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Pakistan’s Urban Challenge   The Creative`City Model          Hilton Root         Andrew Crooks         Ammar Malik
Presentation Outline• The Urban Century• Role of Creativity in Urban Development• The Creative City Model• The Next Steps
Percentage of Urban Population by Size, 1960Source: UN Stats
Percentage of Urban Population by Size, 1980Source: UN Stats
Percentage of Urban Population by Size, 2011Source: UN Stats
Percentage of Urban Population by Size, 2025Source: UN Stats
Pakistan’s Population: Urban vs. Rural           300           250           200Millions           150           100      ...
Developing Country Megacities                              Population Growth Comparison           18           16         ...
Why Karachi?• A microcosm of Pakistan, representation of all ethnicities.• Home to 7.5 - 10 percent of Pakistan’s entire p...
Creativity & Urban Development
Insights from Literature• Individual or Social?• Creative ideas have “novelty, usefulness and surprise”  (Simonton 2012)• ...
New Urban Thinking• Density fosters human interactions, “the loci for  development” (Glaeser 2011)   o Environmental Effic...
Why use Agent-Based Models?
Simple Agent-Based ModelExample below demonstrates how traffic jams can formwithout any incident. Each car is an agent tha...
The Creative City Model
Model Purpose• An Urban Laboratory for asking what if questions and testing  policy ideas.• To Explain:   o The relationsh...
The Creative City Model• Scale   • City• Agent Attributes   •   Income   •   Tolerance   •   Neighborhood   •   Education•...
Model Features and Attributes  Environment           Individual Agents                                  Med               ...
Basic Model InterfaceInputs   Environment                  Outputs         http://malik.gmu.edu/Creativity
Typical Model Runhttp://malik.gmu.edu/Creativity
Model Outputs
Verification Process                  Segregation ON                                   Segregation OFF   Segregation OFF  ...
Status Quo Scenario                            3 Years   5 Years Key Outputs       Today                        10 Years L...
Preliminary Findings• Emergence of “celebrities”• Path Dependency in Creative Cluster formation• Tipping Points• Neighborh...
The Next Steps•   Apply verified theoretical model to Karachi•   GIS Integration with spatial economic data•   Income & Re...
Source: DemoBase Pakistan (http://egeoint.nrlssc.navy.mil/pakistan/)
Pakistan’s Urban Challenge   The Creative City Model              `
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Agent-Based Modeling Simulations for Solving Pakistan's Urban Challenges by Dr. Hilton Root and Mr. Ammar Malik,George Mason University, USA

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Presented on February 9th, 2013 at the Second Research Competitive Grants Conference in Islamabad, Pakistan.

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  • The larger project is titled the above, however specifically we’re looking at the issue of creativity in the urban sphere, trying to apply Richard Florida’s ideas on creative cities onto the case of Karachi, Pakistan. Therefore, we will discuss both urban development & creativity thinking.
  • - Throw statistics on Karachi’s population growth, mega city status and proportion of GDP of Pak
  • We took insights from leading urban creativity thinking & turned it into a model, we needed to build theory of creativity.
  • Creativity is either an individual level phenomenon or an outcome to social interactionsDefinition from social psychology helps.Anyone “lucky enough” to be utilizing creative problem solving at work belongs to the “creative class” (Florida 2002) – broad definition.Ed Glaeser’s work support Florida’s thinking, yet we’re
  • We obtained stylized facts from leading experts, then applied them combined with social complexity theory.The idea that the most prosperous cities are the most fun to live in, they promote culture & the arts etc.Idea of serendipity works when you let people meet outside of their usual networks
  • Talk initially about cities as complex systems, quote Batty & Simon, explain why cities are complex systems (whole more than sum of parts)Land Use Transport I models; Linear regression models
  • - ABM is a new modelling paradigm which allows us to explore the interaction of many individuals and how these individuals interact to form more aggregate phenomena. In essence there are two components for agent-based modelling that of the agent and the world that they inhabit. Ie the artificial world. What distinguishes these agents from other modelling approaches is that individuals are not centrally governed. They have their own rules therefore dictate their own behaviour, they are dynamic and interact with each other and their environment and are capable of modelling processes from the bottom up.Stress that each car is an agent.This application highlights how simple rules applied to many individuals (such as microscopic variables of acceleration and speed related to position) can lead to more macroscopic phenomena, Such models allow us to gain insights into urban phenomena. With this type of computer simulation, its open, its not a black box like traditional urban models. We know what is going on inside of these urban models
  • First step, building a theory of creative cities; Second step, operationalizing it with real-world Karachi.There’s no model of “creativity”
  • We’re interested in this technique due to its ability to project macro-level phenomenon from micro-level interactions between agents, i.e. interactions/decisions of individuals has impact on urban form & function, thus creative entrepreneurship. There’s no real creative city model in the literature, therefore we’re looking to build the theory of creative cities in developing world first, only then can be apply it to real world cities like Karachi, by combining social complexity theory with creativity thinking.
  • Darker shades of patches represent higher creativity values, gray are undevelopable, yellow are commercial, light pink are residential etc.Conceptual framework shows that Creativity depends on (a) Economic Factors – total income, distribution, rent affordability; (b) Rental Market – land-use regulation, transportation/access, segregation; (c) Human Capital – educational attainment, brain drain; (d) Urbanization – natural growth, migration.
  • Explain how agents move around, the notion of purpose in our model as well as interactions based on rents; settling in; transportation; segregation etc.
  • These outcomes show averages of 100 runs for 60 ticks, for checking that theoretical model runs as expected.This checks for the “internal validity” of the model, makes sure there’s no bug in the system, everything works in line w/ theory.While in depth experimentation will be done as next step, we’re going to show some basic correlations b/w variables; e.g. greater educational attainment leads to better income levels and eventually, more creative spaces.
  • Celebrities are defined as agents with more than 5 inspirational connections, thus they’re proactively entrepreneurial for others as well.Path dependency implies that current places with amenities will most likely be the top places for future, hence that’s a great finding.Time periods where things like creative spaces turn around, we need to explain them & see how policy interventions will turn them around.Neighborhood effects, or spillovers, happen right outside creative areas – key finding, but need to ensure they’re stronger.
  • There exists no creative city model so we had to develop it from the bottom up, taking stylized facts from Glaeser, Landry & Florida and combining them with social complexity theory for this theoretical model. We then verified this theoretical model, so now we’re satisfied that it makes sense internally. Later, we’ll apply this to Karachi’s spatial realities followed by validation, following which we’ll test policy scenarios, which we’re leaving for year 2.
  • The larger project is titled the above, however specifically we’re looking at the issue of creativity in the urban sphere, trying to apply Richard Florida’s ideas on creative cities onto the case of Karachi, Pakistan. Therefore, we will discuss both urban development & creativity thinking.
  • Transcript of "Agent-Based Modeling Simulations for Solving Pakistan's Urban Challenges by Dr. Hilton Root and Mr. Ammar Malik,George Mason University, USA"

    1. 1. Pakistan’s Urban Challenge The Creative`City Model Hilton Root Andrew Crooks Ammar Malik
    2. 2. Presentation Outline• The Urban Century• Role of Creativity in Urban Development• The Creative City Model• The Next Steps
    3. 3. Percentage of Urban Population by Size, 1960Source: UN Stats
    4. 4. Percentage of Urban Population by Size, 1980Source: UN Stats
    5. 5. Percentage of Urban Population by Size, 2011Source: UN Stats
    6. 6. Percentage of Urban Population by Size, 2025Source: UN Stats
    7. 7. Pakistan’s Population: Urban vs. Rural 300 250 200Millions 150 100 50 0 1951 1961 1972 1981 1990 2001 2010 2020 2030 Source: UN-Habitat (2008) Rural Urban
    8. 8. Developing Country Megacities Population Growth Comparison 18 16 14 12 CairoMillions 10 Beijing Jakarta 8 Delhi 6 Karachi 4 2 0 1970 1980 1990 2000 2010 Source: United Nations
    9. 9. Why Karachi?• A microcosm of Pakistan, representation of all ethnicities.• Home to 7.5 - 10 percent of Pakistan’s entire population, 11th largest city in the world (UN 2012)• Produces 20% of national GDP, 25% of national revenues, handles 95% of foreign trade, retains 45% of employment in large-scale manufacturing (ADB 2005)• Pakistan’s financial and banking hub: hosts 40% of all financial activity and 50% of bank deposits (KSDP 2007)
    10. 10. Creativity & Urban Development
    11. 11. Insights from Literature• Individual or Social?• Creative ideas have “novelty, usefulness and surprise” (Simonton 2012)• Richard Florida’s (2002) “Theory of Creative Class” o Creative workforce associated with prosperity o The 3Ts: Technology; Tolerance & Talent• Human Capital driving long-term economic growth (Barro 2001; Cohen and Soto 2007) o Creative Clusters in cities are formed by free flow of ideas (Andersson 1985)
    12. 12. New Urban Thinking• Density fosters human interactions, “the loci for development” (Glaeser 2011) o Environmental Efficiency o Education as the “most reliable predictor of urban growth” o Successful cities attract the poor; they thrive on diversity• Vibrant Urban Culture & Public Spaces (Landry 2000) o Cultural and physical amenities attract creative individuals• Jacobs (1961) “cities happen to be problems in organized complexity, like the life sciences” • “the whole is more than the sum of the parts” (Simon 1962) • Understanding the macro level from the individual level
    13. 13. Why use Agent-Based Models?
    14. 14. Simple Agent-Based ModelExample below demonstrates how traffic jams can formwithout any incident. Each car is an agent that follows asimple rule set: • If there’s a car close ahead, it slows down. • If there’s no car ahead, it speeds up.
    15. 15. The Creative City Model
    16. 16. Model Purpose• An Urban Laboratory for asking what if questions and testing policy ideas.• To Explain: o The relationship between land-use regulation and creativity. o When, where and how creative clusters emerge in cities.• To Test Policy Scenarios: o What if land-use zones are altered in favor of mixed land-use? o What if urban mobility or transportation costs change? o What if income inequality across households improves?
    17. 17. The Creative City Model• Scale • City• Agent Attributes • Income • Tolerance • Neighborhood • Education• Context • Karachi• Land Use • Zones • Creative Values
    18. 18. Model Features and Attributes Environment Individual Agents Med High Low Creativity LevelCreative Value Assigned at startBased on frequency ofvisits by medium and When an agent is “inspired”high creative agents by partnering with a high creative agent in a creativeOr based on creative- space, the agent can raise adensity levelRules and assumptions Interactions between agents and the environment
    19. 19. Basic Model InterfaceInputs Environment Outputs http://malik.gmu.edu/Creativity
    20. 20. Typical Model Runhttp://malik.gmu.edu/Creativity
    21. 21. Model Outputs
    22. 22. Verification Process Segregation ON Segregation OFF Segregation OFF Segregation ON Outputs Movement OFF Movement OFF Movement ON Movement ON Parameters (BASE) Percent 6 7 (+1) 9 (+3) 8 (+2)Highly Creative Percent 6 8.5 (+2.5) 11 (+5) 9 (+3)Creative Space Percent 32 38 (+6) 39 (+7) 35 (+3)University Edu. Average 45,200 51,165 (+13%) 55,210 (+22%) 52,013 (+15%) Income (Rs.) Percent 44 45 (+1) 46 (+2) 45 (+1)Affording Rent
    23. 23. Status Quo Scenario 3 Years 5 Years Key Outputs Today 10 Years Later 20 Years Later Later Later Percent 10 7 6 3 1Highly CreativeGini Coefficient 0.67 0.66 0.69 0.72 0.75 Percent 1.8 3.7 6 4.5 4.8Creative Space Percent 50 38 32 21 15University Edu. Average 37,000 41,165 45,200 55,013 60,394 Income (Rs.) Percent 46 45 44 43 45Affording Rent
    24. 24. Preliminary Findings• Emergence of “celebrities”• Path Dependency in Creative Cluster formation• Tipping Points• Neighborhood Effects or Externalities
    25. 25. The Next Steps• Apply verified theoretical model to Karachi• GIS Integration with spatial economic data• Income & Rents distribution from real-world data• Empirically grounded behavioral rules
    26. 26. Source: DemoBase Pakistan (http://egeoint.nrlssc.navy.mil/pakistan/)
    27. 27. Pakistan’s Urban Challenge The Creative City Model `
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