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d efining critical success factors in TOD implementation using rough set analysis

d efining critical success factors in TOD implementation using rough set analysis. Ren Thomas, Postdoctoral Researcher, University of Amsterdam Luca Bertolini , Professor, University of Amsterdam. iTOD. Study funded by NWO/National Organization for Scientific Research. Project 1

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d efining critical success factors in TOD implementation using rough set analysis

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  1. defining critical success factors in TOD implementation using rough set analysis Ren Thomas, Postdoctoral Researcher, University of Amsterdam Luca Bertolini, Professor, University of Amsterdam

  2. iTOD • Study funded by NWO/National Organization for Scientific Research Project 1 policies, practices, institutions University of Amsterdam Project 2 financial tools and arrangements Radboud University Project 3 urban design, knowledge and policy transfer Technical University of Delft

  3. methodology • Phase 1 (July 2012-July 2013) meta-analysis (meta-matrix and rough set analysis) to determine which policies, practices, and institutions are most influential in TOD implementation • What can we learn from other contexts? • Phase 2 (July 2013-July 2014) workshops with Dutch planners to determine which of these could work in The Netherlands • Can we learn from other contexts, e.g. are policy ideas transferable, how are they transferred and to what end?

  4. our definition of TOD TOD can be described as land use and transportation planning that makes walking, cycling, and transit use convenient and desirable, and that maximizes the efficiency of existing transit services by focusing development around transit stations, stops, and exchanges. TOD can be seen as part of a broader approach to urban development. Successful TOD can be defined as implementation of this type of development at a regional scale.

  5. meta-analysis We used in-depth case studies todeterminecriticalsuccessfactors: 11 case city-regions

  6. critical success factors IMPLEMENTATION • Use of site-specific planning tools (FAR bonuses, leasing of air rights, density targets) • Corridor-level planning • Certainty for developers • Willingness to experiment • Degree of implementation PLANS AND POLICIES • Consistency in planning policy supporting TOD over time • Vision stability • Support of higher levels of government • Political stability: national • Political stability: local ACTORS • Relationships between actors • Presence of a regional transport-land use planning body • Level of competition among municipalities • Presence of interdisciplinary teams • Public participation • Public acceptance • Presence of key visionaries

  7. performancemeasures • CONVENIENCE AND DESIRABILITY Overall convenience and desirability of walking, cycling, and public transit • MODAL SPLIT Modal split for cycling, walking, and public transit in the city and region • SCALE OF IMPLEMENTATION Scale of implementation of TOD across the city-region • EFFICIENT INFRASTRUCTURE Maximization of efficiency in existing transit services (concentration of development at stations and in corridors) • OVERALL SUCCESS Aggregate measure

  8. local expert feedback • Local expert questions prevented ‘insider bias’ of researchers/grounded the meta-analysis with in-depth knowledge of local planners

  9. codified data matrix

  10. rough set analysis • Using ROSE2 software, we applied a RSA to the codified data matrix • RSA extracts characteristic patterns from the data, determines decision rules, and evaluates the rules using validation techniques • Decision rules are conditional statements, specifying the conditions under which the statements are valid • Our goal was discovery rather than categorization, so we extracted the satisfactory descriptive set of rules: 75% strength and 3 length, generates the fewest and strongest rules • A total of 20 rules were found

  11. a3. IF Political Stability (Local)=4 THEN Overall Success=4 e2. IF Government Support=3 AND Willingness to Experiment=4 THEN Modal Split=2 (26-35%)

  12. rough set analysis • The CSFs with the highest frequencies in the decision rules are: • Political stability (national) • Actor relationships • Regional land use-transportation body • Interdisciplinary implementation teams • Public participation

  13. observations • Absence of very high or very low values for the decision attributes • But, number and strength of rules was similar to other studies (e.g. Nijkamp et al 2002, Walter and Scholtz 2007) • Evidently, a lot can be learned from “imperfect” success, or even failure, in TOD implementation

  14. conclusions • Meta-analysis provides planners with a way to develop more generalizable and reliable findings from case studies • There are generalizable cross-case patterns among international TOD cases: 16 CSFs or transferable lessons were tested and assessed for each city-region, resulting a set of values that could be used in RSA • RSA has revealed which combinations of CSFs were used in the case city-regions • In Phase 2 we used these results in workshops to determine how Dutch planners might use these policy lessons (e.g. inspiration, learning)

  15. rae.thomas@gmail.com www.renthomas.ca l.bertolini@uva.nl

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