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Effects of niche construction for the evolution of industries

Effects of niche construction for the evolution of industries

Presentation for EAEPE Conference 2008Session on the Theory of the Firm

University RomaTre, Italy

8 November 2006

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Evolutionary perspective of industrial transformation

• Focus on R&D and its consequences for heterogeneity of technologies and different levels of fitness of firms in the industry (Nelson, Winter, 1982; Dosi et. al. 1994; Dopfer, 2005)

• Process of industrial transformation is generated by the selection of heterogeneously fit organizations

• Selectionist or coevolutionist perspective: selection criteria as exogenous / coevolving with the population

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Evolutionary perspective of industrial transformation (2)

• Adaptation / selection as drivers of evolution (Barnett, Caroll, 1995; Levinthal, 1991)

• Evolutionary economics: markets as vehicles of selection AND R&D / imitation as adaptations (Nelson, Winter, 1982; Metcalf, 1988)

• Coevolutionist view (Baum, Singh, 1994; Tushman, Rosenkopf, 1998; Jacobides, Winter, 2005): mutual causality relationship between organizations and environments (YET seen as mutual adaptations (March, 1994))

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Transformation of environment as a driver of economic evolution

• Inspirations from management / organizational science: role of environment-transforming action– Demand-augmenting– Creation of supplier capabilities (Normann, 2001; Sako,

2006)– Political action theory: active transformation of institutional

constraints (Pfeffer, Salancik, 1978; Oliver, 1991), social movements and organizations as ‘institutional entrepreneurs’ (DiMaggio, 1988; Rao et al., 2000)

• Organizational ability to modify its environmental constraints may serve as (another) source of heterogeneity and thus the driver of evolution

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Consideration of environment in adaptationist / selectionist paradigm

E

E’

G

G’

natural selection

natural selection

gen

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variation

disturban-ces

G – gene pool of a given population of organismsE – environment for given population of organisms

G’ = f (G, E, ∆ (G))∆ (E)

∆ (G)

Much of the studies in evolutionary biology traditionally treat environment as complex and independent from impact of population (Lewontin, 2000; Laland et al., 2000)

[from (Laland et al.,2000), amended by the present author]

E’ = h (E, ∆ (E))

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Organisms matter: actively changing environments

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Concept of niche constructionNiche construction: the process whereby organisms, through their metabolism, their activities, and their choices, modify their own and each other’s niches. Niche construction may result in changes in one or more natural selection pressures (Odling-Smee et al., 2003).

E

E’

G

G’

∆ (E) ∆ (G)natural selection

niche construction

niche construction

natural selection

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[from (Laland et al.,2000), amended by the present author]

E’ = h(G, E, ∆ (E))

G’ = f(G, E, ∆ (G))

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Use of evolutionary biology insights in economics

• Darwinian ideas as a set of general evolutionary principles– universal Darwinism (Dawkins, Dennett, Plotkin etc.)– generalized Darwinism (Hodgson, Knudsen,

Vanberg, Aldrich etc.)

• Darwinism as a useful heuristics– (b)VSR (Campbell)– evolutionary economics modeling (Nelson&Winter)– organizational ecology (Hannan&Freeman)

• Niche construction: a transferable concept?

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Niche construction concept in industrial evolution

E

E’

R

R’

∆ (E) ∆ (R)environmental pressures

construction of environment

construction of environment

environmental pressures

inst

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nce

R’ = f (R, E, ∆(R))

E’ = h (R, E, ∆(E))

Niche construction: a sustained change made to the resources and relations in the organizational environment that has long-lasting effects upon the strategy of the firm and its constituents

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Niche construction vs other forms of firm-environment relation

Niche construction as opposed to• adaptation: a change occurring within the boundaries of

the firm, even without necessarily any change in its environment:– e.g. production volume decision; modification of production

technology; expansion / reduction of units, etc.

• niche utilization: adjusting the positioning in the environment, without necessarily any other change in decisions, behavior, structure or components – e.g. supplying to existing outlets, purchasing from range of

available suppliers, etc.

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Simulation modeling: seeing niche construction at work

• Classical technological evolution model used as a basis (Nelson, Winter, 1978; Yildizoglu, 2002)

• Population of firms competing in one industry / one product situation

• Three ‘strategies’ available:– niche utilization– adaptation (through productivity-improving innovation)– niche construction (through demand-augmenting

activities)

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Model representation

• Production function: Qj = AjKj

• Demand: p = D / (Q1/) , Q = Qj

• Profit per unit: пj=(p(1+j)Aj-c)

• Profit: Пj = пjKj

• Capital dynamics: Kj(t+1) = (1-)Kj(t) + IK

j(t)

• Investment:Ij(t) = max (0, Пj )= IR

j(t) + INj(t) + IK

j(t) =RI + NI + (1- R- N)I

Q – quantity of outputA – productivityK – capital stockp – unit price - elasticity of demand - market premium - proportions of investmentD, c, – constants

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Effects of R&D investment• R&D investment:

– the firm ‘draws’ to see if its investment made effect (new technology was developed): P[dinnovation=1] = a1n(t) IR

j, a1n(t) = max (IRi) * 1, 0<1<1

– the firm then ‘draws’ to see the outcome of researchAIN

j ~ N(Aj, 2)

• Technological imitation:– the firm ‘draws’ to see if was able to imitate better technology:

deff = 2* a2n(t) IRj -1, a2n(t) = max (IR

i) * 2, 0< 2<1

AIMj(t+1)= Aj+ (AMAX-Aj)*deff, AMAX = max (Ai)

• The outcome of technological improvement activity is the best of three options – the existing technology, the innovation, and the imitated technology Aj(t+1)= max (Aj(t), AIN

j, AIMj)

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Niche construction investment• Investment in the ‘firm-specific environment resource’:

– Rj (t+1) = Rj (t)*(1-) + INj(t)

• ‘Market premium’ effect– the firm ‘draws’ to see the outcome of improvement for its

individual marginP[dpr_impr=1] = b1n(t)Rj, b1n(t) = max (Ri) * θ1, 0< θ1 <1μIN

j (t) ~ (μj, r2)

μj(t+1) = max (μj, μINj)

• Change in the market size– P[ddem_impr=1] = IN

j/Rj

DN ~ (D, m2)

D(t+1) = max (DN, D)

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First stage: model dynamics

• The question is which pure strategy is evolutionary viable, and what are the factors of the success

• Niche utilization strategy is winning in the short-term but is not evolutionary viable

• Niche construction and adaptation, are two possible surviving strategies – relative viability is dependent upon model parameters

(parametric analysis currently carried out)

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Population dynamics

• EXIT: Firms exit if they reach minimal level of capital: Kj<KMIN

• ENTRY:– Number of entering firms

E * (1-Xς), E, ς – const, 1ς0 concentration index: X = (Kj/Kj)2

– Firms enter industry:• with a capital average for the industry • with a technology that lies in the neighborhood of best-

performing firms

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First stage: pure types

• Three populations of ‘pure types’ (each employing different strategy)– compete in the same industry

– chances of entry for each ‘pure type’ population dependent on the concentration of capital within the population

– firms enter the industry with the capital average for their type, and with technology average for their type.

capital investment IK

R&D investment IR

niche constructing investment IN

A: ‘adaptive’ (n1) 1-R R0

B: ‘rigid’ (n2) 1 0 0

C: ‘niche constructing’ (n3) 1-N0 N

Investment distribution:

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Simulation results sample

Legend: green = ‘niche utilizing’, red = ‘niche constructing’, blue = ‘adapting’

Note: variables in the last period DO NOT go to zero

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Dynamics of the number of firms

• Population A (‘adaptive’) steadily grows in most cases. • Population B (‘rigid’) tends to grow faster than

populations A and C in early periods (t=0…250), and may decline or steadily grow afterwards (t=500…1000). It typically dies out in later periods (t=500…1000) due to falling of capital stock below the minimal level KMIN.

• Population C (‘niche constructing’) grows slowly and begins to decline some time (t=200…500). The number of firms in a number of runs was reduced to 1 (monopolization of the segment). The remaining firm survived because it had a high level of capital stock.

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Dynamics of the share of capital attributed to the population

• Population B (‘rigid’) accumulates the largest share in in early periods (t=0…250), and declines afterwards (t=500…1000). The average capital per firm goes down, usually reducing below the minimal capital level.

• Populations A and C. Either ‘adaptive’ or ‘niche constructing’ firms dominate (get the largest share of capital) depending on the combination of parameters.

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Second stage (to be conducted): ‘mixed’ strategies

• Firms dynamically choose a combination of three strategies (modeled as a investment allocation by activity (Rj, Nj))

• Evolutionary modeling– firms learn from best practices (convergence of firms to

best performing) AND / OR firms learn from experience (neural network)

– new entrants appearing in the ‘neighborhood’ of best performing firms.

• The question is, what combination, or set of combinations, of strategies is evolutionary viable, and what are the factors which influence their viability.

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Preliminary conclusions• Niche utilization strategy is ‘winning’ in the short-term but

is not evolutionary viable• Adaptation and niche construction are two possible

surviving strategies (relative viability is dependent upon model parameters). Thus, benefits of niche construction in industrial evolution are evident.

• Since ‘demand creation’ investment increases market for all types, it is not essential for evolutionary dynamics

• Unlike adaptation, the niche construction strategy encourages industry concentration, with pure monopolization under specific circumstances.