size is achieved, both disequilibriaand increasing returns coexist.Specifically, we see that, because of the positive slope of communication

costs associated with the number of firms engaged in complementaryinnovations and the positive but decreasing slope of the revenues associatedwith the number of complementary technological knowledges, for each

28 Institutions and Systems in the Geography ofInnovation

technological district i, the profit (Uti) stemming from the introduction ofcomplementary technologies within the technology district i can be shapedas a quadratic function in Nt:

TIti =aNti - bNti2 (6)

Let us now assume that at each point in time the number of new firmsthat are able to enter the communication network and to communicateeffectively within the technological district i (dNti) is a function (v) of thenet revenue stemming from the knowledge externalities. Such a process hasall the characters of traditional entry in Marshallian markets, and it can beconsidered to be the result of a process of learning to communicate: newfirms are attracted into the web of communication channels by the profitsstemming from technological externalities made actually available bycommunication channels. Hence:

dNti =v ( TIti)

The substitution of (6) into (7) leads to the following:

dNti = (v (aNti -bNti2»

(7)

(8)

Equation (8) establishes a functional relationship between the flow offirms that have learned to communicate as induced by its profitability andenter into the web of connected agents and the stock of connected agents.Specifically, moreover, we find a relationship of a rate of growth thatdepends on the quadratic specification of the stock. This differentialequation has its solution in the standard logistic function (see Figure 4).

N

Figure 4. The dynamics of technological districts

Learning to Communicate 29

The interpretative framework implemented so far is consistent with theempirical evidence. A large empirical evidence suggests in fact that the timeprofile of the completion of a technological district can be easilyapproximated by a logistic distribution that exhibits a long phase of slowprogresses, a period of fast entry of new firms engaged in the production ofcomplementary technologies and actual emergence of a local technologicalsystem characterized by high levels of local complementarity of thetechnological base and eventually a stretched period of approximation to theasymptotic number of complementary technological knowledge (Clark,Feldman, and Gertler 2000; Feldman 1994; Harrison 1992).

4. CONCLUSIONS

The approach elaborated so far has important economic implications. Withinatomistic competition the production of technological knowledge is doomedto be sub-optimal because of limited appropriability and hence insufficientincentives for producers to commit resources in such a risky activity. Privateand social optima diverge. Within technological districts, characterized asnetworks of connected innovators, knowledge acquires the attributes of acollective activity: it is no longer just an output but also an input in furtheractivities. The larger the amount of collective knowledge, the smaller is thedivergence between private and social optima. It is clear in fact that totalfactor productivity levels at each point in time are determined by the amountof collective knowledge available within a system. The latter is clearlyinfluenced by the size of the technological districts. Hence we see that thefaster the rate of growth of N and larger the equilibrium level of N, (thenumber of complementary technologies), the larger the general levels ofefficiency of the economic system.All reductions in communication costs make it possible to increase the

size of the district and most important the amount of technologicalknowledge that can be produced in efficient conditions. Clearly,telecommunications are an important enabling technology for technologicalcommunication to take place: the diffusion of new telecommunications andcommunication technologies is likely to reduce the costs of technologicalcommunication and hence to increase the size of technological districts.Policy interventions that identify technological communication as animportant goal can contribute to the reduction of these specific costs andincrease the size of technological districts and relatedly the amount ofcollective knowledge.Second and most important all advances in the organization of the

communication network make it possible to reduce the number of necessary

30 Institutions and Systems in the Geography ofInnovation

links and consequently to reduce the negative effects of the exponentialincrease of total communication costs. The evolution from a geodesicnetwork into more structured network designs where interconnection isviable and communication can take place on preexisting links and channelshas the evident effect of increasing the number of firms that can participateefficiently in the network and amount of collective knowledge a system cangenerate. Learning to organize the communication network becomes acentral issue and provides large scope for policy intervention, especially atthe local level (Olson 1965; Richardson 1998; Romer 1994).From a dynamic viewpoint it is also clear that such general efficiency

grows, along a logistic time path, as long as the maximum size of thetechnological district is achieved the dynamics of technological convergencelasts for a long time. Fast rates of learning to communicate translate into fastrates of completion of the maximum size of technological districts. Theconsequences of the logistic path along which technological clusters emergeare also relevant in this context. Total factor productivity growth in fact willtake place along such an S-shaped time profile with evident effects in termsof the time distribution of the rates ofgrowth of the system at large.In this context the size of the renewable pools of collective knowledge

also plays a key role. The larger the modules of complementarytechnological knowledges and the larger the pools of local indivisibilities,the larger is the size of the technological districts and hence the amount ofcollective knowledge. Clearly, the more generic the technological base, thelarger the size of the technological district. Decreasing returns in externalincreasing returns in fact are shaped by the limited cumulability andcomplementarity among technological knowledges. The more generic thetechnological base and the larger the positive effects in terms oftechnological opportunities and size of the renewable common pool ofaccessible knowledge-inputs, the larger the size of the technological district.In turn, the smaller the negative effects of declining technologicalopportunities, the larger the size of the technological district with all thepositive effects already considered (Carlsson and Stankiewitz 1991; Loasby1998).The analysis of the conditions for technological communication and the

context for technological communication lies at the heart of the innovationsystem approach and provides the basic conditions for localizedtechnological knowledge to become collective and external increasingreturns in the production ofknowledge to take place.The production of technological knowledge by each firm can be

formalized as the result of the interaction of internal research and learningactivities, the creative access to external technological knowledge and itsactual implementation. The different levels of effective communication

Learning to Communicate 31

among innovators significantly affect the productivity of the total amount ofresources devoted by each firm to research and learning activities and hencereduce substantially innovation costs (Nelson 1987). This in tum helpsincrease the absolute levels of innovations introduced within the localinnovation system (Antonelli 1999,2001; Dorfman 1983).An innovation policy aimed at strengthening the communication links

among innovators, reducing communication costs, and structuringcommunication networks in an efficient way may be instrumental inaccelerating the rates of learning to communicate and in increasing the sizeof technological districts. Both are likely to have important positive effectsin terms of the amount of collective technological knowledge that a systemcan generate and alternatively benefit from. The evidence suggests thatmarkets face major problems in evolving toward an efficient design andgovernance mechanism of communication networks: the experience intelecommunications networks suggests that regulation is required toestablish open interconnection rules.

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