Technological Change and Industrial Dynamics Lecture 4

Technological Change and Industrial Dynamics Lecture 4 Fabrizio Pompei Department of Economics University of Perugia Economics of Innovation (2016/201...

0 downloads 15 Views 962KB Size
Technological Change and Industrial Dynamics Lecture 4 Fabrizio Pompei Department of Economics University of Perugia

Economics of Innovation (2016/2017) (II Semester, 2017)

Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

1 / 38

Contents of the Lecture* 1

Technological Change as Evolutionary Process

2

The Nature of Technology

3

How Technologies Evolve

4

The Klepper’s model

*References: 1

Technological Change and Industrial Dynamics as Evolutionary Process, Dosi G. and Nelson R. (2009), sections: 1; 2.1; 2.3; 2.4; 3; 3.1; 4 (no sub-sections)

2

Entry, Exit, Growth and Innovation over the Product Life-Cycle; Klepper S. (1996), sections: introduction; I; II; VI.

Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

2 / 38

Technological Change as Evolutionary Process

What does Evolutionary Process mean? 1

Evolutionary theory departs from any assumption of strong rationality: the uncertain nature of innovative activity hinders the fully informed global scan of alternatives made by inventors at any time and limits accurate forward looking technological expectations according to the evolutionary theory, firms avoid the complex calculations to maximize profit and decide on the base of routines, habits, past experience

2

Evolutionary ideas mainly focus on disequilibrium dynamics: the search for new techniques of production and new products most often entail trials and errors, gross mistakes and unexpected successes hence, it is difficult at any stage in time identify an equilibrium situation

3

Notwithstanding the lack of an equilibrium notion, Evolutionary Theory constantly tries to identify regularities in technological change: How are innovation selected? Relationships between technologies and forms of corporate organization? ..and between innovation and market structure (or forms of competition?) How is it possible to observe orderly processes of industrial dynamics emerging out of disequilibrium behaviours? Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

3 / 38

Technological Change as Evolutionary Process

Firm’s behaviour with strong rationality The entrepreneur, according the neoclassical school of thought, has to solve a maximisation program: Maxπt = pt (Qt ) ∗ Qt − [wt ∗ Lt + rt ∗ Kt ] β subject to constraint Qt = At ∗ Lα t ∗ Kt where subscript t refers to a given point in time; π= profits of a innovative monopolistic firm; p = price of the final good; Q = quantity produced A = level of productivity L and K units of labour and capital employed; w and r costs of labour and capital In addition A, L and K are influenced by the following knowledge production function: Patentst = f (R&Dt ) Therefore the firm has also to decide the units of labour to dedicate to R&D activities (z) and those to employ for the good produced (y): L = z + y If firm gets a patent, there will be improvements on K efficiency or on A There will be optimal prices, K units; z units (R&D labour); y units (labour employed to produce Q) that allows the firm to gain maximum equilibrium profits Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

4 / 38

Technological Change as Evolutionary Process

Firm’s behaviour with strong rationality (II) Even when uncertainty characterises the innovation process, the strong rationality holds Let’s suppose that an incumbent firm is threatened by a new entrant There is a competition to obtain an incremental innovation that is protected by a patent Therefore we have a competition between two monopolistic firms: Incumbent and New Entrant By employing workers in R&D activities the incumbent could win the patent race, gain monopoly profits π m and remain the leader on the market The incumbent could also decide to employ no workers in R&D activities; in that case a new entrant could employ workers on R&D activities but there is a probability ρ that it does not get the patent because uncertainty

Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

5 / 38

Technological Change as Evolutionary Process

Firm’s behaviour with strong rationality (III) Uncertainty raises the following alternative scenarios: 1 2

3

Incumbent searches for innovation and wins: πInc = π m Incumbent searches for innovation and fails (or does not search for innovation); new entrant searches for innovation and fails with probability ρ In this case only the Incumbent remains on the market as monopolistic firm Therefore, in the scenario 2) there is a probability ρ that the incumbent still gains a profit π m , that is ρ ∗ πInc = ρ ∗ π m New Entrant searches for innovation and wins (Incumbent fails or does not search for innovation) with probability (1 − ρ) because the incremental innovation, the Incumbent is not forced to exit from the market, so we have in that case: Incumbent gains a duopolist profit (1 − ρ) ∗ πInc = (1 − ρ) ∗ π d Also the New Entrant gains a duopolist profit πNewEnt = π d Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

6 / 38

Technological Change as Evolutionary Process

Firm’s behaviour with strong rationality (IV) Let us sum up the scenarios above: The Incumbent achieves innovation: πIncInn = π m The Incumbent does not gain innovation: πIncNoInn = ρ ∗ π m + (1 − ρ) ∗ π d The incentive for Incumbent will be πIncInn − πIncNoInn = π m - [ρ ∗ π m + (1 − ρ) ∗ π d ], after some algebra it is (π m − π d ) ∗ (1 − ρ) The New Entrant achieves innovation: πNewEntInn = π d The New Entrant does not gain innovation: πNewEntNoInn = 0 The incentive for the New Entrant will be πNewEntInn − πNewEntNoInn = π d − 0 Therefore the New Entrant gains Innovation if its incentive is larger that the Incumbent’s incentive (π m − π d ) ∗ (1 − ρ) < π d , after some algebra it is ρ<

π m −2π d π m −π d

Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

7 / 38

Technological Change as Evolutionary Process

Evolutionary process at work In the book Evolutionary Theory of Economic Change, Nelson and Winter (1982), gave an idea about how an evolutionary theory works 1

Strong rationality versus bounded rationality: In the Nelson and Winter models firms do behave in the future according to the routines and experience they have acquired in the past For example, they have specific decision rules concerning the investments and innovative activity that can be imitative or innovative

2

Absence of equilibrium: In the Nelson and Winter’s model the economy is undergoing continuing changes and it is changing in unanticipated ways there is no long run equilibrium at which firms move towards there is a selection process, firms that do not innovate exit the market, that is a transient phase

3

Regularities in technological change: Nelson and Winter found that some environments favor imitative behavior whereas some others foster innovative behavior For example, where the protection regime of innovation is not strong and the speed at which new process innovations are generated is very low imitative firms can survive on the market When the opposite occurs, it is only the innovative firm that successfully survives Pompei

Technological Change and Industrial Dynamics Academic Year 2016/2017

8 / 38

Technological Change as Evolutionary Process

Neoclassical vs Evolutionary Theory of Innovation In the Malerba’s textbook on Economics of Innovation, published in 2000 We find an attempt to sum up the main differences between the Neoclassical and Evolutionary Economic Theories Neoclassical Strong Rationality Maximising Agents Equilibrium Innovation as Information

Pompei

Evolutionary Bounded Rationality Adaptive Behaviour Disequilibrium Innovation as Knowledge

Technological Change and Industrial Dynamics Academic Year 2016/2017

9 / 38

Technological Change as Evolutionary Process

Towards a pragmatic approach in using theories on innovation Despite the last three-decades debate has viewed sometimes very hard confrontation between these two schools of thought One should not be a fanatic supporter In the following you find part of the talk that the Nobel Prize winner Paul Krugman gave at the European Association for Evolutionary Political Economy in 1996 ’Personally, I consider myself a proud neoclassicist. By this I clearly don’t mean that I believe in perfect competition all the way. What I mean is that I prefer, when I can, to make sense of the world using models in which individuals maximize and the interaction of these individuals can be summarized by some concept of equilibrium. The reason I like that kind of model is not that I believe it to be literally true, but that I am intensely aware of the power of maximization-and-equilibrium to organize one’s thinking and I have seen the propensity of those who try to do economics without those organizing devices to produce sheer nonsense when they imagine they are freeing themselves from some confining orthodoxy’ ’That said, there are indeed economists who regard maximization and equilibrium as more than useful fictions. They regard them either as literal truths, which I find a bit hard to understand given the reality of daily experience, or as principles so central to economics that one dare not bend them even a little, no matter how useful it might seem to do so.’ Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

10 / 38

The Nature of Technology

Information and Technological Knowledge Information and Technological Knowledge are important sources of innovation, even though they are not the same thing: 1

Technology (even when taken to be equal to information) is non-rivalrous in use. Use by one economic agent never reduces the ability of other economic agents to use that technology

2

intrinsic indivisibility in the use of information (half of a statement about whatever property of the world or of a technology is not worth half of the full one: most likely it is worth zero)

3

Both technology and sheer information involve high up-front generation cost as compared with lower cost in their repeated utilization, when the technology is ’in place’: this negligible cost of reproduction closely relates to the proposition that information can be used on any scale (scale free property).

4

Differently from standard economic inputs,such as machine tools, both information and technological knowledge do not depreciate (at least in technical terms): this means that a sort of ’extreme increasing returns property’ characterizes information/technological knowledge As Kennet Arrow (1996) noticed, the presence of increasing returns is incompatible with the idea of competitive equilibrium Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

11 / 38

The Nature of Technology

Information and Technological Knowledge (II) However, according to the ’Stanford-Yale-Sussex (SYS) synthesis’ scientific and technological knowledge have important characteristics of their own Non-depletability by reproduction or by transfer of both scientific and technological knowledge is quite distinct from the easiness and cost of replication of knowledge: let’s take for example the Pythagoras’ theorem, of course it was neither depleted by repeated use by Pythagoras himself, nor by learning on the part of his disciples nevertheless a successful transfer of this scientific knowledge to all is not guaranteed Scientific and technological knowledge share, to different extents, some degrees of tacitness: they are specific, complex cumulative in their development, specific to firms where most technological activity is carried out, and specific to products and processes Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

12 / 38

The Nature of Technology

Cost to transfer technological knowledge and the concept of tacitness The cost of replication across diverse economic actors is generally positive, often quite significant, and varies according to different technologies Knowledge differs from sheer information in its modes and costs of replication Taxonomies based on different degrees of tacitness provide a useful interpretation grid by which to classify different types of knowledge Tacitness refers to the inability by the actor(s) to explicitly articulate the sequences of procedures by which ’things are done’, problems are solved, behavioral patterns are formed, etc. (See M. Polanyi, 1967) In a nutshell, tacitness is a measure of the degree to which ’we know more than we can tell’ (See M. Polanyi, 1967) The higher the content of tacitness in a given technological knowledge and the more expensive is to transfer the technology supported by this knowledge across firms Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

13 / 38

The Nature of Technology

Cost to transfer technological knowledge and the concept of tacitness (II) Technological activities draw upon specific elements of knowledge, partly of the know-how variety (tacit knowledge) and partly of a more theoretical kind It is important to identify across different technologies characteristics and sources of knowledge underlying these technologies Characteristics means to what extent is it codified and openly available in the relevant professional communities as distinct from the tacit skills of the actors themselves Sources: it comes from external institutions such as universities and public laboratories, from other industrial actors such as suppliers and customers, or is it endogenously accumulated by the people and organizations who actually use it within a given firm? In order to understand both the nature and the dynamics of technological knowledge , a crucial step regards the understanding of where technological knowledge resides and how it is expressed, stored, improved upon Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

14 / 38

The Nature of Technology

Tacit and explicit knowledge within firms Knowledge still ultimately resides in the heads of individuals; however, when this knowledge is combined and ’aggregated’ in certain ways, it means that considered as a system, a set of agents possesses knowledge that they do not possess if separated Starting from the assumption that individual knowledge is scarce and incomplete, intelligent organizations should be able to valorise employees’ diversity, encouraging processes of learning by interaction Drawing on the Polanyi notion of tacit knowledge, suggest the identification of two types of knowledge: tacit (not codified, not easily transferable) and explicit (codified, easily transferable). An organisation creates knowledge through the interactions between explicit knowledge and tacit knowledge. We call the interaction between the two types of knowledge ’knowledge conversion’ Through the conversion process, tacit and explicit knowledge expands in both quality and quantity Within firms, the conversion of tacit to explicit knowledge, and vice-versa, gives rise to a four-phase learning process, Nonaka and Toyama (2002) Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

15 / 38

The Nature of Technology

Tacit and explicit knowledge within firms (II)

1

Socialisation: learning as knowledge transfer from one agent to another, sharing and creating tacit knowledge through direct experience (tacit to tacit knowledge);

2

Externalisation: learning as the capability to produce new relevant pieces of knowledge, articulating tacit knowledge through dialogue and reflection (tacit knowledge to explicit knowledge);

3

(Re-) Combination learning as knowledge improvement, systemising and applying explicit knowledge and information (explicit to explicit knowledge)

4

Internalisation learning as absorption capability, acquiring new tacit knowledge in practice (explicit knowledge to tacit knowledge).

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

16 / 38

The Nature of Technology

The importance of tacit knowledge for Italian Industrial Districts Knowledge does not only reside in individuals and organisations, but is also localised in hybrid organisational forms (networks and districts), thus, it is concentrated in specific local systems One of the sources of competitive advantage of a local agglomeration of small and medium enterprises (Industrial District) lies in the capability to share tacit knowledge Sticky, non-articulated, tacit forms of knowledge are among the most relevant drivers of innovations for firms located in an Industrial District For example, from mid 1980s to mid1990s Montebelluna came to top as district specialised in sport-system shoes and it was an area of extraordinary international concentration of competencies, practical know how and production capabilities External multinationals were attracted by the existence of local competence and technological capabilities and tapped into the local district for absorbing the relevant accumulated tacit knowledge Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

17 / 38

The Nature of Technology

Technologies as routines A routine that is commanded by an organization is ’an executable capability for repeated performance in some context that has been learned by an organisation’ According to Nelson and Winter (1982) routines are organisational memory: a set of skills that a particular member of the organisation can perform in some appropriate environment Routines are a repertoire where knowledge resides and where organisational knowledge is stored Organisations do not become capable of a productive performance merely by acquiring all the necessary ’ingredients’ (inputs, like technology or capital). They must have the ’recipe’ (prescriptive instructions on the use of resources), and the ability to perform it based on a fine-tuning of complex activities of coordination. Routines involve multiple organisational members who ’know’ how to appropriately get information from an action pattern or a signal in response to the specific environmental circumstances. Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

18 / 38

The Nature of Technology

Technologies as routines (II) Each individual is constantly engaged in receiving signals from other members of the organization or from the environment, responding to the signal with some operation from his repertoire, and thereby creating a signal for other members of the organization, For example, the incoming signal might be the appearance of a partially finished automobile on a production line, the operation may be tightening particular screws and the outgoing ’signal’ is the slightly-more-finished automobile going down the line Note that the ’program’ built into routines generally involves, at the same time, recipes together with particular divisions of labour, plus specific modes of coordination Organizational routines are the building blocks of distinct organizational competences and capabilities of firms, because they do not simply represent quantitative relationships with which inputs are used together Routines feature the different modes to make the same thing that firms show; heterogeneity of firms we observe in a given sector is mainly due to the presence of different routines to achieve the same production process Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

19 / 38

The Nature of Technology

Technologies as artifacts

Of course, technologies also include physical outputs (new products, new machinery and equipments) Indeed, recipes often involve designs of what it is there to be achieved as a final output Even when the procedure involves a notion of design, the latter is in general only one of the many possible configurations which can be achieved on the grounds of any one knowledge base The artifact perspective on technologies is in fact useful for a rather general purpose, namely the identification of the techno-economic characteristics of specific final products, on the one hand, and of machines, components, intermediate inputs, on the other

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

20 / 38

How Technologies Evolve

Technological variety and selection mechanisms According to the scholars belonging to Stanford-Yale-Sussex synthesis also technological advance needs to be understood as proceeding through an evolutionary process. At any time there generally are a wide variety of efforts going on to advance the technology (a large variety of technological solutions), which to some extent are in competition with each other, as well as with the prevailing practices. The winners and losers in this competition are determined to a good extent through some ex-post selection mechanisms Of course, the technology evolution is different from evolutionary processes in biology The role of human purpose in the process is always crucial, it means that efforts at invention and innovation are never totally blind, or strictly random, as often is assumed to be the case regarding biological ’mutation’ Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

21 / 38

How Technologies Evolve

Technological paradigms and technological trajectories Directly from the nature of technology previously discussed follows that we can understand the concept of technological paradigm as composed by three parts: 1) a specific body of practice in the form of processes for achieving particular ends, together with an ensemble of required artifacts on the ’input side’; 2) some distinct notion of a design of a desired ’output’ artifacts; 3) a specific body of understanding (knowledge) , some relatively private, but much of it shared among professionals in a field A technological paradigm includes the scientific and technical principles relevant to achieve an artifact, and the specific technologies employed. A paradigm also entails specific patterns of solution to selected techno-economic problems that emerge in the production process The establishment of a given technological paradigm is quite often linked with the emergence of some dominant design Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

22 / 38

How Technologies Evolve

Technological paradigms and technological trajectories (II) Microprocessor paradigm and internal combustion engine paradigm are examples of technological paradigms Technological paradigms identify the operative constraints on prevailing best practices and the problem solving heuristics deemed promising for pushing back those constraints Each paradigm involves a specific ’technology of technical change’, that is specific heuristics of search: Where do we go from here? Where should we search? What sort of knowledge should we draw on?. In microelectronics (microprocessor paradigm) search concerns methods for further miniaturization of electrical circuits, the development of the appropriate hardware capable of ’writing’ semiconductor chips at such a required level of miniaturization

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

23 / 38

How Technologies Evolve

Technological paradigms and technological trajectories (III) The foregoing features of technological paradigms both provide a focus for efforts to advance a technology and channel them along distinct technological trajectories Trajectories may by understood in terms of the progressive refinement and improvement in the supply responses to such potential demand requirements Trajectories order and confine but do not at all eliminate the persistent generation of variety, in the product- and process-spaces, which innovative search always produces Trajectories are a powerful uncertainty reducing representations of what the future is likely to yield in technological terms Notwithstanding roughly predictable trajectories of advance, uncertainty concerning the innovation process continues to be ubiquitous Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

24 / 38

How Technologies Evolve

Technological paradigms and technological trajectories (IV) Examples of technological trajectories are technological advances in aircraft technologies, that have followed two quite distinct trajectories (one civilian and one military) characterized by log-linear improvements in the trade offs between horsepower, gross takeoff weight, cruise speed, wing load and cruise range Semiconductors represented in the figure below offer an archetypical example of a trajectory driven by miniaturisation efforts yielding the so-called Moore’s law involving the doubling of the density of elementary transistor-per-chip and later microprocessors every 2-3 years

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

25 / 38

How Technologies Evolve

Technological paradigms and technological trajectories (V) The paradigmatic, cumulative, nature of technological knowledge provides innovation avenues which channel technological evolution, while major discontinuities tend to be associated with changes in paradigms According to this approach we call ’normal’ technical progress those advances occurring along a given trajectory, while we reserve the name of ’radical innovations’ to those innovations linked with paradigm changes A change in the paradigm generally implies a change in the trajectories. Together with different knowledge bases and different prototypes of artifacts, the techno-economic dimensions of innovation also vary For example, the shift from transistor technology to microprocessor technology is the most important change in technological paradigm occurred in the computer industry during the 1970s Transistor technology improved greatly during the 1950s. These developments enabled significant improvements in mainframe performance, and some reduction in costs.

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

26 / 38

How Technologies Evolve

Technological paradigm change in the computer industry In the early 1960s, IBM introduced the 360 family and seized an even large share of the mainframe market: by the end of the 1960s IBM enjoyed a market predominance of 70% in the world’s general service computer market The transistor paradigm evolved towards invention and development of the integrated circuits and enabled even further improvements in mainframe computers, hence the transistor technology had its own technological trajectory To sum up: in the first period of computer industry there were a technological paradigm based on transistor technology, a technological trajectory evolving towards performances (calculation potential) neglecting physical space problems and a final product, that is the mainframe computer (see the figure) The computer industry was highly concentrated and IBM, thanks to full vertical integration into semiconductors became the indisputable leader in the market Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

27 / 38

How Technologies Evolve

Technological paradigm change in the computer industry (II) The introduction of the microprocessor in the mid-1970s marked another punctuation in the history of the industry Microprocessors enabled significant improvements in mainframes. In addition they permitted the design of reasonably powerful computers that could be produced at low cost- microcomputers (personal computers). Personal computers opened up a new demand class which had not been touched by mainframes: small firms and personal users Three American companies entered soon: Apple Computer in California (see the first McIntosh in the figure), Radio Shack in Texas and Commodore in Pennsylvania, all non vertically integrated and all specialized in microcomputers Microprocessor was a radical innovation with its own technological paradigm (specific artifacts, new problems solving such as miniaturisation, new competences to develop the products) and hence its own technological trajectory such as the one we see in the previous slide Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

28 / 38

How Technologies Evolve

Technological paradigm change in the computer industry (III) As we saw, the microprocessor paradigm evolved towards a trajectory based on increasing miniaturisation (this is valid so far, let’s think for example to smartphones, tablets and more an more small laptops, such as apple macbook air) The microprocessor technology allowed the emergence of a new industry, the pc industry, that differently from mainframe, has different users (individuals, family and small firms, whereas users of mainframes were large firms, large public organizations and scientific laboratories with massive computation tasks) The companies in the pc industry are no longer vertically integrated: many pc producers (IBM, Dell, Hewlett Packard) buy components such as microprocessors and software from other big companies (Intel for microprocessors and Microsoft for software) Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

29 / 38

How Technologies Evolve

Technological paradigm change in machine tools and production processes A recent paradigm change could involve process technologies and refers to additive manufacturing (AM), also know under the umbrella of 3D printings AM denotes a family of manufacturing techniques that allow for the generation of arbitrary physical objects layer by layer from digital 3D blueprints AM allows radical change in practices, artifacts, design, specific heuristic of search and trade-offs, for example: the traditional trade-off between flexibility and efficiency could be upended This is because AM offers at the same time greater flexibility: a broader product range and individualized products ( even the option of generating objects that would have been impossible to make with any other technology)... and greater efficiency: for example, AM can be used as an automation technology which substitutes human labor, moreover huge economies in terms of both less flaws and less wastes of raw materials can be reached by using 3D printings here you have an example of 3d printing https://youtu.be/X5AZzOw7FwA Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

30 / 38

How Technologies Evolve

Schumpeterian competition and industrial dynamics Let’ s call Schumpeterian competition the process through which heterogeneous firms compete on the basis of the products and services they offer and get selected with some firms growing, some declining, some going out of business, some new ones always entering on the belief that they can be successful in this competition Industrial dynamics is based on these processes of competition and selection that in turn are continuously fuelled by the activities of innovation, adaptation, imitation by incumbent firms and by entrants. In industries where a company which introduces a very attractive innovation is able to prevent rapid imitation by competitors, and also is able to expand its own market share rapidly, the result may be a highly concentrated industry, this was the case of the IBM’s long domination of the mainframe computer industry In many other instances successful innovators have not been able to develop and hold on to a dominant market position, in the face of continuing efforts at innovation by their competitors. In this case, Joseph Schumpeter employed the term ’creative destruction’ to refer both to the nature of technological advance, and to what often happens to leading firms in industries where technological advance is rapid and incumbents are unable to seize novel opportunities

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

31 / 38

The Klepper’s model

Industry-specific dynamics and Industry Life-Cycles: the Klepper’s model Some scholars noticed that specific patterns of industrial dynamics emerge in some specific sectors (Abernathy and Utterback, 1978; Klepper, 1996) The market structure, the expected profits for firms, their competences and their innovative behaviour change when industries evolve from birth trough maturity Klepper (1996) was the first scholar to formalise an industry life-cycle model in which: a) In the initial exploratory or embryonic stage (the birth of a new industry), market volume is low, uncertainty is high, the products design is primitive, and unspecialized machinery is used to manufacture the product; many firms enter and competition based on product innovation is intense; b) In the second, intermediate or growth stage, output growth is high, the design of the product begins to stabilize, product innovation declines, and the production process becomes more refined as specialized machinery is substituted for labour; entry slows and a shakeout of producers occurs; c) Stage three, the mature stage, corresponds to a mature market; output growth slows, entry declines further, market shares stabilize, product innovation continues to be less significant, whereas only process innovation matters; management, marketing and manufacturing techniques become more refined Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

32 / 38

The Klepper’s model

Overview on the Klepper’s formal model The Klepper’s model is aimed to explain regularities, i.e.entry, exit, stabilisation of the firms’ market share, product innovations and process innovation, that characterise specific period of the industry life-cycle (especially in industries such as automotive, tires, tv) In each period t, there are Kt , potential entrants As firms enter and others randomly develop the innovative capabilities required to enter change over time Each potential entrant is randomly endowed with innovative expertise which it cannot modify over time: Let si , denote the innovation expertise of firm i, which it knows prior to entry, and smax the maximum possible innovation expertise Each period there are one or more potential entrants with innovative expertise smax and there is a cumulative function for innovative expertise H(s), such that s < smax and H(smax ) = 1 The firm’s innovative expertise influences its success at product R&D The probability of firm i developing a product innovation in period t is si + g (rdi,t ), were rdi,t is its spending on product R&D and the function g (rdi,t ) reflects the opportunities for product innovation

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

33 / 38

The Klepper’s model

Overview on the Klepper’s formal model (II) Each successful innovator adds its innovation to the standard product and markets a distinctive variant of the industry’s product, which it sells at a price exceeding the price of the standard product, reflecting the value of its innovation. After one period, all product innovations are copied and incorporated into the standard product, so successful innovators have a one period monopoly over their distinctive variants Let G denote the one-period gross monopoly profit (before subtracting the amount spent on product R&D) earned by each seller of a distinctive variant, therefore in the second period other incumbents can costless imitate ideas to innovators In order to be able to innovate costlessly the innovations of its rivals, which is required to market a distinctive product variant and also the standard product, firms monitor the innovations of their rivals at a cost of F per period. However, each firm in each period has to produce also the standard product in order to survive in the market, this because the monitoring costs F are very high Let Qt = ft (pt ) denote the total market demand for the standard product in period t, where Qt , is the quantity demanded, pt , is the price of the standard product, and ft is the market demand schedule for the standard product in period t Let Qi,t denote the output of the standard product by firm i in period t

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

34 / 38

The Klepper’s model

Overview on the Klepper’s formal model (III) Assuming that pt , falls over time, the total quantity demanded, Qt expands over time It is assumed that incumbents in period t experience a rise in their sales of the t t standard product from Qi,t−1 to [Qi,t−1 ( QQt−1 )], where QQt−1 denotes the growth in the total quantity demanded of the standard product from period t − 1 to period t If desired, the firm can expand its output further resulting in an increase of its market share of the standard product To do so it must incur an adjustment cost of m(∆qi,t ), where ∆qi,t is the t expansion of its output in period t above [Qi,t−1 ( QQt−1 )] The average cost of production of the standard product for firm i is assumed to be independent of Qi,t and equal to c − l(rci,t ) where rci,t is the amount spent on process R&D by firm i in period t and the function l(rci,t ) reflects the opportunities for process innovation Therefore, the cost in period t is only assumed to be function of innovation process, as opportunities for process innovation increase, l(rci,t ) , the average costs of firms deacrease Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

35 / 38

The Klepper’s model

Overview on the Klepper’s formal model (IV) Given all these assumptions we can show the full expression of expected profits of firm i in period t E (Πi ,t ) = [si + g (rdi ,t ]G − rdi ,t + [Qi ,t−1 ( QQt ) + ∆qi ,t ]x[pt − c + l (rci ,t )] − t−1

rci ,t − m(∆qi ,t ) − F where [si + g (rdi ,t ]G − rdi ,t is the firm’s expected net profit from product R&D after subtracting the cost of its product R&D [Qi ,t−1 ( QQt ) + ∆qi ,t ]x[pt − c + l (rci ,t )] − rci ,t − m(∆qi ,t ) is its net profit t−1 from producing the standard product after subtracting both its spending on process R&D and the costs of adjusting its output F is the cost of monitoring the innovations of its rivals Potential entrants and incumbents: entry/stay in the industry if E (Πi ,t ) > 0... are indifferent about entering/staying if E (Πi ,t ) = 0... and do not enter/exit the industry if E (Πi ,t ) < 0

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

36 / 38

The Klepper’s model

Overview on the Klepper’s formal model (V) The entry process is such that Et = Kt (1 − H(si )) where H(si ) is the cumulated expertise necessary to entry the industry at time t Intuitively, in every period, incumbents have a lower average cost than entrants because they spend more on process R&D due to the greater output over which they can apply the benefits of their R&D Entrants can nonetheless gain a foothold in the industry if they can earn sufficient profits from developing a distinctive product variant, which requires sufficient product-innovation expertise si Over time, price is driven down and the advantage of incumbents over entrants grows, increasing the product-innovation expertise required for entry to be profitable, H(si ) ↑ and if the number of potential entrants Kt is constant, the actual entrants diminishEt ↓ Eventually, price is driven to a level such that regardless of their product innovation expertise, the expected profits of all potential entrants are less than or equal to zero and entry ceases. Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

37 / 38

The Klepper’s model

Empirical evidence of the Klepper’s model Very often the birth of an industry corresponds to a phase in which product innovation are more important than process innovations Potential and actual entrants increase and a lot of firms with different products are in the market; there is not a dominant design. This corresponds to a early period with a lot of firms in the industry (see the figure) Over time every firm that remains in the market increases its effort on process relative to product R&D. Intuitively, since the returns to product R&D are independent of firm size while the returns to process R&D are a direct function of firm size, as firms grow they increase their effort on process relative to product R&D Consequently we observe an industry shake out and a dominant design emerges

Pompei

Technological Change and Industrial DynamicsAcademic Year 2016/2017

38 / 38