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Manchester Institute of Innovation Research (MIoIR) Foresight for ‘Beyond business as usual’ Team D: Alessandro Pinheiro (Brazil) Simone Ehrenberg-Silies (Germany) Annelie Eriksson Helmersdotter (Sweden) Kil Woo Lee (South Korea)
Pacific Egde High fertility, low economic growth ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Illustration of the scenario,  Peter 49, Hampsted ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Wang 46 and Lisa 42, children Bob and Sarah, Manchester ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Nora, 35, unemployed, 5 children, Newcastle ,[object Object],[object Object],[object Object],[object Object],[object Object]
Recommendations  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Core recommendations ,[object Object],[object Object],[object Object]
Model – an overview Growth of population Science & technology Demography Individuals mobility Economy Social factors
Model – a more detailed picture  Growth  of population Science & technique Mortality Immigration GDP growth Fertility Ageing Education Health Welfare state Regulations Climate change War & conflicts Strong beliefs in religion Emmigration
How we got there ,[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object]
Methodology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],2 3 4 5 6 1
Black Swans ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Drivers ranking ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Most unpredictable
Scenarios Economy + Economy - Environment/fertility - Environment/fertility + A B C D
Datacollection S Diet, Choice of work /workplace, demography, diseases etc statistics, psychological and working life science T Technical innovation, dispersion of techniques Innvation reserach and evaluations E Production and/or demand for special health products, ageing society ? And statistics E Chemical waste Need more resources Ecological footpring Innovation surveys, Interviews with experts, Document, research etc P IP laws, labour policy Interviews with gov repr, government bills etc, statistics on working sectors V Fear of discrimination, data protection Survey of individuals
Scenario B and D Senario B” Gold coast” Scenario  D ”Pacific edge” Increasing GDP Decreasing unemployment More tax for treasury More resources for S&T More immigration Elderly population Education resources Higher energy consumption Impact of pollution will increase Family values (individualism) Longevity High unemplyment, Low GDP, goverrnment budget constraints Less resources for S&T, education, healthcare etc.  Infant mortality is high, Childrens health situation, childrens products, greater demand for childrens healthcare Social tensions, possible segregation in society,  Low environment protection Xenophopbia, emphasis on security Constraints on cultural values, i.e. Family living Demand for creativity & flexibility in policy making.

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Foresight for ‘Beyond business as usual’

  • 1. Manchester Institute of Innovation Research (MIoIR) Foresight for ‘Beyond business as usual’ Team D: Alessandro Pinheiro (Brazil) Simone Ehrenberg-Silies (Germany) Annelie Eriksson Helmersdotter (Sweden) Kil Woo Lee (South Korea)
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8. Model – an overview Growth of population Science & technology Demography Individuals mobility Economy Social factors
  • 9. Model – a more detailed picture Growth of population Science & technique Mortality Immigration GDP growth Fertility Ageing Education Health Welfare state Regulations Climate change War & conflicts Strong beliefs in religion Emmigration
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15. Scenarios Economy + Economy - Environment/fertility - Environment/fertility + A B C D
  • 16. Datacollection S Diet, Choice of work /workplace, demography, diseases etc statistics, psychological and working life science T Technical innovation, dispersion of techniques Innvation reserach and evaluations E Production and/or demand for special health products, ageing society ? And statistics E Chemical waste Need more resources Ecological footpring Innovation surveys, Interviews with experts, Document, research etc P IP laws, labour policy Interviews with gov repr, government bills etc, statistics on working sectors V Fear of discrimination, data protection Survey of individuals
  • 17. Scenario B and D Senario B” Gold coast” Scenario D ”Pacific edge” Increasing GDP Decreasing unemployment More tax for treasury More resources for S&T More immigration Elderly population Education resources Higher energy consumption Impact of pollution will increase Family values (individualism) Longevity High unemplyment, Low GDP, goverrnment budget constraints Less resources for S&T, education, healthcare etc. Infant mortality is high, Childrens health situation, childrens products, greater demand for childrens healthcare Social tensions, possible segregation in society, Low environment protection Xenophopbia, emphasis on security Constraints on cultural values, i.e. Family living Demand for creativity & flexibility in policy making.