SEARCH
You are in browse mode. You must login to use MEMORY

   Log in to start

Economics of innovation


🇬🇧
In English
Created:


Public
Created by:
Nasta Charniak


5 / 5  (1 ratings)



» To start learning, click login

1 / 25

[Front]


Discuss the main drawbacks of patents as indicators of innovation output
[Back]


1. Not all patents represent innovation, nor are all innovations patented 2. The value of patents is highly skewed, as there are a small number of highly valuable patents and a large number of patents with little value (Scherer and Harhoff (2000) showed that about 10% of the most valuable patents account for more than 80% of the value of all the patents) 3. A patent refers to a temporary property right on an invention, but not a guarantee to exclude others from making, using or selling the patented property. While the embodiment of the innovation is protected by the patent, the underlying idea is not. 4. Patents are only strong as their enforcement 5. They are indicator of invention rather than innovation; some types of technology are not patentable

Practice Known Questions

Stay up to date with your due questions

Complete 5 questions to enable practice

Exams

Exam: Test your skills

Test your skills in exam mode

Learn New Questions

Popular in this course

Learn with flashcards

Dynamic Modes

SmartIntelligent mix of all modes
CustomUse settings to weight dynamic modes

Manual Mode [BETA]

Select your own question and answer types
Other available modes

Complete the sentence
Listening & SpellingSpelling: Type what you hear
multiple choiceMultiple choice mode
SpeakingAnswer with voice
Speaking & ListeningPractice pronunciation
TypingTyping only mode

Economics of innovation - Leaderboard

The course owner has disabled public visibility of the leaderboard for this course.


Economics of innovation - Details

Levels:

Questions:

80 questions
🇬🇧🇬🇧
Discuss the main drawbacks of patents as indicators of innovation output
1. Not all patents represent innovation, nor are all innovations patented 2. The value of patents is highly skewed, as there are a small number of highly valuable patents and a large number of patents with little value (Scherer and Harhoff (2000) showed that about 10% of the most valuable patents account for more than 80% of the value of all the patents) 3. A patent refers to a temporary property right on an invention, but not a guarantee to exclude others from making, using or selling the patented property. While the embodiment of the innovation is protected by the patent, the underlying idea is not. 4. Patents are only strong as their enforcement 5. They are indicator of invention rather than innovation; some types of technology are not patentable
Discuss the main differences between the linear and the chain-link model of innovation
Linear Model of innovation: 1) Sequential process (basic research, applied research, development, production, marketing) 2) Research-centric (primary driver of innovation) 3) Unidirectional flow (inf flows in one direction, no feedback) 4) Predictability and control (logical step-by-step process) 5) Criticism (overly simplistic, ignores the role of market demand) Chain-link model (Stephen Kline and Nathan Rosenberg): 1) Interactive and iterative process (Knowledge → Invention → Design → Development → Production → Marketing, with constant feedback loops) 2) Multiple pathways (innovation can be demand-pulled (market-driven) or technology-pushed (research-driven)) 3) Feedback loops 4) Interconnected components (interdependance between different components) 5) Adaptability and flexibility 6) Real worlad relevance (reflects real processes)
Discuss the differences between normal technical progress and radical innovations according to the technological paradigm approach
Normal technical progress refers to incremental improvements within an existing technological paradigm. These are typically gradual and predictable enhancements in performance, efficiency, or cost. Radical innovations, also known as revolutionary or disruptive innovations, involve significant breakthroughs that create new technological paradigms or fundamentally alter existing ones. These innovations often lead to the creation of entirely new industries or the radical transformation of existing ones.
Critically discuss the main open issues of the Industry Life Cycle model (Klepper, 1996)
The industry life cycle model (ILC) - it is an attempt to examine and reconstruct the structural dynamics of specific industries (structural dynamics). The formal model (Klepper, 1996 AER) «five stages in the evolution of the market with respect to the number of producers in it. These five stages represent a prototype of the life-cycle of the market from its beginning up to, but not including, the period of eventual decay or contraction in absolute market size» (p. 630); «the identification of stages in the history of a continuously changing phenomenon is, essentially, an analytical convenience. [...] The five periods, however, capture the major transitions in the forces that we believe determine the number of producers in a market during most of its life-cycle». Gives an ultimate structure of new product markets
Gibrat’s Law (skewed distribution of firm size)
Xt - size of a firm at time t, et - random (normally distributed) variable representing idiosyncratic, multiplicative growth shock over the period of time (t-1:t) The distribution of firm size is asymmetric: in statistical terms such distributions are qualified as “positive skewed”: the tail on the right side is longer (or fatter) than the tail on the left side. Gibrat's law of proportionate effect states that the proportional change in the size of a firm is independent of its absolute size. An implication of this is that large and small firms have the same average proportionate rates of growth. Gibrat’s law has been very popular in economic research because: it explains very asymetric firm size distributions (that is with a frequency of small firms much higher than a normal distribution would predict; there is empirical evidence supporting the idea that firm grwoth rates are largely erratic and hard to predict However, research has also shown that: - small firms grow faster - but they have a lower survival probability - the relation between firm size and growth is moderated by firm age (which has a negative correlation with firm growth and positive with survival) - Gibrat’s law is supported among firms above a certain threshold Ubiquitous fat tails are a sign of some underlying correlating mechanism which one would rule out if growth events were normally distributed, small and independent.
Criteria of invention
Novelty, nonobviousness (or inventive step), and industrial usefulness
Discuss the main features of the Industry Life Cycle model (Klepper, 1996)
It is difficult to generalize it to all industries. The sequence of product innovations followed by process innovations does not hold in capital-intensive industries such as commodity chemicals, synthetic fibers, plastics and petrochemicals, where innovation is mainly of the process type. Nor it holds in industries where products are customized, where product innovation is mainly type of innovation. An initial major discontinuity (a major product innovation), followed by the emergence and consolidation of a dominant design. This story does not hold in several industries: i.e. semiconductor industries. 1950s: dominant design (planar transistor) -> new discontinuity (integrated circuit) -> new discontinuity (microprocessor). Technological discontinuity is not always associated with the first major innovator
Discuss why the neoclassical theory of the firm cannot explain the skewed distribution of firm size
Neo-classical theory of the firm (perfectly competitive markets) Single product firms in an industry with a U-shaped average cost curve. No incentive to grow beyond this size (concept of “optimal” [industry] size). Convergence toward an “equilibrium” size and static optimization by the firm. The dispersion of firm size should be small, attributable to disequilibrium or mistakes and it will reduce over time as firms converge towards the equilibrium size. Fact-checking: The wide (and persistent) support of the firm size distribution even in narrowly defined industries and the asymmetric nature of it does not support this theoretical approach
Critically discuss the following statement: “Firm growth is random”
As Paul Geroski (1999, p. 4) underlines, saying that firm growth is driven by unexpected shocks does not mean that is driven by “mere chance” or “good luck”. It may be that the researcher does not know, but firm insiders (entrepreneur/manager) do - what will cause the growth opportunity (omitted factor at the firm- or macro-level), - when the opportunity will actually take place. 1. Firms which want to grow incur in adjustment costs: these costs are linked to the change in the level and/or the composition of labor and physical capital due to demand shocks and/or changes in technology adopted by the firm. firms will typically make large but infrequent and clearly discrete changes in their operations (e.g. in employment and investments), rather than continuous but small ones toward a theoretical framework 2. Most firms are erratic and irregular innovators: few firms produce major innovations or patents on a regular basis. The typical pattern is that firms will innovate every once and a while, opening up what are sometimes very long periods of time between successive innovations.
Discuss the concepts of tacit and explicit (or codified) knowledge
Knowledge is also accumulated through experience in production and use on what has come to be known as ‘learning by doing’ and ‘learning by using’ (Pavitt (1987)) Tacit (awareness or consciousness and communication difficulties). 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.
Discuss why innovation is very concentrated geographically; Discuss why tacit knowledge is a key determinant of the geography of innovation
Rothwell (2013) has shown that 93% of the world´s patent applications are filed by inventors living in metropolitan areas with just 23 percent of the world´s population. The more knowledge-intensive the economic activity, the more geographically clustered it tends to be. Tacit knowledge is a key determinant of the geography of innovative activity. • spatial stickyness and social interaction: This approach adopts the learning-by-interacting model as the cornerstone of its conceptual framework. According to this perspective, knowledge does not flow unidirectionally from technology producers to users. Instead, users provide tacit and proprietary, codifiable knowledge to producers in order to enable the latter to devise innovative solutions to users’ practical problems. But, at the same time, by supplying users with innovative technologies, producers are also sharing their tacit and other proprietary knowledge with their customers. patent applicants in analytically based industries cite other patents originating in the same city more frequently than they cite patents originating non-locally. Furthermore, they find that patent citations are more likely to be localized in the first year following the establishment of the patent, with the effect fading over time, as the knowledge diffuses more widely. 1. circulation of knowledge and spillovers occur withing established networks of scientists (local ‘buzz’) 2. knowledge production relies on scientists and intellectual talents (which Richard Florida calls the ‘creative class’), and only few places offer attractive employment opportunities for these workers. In turn, this creates a virtous circle. 3. locations that offer high-quality of life have a further advantage in the ‘battle for talents’. These are often cities with a critical mass of creative activity and workers, strong social diversity and tolerance
Critically discuss the incentives to innovate in the Arrow model.
Arrow (1962) formalized a model explaining technical change as a function of learning derived from the accumulation of experiences in production. Radical innovation – one that reduces marginal costs a lot. This outcome is well represented in the following simplified version of the Arrow’s model that, in turn is based on the following assumptions: 1. Knowledge underlying innovation is a public good (non-rival and not excludable) 2. Radical process innovation, that reduces marginal costs 3. Only one firm wins the race to innovate and gets to apply for a patent 4. The uncertainty in the innovation process is limited. We can imagine that the innovation is available to the firm that is willing to pay more for the patent right 5. The model compares the incentives under two scenarios: monopoly vs. perfect competition There is an incentive (TI) to innovate if: TI = π post−innovation − π pre−innovation This monopolistic firm decides to innovate according to TI, that is the positive difference between the post innovation profit (rectangle P ′mehc′) and the pre-innovation profit (rectangle Pmbgc). By introducing a radical process innovation, the monopolistic firm not only sets the post innovation price (P ′m) lower than the previous one (Pm), but P ′m is also lower than the previous constant marginal cost (c) Incentive to innovate in a perfectly competitive market: Many competitive firms, but only one can win the race and gets the patent. Now, TI is the positive difference between the post innovation profit (rectangle P ′mehc′) and zero, the TI of competitive firm is larger than TI of monopolistic firm. This because no profits were accruing to the competitive firms before introducing innovation. After introducing innovation, the competitive firm becomes a monopolistic firm. Incentive to innovate of the social planner: If the government supports innovation a competitive market is guaranteed, competitive firms sell goods at lower prices, no monopoly emerges and the social welfare increases. The social planner has the biggest TI, but the government may not have the resources to finance all innovations, hence reducing the overall amount of innovation. By endowing discoverers with property rights over the fruits of their efforts, patents affect the incentive to innovate and are likely to increase the flow of innovations. But by giving the patentee exclusive rights on the exploitation of a unique economic good that is still non-rival in consumption, a patent creates a monopoly situation
Critically discuss the role of the probability of entry on the relative incentives to innovate in a patent race between an incumbent and entrant.
Incumbents VS new Entrants By investing in R&D activities the incumbent could win the patent race, gain monopoly profits πm and remain the leader on the market. There is a probability ρ that the entrant does not invest in R&D if both firms innovate, they end up in a duopoly with profits πd. Incremental innovation: entrant threatens an incumbent and creates competition to obtain an incremental innovation protected by patent. And then firms choose whether they want to innovate or not. Profit from a duopoly is smaller from a monopoly/ Actually, it is smaller WATCH THE FORMULAS FOR INCENTIVE TO INNOVATE
Discuss the role of communities of practice in the ‘local buzz’ and ‘global pipelines’ model
Communities of practice are: • groups of workers bound together by shared experience, expertise and commitment to a joint enterprise • joint production and diffusion/transmission of tacit knowledge across intra/inter-organisational boundaries is possible as long as it is mediated within these communities • relational proximity can partially substitute for geographical proximity • Multinational Enterprises (MNEs) are privileged actors to create such relational proximity between their geographically dispersed units Conditions for more effective relational proximity in communities of practice • social affinities: optimal cognitive distance; individual traits; organisational attributes; institutional context In the context of local buzz, communities of practice are often formed within localized networks, such as regional innovation clusters or industry-specific groups. These communities bring together individuals with shared interests, expertise, and goals, creating a supportive environment for learning, problem-solving, and innovation. By fostering close interactions and relationships among members, communities of practice contribute to the generation of local buzz by amplifying the spread of knowledge, ideas, and innovations within a specific geographic region or industry sector. Within the global pipelines model, communities of practice can span across national or international boundaries, connecting individuals and organizations from different geographic regions who share common interests or work in similar fields. These global communities of practice leverage digital communication tools, online platforms, and international networks to facilitate collaboration and knowledge exchange on a global scale. By transcending geographic limitations, they play a crucial role in accelerating the flow of information, expertise, and innovation across global markets and supply chains. temporary proximity - organis. culture that allows managers to change how the things are done all around the world, still scientists are not pressed by it. Marshal’s localization, Marshallian externalities. Advantage of inputs, of labor market, spillovers.
Discuss, with the help of examples, the difference between technological paradigms and trajectories.
A technological paradigm includes the scientific and technical principles relevant to achieve an artifact, and the specific technologies employed. entails specific patterns of solution to selected techno-economic problems that emerge in the production process is often linked with the emergence of some dominant design identifies the operative constraints on prevailing best practices and the problem solving heuristics deemed promising for pushing back those constraints 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? both provide a focus for efforts to advance a technology and channel them along distinct technological trajectories Examples of technological paradigms include the transition from mechanical to digital computing, the shift from combustion engines to electric propulsion in automobiles, and the evolution from traditional to biotechnological methods in medicine. A technological trajectorie may be understood in terms of the progressive refinement and improvement in the supply responses to such potential demand requirements 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 are a powerful uncertainty reducing representations of what the future is likely to yield in technological terms Examples of technological trajectories include the development of computer processors becoming smaller, faster, and more energy-efficient over time, the evolution of renewable energy technologies like solar panels becoming cheaper and more efficient, and the advancement of medical imaging technologies such as MRI machines becoming more accurate and versatile.
Critically discuss why patents may hamper innovation.
A large share of scientific knowledge has been generated within a regime of open science. In some fields of technology, progress is cumulative, with yesterday’s efforts setting the stage for today’s efforts and achievements (current debate on property rights in biotechnology suggests similar problems) IPRs are more likely to be a hindrance than an incentive to innovate excessive fragmentation of IPRs among too many owners may well slow down research activities because each owner can block each other. Patenting often appears to be a complementary mechanism for appropriating returns to product innovation Fom CGPT friend: Monopoly Power, Blocking Innovation, Inhibiting Collaboration, High Transaction Costs, Misallocation of Resources (patent race mentality)
Critically discuss why some technologies may become dominant in an industry even if they are not superior to the alternative
Network Effects (Network effects occur when the value of a product or service increases as more people use it. This creates a feedback loop where users are incentivized to adopt the dominant technology, further reinforcing its dominance) First-Mover Advantage (The first technology to gain widespread adoption; brand recognition, established user bases, and control over key resources or infrastructure.) Economies of Scale (lower costs per unit as production volumes increase; undercut) Regulatory Barriers (Regulatory capture can hinder innovation and competition in the market. Similarly, patents and intellectual property rights can be used to restrict access to key technologies, further entren) Consumer Behavior and Perception (Consumer preferences, habits, and perceptions can play a significant role in determining the dominance of technologies in an industry)
Discuss the concept of path dependence in technological development
Path dependence in the economics of innovation refers to the idea that the historical trajectory of technological development and institutional arrangements can shape the future direction of innovation and economic outcomes. In other words, the choices made in the past, even if suboptimal or arbitrary, can have lasting effects on the paths that subsequent innovation and economic activity follow. One might think that the technology that dominated the market was superior to the altnernative, but there is, an alternative explanation grounded in the interaction between dynamic increasing returns of some kind, network externalities, and path dependence. In this second interpretation, the internal combustion engine need not have been innately superior. All that would have been required was that, because of a run of luck, it became heavily used or bought, and this started a rolling snowball mechanism fuelled by some sort of collective positive feedback. What might be behind these path dependent developments? Cumulativeness in technological evolution; Network externalities or other advantages to consumers or users; Specialised complementary products or services; running the tape of history another time’
Critically discuss Joseph Schumpeter’s view of the role of innovation in economic and social change
Economic development in his view has to be seen as a process of qualitative change, driven by innovation seen as new combination of existing resources, leading to new products, new methods of production, new sources of supply, exploitation of new markets and new ways to organise business. This combinatorial activity he labeled the 'entrepreneurial function’ against inertia and 'resistance to new ways’. Mark I (1912): entrepreneur as the engine of innovation, Mark II (1942): innovation needs large firms and R&D labs. There is no single, unified theory of innovation. There are partial explanations from various disciplines, including economics, political science, sociology, geography, organizational studies, psychology, business strategy. Innovation studies is a discipline which draws on all of these. The challenge for any theory of innovation is that it has to explain an empirical phenomenon that takes many guises. It has to encompass its complexity, dynamism, and uncertainty, often compounded by the way innovation results from the contribution of many parties with occasionally divergent and not fully established agendas. Innovation results from a collective process whose outcomes may not be known or expected when it begins.
Discuss the concepts of invention and innovation
1. Invention: • Invention refers to the creation of a new idea, technology, product, or process that has not existed before. It involves the development of something novel or original that addresses a specific problem or satisfies a need. • Inventions can range from tangible products, such as new devices or machines, to intangible concepts, such as mathematical theorems or scientific theories. • Inventions often arise from individual creativity, scientific research, experimentation, or serendipitous discoveries. They represent the initial spark of innovation, laying the foundation for further development and implementation. 2. Innovation: • Innovation, on the other hand, refers to the process of taking an invention and transforming it into a practical application or commercial product that creates value for individuals, organizations, or society as a whole. • Innovation involves not only the creation of new ideas but also their implementation and adoption in real-world settings. It encompasses activities such as product development, marketing, distribution, and organizational change. • Innovations can take various forms, including incremental improvements to existing products or processes, radical breakthroughs that disrupt entire industries, or the introduction of new business models or ways of organizing economic activity.
Critically discuss the figure below showing the distribution of population and patents across the world
Innovation tends to be spiky and concentrated in space due to several factors: 1. Agglomeration Effects 2. Network Effects 3. Ecosystem Dynamics 4. Critical Mass 5. Path Dependence
Discuss the knowledge production function approach
Starting from Griliches (1979) and Griliches and Pakes (1984) a strand of literature concentrated on innovation as a knowledge production function (KPF) in which innovation is the transformation of innovative inputs in innovative outputs. Of course, both inputs and outputs should be represented by means of economic entities. For this reason, originally, inputs such as R&D (expenditure and research personnel) and output such as patents (rights about inventions perfectly accountable) have been selected for representing the KPF Patents = f(R&D) Frascati Manual is a world standard on collecting R&D statistics This manual defines R&D as comprising both the production of new knowledge and new practical applications of knowledge and including: i) basic research; ii) applied research and iii) experimental development. The following activities are excluded from R&D statistics: i) Education and Training; ii) Market Research; iii) Acquisition of Licences; iv) Product Design; v) Trial Production; vi) Acquisition of machinery related to product or process innovation.
Critically discuss the key results from the figure below
The figure presents data from the Community Innovation Survey (CIS) 2018, detailing the percentage of enterprises in Italy that applied for a patent, registered an industrial design, trademark, or used trade secrets, segmented by whether they are classified as innovative or non-innovative enterprises.
Critically discuss the trade-off between patent breadth and length.
Suppose that the innovation generates a notional maximum discounted social value W¯ that could be earned if it were available for free immediately but a deadweight loss, d, is incurred during each period of protection. Let the flow profits for each period of protection be π for the innovator. Profits fall to a baseline level of zero after protection expires. Suppose also that there are T periods of patent protection (for example, T = 20 years). This patent protection allows entrepreneur to gain a profit π, but also raises a penalty for social value, that equals the deadweight loss d. Now, let’s define the discounted rate ρ(T) we use to calculate discounted values for profits (π) and deadweight loss (d). Therefore, the net discounted benefits to society will be: N(T) = W¯ − dρ(T) where dρ(T) is the discounted value of deadweight losses accumulated over the years T of duration of the patent protection. dρ(T) = d + d*(1/(1+r )) + d*(1/(1+r )2) + d*(1/(1+r )3) + · · · + d*(1/(1+r )T)= d*SUM T, t=0 (1/(1+r )t) The expression N(T) = W¯ − dρ(T) is decreasing in T We can either think of maximising this expression with respect to T or minimising dρ(T) with respect to T... ...subject to the constraint that the discounted benefits generated from innovation, πρ(T), meet a value, c, required to induce innovation. Noting that πρ(T) is increasing in T, the solution to this problem is the minimum T that allows the constraint to be met. Formally, society’s problem is to maximise total discounted social welfare from innovating (or minimise the total discounted social costs), where welfare in each period decreases with the price premium over marginal cost and the patent expires at time T. If we take π to reflect the price cost margin, we have the following social planner’s problem: Max [W¯ − ρ(T)d] subject to the constraint that c ≤ πρ(T) What’s matter now is that in this maximisation program the social planner has two different tools to maximise social welfare by implementing patenting rules: 1) The statutory length T 2) The price-cost margin (or profit π) 3) Note that the deadweight loss function d is also a function of π (d(π)) MaxW¯ − [X(T)d(π)] subject to the constraint that c ≤ X(T)π
What is the optimal breadth for patents?
Gilbert and Shapiro (1990) associate the ’patent breadth’ to the possibility to protect by means of new collateral patents (incremental improvements) the original design. It means that broader claims could be approved by the patent office, resulting in a larger ’exclusion zone’ around an innovation in product space This could translate into higher monopoly profits if close substitutes are not permissible. According to Gilbert and Shapiro (1990) narrow and long patents be optimal because broad patents are costly for society in that they give excessive monopoly power to the patent holder. Gallini (1992) noted instead that broader patent breadth could be an important lever to limit excessive social welfare losses. Narrow patents increase imitation possibilities perceived by competitors that try to practice the inventing around. This makes entry more attractive, but entrants incur sunk costs and duplicate innovative efforts. This is also a cause of social loss. By setting a larger breadth, imitation is discouraged, there is no resource cost to imitation for any given level of industry profits. Then the best policy is to set breadth large enough to discourage all imitation... and the length to generate the desired reward for innovation. This is an argument for optimal patents to be broad and short. The trade-off between patent breadth and length refers to the balancing act that policymakers and inventors must consider when determining the scope and duration of patent protection.
Main actors in the innovation process (Entreprenuers and venture capitalists)
Schumpeter distinguished between two models of innovation. In the Mark I model, creative destruction is driven by the entrepreneurial task of ‘breaking up old, and creating new tradition’. Schumpeter’s Mark II model recognized that entrepreneurship occurs in large established firms as well as newly created firms, reflecting the changing industrial realities as formally organized, large-scale R&D activities grew in scale from the 1920s. Entrepreneurship is therefore the organizational process by which opportunities are sought, developed, and exploited in many different kinds of company and organization. Entrepreneurial start-up firms often receive investments from venture capitalists who are prepared to assume higher risks than high street and investment banks. Different international models of venture capital exist, but the US is often considered exemplary. US venture capital may include funds from private investors or corporations, and their managers may possess deep experience or knowledge of particular technological sectors and become engaged in the governance of start-up companies. The objective of venture capitalists is usually to acquire shares in companies in their early years that then reap extraordinary returns after they exit when the firms have reached sufficient maturity to attract a purchaser or to be floated on a stock market. Among their portfolio of investments, venture capitalists recognize that the majority of returns will come from a limited number of cases (power law)
Main actors in the innovation process (R&D)
R&D is a significant (but not always essential) source of innovation. Investments in R&D help organizations search for and find new ideas and improve their capacities to absorb knowledge from external sources. R&D ranges from basic research driven by curiosity and little concern for its application, to highly practical problem-solving. In 1963, the Organisation for Economic Co-operation and Development (OECD) decided it would be useful for policy-making to have consistent international data on R&D statistics. Following a meeting in Frascati, Italy, this became known as the Frascati Manual. The OECD has also developed the Oslo Manual to guide national innovation surveys, the Canberra Manual for measuring human resources in science and technology, and a Patent Manual on the use of patent statistics
Main actors in the innovation process (Customers and suppliers)
Innovations do not succeed unless customers or clients use them. If the users of new products and services are involved in designing what they need, there is generally a better chance of success than if something is being designed for them. Active engagement of customers helps better articulate their needs. When Boeing developed the 777 aircraft, it involved its major customers, United, British Airways, Singapore Airlines, and Qantas, in trying to understand the demands of the market. It needed to know about optimum passenger loadings for airlines’ favoured routes. It also worked to understand the demands of the users of the aircraft: the pilots and aircrew, maintenance engineers, and cleaners. Software companies sometimes release their products in ‘beta’ form, that is, in prototype, to allow users to play with the software and suggest improvements. Essentially, customers do much of the final polishing of the product. Customers can also inhibit innovation: • they can be conservative and complacent and locked into ways of doing things that preclude novelty and risk • if innovators only respond to the immediate demands of customers, they often miss big changes occurring in technologies and markets that may eventually put them out of business • there is an advantage in working with ‘lead customers’, governments, firms, or individuals that are prepared to take risks to promote innovation in the belief that greater benefits will accrue than pursuing the safer short-term option of not innovating Innovative suppliers are also major stimulants to new ideas. In the automotive industry, a high percentage of the value of a car is bought from suppliers of components. In Toyota’s case they account for up to 70 per cent of the car’s total cost. Toyota enjoys very close relationships with Nippondenso, a very large components supplier of innovative products such as lighting and braking systems. The automotive supplier Robert Bosch plays a similar role in the European car industry. The task of the car manufacturer—or the organization responsible for integrating any system of different elements— is to encourage innovation in suppliers of modules or components while ensuring the compatibility of components with overall design architectures or systems.
Main actors in the innovation process (Collaborators)
Innovation rarely results from the activities of single organizations and more commonly occurs when two or more organizations collaborate. The benefits of using collaboration to contribute to innovation outweigh the costs of sharing the returns to that innovation. Collaborations take the form of joint ventures and various types of partnerships, alliances, and contracts that involve joint commitments to mutually agreed aims. They can be with customers and suppliers, organizations in other industries, and even with competitors. Organizations collaborate to reduce the costs of developing innovation, access different knowledge sets and skills to the ones they possess, and use it as an opportunity to learn from partners about new technologies, organizational practices, and strategies. In uncertain and evolving circumstances, innovating collaboratively provides a greater chance of success than going it alone. ICTs and other technologies, have made collaboration cheaper and easier. Governments around the world have actively promoted collaboration as a source of innovation. Different types of collaboration work better in different situations. • When the objectives of collaboration are clear, or the focus is on quickly reducing costs, it works better when organizations are similar. The opportunities for misunderstandings and miscommunication are fewer. • When objectives are emergent, and the objective is exploration and learning, collaboration benefits from dissimilar organizations working together. More is learned from variety than uniformity. • Larger numbers of partners increase the scale of effort; fewer partners improve speed. Collaboration can be difficult to manage. Partners may have different priorities and organizational cultures. There are many opportunities for misunderstanding.
Main actors in the innovation process (Universities)
Universities contribute to the innovation process with their three main functions: Teaching, Research and Engagement with industry. Teaching: by educating skilled undergraduates, graduates, and post-doctoral students, universities prepare a labour force capable to create and apply new ideas. Research: One of the traditional distinctions in research, seen in the Frascati Manual, is between that which is ‘basic’ and that which is ‘applied’. The former is thought to be curiosity-driven, with no consideration of its application, and is the particular concern of universities. The latter is believed to be directed towards an identified use and is usually explored in industry. Yet some businesses invest substantially in basic research and universities conduct extensive applied research, especially in professional departments such as medicine and engineering. In reality, basic and applied research are elements of a continuum, with many interconnections. Applied research may result from basic research findings, and basic research may be undertaken to explain how an existing technology works. One of the most useful outcomes from pure basic research is the instrumentation developed to assist experimentation. Engagement with industry: Since the passing of the Bayh-Dole Act in the USA in 1980, which allowed research institutions to own the results of publicly funded research, universities have become preoccupied with making money from their research. This has usually taken the form of patent-protected intellectual property, licensed to businesses, or through start-up companies, spun out of and part-owned by the university. Evidence suggests, however, that the number of successful instances of this model of commercialization is limited. Also important are the networking activities between universities and business about new developments and their potential applications. For many businesses, particularly smaller ones, the purpose of collaborating with universities is immediate problem-solving, larger firms will engage in broader dialogue with universities to learn about the directions of future research.
Main actors in the innovation process (Regions and cities)
Innovation agglomerates by localizing within particular geographies • for economic reasons (as proximity reduces the costs of transactions and transportation, and firms in close association stimulate the creation and diffusion of innovation through improved awareness and knowledge of each other) • for social and cultural reasons (including the advantages derived from shared identity and higher trust in affiliated and cohesive groups; communications are assisted by proximity because knowledge is sticky and travels badly from its source, especially when it is complex or tacit and cannot be written down) These factors contribute to a local culture, or ‘buzz’, that is technology-focused, risk-taking, and highly competitive, and it creates a virtuous circle of initiative and reward. It is often cities that provide the locus of innovation.
Main actors in the innovation process (Government)
Government intervention in the innovative process is often motivated by ‘market failure’. Due to limited appropriability of the results of R&D, the private returns to R&D are lower than the public returns, leading to under-investment. This justifies financially supporting R&D in firms with public money, but also IPR regimes and R&D by government branches. Other reasons for innovation policy rely on: • Fear of international competition and building national champions • Failures in national innovation systems Beside innovation policy governments contribute to innovation with monetary and fiscal policies, education, competition policies, immigration policies, industrial relations, procurement.
Critically discuss the national innovation systems approach to interpreting the innovation process
Oversimplified approach; why certain countries are more successful in innovation; economic and legal focused on nation's key institutions AND close ties between customers and suppliers of innovation through trust; nations are not always the best level of analysis (regional and sectoral)
Critically discuss the scatterplot below
The figure illustrates a scatter plot examining the relationship between assessed management practice scores and labor productivity across various types of firm ownership and management structures. The x-axis represents the assessed management practice score, ranging from about 2.5 to 3.3, while the y-axis represents labor productivity, ranging from 5.0 to 5.6. Different types of firms are plotted as individual points on this graph, and a positive trend line indicates a general correlation between better management practices and higher labor productivity. Critical Discussion 1. Correlation vs. Causation: • The positive correlation suggests that better management practices are associated with higher labor productivity. However, it’s important to note that correlation does not imply causation. Other factors might contribute to higher productivity, such as industry sector, market conditions, or external economic factors. 2. Management Practice Score Measurement: • The way management practice scores are assessed can significantly impact the interpretation of this figure. If the assessment criteria are subjective or vary significantly across industries, the comparison might be less reliable. 3. Firm Size and Resources: • Larger firms, such as multinationals, typically have more resources to invest in advanced management practices, training, and technology, which can drive higher productivity. Smaller firms or those led by founders might lack these resources. 4. Cultural and Regional Differences: • The figure highlights that U.S. and EU multinationals score highly, which might reflect cultural differences in management practices and business environments. These firms often operate in highly competitive global markets, necessitating superior management practices. 5. Policy Implications: • The findings suggest that policies promoting professional management practices, especially in family-owned and founder-led firms, could enhance productivity. Support for management training, access to external professional managers, and incentives for adopting best practices might help improve overall firm productivity.
Critically discuss the internal determinants of firm productivity
Management and organization Quality of human and physical capital IT e R&D Learning-by-doing Innovation
Critically discuss the external determinants of firm productivity
Technological externalities/spillovers Competition Regulation Factor markets
Critically discuss the figure below
The figure presents a table titled "Table 2 Management quality," which analyzes the impact of different measures of competition on the dependent variable, management quality, in the product market. The table shows results from three regression models, each using a different measure of competition as an independent variable. Here's a critical discussion of the findings: 1. Dependent Variable: Management Quality: • The dependent variable across all three models is "management quality," which is likely a composite measure capturing various aspects of managerial effectiveness and practices within firms. 2. Independent Variables: • Model 1: Import Penetration: This variable measures the extent to which foreign goods and services penetrate the domestic market. • Model 2: (1 - Lerner) Index of Competition: The Lerner Index is an inverse measure of market power. Here, (1 - Lerner) indicates the degree of competition (higher values mean more competition). • Model 3: Number of Competitors: This variable simply counts the number of competitors in the market. 3. Coefficients and Significance Levels: • Each cell in the table reports the coefficient of the independent variable on management quality, with standard errors in parentheses. • Significance levels are indicated by asterisks: • *p < 0.1 (weak significance) • **p < 0.05 (moderate significance) • ***p < 0.01 (strong significance) 4. Observations: • The number of observations (firms or data points) varies slightly across the three models, ranging from 2657 to 2819.
Critically discuss how the geography of innovation affects the internationalisation of R&D in multinational enterprises (MNEs).
Lead firms can use different types of linkages to tap into foreign knowledge pockets: • organization-based pipelines by setting up foreign subsidiaries or formal inter-firm linkages • individual-based linkages through global mobility of inventors and experts Offshoring innovation activities or building knowledge pipelines allows firms to tap into knowledge clusters or centres of excellence around the world, so to diversify the firm knowledge base and speed up the acquisition of knowledge inputs that would otherwise be difficult to generate internally. However, it has also uncovered the most critical aspects of this knowledge sourcing approach, emphasizing the key role of integrative mechanisms and embeddedness in global knowledge networks. Lead firms need to develop orchestration capabilities to ensure that the entire value chain operates as a harmonious whole. The need to “know more than they make” create technological capabilities in a much broader range of technical fields than the core product fields in which they compete so they can identify and coordinate the integration of new technological developments along the GVC. Develop organizational knowledge that allows them to deal with both internal and external partners that are dispersed across the globe. Concentration: • Economies of scale and scope in R&D • Embeddedness in home innovation systems • Coordination costs, complexity and managerial bandwidth Dispersion: • Need to adapt products to local demand conditions • Tap into host innovation systems and access to a portfolio of knowledge pockets around the globe • Growing complexity and interdependence of technologies requires to widen the scope of knowledge search by building linkages to other locations Where innovation happens? 1) Within large MNEs/independent suppliers; 2) Concentrated/dispersed According to these studies, innovation takes place in the MNE’s home country, while foreign subsidiaries mostly adapt the product and process technology to the local context. Foreign subsidiaries are categorized as ‘Home-Base-Exploiting’ (Kuemmerle, 1999) or ‘Competence-Exploiting’ (Cantwell & Mudambi, 2005) since they mainly receive knowledge developed in the MNE’s domestic R&D centres and only carry out the final adaptation steps of the innovation process prior to commercialization. Over time MNEs’ foreign subsidiaries moved away from being mere “replicators” of their parent companies’ activities abroad, whose R&D efforts are limited to the adaptation of central units’ products and services to local needs. Rather, foreign units can engage in creative tasks to exploit opportunities emerging from their local contexts, and the innovative activities they perform locally may follow diverse routes and pursue different projects than those of the home country. Thus, supply-side factors emerged as critical triggers toward more home-base augmenting types of foreign R&D. This perspective has further been stimulated by the rise of global centers of excellence in geographically distributed areas of the world, which have worked as a powerful centrifugal force that pull MNE R&D activities outside of their home countries.
Critically discuss the models to manage innovation in multinational enterprises (MNEs)
Models of innovation in GVCs: • Linear and closed • Interactive and closed (chain-link model) • Interactive and open 1) According to these studies, innovation takes place in the MNE’s home country, while foreign subsidiaries mostly adapt the product and process technology to the local context. Foreign subsidiaries are categorized as ‘Home-Base-Exploiting’ (Kuemmerle, 1999) or ‘Competence-Exploiting’ (Cantwell & Mudambi, 2005) since they mainly receive knowledge developed in the MNE’s domestic R&D centre and only carry out the final adaptation steps of the innovation process prior to commercialization. Over time MNEs’ foreign subsidiaries moved away from being mere “replicators” of their parent companies’ activities abroad, whose R&D efforts are limited to the adaptation of central units’ products and services to local needs. Rather, foreign units can engage in creative tasks. 2) Innovation can be conceived as the result of interactions between various actors at different stages of the innovation process. Interaction between: Production and R&D and Sales/Marketing and R&D. 60% of all international R&D FDI (foreign direct investment) by MNEs are concentrated in just the top 5% of cities. Why do firms co-locate different value-chain activities in the same place? The need/advantage from co-location can be very heterogeneous: - Across sectors - degree of modularity and maturity of technologies - Based on the importance of tacit vs. codified knowledge - Based on firm sensitivity to coordination and control costs 3) Technological knowledge is no longer considered to be solely sourced within the intra-organizational network. External organizations along with different types of knowledge acquisition practices gain a prominent role in the firm innovation process.
Critically discuss the forces that can lead to centralization and decentralization of R&D in multinational enterprises (MNEs).
Centripetal forces (geographical concentration of R&D) • Economies of scale and scope in R&D • Embeddedness in home innovation systems • Coordination costs, complexity and managerial bandwidth Centrifugal forces (geographical dispersion of R&D) • Need to adapt products to local demand conditions • Tap into host innovation systems and access to a portfolio of knowledge pockets around the globe • Growing complexity and interdependence of technologies requires to widen the scope of knowledge search by building linkages to other locations
What do we mean by dual embeddedness of multinational enterprises (MNEs) and how does this relate to innovation in MNEs?
Dual embeddedness of multinational enterprises (MNEs) refers to the simultaneous integration and involvement of MNE subsidiaries in both the local host-country environment and the global network of the parent company. This concept captures the dual pressures and opportunities faced by MNEs as they navigate and leverage resources, knowledge, and capabilities from both local and global contexts.
Pavitt's Taxonomy
1. Supplier-dominated: includes firms from mostly traditional manufacturing such as textiles and agriculture which rely on sources of innovation external to the firm. 2. Scale-intensive: characterized by mainly large firms producing basic materials and consumer durables, e.g. automotive sector. Sources of innovation may be both internal and external to the firm with a medium-level of appropriability. 3. Specialized suppliers: smaller, more specialized firms producing technology to be sold into other firms, e.g. specialized machinery production and high-tech instruments. There is a high level of appropriability due to the tacit nature of the knowledge. 4. Science-based: high-tech firms which rely on R&D from both in-house sources and university research, including industries such as pharmaceuticals and electronics. Firms in this sector develop new products or processes and have a high degree of appropriability from patents, secrecy, and tacit know-how.
What is the power law of distribution?
In a power-law distribution, the largest entity is typically bigger, more valuable, or more powerful than all others combined. The second-largest is likewise bigger than the total of all those after it, and so on. Also, in a power-law distribution, the top 20% of the entities typically hold 80% of the value or power. The vast majority of returns come from a small percentage of innovative investments.