Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Dissertation Defense: Planning Support Systems for Spatial Planning Through Social Learning


Published on

Dissertation defense slides

Published in: Technology, Real Estate
  • Be the first to comment

Dissertation Defense: Planning Support Systems for Spatial Planning Through Social Learning

  1. 1. Planning Support Systems for Spatial PlanningThrough Social LearningRobert GoodspeedDissertation DefenseMIT Department of Urban Studies and PlanningMay 22, 2013Dissertation Committee:Professor Joseph Ferreira, Jr. (chair)Professor Annette M. KimProfessor Brent D. RyanFig. 5.3c
  2. 2. Introduction• Thank you to everyone who helped make this possible!• Figures and tables are labeled with their numbers fromthe dissertation.It is an exciting time for U.S. metropolitanspatial planning …2
  3. 3. Vignette: Salt Lake City, UtahPhoto: Flickr/arbyreed1990s 1999-presentPhoto: Flickr/Porchista• Adopted Envision Utah/Quality Growth Strategy• 40+ miles of new light rail, 50 stations• New TOD: Daybreak (4,000 acres, 10k people, 1 in 6new homes being sold in Utah, 70% walk to school)• 1970-1990, 65% population growth,38% growth in land area(Kolankiewicz and Beck 2001)3See Briggs (2008), Matheson (2011), and Scheer (2012)
  4. 4. New Planning Practices have Emerged …4Sacramento spatial planning workshop. Laptoprunning I-PLACE3S PSS. Photo: SACOG.Envision Utah planning workshop. Outputs fromparticipatory meetings analyzed in GIS to create twoalternative scenarios, subsequent meetings haveused PSS. Photo: Envision Utah.Weston Nursery: Sasaki developed and usedcomputer tool: “The software would do the scenario, soif you changed the density you get new numbers ...[helped people] argue about what it means, [develop] abit of a common language.”
  5. 5. … that Feature New Spatial Planning Support SystemsEnvisionTomorrowINDEX UrbanFootprintI-PLACE3SWhere?Across theU.S.30 states and6 countriesCaliforniaMetrosMetroSacramentoIllustrativeIndicators• Estimated Vehicle Miles Traveled / Greenhouse Gas Emissions• Impervious Surface• Housing Diversity / Affordability• Energy Use• Air QualityINDEX PlanBuilder Getting Started Guide505/200 59 June 2010Indicator maps are also accessed through the Indicator Results table by clicking the map icon in theright-side column.I-PLACE3S User Guide Chapter 8Page 90 Revised: 4/29/08Figure 108Select Mark Place Type from the command menu and then select the Place Type youd like tomark (Figure 109). Clicking on a polygon will mark all parcels that are contained within thepolygon with the Place Type you have selected.Figure 109For tool description see Chapter 3. 5
  6. 6. Research Motivation• Many forces at work in new spatial planning practice, myinterest is in the creation and implementation of specificspatial plans.• GIS and new planning support systems (PSS) are widespreadin professional practice (Grant, Rooney, and Assasie 2010; Condon, Cavensand Miller 2009; Hoglund 2011)• Time is ripe for close empirical examination of theseprocesses:• Opportunity to learn from and scrutinize professional techniques• Context to answer theoretical questions about planning & sociallearning• Provide useful insights at a time of rapid technological development• This dissertation is set in regional planning contexts but NOTabout regional planning as a whole – only one part of it.6
  7. 7. Overview1. Introduction2. Theories & Previous Research3. Hypotheses, Cases and Research Methodology4. Results5. Discussion & Topics for Future Research6. Conclusion7
  8. 8. 1. Introduction
  9. 9. The “oft-foretold revolution in computer-aidedplanning” has arrived!9Galveston, TexasCape Cod, Mass.Meridian, IdahoMedford, Mass.Sources: Medford (MAPC), Marshfield (author), allothers from CommunityViz case studiesSouth Holland, NetherlandsMarshfield, Mass.(Similar to Fig. 5.9)Klosterman (1997)
  10. 10. Theoretical Perspectives on PSS10GIS-based modeling systems used for:• Interactive Representation• Rule Extrapolation• Indicator Construction and CalculationUsed in specific sociocultural practices(spatial planning)Alternative theoretical perspectives:• Social Learning: Changes to factual knowledge, skills, attitudes, and emergence of newcollective understanding (Wenger 1998; Muro and Jeffrey 2008; Holden 2008).• Social choice: Planning primarily about trade-offs, interests and preferences pre-existing(Sager 2002; Arrow 1951).• Structured coercion: Elite manipulation or coercion (Peattie 1987; Arnstein 1969).
  11. 11. Theoretical ApproachArtifactsMethodsToolsBehavioralTheoriesSocial LearningPsychologyFraming TheoriesCollaborative PlanningPragmatismDiagram inspired by Allmendinger (2002)See Chapter 2 for full description of theoretical framework.“Design Research”March and Smith (1995)Hevner et al. (2004)Planning Support SystemsParticipatory GISLink learning & planning:• Frames (Schön and Rein 1994)• Institutions (e.g., Powell and Dimaggio 1991;Kim 2011) 11
  12. 12. Which scales?12Planning ProcessKnowledge InfrastructureInteractionOpportunitiesInteractionOpportunitiesIndividual interactionLongerScalesofSpace&TimeMicroMesoMacroAfter Edwards (2003)
  13. 13. 2. Theories and Previous Research
  14. 14. Previous Paradigms Do Not Fully DescribePlanning PracticeBurnham (1909);Calthorpe (2001)Kent (1964)Susskind (1987);Healey (1997)Davidoff (1965)Bartholomew andEwing (2008)14
  15. 15. Spatial planning combines communicative,instrumental, strategic, and value rationality.Albrecht (2004) 15
  16. 16. What is (Social) Learning?• Historical Views• Behaviorism (Skinner 1974)• Constructionism (Piaget 1963)• Psychological Social Learning (Bandura 1977)• Individual development in an environment (Vygotsky, from Rogoff 1990)• Phylogenic – slowly changing species history (genes)• Sociocultural – changing cultural history, artifacts & norms• Ontogenetic – Changes in individuals over their life history, such aschildhood or educational experiences• Microgenetic – “moment-to-moment learning by individuals” built onspecific genetic and sociocultural backgrounds.• “Social” perspectives emphasize the importance of social context inunderstanding individual development, and the emergence of uniquelysocial phenomenon like new understandings16
  17. 17. Social Learning Theories• Macro (Sociocultural)• Frames (Schön and Rein 1994) and Institutional Theory (e.g., Kim 2011, 2012;Powell and Dimaggio 1991)• Diffusion Theory (Rogers 2003)• Meso (Ontogenetic and collective)• Organizational Learning (single/double loop) (Argyris and Schön 1978, 1996)• Wenger (1998)• Micro (Microgenetic)• Wenger’s “social theory of learning” (1998)• Three infrastructures for design: imagination, alignment, and engagement• Design for learning:• participation/reification• designed/emergent• local/global• identification/negotiability17
  18. 18. Double-loop Learning Adds Detail ToCollaborative Planning TheoryArgyris and Schön (1996, 1978)18
  19. 19. Operationalizing LearningSingle Loop/”Factual” Learning• “I learned a great deal.”• Widespread use in education assessment, correlated with student stimulation (Holmes1971)Double Loop Learning• Five questions used to create a summative scale (Spector 1992)• Cronbach’s Alpha = 0.82 for all surveys, 0.86 for Austin workshops19Table 4.1
  20. 20. Categorizing Computation in Planning• Many possible ways to categorized models/tools: substance, technical or theoreticalapproach, complexity (e.g., Klosterman 2012; Klosterman and Pettit 2012; Landis 2011)• “Epistemic lifestyles” of climate modeling (Shackley 2001)• Study informed by studies in participatory GIS and modeling and GIS evaluation(Arciniegas, Janssen, and Rietveld 2012; Jones et al. 2009; Salter et al. 2009; Smith et al. 2012; Nyerges andAguirre 2011; Schively 2007; Van den Belt 2004; Cockerill, Tidwell, and Passell 2004)20Urban System Models Planning Support SystemsPrimary focusRepresent complexity ofurban systemPractical usefulness inplanning processAdvantages(selected)Capture interactions &emergent behavior ofcomplex systemsPractical, easier to understand&less data requiredDisadvantages(selected)High cost and complexityLimited topical scope, simplicitycan lead to misleading resultsExamples UrbanSim, SLEUTHCommunityViz, EnvisionTomorrowFor discussion see Chapter 3
  21. 21. 3. Hypotheses, Cases and Research Methodology
  22. 22. Research Questions & Hypotheses22Research Questions• Q1: How do spatial PSS contribute to social learning in participatory workshops, inlight of evolving technology and infrastructure?• Q2: What characteristics of the sociotechnical PSS process facilitate single loopand double loop learning?• Q3: How do metropolitan regions develop a sociotechnical infrastructure for sociallearning in spatial planning?Summary of HypothesesQ1 and Q2:• What type of workshops resulted in the greatest learning? How did PSS comparewith paper maps only? (1.1)• What factors of the workshop and participant backgrounds helped explain thislearning? (1.2, 1.3 2.1, 2.2)• What is the relationship between the two learning measures at the workshops?Are they complements or substitutes? (2.3)Q3:• What can we learn from applying Rogers’ theory of the diffusion of innovations orframe analysis to understand how PSS are developed?
  23. 23. Potential Cases• Boston• Hingham Master Plan• Marshfield Buildout andAlternative Futures Project• North Suburban PriorityMapping Project• Boston (BRA)• Fairmount-Indigo PlanningInitiative• Austin• Hutto• Dripping Springs• Elgin• Lockhart• Austin• Kansas City• State Avenue Corridor• North Oak• U.S. 40• Troost• Rock Island• Shawnee Mission/Metcalf• Others• Singapore• Tacoma, WA• East Tennessee• Central Arkansas• Provincetown, MA• North Kingstown, RI23
  24. 24. Final Cases• Boston• Hingham Master Plan• Marshfield Buildout andAlternative Futures Project• North Suburban PriorityMapping Project• Boston (BRA)• Fairmount-Indigo PlanningInitiative• Austin• Hutto• Dripping Springs• Elgin• Lockhart• Austin• Kansas City• State Avenue Corridor• North Oak• U.S. 40• Troost• Rock Island• Shawnee Mission/Metcalf• Others• Singapore• Tacoma, WA• East Tennessee• Central Arkansas• Provincetown, MA• North Kingstown, RI24
  25. 25. Cases25Fig. 4.1
  26. 26. Workshop Data Collection SummaryAdditional data sources:• Key informant interviews• Many internal documents/meetings• Two planner focus groupsTable 4.726
  27. 27. Case ContextsFig. 4.2327
  28. 28. AustinFig. 4.9Image: Tour Texas28
  29. 29. “Gateway to the hillcountry”“BBQ Capital of Texas”“Perfectly Situated”“Growing a QualityCommunity”See Fig. 4.11,4.13, 4.14, 4.16Austin29
  30. 30. BostonFig. 4.3 30
  31. 31. BostonSee Fig 4.4,4.21, 4.631Fig. 4.3
  32. 32. 4. Results
  33. 33. Which workshops had the most learning?33Table 5.3
  34. 34. Mediated PSSAustin Sustainable Places Project, Lockhart, TX (Fig. 5.3) 3434
  35. 35. Mediated PSS Workshop DynamicsDourish (2001)See Fig. 5.335
  36. 36. Austin Workshop Interaction Design36Mapdd dDevelopment TypeChipsDescriptiveIndicatorsProjectPlanExistingPlansExternalKnowledgeParticipantsDigitizerFig. 5.1
  37. 37. Interactive PSS37Fig. 5.5Fig. 5.8
  38. 38. Paper Map ExercisesUpham’s Corner Visioning Forum North Suburban Priority Mapping ProjectPublic ForumFig. 5.13Fig. 5.12Fig. 5.6Fig. 5.738
  39. 39. Does participant personality explain learning?Percentage ofParticipantsSensation Seeking(e.g., Zuckerman 1979)Goal Orientation(e.g., Locke andLatham 1990)Very strong preference(≈ 95th percentile) 84.1% 58.6%Moderate preference(≈ 50th percentile) 9.9% 21.2%Low Preference(< 50th percentile) 5.9% 20.2%Operationalization and percentile from Jackson’s Learning Styles Profilerinstrument (Jackson 2005). For integrated model see also O’Connor andJackson (2008) and Jackson (2008).Table 5.739
  40. 40. Participation, Identification, and Reification ofPSS and Learning Variables• Participation not strongly related with either type of learning; may alsoreflect the lack of participation in this project as a whole• Agreeing with the statements, “The computer tool reflects my uniqueissues and concerns” (identification) and “workshop participants felt freeto question the outputs from the computer tool” (reification) werepositively related to learning.40Table 5.8
  41. 41. Analyzing the Learning ContextSource: Wenger (1998: 237)Also:• Participant Self-Perception (Rogoff 1990; Lave and Wenger 1991)41
  42. 42. 42Fig. 5.6
  43. 43. 43Fig. 5.9
  44. 44. Model SummaryPositive Impact on DoubleLoop Index• Wenger’s model• Participant identity• Learning from modelfeedback (imagination)Negative Impact on DoubleLoop Index• Attend frequent meetings• 3D visual rendering(possibly)44Differences in model for Reported Learning:• Identity and previous meetings less important• Larger coefficients on PSS variables, smaller ondiscussion-related variables
  45. 45. Complements or substitutes?452.502.702.903.103.303.503.703.904.104.304.503.50 3.70 3.90 4.10 4.30 4.50 4.70ReportedLearningDouble Loop IndexReported learning and double-loop indexFig. 5.17
  46. 46. View Diversity and LearningFig. 5.1546
  47. 47. The Puzzle of Non-AdoptionKansas City Creating Sustainable Places:• HUD funding• Fregonese & Associates provided detailed, day-longtrainings to project planners on Envision Tomorrow• Original focus on new PSS has shifted to focus on“toolbox,” and only two of the corridors using it in anyway at all• Why?47
  48. 48. First Perspective: Diffusion of InnovationsRogers (2003) diffusion characteristics:• Relative advantage• Compatibility• Complexity• Trialability• ObservabilityTheory predicts slow adoptionHowever, poorly describes PSS – uniquely dependent oncontextual factors48Wikipedia Authors, “Diffusion of Innovations,” Last modified18 May 2013.
  49. 49. Second Perspective: Frames• Kansas City Planner: “If we were using it moreappropriately, none of us could perceive it could be handy that way.We saw a bunch of quantitative numbers … I didn’t realize it couldbe used in a visionary planning kind of way.”• Uncertain role for PSS in Focus Groups:• Provide factual inputs?• Help develop a “bit of a common language”?• “Make them think … allowed some questions to be asked”?• Reconcile “tradeoffs” and “competing values”?• Conclusion: Adoption requires professional reframing, one reasonPSS are adopted as part of a new planning paradigm (scenarioplanning)49
  50. 50. 5. Discussion, Recommendations, & Future Research
  51. 51. Discussion Issues• Demographics: Limited ability to explorerace, culture, class.• Gender: Qualitative evidence that highly genderedpatterns occurred for one table, facilitators helped avoidelsewhere• The Black Box: Two “errors,” only one detected, raiseimportant issues regarding trust and transparency51
  52. 52. Recommendations1. Planners should incorporate PSS into projects, focusingon their use to facilitate stakeholder dialog and learning.2. Metropolitan planning agencies should use projects todevelop PSS and broader IT capacity.3. Planning agencies should cultivate organizationallearning, including evaluating workshops and projects.4. Planning researchers should develop theoretical modelswhich acknowledge dimensions beyond communicativerationality5. Planning as a field needs sociotechnical research andresearch paradigms in planning (forthcoming article)52
  53. 53. Further ResearchDeveloped in Optional Slides:• Trust in PSS• Linking micro and macro• Analyzing PSS as sociotechnical infrastructures53
  54. 54. 6. Conclusions
  55. 55. Conclusions55A survey finds find very high reported learning and doubleloop index scores at workshops which use PSS. Designswhich use a mediated PSS have the highest learningoutcomes. Participant personality and planner identitypartly explains learning. Findings confirm thecommunicative planning paradigm, but with a framingtheory that adds additional dimensions.In these cases, participation in PSS development is notrelated to learning measures, but there must be highidentification and low reification of the PSS, translatingand testing Wenger’s theory in a new context.Qualitative evidence suggests that while “innovationcharacteristics” from conventional diffusion theory explainslow adoption, the durability of professional frames is amore nuanced explanation.
  56. 56. Thank you!Robert GoodspeedPhD CandidateMIT Department of Urban Studies and Planningrgoodspe at mit.eduFall 2013Assistant Professor of Urban PlanningA. Alfred Taubman College of Architecture and Urban PlanningUniversity of Michiganrgoodspe at umich.edu56
  57. 57. Works Cited (A-G)Albrechts, L. 2004. Strategic (spatial) planning reexamined. Environment and Planning B 31:743-758.Allmendinger, P. 2002. Towards a post-positivist typology of planning theory. Planning Theory 1 (1):77.Arciniegas, Gustavo, and Ron Janssen. 2012. Spatial decision support for collaborative land use planning workshops. Landscape and UrbanPlanning 107 (3):332-342.Arciniegas, Gustavo, Ron Janssen, and Piet Rietveld. 2012. Effectiveness of collaborative map-based decision support tools: Results of anexperiment. Environmental Modelling &amp; Software (0).Argyris, Chris, and Donald Schön. 1996. Organizational Learning II: Theory, Method, and Practice. New York: Addison-Wesley.Argyris, Chris, and Donald A. Schön. 1978. Organizational learning. 2 vols, Addison-Wesley OD series. Reading, Mass.: Addison-Wesley Pub.Co.Arnstein, Sherry R. 1969. A ladder of citizen participation. Journal of the American Planning Association 35 (4):216-224.Arrow, Kenneth Joseph. 1951. Social choice and individual values. New York: Wiley.Bandura, Albert. 1977. Social learning theory. Englewood Cliffs, N.J.: Prentice Hall.Bartholomew, K., and R. Ewing. 2008. Land use‚Äìtransportation scenarios and future vehicle travel and land consumption: a meta-analysis.Journal of the American Planning Association 75 (1):13-27.Briggs, Xavier de Souza. 2008. Democracy as problem solving : civic capacity in communities across the globe. Cambridge, Mass.: MIT Press.Calthorpe, Peter, and William B. Fulton. 2001. The regional city : planning for the end of sprawl. Washington, DC: Island Press.Clarke, Karen. 2006. Trust in technology : a socio-technical perspective, Computer supported cooperative work. Dordrecht: Springer.Condon, Patrick, Duncan Cavens, and Nicole Miller. 2009. Urban Planning Tools for Climate Change Mitigation. In Policy Focus Report.Cambridge: Lincoln Institute of Land Policy.Davidoff, P. 1965. Advocacy and pluralism in planning. Journal of the American Planning Association 31 (4):331-338.Dourish, Paul. 2001. Where the action is : the foundations of embodied interaction. Cambridge, Mass.: MIT Press.Edwards, P.N. 2003. Infrastructure and modernity: force, time, and social organization in the history of sociotechnical systems. In Modernity andtechnology, edited by T. J. Misa, P. Brey and A. Feenberg. Cambridge, Mass.: MIT Press.Grant, Michael, Kathleen Rooney, and Kojo Assasie. 2010. WA 4-55 Smart Growth and Climate Protection Policy Analysis, Task 3 -Assessment of Tools. ICF International, for U.S. EPA.Guhathakurta, S. 1999. Urban modeling and contemporary planning theory: Is there a common ground? Journal of Planning Education andResearch 18 (4):281-292.57
  58. 58. Works Cited (H-K)Healey, P. 1998. Building institutional capacity through collaborative approaches to urban planning. Environment and Planning A 30:1531-1546.Healey, Patsy. 1997. Collaborative planning : shaping places in fragmented societies. Vancouver: UBC Press.Hevner, A. R., S. T. March, J. Park, and S. Ram. 2004. Design science in Information Systems research. Mis Quarterly 28 (1):75-105.Hoglund, Mike. 2011. Memorandum to the Oregon Modeling Steering Committee on Climate Smart Communities Scenarios: Portland MetroGreenhouse Gas Scenario Planning (House Bill 2001) - Requirements & Technical Approach. Portland, OR: Metro.Holden, M. 2008. Social learning in planning: Seattles sustainable development codebooks. Progress in Planning 69 (1):1-40.Holmes, David S. 1971. The Teaching Assessment Blank: A Form for the Student Assessment of College Instructors. The Journal ofExperimental Education 39 (3):34-38.Jackson, C.J. 2008. Measurement Issues Concerning a Personality Model Spanning Temperament, Character, and Experience. In The SAGEHandbook of Personality Theory and Assessment, edited by G. Boyle, G. Matthews and D. Saklofske: SAGE Publications Ltd.Jackson, Chris. 2005. Learning Styles Profiler (LSP-iii).Jankowski, P., and T. Nyerges. 2003. Toward a framework for research on geographic information-supported participatory decision-making.URISA Journal 15 (1):9-17.Jankowski, Piotr, and Timothy L. Nyerges. 2001. Geographic information systems for group decision making : towards aparticipatory, geographic information science, Research monographs in GIS series. London ; New York: Taylor & Francis.Joerin, F., and A. Nembrini. 2005. Post-Experiment Evaluation of the Use of Geographic Information in a Public Participatory Process. URISAJournal 17 (1).Jones, N.A., P. Perez, T.G. Measham, G.J. Kelly, P. d’Aquino, K.A. Daniell, A. Dray, and N. Ferrand. 2009. Evaluating participatorymodeling: Developing a framework for cross-case analysis. Environmental management 44 (6):1180-1195.Kent, T. J. 1964. The urban general plan. San Francisco,: Chandler Pub. Co.Kim, A.M. 2011. Unimaginable Change. Journal of the American Planning Association 77 (4):328-337.Kim, Annette M. 2012. The Evolution of The Institutional Approach in Planning. In The Oxford Handbook of Urban Planning, edited by R. Craneand R. Weber: Oxford University Press.Kim, Annette Miae. 2008. Learning to be capitalists : entrepreneurs in Vietnams transition economy. New York: Oxford University Press.Klosterman, R. E. 2012. Simple and complex models. Environment and Planning B: Planning and Design 39 (1):1-6.Klosterman, R.E., and C.J. Pettit. 2012. An update on planning support systems. Environment and Planning B: Planning and Design 32 (4):477-484.Klosterman, Richard E. 1997. Planning Support Systems: A New Perspective on Computer-Aided Planning. Journal of Planning Education andResearch 17 (1):45-54.Kolankiewicz, Leon, and Roy Beck. 2001. Weighing sprawl factors in large US cities. Washington, DC: NumbersUSA. com.58
  59. 59. Works Cited (L-S)Landis, J.D. 2011. Urban Growth Models: State of the Art and Prospects. In Global urbanization, edited by E. L. Birch and S. M. Wachter.Philadelphia: University of Pennsylvania Press.Lave, Jean, and Etienne Wenger. 1991. Situated learning : legitimate peripheral participation, Learning in doing. Cambridge England ; NewYork: Cambridge University Press.Lewis, J. David, and Andrew Weigert. 1985. Trust as a Social Reality. Social Forces 63 (4):967-985.Lewis, J. David, and Andrew J. Weigert. 2012. The Social Dynamics of Trust: Theoretical and Empirical Research, 1985-2012. Social Forces 91(1):25-31.March, S. T., and G. F. Smith. 1995. Design and Natural-Science Research on Information Technology. Decision Support Systems 15 (4):251-266.Matheson, Alan, Jr. 2011. Envision Utah: Building Communities on Values. In Regional Planning for a Sustainable America, edited by C. K.Montgomery. New Brunsick, New Jersey: Rutgers University Press.Merrill, Fred, Elaine Lazarus, Steven Zieff, and Joe Markey. 2011. Smart Growth in Action: The Legacy Farm Story, Hopkinton, MA.Muro, M., and P. Jeffrey. 2008. A critical review of the theory and application of social learning in participatory natural resource managementprocesses. Journal of Environmental Planning and Management 51 (3):325-344.Nyerges, Timothy, and Robert W. Aguirre. 2011. Public Participation in Analytic-Deliberative Decision Making: Evaluating a Large-Group OnlineField Experiment. Annals of the Association of American Geographers 101 (3):561-586.OConnor, Peter J., and Chris Jackson. 2008. Learning To Be Saints or Sinners: The Indirect Pathway From Sensation Seeking to BehaviorThrough Mastery Orientation. Journal of Personality 76 (4):733-752.Peattie, Lisa Redfield. 1987. Planning: Rethinking Ciudad Guayana. Ann Arbor: University of Michigan Press.Piaget, Jean. 1963. The origins of intelligence in children, Norton library. New York: W.W. Norton.Powell, Walter W., and Paul DiMaggio. 1991. The New institutionalism in organizational analysis. Chicago: University of Chicago Press.Rogers, Everett M. 2003. Diffusion of innovations. 5th ed. New York: Free Press.Rogoff, Barbara. 1990. Apprenticeship in thinking : cognitive development in social context. New York: Oxford University Press.Ryan, BD. 2006. Incomplete and incremental plan implementation in Downtown Providence, Rhode Island, 1960-2000. Journal of PlanningHistory 5 (1):35.59
  60. 60. Works Cited S-WSager, T. 2002. Democratic planning and social choice dilemmas : prelude to institutional planning theory. Aldershot, Hampshire, England ;Burlington, VT: Ashgate.Salter, J.D., C. Campbell, M. Journeay, and S.R.J. Sheppard. 2009. The digital workshop: Exploring the use of interactive and immersivevisualisation tools in participatory planning. Journal of environmental management 90 (6):2090-2101.Scheer, Brenda. 2012. The Utah Model: Lessons for Regional Planning. Brookings Mountain WestUniversity of Nevada Las Vegas.Schön, Donald A., and Martin Rein. 1994. Frame reflection : toward the resolution of intractable policy controversies. New York: BasicBooks.Shackley, S. 2001. Epistemic lifestyles in climate change modeling. Changing the atmosphere: Expert knowledge and environmentalgovernance:107-33.Skinner, B. F. 1974. About behaviorism. [Book Club ed. New York: Knopf.Smith, Eric Legge, Ian D. Bishop, Kathryn J. H. Williams, and Rebecca M. Ford. 2012. Scenario Chooser: An interactive approach to elicitingpublic landscape preferences. Landscape and Urban Planning (0).Spector, Paul E. 1992. Summated rating scale construction : an introduction, Sage university papers series Quantitative applications in thesocial sciences. Newbury Park, Calif.: Sage Publications.Stone, C.N. 2001. Civic capacity and urban education. Urban Affairs Review 36 (5):595-619.Susskind, Lawrence, and Jeffrey L. Cruikshank. 1987. Breaking the impasse : consensual approaches to resolving public disputes. New York:Basic Books.Weigert, Andrew J. 2011. Pragmatic trust in a world of strangers: trustworthy actions. Comparative Sociology 10 (3):321-336.Wenger, Etienne. 1998. Communities of practice : learning, meaning, and identity, Learning in doing. Cambridge, U.K. ; New York, N.Y.:Cambridge University Press.60