cognitive rationality, public engagement and quantitative

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MULTITUDE Final Conference, Naples December 4th, 2013

Cognitive Rationality,

Public Engagement and

Quantitative Analyses in

Transportation Decision-Making

Prof. Ennio Cascetta

Università degli Studi di Napoli Federico II

Dipartimento di Ingegneria dei Trasporti “L. Tocchetti”

Cognitive Rationality, Public Engagement and Quantitative Analyses in Transportation Decision-Making

Naples, December 4th, 2013

Decisions related to transportation systems, made by both public and private subjects are difficult to make Decisions impact on diverse and contrasting interests

The complexity of the legal procedures and the fragmentation of the

decision-makers system make them time-consuming and non-efficient

Decision on transportation systems often capture the public attention

Often, decisions on transportation systems do not perform as expected

background

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Main causes

1. Unpredictable events modifying the scenario (deep uncertainty) Economic crisis 2008-2013, 9/11, oil prices, local changes,

unexpected market behaviour

2. Mistakes in forecasting times, costs and effects Implementation times and costsTraffic, revenues, costs,

pollution, etc.

3. Inability to implement the project as intended Protests against new infrastructures/services/fares, etc.

Failures in decision-making processes

PLANNING FAILURES

background



TRADITIONAL APPROACHES TOWARDS DECISION-MAKING IN TRANSPORTATION PLANNING

The decision-making process has some form of “rationality” and quantitative tools, i.e. statistical analyses and mathematical models, play a central role in it, contributing to define the decisions or at least influencing them. (Manheim, 1979; Meyer and Miller, 2001; Ortuzar and Willumsen, 2011; Cascetta, 2009) Transport system analysis and transportation planning are seen mostly as public-oriented activities, based on the simulation of alternative projects and the assessment of priorities.

…but this is often not the case

background

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1

outline

Models of decision-making processes

Public Engagement

Quantitative Analyses and

their roles in decision-making

Some indications for quantitative analyses from the new persepctive

3

4

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CLASSIFICATION

A-RATIONAL models

RATIONAL models

A sequence of activities performed by several actors (decision-makers and possibly stakeholders) in order to decide on options including not deciding (delaying)

TRANSPORT-RELATED DECISION-MAKING PROCESS

1. models of decision-making processes

Lectio_02_elementi.pptx



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A-RATIONAL MODELS

The garbage can model (Cohen et al., 1972; Daft, 2001; Lipson, 2007)

The variables

Actors/participants(A) Problems (P) Solutions (S) Decision Opportunities (O)

Originally proposed for describing organizational decision-making processes in companies

O are the cans in which A throw P and S. The decision depends on the random coupling of P and S

Applications to public decision-making in transportation can be found in Cascetta and Cartenì (2012) on eco-rationality

O

P P

P

P

P P

P

P

P

P P P

P P

P P

P

S

S S S

S

S

S

S P

S

S

S S

S

S

S

A

A

O

P P

P

P

P P

P

P

P

P P P

P P

P P

P

S

S S S

S

S

S

S P

S

S

S S

S

S

S

A

A

O O




A-RATIONAL MODELS

The garbage can model

It deals with “organized anarchies”, i.e. organizations where there are three properties:

1) Choices are made on the basis of ill-posed and inconsistent ideas

2) A solution/idea could be proposed even if there is not a problem or it could contribute to define it. On the contrary, a problem could exist without being able to find a solution

3) Participation changes: different actors are involved over time

Non-efficiency, Instability, Lack of legitimization

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RATIONAL MODELS

• consistent - both internally w. r. t. the stated objectives and existing constraints, and externally

with other decisions (plans, projects) taken in other interacting contexts or at different moments in time

• comparative - considering one or more alternatives (e.g. not deciding, one of the available options,

searching for other possibilities)

• aware - based on unbiased information about the options (features), the context (physical

and decisional) and their likely impacts (costs, benefits, risks and opportunities), for technical, economic and administrative feasibility

Rationality: Acting in the best possible way considering the aim (Elster, 1986)

• flexible - open to changes due to new information on alternative options and their effects, to

changes in the economic, physical, institutional contexts, and taking into account decision “opportunity costs” (i.e. postponing unnecessary decisions)

Minimal Requirements of Rational decisions: (Cascetta et al., 2013)



Strongly Rational model

Homo oeconomicus is a utility maximizer relative to his/her choices

Comprehensive (full enumeration of possible solutions)

Aware (evaluation of all the impacts)

Optimization algorithm (chosen solution is the one that maximize objectives and fulfill the constraints)

Conclusive


RATIONAL MODELS

IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

IMPLEMENTATION

CHOICES

(PHASES)

PRESENT SITUATION

ANALYSIS

-Activity system

- Transportation system

DECISION-MAKING

CONTEXT

IDENTIFICATION

MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENTED

OPTIONS

OPTIMALITY

TEST

PROJECT

IMPLEMENTATION

NO

YES

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

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RATIONAL MODELS The cognitive or bounded rational approach


“The Fox and

the Grapes” IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

IMPLEMENTATION

CHOICES

(PHASES)

PRESENT SITUATION

ANALYSIS

-Activity system


DECISION-MAKING

CONTEXT

IDENTIFICATION

SATISFYSING

OBJECTIVES

IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

IMPLEMENTATION

CHOICES

(PHASES)

PRESENT SITUATION

ANALYSIS

-Activity system


DECISION-MAKING

CONTEXT

IDENTIFICATION

SATISFYSING

OBJECTIVES

MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENTED

OPTIONS

IMPLEMENTATION

1ST PHASE

IMPLEMENTATION

2ND PHASE

NO

YES

NO

YES

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENTED

OPTIONS

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

IMPLEMENTATION

CHOICES

(STAGES)

IMPLEMENTATION

CHOICES

(STAGES)

IMPLEMENTATION

1ST STAGE

IMPLEMENTATION

2ND STAGE



RATIONAL MODELS

Cognitive/Bounded Rational approach

It is loosely consistent with:

Bounded Rationality Choice Theory (Simon 1957; Rubinstein,

1999; Kahneman, 2003) (Behavioral Economics)

Learning Theory in Dynamic Decision-Making Models

(Brehemer, 1992; Gonzalez et al., 2003)

(Management science/Psychology)

Cognitive Processes in Decision-Making (Wang et al. 2003, 2007)

(Cognitive Sciences)


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Application areas of the cognitive/bounded rationality approach

Multiple (and possibly ill-posed) objectives, also related to

non-quantitative variables

Not exhaustive knowledge of the context variables/available

solutions

Impacts on multiple stakeholders

Several decision-makers with different agendas

Significant uncertainty in the simulated impacts

Opportunity/need to implement decisions in stages




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1

outline


Public Engagement




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2. public engagement

Public Engagement (PE) is the process of identifying and incorporating stakeholders’ concerns, needs and values in the transport decision-making process.

It is a two-way communication process promoting stakeholder interaction with the formal decision-makers and the transport project team.

The overall goal of engagement is to achieve a more transparent decision-making process with greater input from stakeholders and their support of the decisions (larger coalitions)

Stakeholders management is also studied in organization and management sciences (Clarkson, 1999)



1. Stakeholders identification: e.g. authorities, local communities, etc.

2. Listening and stakeholders management: systematic analysis of the current social, cultural and economic conditions with a direct impact on stakeholders

3. Information communication: information relative to the project provided by the stakeholders

4. Consultation: decision-makers interact with the stakeholders in defining/evaluating alternatives

5. Participation: extension of the consultation level where the groups, directly interested, become joint partners of the project and in the project implementation. They take part in making the final choice

THE FIVE LEVELS OF PE

STAKEHOLDERS IDENTIFICATION

LISTENING AND

STAKEHOLDERS MANAGEMENT

INFORMATION COMMUNICATION

CONSULTATION

PARTICIPATION


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ENGAGEMENT STRATEGIES

INTEREST/POWER MATRIX

PO

WER

HIG

H

Institutional Stakeholder

(Identification)

Key Stakeholder

(Consultation/Participation)

LOW

Marginal Stakeholder

(Information communication)

Operative Stakeholder

(Active listening)

LOW HIGH

INTEREST

Stakeholders Empowerment




Limits of the DAD

It fosters consensus barriers

It increase costs

It increases times

THE ARCH-ENEMY OF PE: THE DAD (DECIDE, ANNOUNCE, DEFEND) SYNDROME (e.g. Susskind et al., 1983; Walker, 2009)

Administration makes a DECISION (the best project/plan), it ANNOUNCES the project to the population and other stakeholders that have not been involved previously. This produces many oppositions and the Administration is obligated to DEFEND the decision against criticism, accusations and controversy without having the opportunity to change the project (if only marginally)


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3

1

outline


Public Engagement



Some indications for quantitative analyses from the new persepctive 4

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1. Understanding and modeling mobility and transport related phenomena (mostly in physical terms)

2. To assist in the design, assessment and evaluation of transport-related decisions:

What If What To

TRADITIONAL ROLES OF TRANSPORTATION SYSTEM ANALYSIS

3. To contribute towards reaching larger consensus through Public Engagement

(e.g. information-based PE)

4. To provide inputs for economic/financial plans of market operators

NEW ROLES

3. quantitative analyses and their roles




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Quantitative analyses in a-rational decision-making play only a cosmetic role (if any)

PE and rational decision-making do not necessarily imply each other (e.g. DAD syndrome and PE based on pure “negotatiation”)

Cognitive model has the greater potential for integration with PE, both in public and private contexts

cognitive rationality, PE and quantitative analyses



The model proposed here is based on “three legs”:

Cognitive or Bounded rational decision-making processes

Public Engagement

Transportation System Analysis

cognitive rationality, PE and quantitative analyses

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IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

PRESENT SITUATION

ANALYSIS

-Activity system

-- Transportation system

IMPLEMENTATION

1° STAGE

NO

SI

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENT.

OPTIONS

DECISION-MAKING

PROCESS

DECISION-MAKING

CONTEXT

IDENTIFICATION

three-legs model

SATISFYING

RESULTS

AND

CONSENSUS



IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

PRESENT SITUATION

ANALYSIS

-Activity system


IMPLEMENTATION

1° STAGE

NO

SI

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

STAKEHOLDER IDENTIFICATION

LISTENING AND STAKEHOLDER MANAG.


AND CONSULTATION


MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENT.

OPTIONS

CONSULTATION AND PARTICIPATION

DECISION-MAKING

PROCESS STAKEHOLDERS ENGAGEMENT

DECISION-MAKING

CONTEXT

IDENTIFICATION

three-legs model

SATISFYING

RESULTS

AND

CONSENSUS

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IDENTIFICATION OF

OBJECTIVES,

CONSTRAINTS AND

PROJECT TYPOLOGIES

FORMULATION OF

ALTERNATIVE OPTIONS

(PLANS/PROJECTS)

SIMULATION AND

TECHNICAL

ASSESSMENT

PRESENT SITUATION

ANALYSIS

-Activity system


IMPLEMENTATION

1° STAGE

NO

SI

COMPARISON OF

ALTERNATIVE

SOLUTIONS

(ASSESSMENT/

EVALUATION)

STAKEHOLDER IDENTIFICATION

LISTENING AND STAKEHOLDER MANAG.


AND CONSULTATION


MONITORING

AND EX-POST

EVALUATION

OF

IMPLEMENT.

OPTIONS

CONSULTATION AND PARTICIPATION

DEMAND/SUPPLY INTERACTION MODELING AND SIMULATION IN REFERENCE SCENARIO

DEMAND/SUPPLY INTERACTION MODELING AND SIMULATION IN PROJECT SCENARIO

SYSTEM PERFORMANCE ASSESSMENT

PRESENTATION OF RESULTS DECISION-MAKING

PROCESS STAKEHOLDERS ENGAGEMENT

TRANSPORTATION

SYSTEM ANALYSIS

DECISION-MAKING

CONTEXT

IDENTIFICATION

three-legs model

DEMAND ANALYSIS AND MODELING

DEMAND/ SUPPLY INTERACTION MODELING AND SIMULATION

ANALYSIS OF EXISTING PLANNIG DOCUMENTS

INSTITUTIONAL AND ORGANIZATION ANALYIS

PASSENGER AND FREIGHT DEMAND ESTIMATION

SOCIO-ECONOMIC ANALYSIS

IDENTIFICATION OF FUTURE SCENARIOS AND REFERENCE ONE

WEAKNESSES AND PLANNING STRATEGIES

INDENTIFICATION OF PROJECT SCENARIOS

PERFORMANCE ASSESSMENT

ECONOMIC ASSESSMENT

FINANCIAL ASSESSMENT

ENVIRONMENTAL ASSESSMENT

COMPARISON OF ALTERNATIVES

SATISFYING

RESULTS

AND

CONSENSUS

DEMAND ANALYSIS AND MODELING



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1

outline


Public Engagement




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2




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4. some indications from the new perspective

To model the impacts relevant to stakeholders and decision-makers (e.g. being informed vs. average travel times)

To adopt assessment methods allowing the evaluation of both quantitative and qualitative impacts for different actors

To present results in ways that can be understood by non-experts

To quantify the uncertainty entailed in the simulation results and in the assessment methodology

To improve the capability to capture users’ willingness to pay for transport services



4. some indications from the new perspective

Standardization of procedures and DSS

Third-part assessment and performance comparison with base-rates

The (neglected) relevance of monitoring and ex-post studies

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Thank you for your attention!



basic references (1/4) Reference papers

Cascetta et al. (2013). A new look at planning and designing transportation systems: decision processes, stakeholders management and the role of quantitative methods, Transport Policy, under review.

Cascetta, E. (2011). Transportation planning: decision-making, public engagement and system engineering. SIDT International Conference. Venice.

Planning failures Flyvbjerg et al. (2005). How (In)accurate Are Demand Forecasts in Public Works

Projects: The Case of Transportation. Journal of the American Planning Association, 71(2), 131–146.

Lemp, J. D., and K. M. Kockelman (2009). Understanding and Accommodating Risk and Uncertainty in Toll Road Projects: A Review of the Literature. Transportation Research Record, 2132, 106–112.

Buehler et al. (2010). The Planning Fallacy: Cognitive, Motivational, and Social Origins. Advances in Experimental Social Psychology, 43, 1–62.

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basic references (2/4)

Decision-Making in Transportation and Models – RATIONAL MODELS

Simon, H. (1957). A Behavioral Model of Rational Choice, in Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting. New York, Wiley.

Brehmer, B. (1992). Dynamic decision making: Human control of complex systems. Acta Psychologica, 81(3), 211–241.

Gonzalez, C., Lerch, J. F., & Lebiere, C. (2003). Instance-based learning in dynamic decision making. Cognitive Science, 27(4), 591–635.

Kahneman, D. (2003). Maps of bounded rationality: psychology for behavioral economics. The American Economic Review.

Wang, Y., and Ruhe, G. (2007). The Cognitive Process of Decision-Making. Int. Journal of Cognitive Informatics and Natural Intelligence, 1(2), 73-85.

Decision-Making in Transportation and Models – A-RATIONAL MODELS

Cohen, M. D., March, J. G., Olsen, J. P. (1972). A Garbage Can Model of Organizational Choice. Administrative Science Quarterly.




Decision-Making in Transportation and Models – PUBLIC ENGAGEMENT

Cascetta, E., Pagliara, F. (2013). Public engagement for planning and design transportation systems: tools and experiences, Proceedia – Social and Behavioral Sciences, 87.

Cascetta, E. (2011). Transportation planning: decision-making, public engagement and system engineering. SIDT International Conference. Venice.

Kelly, J., Jones, P., Barta, F., Hossinger, R., Witte, A., Christian, A. (2004). Successful transport decision-making – A project management and stakeholder engagement handbook. Guidemaps consortium.

Clarkson Centre for Business Ethics (1991). Principles of Stakeholder Management.

Susskind, L., Elliot, M. (1983). Paternalism, Conflict and Coproduction. Susskind and Elliot eds., Plenum Press, New York.

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The role of quantitative methods in transportation decision-making

Cascetta (2009). Transportation System Analysis: models and applications. 2nd edition. Springer.

CE Delft Report (2007). Handbook on estimation of external cost in the transport sector. EC DG Tren.

Cunningham, S. W., and van der Lei, T., E. (2007). Decision-Making for New Technology: A Multi-Actor, Multi-Objective Method. PICMET Proceedings. Portland.

Manheim (1979). Fundamentals of Transportation Systems Analysis, Volume 1: Basic Concepts (Transportation Studies). MIT Press

Meyer and Miller (2001). Urban Transportation Planning. 2nd edition. McGraw-Hill.

Ortuzar and Willumsen (2011). Modelling Transport. 4th edition. Wiley.

Saltelli et al. (2008). Global Sensitivity Analysis: The Primer. Great Britain. Wiley.

Sinha, K.C. and Labi, S. (2007). Transportation Decision Making. Principles of Project Evaluation and Programming. Wiley.

cognitive rationality, public engagement and quantitative

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