《技术创新管理》课程教学课件（英文）Diffusion and Adoption of Innovations

Masters Course: Innovation SciencesDiffusion and Adoption of InnovationsDr.MScBertSadowskiTechnischeUniversiteitTUeEindhovenUniversity of TechnologyWhereinnovationstarts

Diffusion and Adoption of Innovations Dr. MSc Bert Sadowski Masters Course: Innovation Sciences

StructureDifferentmodelsof diffusion ofinnovationDiffusionofinnovationandnetworkeffectsTherole ofactive users in diffusionof innovationsTowards a different model of diffusion of innovationsTechnischeUniversiteitTUEindhoveneUniversityofTechnologyPAGE1EconomicsofInnovation201310/3/2013

Structure • Different models of diffusion of innovation • Diffusion of innovation and network effects • The role of active users in diffusion of innovations • Towards a different model of diffusion of innovations Economics of Innovation 2013 10/3/2013 PAGE 1

Demand-SideModelsofDiffusionof InnovationTechnischeUniversiteitTUEindhoveneUniversity of Technology10/3/2013PAGE2EconomicsofInnovation2013

Demand-Side Models of Diffusion of Innovation Economics of Innovation 2013 10/3/2013 PAGE 2

Use oftheEconomics of DiffusionofInnovationDisciplineUsageExample(s)MarketingHowinformation and acceptanceofLooking for newchannels e.g.Viralsnewproducts is spread throughthemarketGuerilla marketingForecastingChange towards moreAttempts to predict the futurecharacteristics ofusefulenvironmentalfriendlytechnologies,productstechnologies(electriccars)PsychologyE-HealthtechnologiesWhatarethedeterminantsofindividualuserto acceptnewtechnologiesSociologyWhy do different groups of usersIdentifying different useradopt differently technologygroups (earlyadoptersEconomicsIncentives structures ofadoptionImpact of differentmarket structures onadoption10/3/2013PAGE3EconomicsofInnovation2013

Use of the Economics of Diffusion of Innovation Discipline Usage Example(s) Marketing How information and acceptance of new products is spread through the market Looking for new channels e.g. Virals, Guerilla marketing Forecasting Attempts to predict the future characteristics of useful technologies, products Change towards more environmental friendly technologies (electric cars) Psychology What are the determinants of individual user to accept new technologies E-Health technologies Sociology Why do different groups of users adopt differently technology Identifying different user groups (early adopters Economics Incentives structures of adoption Impact of different market structures on adoption Economics of Innovation 2013 10/3/2013 PAGE 3

Used invariety of contextsDifferent levels ofanalysis:Consumer oriented innovationFirmorientedinnovationMarketorientedinnovationInfrastructure oriented innovationTechnischeUniversiteitTUEindhoveneUniversity of Technology10/3/2013PAGE4EconomicsofInnovation2013

Used in variety of contexts • Different levels of analysis: • Consumer oriented innovation • Firm oriented innovation • Market oriented innovation • Infrastructure oriented innovation Economics of Innovation 2013 10/3/2013 PAGE 4

DiffusionmodelsEpidemicmodelsofdiffusion(e.g.Bass,1969)Analysisofspreadofdiseases·Assumption:DiffusionresultsfromthespreadofinformationEconomic(Rank)ModelofDiffusionEffectsofpricesand/orcostsondecisionDifferencesbetween individuals(consumergoods)andfirms (intermediate inputs)Differentassumptions:Informationsearchcosts,differences in households and firms (e.g.income/capitalstock)Technische UniversiteitTUEindhoven-UniversityofTechnology10/3/2013PAGE5EconomicsofInnovation2013

Diffusion models • Epidemic models of diffusion (e.g. Bass, 1969): Analysis of spread of diseases • Assumption: Diffusion results from the spread of information • Economic (Rank) Model of Diffusion • Effects of prices and/or costs on decision • Differences between individuals (consumer goods) and firms (intermediate inputs) • Different assumptions: Information search costs, differences in households and firms (e.g. income/capital stock) Economics of Innovation 2013 10/3/2013 PAGE 5

Epidemicmodels(e.g.Bass,1969)m, / n=1/(1+exp-(α+βt))e.g.examining spreadingVariables:van diseasesmt-usersattimetModel:n-non-usersα -constantof integration(e.g. contact)0000β-constantofinfection000999555000560000565000570000575000TechnischeUniversiteitTUEindhovenJUniversity of Technology10/3/2013PAGE6EconomicsofInnovation2013

Epidemic models (e.g. Bass, 1969) Variables: mt – users at time t n – non-users α - constant of integration (e.g. contact) β – constant of infection Economics of Innovation 2013 10/3/2013 PAGE 6 / 1/(1 exp ( )) t m n t       e.g. examining spreading van diseases Model:

Epidemic models:Adoption curve100%S- ShapedDiffusion CurveRateofadoptioneInflectionpointAfterachieving criticalmass, growthCritical Massbecomesself-sustained0Technische UniversiteittimeTUEindhoveneUniversity of Technology10/3/2013PAGE7EconomicsofInnovation2013

Epidemic models: Adoption curve Economics of Innovation 2013 10/3/2013 PAGE 7 100% 0 time Critical Mass Inflection point S- Shaped Diffusion Curve After achieving critical mass, growth becomes self￾sustained Percentage of Adoption Rate of adoption

AssumptionsofepidemicmodelsineconomicsPopulationof potentialadoptershomogeneousandconstantovertimeNatureoftechnologyisnotchangingovertime·Profitability of adoption may change along diffusionpathIgnoreexternalinformationsourcesEndlevel ofuseofthenewtechnologyDemandsidemodels(noeffectsofsupplyside)>>>supply-sideextensionsTechnischeUniversiteitTUEindhovenUniversityofTechnologyPAGE8EconomicsofInnovation201310/3/2013

Assumptions of epidemic models in economics • Population of potential adopters homogeneous and constant over time • Nature of technology is not changing over time • Profitability of adoption may change along diffusion path • Ignore external information sources • End level of use of the new technology • Demand side models (no effects of supply side) >>> supply-side extensions Economics of Innovation 2013 10/3/2013 PAGE 8

Epidemic models:ExampleDigitalizationLeaders: Sweden, GBDigitalizationof Telephone Network in someEULaggards: CzechCountries(1980-2008)Republic and Hungary100HighGrowthRates in90the1990sforlaggards8070CZE60WhatdeterminesHUN50differentgrowthrates?SWE40GBR30EU212010198019821984198619881990199219941996199820002002200420062008Data:ITU2010TechnischeUniversiteitTUEindhovenUniversityof TechnologyPAGE9EconomicsofInnovation201310/3/2013

Epidemic models: Example Digitalization Economics of Innovation 2013 10/3/2013 PAGE 9 Leaders: Sweden, GB Laggards: Czech Republic and Hungary High Growth Rates in the 1990s for laggards What determines different growth rates? Data: ITU 2010