The Effects of Innovation Characteristics, Country Characteristics and Context on International Diffusion of Multi-generation Cellular Mobile Phone Adoption Towhidul Islam University of Guelph, Canada and Nigel Meade Imperial College, University of London, UK

International Diffusion of Multi-generation Cellular Mobile Phone Adoption Diffusion of technological innovation occurs at different rates in different countries –For cellular telephones –Austrians took 12 years to achieve 5% penetration –Australians took 8 years for to achieve the same penetration Insights into the causes of the differences in national diffusion patterns are valuable – relevant questions: –What is the market potential for this innovation in this country? –How long will it take to reach 50% (say) of the market potential? –If my company enters the market in several countries, what is the optimal sequencing of its product launches?

International Diffusion of Multi-generation Cellular Mobile Phone Adoption Our modeling approach answers these questions for the cellular telephone market by combining: Diffusion model Bass (1969) Multi – Generation Norton & Bass (1982) –exploitation of the generational nature of this technology –launch of the first analog telephones was in 1980 –launch of digital was in 1992 International eg Gatignon et al (1989) –The information set for model estimation includes country specific data, economic, cultural, geographical countries’ adoption of the preceding generation of technology.

Outline Review and Hypotheses Data Description Model Analysis Comparative Forecasting Accuracy Conclusions and Implications

Cumulative Non- Cumulative Sample Data: Australia Analog Digital Analog Digital

Review and Hypotheses - 1 Generalised Bass model Bass et al (1994): –Probability density of an adopter adopting at time t –Coefficient of Innovation – Coefficient of Imitation – Marketing factor –There are m potential adopters ( m = Market potential)

Review and Hypotheses - 2 Hypotheses related to cellular telephones –Connection charge has negative effect on Market Potential Marketing Factor –Main telephones/capita has negative effect on Coefficients of imitation for analog and digital –Coefficient of innovation is constant over generations Price Effect Measured as % of GDP Substitution Effect Why get a mobile if I have a fixed line? Early generations suffer from bugs => p decreases Later generation has more goodies => p increases

Review and Hypotheses - 3 Hypotheses related to the Country –Wealth has positive effect on Market Potential Coefficients of innovation and imitation –Media Density has positive effect on Coefficients of innovation for analog and digital –Mobility has positive effect on Coefficient of imitation –Economic and population heterogeneity has negative effect on Coefficients of imitation and market potential Measured by GDP/capita & growth in GDP Measured by newspapers & TVs per capita Mobility fosters imitation Differences impede diffusion

Review and Hypotheses - 4 More hypotheses related to the Country –% of women in work force has positive effect on Coefficients of imitation –Innovativeness has positive effect on Coefficients of innovation for analog and digital –Geography affects Coefficient of innovation and imitation Increased social interaction fosters diffusion Measured by patents and % of R&D workers Regional learning effect?

Review and Hypotheses - 5 Hypotheses related to the Country Context –Individualism (+ve); Power-Distance (-ve) Uncertainty Avoidance (-ve) Political Rights (-ve) affect Coefficients of innovation –High Context culture has positive effect on Coefficients of imitation for analog and digital –Lag in introduction of technology positively affects Coefficient of imitation Deference & risk averseness decrease diffusion Japan more imitative than UK/US Countries learn from earlier adopters

Network Externalities Direct and Indirect Network Externalities: Measurement Issues and Models Do cellular telephones exhibit a direct network effect? Mahler and Rogers (1999) – do not face externality problem We expect to see evidence of critical mass or externality in the diffusion of analog cellular phones in developing countries Does a model’s forecasting accuracy improve, if direct network effects are taken into consideration? Review and Hypotheses - 6

Diffusion of an Interactive Technology First Purchase Sales Time

Data Description 1 Countries categorised by –Economic sector High, Upper Middle, Lower Middle, Low Income –Geographical Sector Asia and Pacific; Europe, North America and Oceania; Eastern Europe and Central Asia; Middle East and North Africa; Sub-Saharan Africa; Latin America and Caribbean

Data Description 2 Wealth Related Access to and availability of Information Mobility Economic Heterogeneity Population Heterogeneity Demographics Innovativeness Culture Political / Country Risk Fixed Telephone Infrastructure Price

Model 1 Parameterization g – generation c – country t - time Constrained to be Positive Could be negative Negative word of mouth effects

Model 2 Expected cumulative adoption of analog cellular telephones Expected cumulative adoption of digital cellular telephones Erosion due to introduction of Digital Increased potential due to analog owners changing to Digital Analog market potential Incremental digital market potential

Model 3 Taking expected adoptions per period: –New analog adoptions at time t –New digital adoptions at time t

Model 4 Error variance assumptions –Generalisation of binomial assumption –Example for first generation (analog) –We found λ = 2 (λ = 1 for binomial) Objective function (maximum likelihood) Normal density function

Analysis 1 Coefficient of Innovation Positive effects –No of researchers in R&D, no of patents –Uncertainty Avoidance No effect –Newspaper readership –Individualism Negative effect –Power distance, political rights –TV ownership Contrary to expectations

Analysis 2 - Coefficient of Innovation Mean of is low compared with mean of 0.03 found by Sultan, Farley and Lehman (1990) in their meta-analysis of 213 applications.

Analysis 3 Coefficient of Imitation Positive effects –Wealth, women in the labour force, mobility –Lagged introduction –Gini Index No effect –High context culture –Population heterogeneity Negative effect –No of fixed lines Contrary to expectations

Analysis 4 - Coefficient of Imitation Box plots by Economic Sector Analog Digital

Analysis 5 Market potential Positive effects –Wealth, (economic sector membership) –Gini Index No effect –High context culture –Population heterogeneity Negative effect –Connection charge –Economic Risk Contrary to expectations

Analysis 6 - Total Market potential Market potential (per 1000 people) for lower middle income sector Is 35% greater than for low income sector

Comparative Forecasting Accuracy 1 Examples of Model Fit Data: solid line Forecast: dashed Analog: lower lines Digital: upper lines

Comparative Forecasting Accuracy 2 Benchmark – Univariate Bass model fitted by country No better than univariate Comparative accuracy improves with horizon

Network Externalities: Measurement Issues and Models Sales Takeoff Times (Tellis, Stremersch and Yin 2005: Marketing Science) Logistic Hazard Model Gamma-Shifted Gompertz Model Bemmaor and Lee 2002: Marketing Science

Analysis: Sales Takeoff Times

Network Externalities: Covariate Effects Covariates –Economic Regions –Cultural variable Control Variables –Geographical Regions –Lag Introduction Times

Analysis: Sales Takeoff Times

Analysis: Skew Coefficient Estimation of skew coefficients (α )

Forecasting Performance Horizon12345 Country Skew/Bass Covariate Skew/ Bass Geometric mean of the ratio of root mean square errors for the country skew models and the covariate skew models with the root mean square of the Bass model for combined analog and digital adoption. Forecasts were computed for one to five year horizons using data up to 1997 to 2001.

Conclusions and Implications Implications for firms –Model can answer: What is the market potential in country A? What is the likely path to this market potential? In what sequence should these markets be entered? –Model could be used normatively Eg introduce digital in 1, 2, 3 etc years time Implications for Research –Findings are replicable, realistic and the model’s predictive validity has been established –Explicit modelling of variance