economics of innovation secondo parziale- innovation and technology management, Schemi e mappe concettuali di Economia Dell'innovazione

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ECONOMICS OF PATENTS: technological markets: pay licences to use technology Electronics: patents cross licensed through technologies Origins: Science based, federal funding, universities, private funding (incentives) Incentives of innovations for commercialization + cash {to who will invent specific product (ansari.xprize)} CRISPR-CAS9: ability to substitute part of DNA with other one = genome editor (Nobel) - 2 similar patents at 6 months distance: possible bc first one too specific (streptococcus/eukaryotic) WHAT IS A PATENT: monopoly right in specific country, typically last 20 years, to exploit the invention commercially in one or more selected countries, subject to payment of regular renewal phases. - Inreturn for right to exploit invention, details are published via the patent application: disclosure Patentability conditions: - Practical use or utility: industrial applicability, useful - Novelty: new characteristics, unknown in the body of existing knowledge in its technical field - Inventive step: non-obvious invention to a person with average knowledge of technical field Economics of patent: justification for existence of a patent systems relies on answer to followings: - Economicbenefit of a patent system; Costs of patent system; Patent system promotes socially useful innovation; Distortion created by a patent system: IPR systems NOT created by rational, consistent social welfare maximising public agency: - Historical process with consequences; interests of many parties o Role of economists: provide framework to identify mayor problems of allocative efficiency and distributional issues at the stake POLICY OBJECTIVE: creation and diffusion of new & useful knowledge Market failure: - Knowledge as public good (non rival, non excludable, high fixed costs, low marginal cost reproduction) Solution: Incentives, Subsides, Direct participation in production and distribution of the goods - Regulate private monopoly by assigning property rights Economic trade offs — patents - Generaltrade-off: static vs. dynamic efficiency - Optimal duration and scope (what is a broad patent). Smaller things to decide: o Duration of the patent right o Scope the portion of an abstract product/technology covered by the innovation (novelty) = Before injapan very weak bc they wanted to have a lot of innovation o Amountof claims in a patent - Developing countries: benefits from free diffusion of knowledge/products, technological transfers/IPRs Benefits & costs of patents Costs Benefits Deadweight loss = Av Decentralization: rights not negotiated with authority It can't be mitigated by price discrimination: Cost of innovation on users: - Difficulty to implement - Noton the tax— payers - Trade off: common markets/equity issues Classic view: benefits, costs of IPRs: related to idea we have 1 single innovation prpduet èmonopoly prices - Innovation and social value:m+p+% = =total potential consumer surplus with p= MC=0 o Patent value (with duration T) = nT el o AT= Dead Weight Loss o Ifscope of patent > - Patent design affects substitutability and is aimed at balancing these trade-offs7 N MÈ o Strong systems create more incentives o Weak systems create more access and diffusion Classic view Contemporary view Welfare enhancement | Encourage innovation(monopoly right | IPR Encourage competition through specialized companies HiPwio=o Welfare Damage I Stifle competition (deadweight loss, Stifle innovation (risk of infringement high monopoly price) > less investment) Welfare Damage Il Strategic patenting: > invention costs Contemporary theory: stronger focus on commercialisation and development of inventions: Access to financial markets (patent necessary to access) - Patentsat early stage of innovation process: Necessary for any licensing to occur - 2 issues: (incentives) o Appropriability requires that companies need exclusive licensing to develop university inventions? © Can patents taken out on further inventing that is involved in the development work? = Otherwisenoneedto patent the original invention Key assumptions: - __Cumulativeness (1 invention basis for further)/complexity (1 combined with other to obtain 1 product) Effects on: Positive Negative Innovation Creates incentive for R&D and Impedes combination of new ideas & inventions innovation investments Raises transaction costs Inhibits cumulative invention Competition | Facilitates entry of new or small Creates short term monopolies which may firms with limited assets become long term in network industries Enables vertical disintegration Benefit and costs of strong patent protection: cost of being a monopoly What is particularly effective to take advantage of product innovation: Theory I: PATENTS INDUCE INVENTION: create incentives - Small firms: o Meanto appropriate returns through licensing (no manufacturing facilities) o Meanto control technology while production and sales capabilities are built - Trade-off: a broad patent is a disincentive to undertake follow-on inventive work o Alternatives have to be very different - Patents should not be granted when they are not needed to motivate invention (link to open science) - Empirical studies: big established firms: “patents are not particularly effective and costly” US: strong secrecy protection {NOT that important (in US number 5, in Japan number 2)} Theory Il: PATENTS INDUCE COMMERCIALISATION AND DEVELOPMENT OF INVENTIONS - Accessto financial markets, venture capital - Patentsat early stage innovation process NOT so necessary if CAN be taken out at development stage - Patent necessary for any licensing to occur o Trade-off: exclusive licensing to undertake development phase - Issues: o Many patents in development phase o Exclusive licensing of broad patents restricts number of development opportunities [many cases no exclusive licensing BUT initial licensing to # people to reach deeper development]: cohen boyer: = Kohler and Millstein: nobel but didn't patent technology (monoclonal antibodies) © University inventions financed with public funds: subsides. Patent issues and concerns: | - Restricted access to (knowledge) patented upstream, foundational discoveries - Important issues on patenting sciences and knowledge transfers from unis and PROs o Tragedy of anti-commons for therapeutics and diagnostics (finding solution when property of something very fragmented) Theory III: PATENTS INDUCE DISCLOSURE OF INVENTION: Society access to technology: - Companies and inventors may want to keep inventions secret (if want patents need disclosure) - Patents are published and contain codified information - Much more advertising also by universities and PRO Critics: Other vehicles of knowledge spillovers; useful with widespread licensing (conflict with theory II) Static barriers to entry: - Indivisibilities and economies of scale (minimum best scale) in manufacturing - Managerial know-how and knowledge of the market - Channels of distribution Teece model: qualitative, not formal. 1986 “why entrepreneurs often fail to capture value of innovations” Conceptual framework to evaluate appropriability regimes with complementary assets to understand position in your company 2 factors more important than big idea for profit: You can: 1. Complementary assets: up/downstream assets used ta develop, distribute or produce an innovative new product or service - Manufacturing capabilities Core technological know-how in innovation: - Sales & service expertise = Competitive manufacturing - Capture customer knowledge = Distribution You own: = Service - Brand name = Complementary technologies - Distribution channels = Other(x4) - Customer relationship Difficult to capture value of innovation if complementary assets easily available 2. Appropriability regime: how to protect innovation. Likelihood of preventing imitation # x each inn Complementary assets Freely available / unimportant Tightly held and important Difficult to make money Holder of complementary assets Appropriability | Weak (cola: RC > pepsi / coca cola) Strong Inventor or party with bargaining Inventor power MARKET ANALYSIS USING PATENT DATA: Market analysis: 1. Specific product related search. Already existing? Are there some patents? a. In many cases patent very specific + covers just a specific key point of the technology 2. Overview of the market (who is working in the technology, what type of patent) Which companies / institutions and individuals (specific inventors) are involved 4. Provide a strategic assessment: a. Howisit possible to enter the market? b. How many potential competitors? c. Possibility for licensing? PATENTS: impressive / unique source of technical solutions: 80% of technical information not elsewhere - Publishing may compromise patentability of invention formally (earlier disclosure) or substantially (may prove it's obvious) - Technical info not suitable for publication: subject, theoretical support, lack experimental data... - Anticipate technical literature: When have innovative idea PRIOR ART search = key (looking at other patents): - May reveal solutions to your problems - May acquire rights for patent that is a solution to your problem at < cost than invention - Iflicensing NOT available > can help to find alternative solution which doesn't infringe existing patent o Askfor licence to company who patented it - Existing patent on same invention will prevent you to get another about same invention - Design or research could lead to a patent infringement (even proving good faith) Reading a patent for market strategies: essential for innovation strategy and market strategy: - To analyse innovative strength and technological trends: o Firm level, industry level, global and regional level o Recognise lack of advancement in a technology and address improvements ” - Avoid duplication of R&D and waste of human and financial resources - Bring together inventors and investors ‘Identifier — RETI - Retain market position & locate new business CE== Pre] vesemnt partners Das : - Monitor competitors Inventors > and | Applicant The patent document: Z< Identifier: first letters: patent office (European/It...) [WO+PCP patent] {# protections 2° place} Title and Abstract Tit IPC Class - Certification number: ciphers in the middle. Certification state: last 2 elements (A + B) Dates: of publication: typically after 1 year, max 18 months / of filing (at patent office considered) - Of priority: oldest; priority number (GB) where first applied + to UE office after 1 year © Can ask in which offices protect patent (between filing and priority) o Legal value from this date Inventors & applicant: legal / moral responsible, indispensable for validity of patent - Couldbe>1(collaborations) Title & abstract: explanation of nature of invention IP class: technological field; codes to classify technology Technological classification systems (1): - IPC: international patent dassification: revised every 5 years, CPC (cooperative patent dassification) © Used by patent examiners to check overlapping - USPC: united states patent classification: o Hierarchical structure (#IPC), function oriented, correspondence between IPC & USPC / ECLA &USPC Patent family: “all documents having the same priority or combination of priorities belong to same PE” Patents citations: “used by patent examiners to peer patent, check overlappings” - Used to track knowledge flows and spillovers: - Important differences between EPO and USPTO patent citations © US: duty of candour (legally), much more citations in the patent to prior patents and more noisy o EPO: citations mainly assigned from the examiners The search report: Citation to other patents & non patent literature; communicate us result & reasons Objective: “discovering prior art relevant for determining whether the invention meets the novelty and inventive step requirements” VE - Category of documents X (kills the patent), Y (invalidates some parts), A indicates relevance - Documents cited with reference to the claims Category X YA Relevant to Claim INNOVATION AND ECONOMIC GROWTH: Cited documents Examiner Determinant of economic growth in our economics «ses» | Growth of income in the world (1000 — 2016) GDP itonesia per capita: - Exponential growth (who believes in it on a finite planet is a madman/economist) Gdp per person in log scale: 64000. € substantial steady exponential growth 16,000 2.0% per year Why so linear growth: Economic model try to understand what happens and derive some general rules (fundamental rules of specifical phenomenum) 4,000 200 È 1880 1900 1920 1940 1960 19802000 Labour productivity (output per hour worked) + N a CERO Î © Projection for 2098. € Global income distribution: (giù) Median income is increasing. Catching up: # patterns: China 6,9 % in 20 years (USA only 1,6% in 20 years) Growth and sustainable development: Human development: expanding people's choices; is built on shared natural resources. To promote it essential addressing sustainability (should be done in ways equitable and empowering). 3 caveats: 1. Income growth associated with deterioration in environmental indicators (emissions, soils) 2. Distribution of income has worsened at the country level in much of the world despite education Value added — US economy: sector value-added in current prices and shares ‘ofgdp Stable growth rate in the long run - Exponential growth on gdp per capita (it tends to decrease over time) Heterogeneity across and within countries [growth rates are key (US 30 times richer than Uganda)] Persisting gaps in productivity and productivity growth Substantial structural change GDP per capita growth is not everything: neglects health, environment, education... - UN’s human development index (HDI) gives equal weight to life expectancy, education and GDP capita - GDP measures aggregate value added (whether coal power station or wind farm) How technological change and innovation affect economic growth? How can we understand the link between technical change and economic growth? Sources of growth: Yi = ef* Ll1-2) K? gy: growth rate of Y (composed of # growth rates) À = productivity growth rate 8y=A+(1-a)*gi+a*gx per capita GDP growth: (gy-g.)=A+a (gx—g.) 2 sources: 1. Productivity growth (A = technological change driven by R&D) 2. Factors accumulation (traditional...) + capital per unit of the labour force (ultima parentesi) Growth of output = average growth of input + growth of productivity WHAT CAUSES ECONOMIC GROWTH? Country specific characteristics related to economic growth: - Physical and human capital (education): o Capital accumulation has been mayor cause of south Korea/Singapore success respect Nigeria - Productivity (A) technology A = g(K) where dA/dK > 0 A=K8 R>0 20 Cobb Douglas production function: |= an = Y= AKALT=? = [KS]KeLt=a = Ka +B1-a oncan ) 7 If a+B=1 > marginal product of capital constant (dY/dK=L!-?) Assuming A = g(K): intuition>spillovers and learning about technology prevent marginal product declining Investing own capital affect also aggregate capital & growth 3 endogenous explanations: — - Knowledge externalities: firm doesn't control increasing returns (Ai depends on aggregate capital) Romer: proves this model has a competitive equilibrium; importance of externalities in knowledge; endogenous growth theory combines IRS, knowledge externalities & competitive behaviour in models o Decreasing return to scale at firm level | increasing return to scale at economy level o A=knowledge (some public good properties) o Key assumption = knowledge spillovers from private investment> A = K® Y=K2+8L1-2; a+B=1 Important applications: o Competitive growth rate is sub optimal (externalities) = NO socially optimal level of positive externalities + policy interventions to stimulate diffusion of knowledge o Shocks and policies have permanent effects (contrary to the Solow model) o Large countries grow faster (scale effects) - Human capital: LUCAS model: Substitute ideas in production function o Emphasizes external effects o Human capital = skill embodied in workers (knowledge, education, training) measured with h = Usedto produce output (proportion u) or accumulate new human capital (proportion 1-u) Grows at a constant rate: dh/dt = h(1-u) Production of output given by: Constant number of workers in economy is N Y = AK*(uhN)?-*hy O<a<1;y >= 0 Aggregate element of human capital is external to input and increases its general productivity Growth of human capital endogenous Main driver of work: h grows + N grows + Y grows + marginal product of K grows - R&D, creative destruction & firm level a ty: o Many endogenous growth models assume profit seeking firms invest in R&D (ideas, knowledge) = Incentives: monopoly profits (2° probability of inventing) & expected length of monopoly (strength of intellectual property rights) = Cost: expected labour cost (depends on productivity, which depends on extent of spillovers) o Monopolistic competitions (fixed costs of R&D = monopoly profits) creative destruction since new inventions destroy existing markets o Without “knowledge spillovers” such firms run into diminishing returns o 3 potential market failures+policy implications unclear: = Appropriability effect (monopoly profits of new innovation < consumer surplus) 3 Too little R&D in the market (too few products) = Creative destruction: ignored by private innovator + Too much R&D in the market = Knowledge spillovers (each firm’s R&D reduce costs of other’s innovations) + Too little R&D Messages from endogenous growth model: Key element for long run economic growth related to: 1. It points directly to process of knowledge generation and diffusion a. Opportunities and development embedded into specific technologies b. Role of general purpose technologies (GPT) 2. Presence of some forms of knowledge spillovers (externalities) Competitive profit seeking firms can generate investment & growth: 1. Creative destruction and knowledge decay: Role of accumulated knowledge 2. Knowledge depreciation &/or decreasing returns in knowledge production vs. exponential growth Models focused demonstrate long run equilibrium path (too generalized to offer specific policy guidance) output per worker positive, hence growth o ooo Important implications in terms of institutional setting: 1. Balanced IPRs (appropriability & diffusion) 2. Role of government + entrepreneurial states 3. What's the appropriate market structure? More tolerant with market concentration? 4. Geographical clusters, networks, business university links all potentially vital Computer vision expert Fei Fei Li (TED): Smartest machine still blind Photo = numbers > picture # seeing something: Vision takes truly place in brain, not in eyes Train algorithms with experience, not just more sophisticated mathematics Database to recognise objects > recognition algorithm > applied to cameras - PClearnedto see picture and generate complete sentences (still make mistakes: images into pictures) o Notable to describe feelings, art, traditions, actions yet to happen Importance of time: very quick. Interdisciplinarity Actors involved public money, researching in university (partnership between them and private: amazon) ENDOGENOUS GROWTH AND GENERAL PURPOSE TECHNOLOGIES: GPT Artificial intelligence = “inventive method for inventing”. 3 trajectories: Symbolic systems: - Replication of logical flow of human decision through processing symbols (rules for conversation) o Inability to meaningfully impact real world processes in a scalable way Deep learning: - Multi layered neural networks o Increasing predictive power> applied to larger and larger datasets (substantial scalability) = Mostpromising stream in AI Robots: (linked with deep learning) - Highly sophisticated numerically controlled machines o Key technological trajectory but specialized end-use production applications (# robot in # situation) Deep learning and neural networks: It's a General purpose technology (GPT): like “steam engine, electricity, microelectronics” - Has pervasive application across many sectors: spawns further innovation in application sectors - Isitself rapidly improving It's the invention of a method of inventing (IMI): like “optical lenses, hybrid corn” - Greatpotential as a research tool in problems of classification and prediction (www.atomwise.com - Can constitute an entirely new way of creating new products \M Difference: IMI = methods to do new things /// 2° endogenous growth models, GPT & IMI surely big influential drivers of long term technological progress GPT characteristics: spreads throughout economy, fostering innovation in an ever expanding array of application sectors and bringing about generalized productivity grains (need time) - General purposeness: pervasiveness (used as inputs by wide range of downstream sectors) Performs some generic function: vital to functioning of many products & production systems o PREDICTION: “association between pattern observed and output I'm looking for” (continuous rotary motion, binary logic); not obvious that rotary motion would become a universal functionality: many manual jobs hardly be seen ex ante as candidates for mechanical replacement = Oftensubstitution did not make economic sense until steam engine/electric motor (deliver functionality at favourable price/performance = Microelectronics: almost all actions (despite variety) can be done through binary logic - Potential for continuous technical advance: (post sustained improvements in performance) - Innovational complementarities: productivity of innovative activities in user sectors increases as consequence of improvements in the GPT (network of fields affected by evolution - Application sectors: microelectronics (hearing aids, radios, PC, scanners, cars, TV...) o Enormous variety of seemingly disparate products, methods of productions concealing uniformity of few underlying technological principles (principle that give rise to powerful economic forces that shape the process of technical change and growth) Impact of GTPs: a more general view. How GPT impact economy: Often through massive relocation / reorganization of economic activity, concomitant gains in efficiency - Steam engine: allowing urbanisation of industry, agglomeration effects - Electricity: Separate production from use; Design according to workflow, not power requirements - _Computers / interned: facilitate informational exchanges, allow outsourcing/downsizing, reorganise around B2B, telecommuting... General purpose technology = GPT IMI NO YES Invention of | NO Industrial Robots ‘Sense & React’ robots Impact of IMI + GPT: method of | YES | Statistically — coded Deep Learning speed of change inventing Algorithmic Tools New IMI diffuses across many application sectors+resulting explosion in technological opportunities and increased productivity of R&D seem likely to generate economic growth - Caneclipse (superare) any near term impact of AI on jobs, organizations, and productivity Important to: - Develop institutions, policy environment conductive to enhancing innovation through this approach - Promote competition and social welfare Key interplay between a key input required for deep learning (large unstructured databases that provide information about physical or logical events) and the nature of competition Underlying algorithms for deep learning are in the public domain (rapidly improved) - Areainwhicha lot of policy discussion Data pool (essential to generate predictions). Public/private; (boundaries, policy, institutions) - Inapplication area, 1 company could gain persistent innovation advantage through control over data - Incentives x duplicative racing to establish data advantage in particular application sectors (say, search, autonomous driving, cytology) followed by establishment of durable barriers to entry o Duplicative R&D = social waste - Balkanization of data within each sector (not only reducing innovative productivity within the sector, but also reducing spillovers back to the source and other application sectors.) = FRAMMENTAZIONE Economic issues: 3 positive externalities (underinvestment): potential areas in which government could help building institutions. 1 and 2 overlap, they just emphasize # aspects Also 2 and 3 occur in time BUT 1 is about research tools, acceleration of innovation process within the GPT 1. Intertemporal spillovers: from innovators today to innovators tomorrow (research tools, institutions that support their development and diffusion: important role) (HGP) a. Competition private vs public and open results + acceleration of progresses / results 2. Vertical (due to innovation complementarities): very strict integration a. Higher quality of the GPT would result in higher technology level of application sector b. Cumulative technologies > source of underinvestment upstream c. Who and how controls these technologies? (supply chain, market power) Market concentration upstream: Germans very worried in using platforms owned by others 3. Horizontal: due to general purposeness: a. Higher technology level of the application sector, the more applications emerge + higher demand for the GPT > > quality of the GPT. Each application sector acts myopically # type of policy intervention: to understand potential bottleneck in relation between diffusion, creation of GPT and general impact in terms of growth How to overcome disparity between social and private optimum: - Proactive development of institutions & policies that encourage competition, data sharing, openness - Role of large demanders (initial demanders) (government, military, Key — lead users) - Contracting, coordination of key players to break limitations of arms-length market transactions - Informational exchanges to jointly improve quality of the GPT & technology level of application sector o More cooperation needed: < quality of GPT > more difficult for app sectors to anticipate future equality of GPT and vice versa ARTIFICIAL INTELLIGENCE: Machines that can learn, reason, act autonomously without human interaction - Abilities are going beyond physical tasks, engaging mental ones THE BLACK BOX PROBLEM: neural networks entails billions of operations We don't understand how Al systems work > can't really trust them or predict the circumstances under which they will make errors + can't say where error is + MUST control, act on the input: THE CHALLENGE OF GOVERNANCE: need for effective governance - Need for trustworthy and transparent AI - Different speeds of technology on one side and policy making on the other (present governance framework become quickly obsolete) No longer possible to chase technology: enhancing trust in data - Data strategy > data governance > data quality > data ethics AI issues: AI has led to separation between ability to act towards specific goal (agency) and intelligence - Dueto self determination of machine learning (not intelligent by itself in general sense) Counterfactual: if same result + process must be the same + consequently the source - Machines thought to be necessarily intelligent, even if result hasn’t required an intelligent process Loss of control: caused by abandonment of a logical, predetermined, codified context Issue because we live in a two speed world: - Machines improve so rapidly while as well develop unwanted outcomes - Governance frameworks around them have difficulties in keeping up A new governance model: Governance of the digital: logic of information, design as logic of requirements Requirements intended as functions of a system, defining its behaviour & what it is supposed to carry out. Chosen requirements, set of principles to guide decision and achieve wanted outcome can be established Ethics falls perfectly within this reasoning, as the set of principles that guides decisions Flexibility, Choice Principles: able to ensure that actions are strongly based on principle and not on limiting rules Paradigmatic shift instead of chasing technology, requirement approach defines an ex ante flexible tool to govern the digital THE DIFFUSION OF INNOVATION: generally slow (slower than expected) Consumption spreads faster today (> speed of diffusion); it varies across: - Type of innovation - Market, sectors, regions Typically S shaped (sigmoid): Exponential diffusion at beginning. Heterogeneity. {concave in some cases} Why in some cases faster than in others: WILL DETERMINE 3 MODELS - Diffusion of information, changing habits, hanging relationship > epidemiological, sociological studies - Relatedto economic factors: costs of production, inputs / price at which product sold, level of demand - Related to market structures & degree of entry in the market of new competitors (entry selection) Driving forces: 2 MODELS Imitation (sociological model): abandon old technology for new > Neoclassical models: - Key= inter firm and consumers’ diffusion - Problem=adoption of process innovations Selection (evolutionary models): innovator displace traditional firms: combines imitation x industry IvI diff Entry (life cycle models): entrant as innovator / entrants as imitators INFORMATION BASED MODEL: If people have information, they adopt 1.“Critical mass information”: earliest sociological models & diffusion marketing - Earliest: US agricultural studies (1930); Psychological and sociological explanation Key assumption: “innovation is immediately superior to old tech for all potential adopters” - Why not adopted immediately? Because not all potential adopters know about existence/performance - As soonas consumers access information they adopt-> decision depends on information availability Information sources: internal vs. external World of mouth: dissemination process: adopters communicate their experience to non adopters - Probability of catching information > if > number of adopters = X: = n° of infected people Variation of diffusion over time: dx/dt=Bx;(1 -x/2 XK +e)! Logistic curve: symmetric path log{x;/ (X*x,)/=a +fi R = constant of infectiousness (attractiveness of innovation) + diffusion speed These assumptions are responsible for S shape: x = time, y = x/X*, function = (1+e8)1 External source of information: - Continuous info provided by external agent (supplier, public institutions) - Probability of diffusion still increase even if there are not so many infected - Modified exponential positively skewed path > Shape of the curve reveals info source - Excessive simplification of the diffusion process: o Only2actors present (innovator and adopter) è no suppliers, competition; don’t change over time = Innovation not improved (no price changes) (=virus spread) = Individual characteristics of potential adopters (size) do not change & homogeneous demand o Lack of economic microeconomic foundations: = Inmanycases adoption = choice + must be explicitly modelled according to determinants = Economicvalue of innovation is assumed, not proved by any microeconomic model (technical superiority may not imply adoption profitability) = Diffusion lag not derived from individual adoption lags (as function of adoption profitability) è threshold models of adoption Key developments of information based theories. Adoption order: - First adopters: - How information passed on from early adopters to followers: 2° network o Everett Rogers: theory of information leadership and its distribution in society o James Coleman: network theory of influence 2.Network models: Network theory of influence: - Mostcentral actors = early adopters - Individual adoption speed as function of distance from central actors o Inbetween centrality: calculating looking at shortest path between # people - Diffusion speed as function of network density (if denser + shorter distances + quicker diffusion) Small world network theory: lower average distance + quicker diffusion Regular Small-world Random SLA SIR According to network > quicker or slower diffusion Mechanisms that allow people to find a job de. INCENTIVE BASED MODEL: Threshold model: basic microeconomic of adoption To understand precisely which are determinant of decisions to adopt For economic reasons early adoption is more convenient for certain categories / geographical regions Explains adoption lag (distribution over time) in terms of adoption decision Less (no) emphasis on information: - Diffusion need time NOT because info problems BUT because new tech not economically superior to old ones as soon they appear - Noinfo dissemination BUT process with changes in environment that make adoption profitable: o Changes in new technology: o Changes in adoption environment: Equilibrium models: at any time, all firms for which adoption was profitable have indeed adopted - Nonadopters are NOT ill informed BUT they're waiting to maximize profits - Adopters’ heterogeneity > # adoption lags > diffusion lag [heterogeneity respect size, dimension Key assumption: Paul David 1966, Olmstead and Rhode 1995 - a=L/S=input coefficient L=working hours Si= size of company & overall output (fixed) Innovation = same output BUT reduced amount of labour (L) - Innovation allows Lo-> Ln so Aan = (ao- an) ao = input coefficient of old machine; an= new input c. - Costofthe reaper is p = cost of adoption - Normally distributed (soil size) - Price of wheat andwages are NOT affected by innovation (false in long run) - Discounted benefits of adoption for the company are: (wLo — wLn)/ r=(w Aa Si)/r [discounted by r] o r= interest rate 1 Adoption conditions: w*Aa*S; > rp 3 Si Sr Sor = rp / wAa - Reapers diffusion driven by steady increase in wages in XIX century in US o Exogenous drive to diffusion - Diffusion takes time because of heterogeneous firms o Size has logarithmic distribution > at time x only some find adoption profitable - Diffusion path is sigmoid if heterogeneity source distribution is bell shaped & diffusion speed constant Dynamic elements that could explain adoption: play with Sr = rp / wAa - IfAaorwincrease > innovation more interesting Critical size: affected by events on the supply side of technology market (p, Aa) - What created decreasing price and increasing efficiency Learning by doing: on supply side may turn them {Diffusion (suppliers cumulate salesiexperience) |. into the endogenous drive to diffusion LbD: suppliers’ marginal t_ IR E MOI doi Incremental innovations - More diffusion > sell more cost (MC) decline improve the innovation Diffusion not granted: threshold models say: A performance a - Incomplete diffusion Market struclureàlfects speed . sarti of transmission A-MC Ap - Nokickoff situations How fast is diffusion: L {p1]® [Critical size 1: further diffusion |< - Given market structure on D side; matters suppliers’ speed in reducing Pinw or improving inn perform o Suppliers’ learning speed o S side market structure: suppliers’ speed in transferring A costs on Pinn - Key policy implication: adoption subsidies vs. info provision - Business strategy implications: early sales at loss (low Pinn) + kick off LbD - 2 theoretical problems of the model: o There are NO expectations: o Decreasing returns from adoption: more adoption + more competition downstream Expectations: adopters’ expectations of future decline of Pinn/ A* performance delay adoption beyond threshold day + diffusion slows down and possibly come to a halt - Virtuous cycle “LbD diffusion” breaks up: new technology remains marginal Business strategy implication: announces to slow down diffusion of rivals’ technologies Policy implications: public purchases to keep LbD going {evolutionary models. Biological variety and selection mechanisms. Focus on entry/exit patterns. Arthur’s model: Competing technologies and increasing returns to adoption - Tech complementarities, adoption patterns and lock in} - How2 technologies will share market depends on stochastic process underlying adopters’ choice - Share split 50 — 50 very unlikely Competing technologies: diffusion of innovation can be seen as competition: diffusion process connected - Between1old tech and a new one Standardization: comp. among # (incompatible) versions of new tech in competition - Only one of 2/more competing technologies takes entire market - Technical compatibility between users providers = key explanation for the phenomenon - Possible market failure; proprietary standards are key assets for business strategy Government intervention against lock in: Coordinating users’ choices on superior standards (if known) Maintaining technology variety to postpone process of lock in until become clear which technology will be optimal (alternative energy sources). Critique: interior technologies = waste Diffusion of patenting in universities > threats to open science? - Research ethics: decline of sharing culture (open science practices) - Increase in academic research cost / obstacles - Blocking patents/exclusive licensing hold up effects on down stream development, commercialization IP in science: becoming more closed: Distributional issues “socializing the risk but privatizing the rewards” GREEN INNOVATION: Aldo Geuna — eco innovation Sustainability: growth of GDP poses serious challenges to ecological sustainability: - Mostenvironmental problems are related to material consumption and disposal - Any reduction inthe consumption of materials helps sustainable development o Endof pipe treatment (consume, produce pollution, try to reduce pollution) vs. Bottom up approach (waste reduction, cleaner production) - Important differences in various bottom up approaches o Waste reduction>+energy conservation + material use efficiency o Cleaner production?technical change that reduce the emissions o Design for environment (DFE) > waste reduction by making products more repairable and recyclable = Circulareconomy Refurbished IT products/systems®win-win opportunity for value creation being environmentally friendly Gains from pollution prevention and waste reduction might be NOT profitable Radical dematerialization is not likely to happen. Economic growth will demand more &m material product Environmental innovation= “innovation that improves environmental performance of 1 economic activity” Eco innovation = “change in the economic activities that improves both the economic and the environmental performance of society” Eco innovations: “production, assimilation or exploitation of a product, production process, service, management or business method that is novel to the organisation and which results in a reduction of environmental risk, pollution & negative impacts of resources use compared to relevant alternatives.” - (Less environmentally harmful than the use of relevant alternatives) © Use fewer resources o Use less toxic material egizia ariani est o Beingless polluting through special or # process | È organisation Primarity o co-ordinate © Not relying on the use of fossil fuels 2 ee nta ai - Need for stimulating the innovation process ì a towards sustainable development È pi Firariy - Growth responsible: Technology, society, lifestyle, na technological change institutions (need to change to give example) Innovation process towards sustainable development: Modification —Re-design Alternatives Creation - Need for technological regime shifts Seo ncoaito metenere o Reduction of environmental impact canNOT occur through adaptation within existing technologies - Eco innovations bring benefits (reduced costs, increased competitiveness, creation of new markets, employment creation) 3 incentives at both Demand and Supply level - Technological change NOT enough (sustainability needs changes in lifestyles and institutions) Possibilities at the policy level: - European New Green Deal - Use on the Recovery Funds only for supporting eco innovation activities processes GREEN FOOD PACKAGING: “can be reused, recycled or downgraded without producing pollution” - Primary food packaging: all material used to protect and preserve food products for the final consumer - Secondary food packaging: material used to put together more food products for delivery and storing - Tertiary food packaging: pallets and wrappers to take food products People buy food in bags BUT at home changes wrap to preserve food Impact of food packaging: - Most food packaging designed to be single use and NOT recycled - Many of them contain coating and most packaging comes labelled with printer's ink ® not recyclable o Recycle ink dirt wrapping is very costly - Plastic transformed in micro and macro plastic gives polluted oceans and earth (in terms of geological indicators, plastic become distinctive stratal component of earth) o 0f78 million metric tons of plastic every year only 14% recycled Biodegradable: after certain time are decomposed (only under certain conditions) {not clearly regulated} Compostable: need to go into a compost stream to be effectively broken down (less than 3 months) - Ifthey go in normal bin problem: methane, not enough oxygen to break down Food waste: 1/3 of the food produced is wasted during production, distribution, by consumers - Italy: 2019 15 billions € of which 80% (12) for domestic waste Industrial characteristics: - Higher costs & problems in keeping food fresh - Lookgreen but it is NOT (green washing strategy) + problem of certifications - Consumers may say that green packaging is important but don't spend more for them Consumers awareness / willingness to pay: when directly asked only 16% agree with statement Biodegradable packaging market: almost only bioplastic, mainly food packaging Eco innovation: innovative food packaging: - Disappearing / eatable_ packaging - Intelligent packaging to reduce waste: problem: expiry dates overestimated o Bio sensors for humidity, gas, temperature, that assess how fresh the food is o Temperature and time indicators (chemically based) especially good for frozen food o RFID: radio frequency identification for tracing from production to consumption o Growing market but with significant problems due to diminished possibility of recycling Home culture (American: throw excess food) Beeswax wraps: no patent (not to reduce its diffusion), slow diffusion, more or less sustainable How do building affect natural resources: significant impact (responsible for 45% of waste) - Energy to heat and power from burning fossil fuels 3 1/3 of world's greenhouse gas emissions Green building: complement building design with concerns of economy, utility, durability “structure environmentally responsible and resource efficient throughout its life cycle” - To reduce overall impact on human health and on natural environment through building life cycle o Using energy, water, other resources more efficiently May use renewable energy resources, incorporate sustainable materials in their construction; create healthy indoor environments with minimal pollutants and feature landscaping and other systems that reduces water usage According to green building council is possible to save from 15 to 70% of consumption Photo voltaic: battery and auto: And wind turbine: need storage of the energy to be more effective (mayor boost thanks to tesla) - Intelligent local grid management, intelligent house and EV in the garage 2 views of green home: - Smart house: technology driven, home automation, PV and smart batteries, connected to smart greed - Eco house: environment/sustainability driven, local/recycled materials, low or no energy use, low water Certification: efficiency, sustainability... PassviveHaus: uses almost only passive appliances to produce energy needed to heat and cool down - Aimzero energy from the grid Barrier to green building: actual or perceived first costs, time, pay back period for additional cost