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

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

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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 - PowerPoint PPT Presentation

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Page 1: 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

defining critical success factors in TOD implementation using rough set analysis

Page 2: d efining critical success factors in TOD implementation using rough set analysis

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

Page 3: d efining critical success factors in TOD implementation using rough set analysis

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?

Page 4: d efining critical success factors in TOD implementation using rough set analysis

our definition of TODTOD 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.

Page 5: d efining critical success factors in TOD implementation using rough set analysis

We used in-depth case studies to

determine critical success factors: 11

case city-regions

meta-analysis

Page 6: d efining critical success factors in TOD implementation using rough set analysis

PLANS AND POLICIES

1. Consistency in planning policy supporting TOD over time

2. Vision stability

3. Support of higher levels of government

4. Political stability: national

5. Political stability: local

ACTORS

5. Relationships between actors

6. Presence of a regional transport-land use planning body

7. Level of competition among municipalities

8. Presence of interdisciplinary teams

9. Public participation

10.Public acceptance

11. Presence of key visionaries

IMPLEMENTATION

12.Use of site-specific planning tools (FAR bonuses, leasing of air rights, density targets)

13.Corridor-level planning

14.Certainty for developers

15.Willingness to experiment

16.Degree of implementation

critical success factors

Page 7: d efining critical success factors in TOD implementation using rough set analysis

performance measures

• 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

Page 8: d efining critical success factors in TOD implementation using rough set analysis

local expert feedback

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

Page 9: d efining critical success factors in TOD implementation using rough set analysis

codified data matrix

Page 10: d efining critical success factors in TOD implementation using rough set analysis

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

Page 11: d efining critical success factors in TOD implementation using rough set analysis

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

Page 12: d efining critical success factors in TOD implementation using rough set analysis

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

Page 13: d efining critical success factors in TOD implementation using rough set analysis

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

Page 14: d efining critical success factors in TOD implementation using rough set analysis

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)

Page 15: d efining critical success factors in TOD implementation using rough set analysis

[email protected]

www.renthomas.ca

[email protected]