A CONCEPTUAL APPROACH TO DESIGN THE KNOWLEDGE BASED URBAN DEVELOPMENT (KBUD) USING AGENT BASED MODELLING

 

Rengarajan Satyanarain*

&

HO, Kim Hin / David

Department of Real Estate

School of Design and Environment

National University of Singapore

*Email: Satyanarain@nus.edu.sg

 

European Real Estate Society (ERES) conference paper

Introduction: what are knowledge based urban developments?

Contents of the paper

Develop physical planning guidelines which would help urban planners create effective zoning (mixed-use) policies.

We look at how to design (land use planning) a Knowledge Based Urban Development (KBUD) so as to

enhance intra-cluster knowledge interactions.

Research Implication

Knowledge catalysing the process of technological innovation is undisputed in the Science and Technology (S&T) literature.

Sources: Hargadon & Sutton, 1997; Kanter, 1988; I Nonaka & Konno, 1998

Individuals working in knowledge intensive industries require information resources [Medium

of access]

E.g. Face-to-Face, Journal articles and other forms of media (television, internet, newspapers etc.)

Face-to-face (F2F contact )

Sources: Allen (1984) ; Ancona,1990 ;Ancona and Caldwell’s ,1992; Audretsch

& Feldman, 1996 ; Feldman, 2000; Storper & Venables, 2004 ;

Background : Influence of design on knowledge based work

Interaction with peersF2F Productive/innovative

Workspace planning /design studies for knowledge based environments

Space syntax Analysis: Exploit differences in spatial layouts, circulation systems, visibility, adjacencies, mean integration etc to maximize the probability of interaction.

Scale : Building

Sources : Backhouse & Drew, 1992; F Duffy, 1997; Penn, Desyllas, & Vaughan, 1999; Peponis et al.,

2007; Serrato & Wîneman, 1999).

Urban planning/design studies for knowledge based environments

There are almost no studies looking at how to design interactive environments on an urban scale as required for KBUD.

Scale : Precinct

Background: Workspace design / Urban scale designs

3. Research problem

Designs have been Ad-hoc and experimental.

Euclidian (single land use) Mixed use zoning

vs.

A mixed use design should promote “knowledge” interactions (planned and spontaneous)

This is achieved through complimentary zoning

Premise: some actors have higher chances of interaction than others.

3. The research question

What is the urban design criteria of the knowledge based urban development ?

Knowledge interactions

SocialEnvironmental

EconomicTransportation

Source: Alan frost (2003); Adapted from classification given by Asheim and Gertler, (2005)

What are knowledge interactions?

“the continuous and dynamic interaction between tacit and explicit knowledge that happens at the individual, group ,institutional, organizational, and inter-organizational levels that leads to creation/sharing or transfer of knowledge”

- Nonaka & Takeuchi (1995).

Knowledge/information interactions

Source: Alan frost (2003); Adapted from classification given by Asheim and Gertler, (2005)

Knowledge/information interactions

Intra-cluster interactions

Knowledge bases

General rule of mixed land use designs for KBUD’s

I. Diversity

Triple helix model of Innovation . (Leydesdorff & Etzkowitz ,1998).

II. Geographical proximity

“short distances literally bring people together, favour information contacts and facilitate the exchange of tacit knowledge. The larger the distance between agents, the less the intensity of these positive externalities, and the more difficult it becomes to transfer tacit knowledge”

-Boschma, 2005

Literature review – Current design practices

Interactive design = “Accommodate a diverse set of actors into a small area of land”

DMC Seoul KBUD design

a “futuristic info-media industrial complex”, has planned for a city street which is to host “entertainment and retail establishments, technology companies, prestige housing, R&D institutions, and universities”.

The same street supposedly would host leisure activities such as “theatres, cafés, stores, nightclubs and LCD screens as big as whole buildings”.

Literature review – Current design practices

Source: http://sap.mit.edu/resources/portfolio/seoul/

Literature review - Knowledge interaction determinants

Spatial proximity maybe necessary

Not sufficient

Mixed land uses

Other dimensions of proximity ..

Proximity factors

Key dimension

Proximity

Too little Too high

Institution Trust (based on common institutions)

Opportunism Lock-in

Organizational Control Network disruption

Bureaucracy

Knowledge base Base gap Lack of common base

Physical barrier for fertilisation

Cognitive base Knowledge gap

Misunderstanding Unintended spillovers

Geographical Distance An optimal mix of agents on these terms can facilitate reduced physical barriers to

knowledge interaction

Source: Boschma (2005)

Literature review - Knowledge interaction determinants

Theoretical criteria of a knowledge interactive urban design

0 Proximity 1

Knowledge baseInstitutional

OrganizationalCognitive

Lock-in

Interaction level (I)

Lock-in

3. A simple 2-Dimensional Illustration of ‘lock-in’ design effect

*Illustrative purpose only

E.g. Illustration of Design

“lock-in effects” in a KBUD

A) “Institutional lock-in” B) “Cognitive lock-in”

A

B

Methodology

‘Optimal’ design =(Design criteria, Spatial constraints, Actors [Number & Distribution] )

Theoretical model of design(AGM) Design

Theoretical Model of design

3. Methodology- Land use design models in planning

Urban Planning literature

Land use design optimization problems

Single objective

Multiple objective

Multiple objective

Spatially explicit

Regular grid (non-overlapping)No explicit representation of space

LinearProgramming methodology

Multiple land use : Kenneth (1965) ;Barber (1976); Arad and Berechman (1978); Williams and Revelle (1996); Makowski (1997); Janssen et al (2008);  

Single land use model: Meier,(1968) Multiple land use: Correia and Madden,(1985); Davis and grant,(1987)

Multiple land use Overlapping

S

Physical definition (conceptual/real)

Actor classification

Constraints (limits of the system)

Operational objective functions (evaluation)

Methodology- Agent based modeling

Agents criteria zones

Self-select

constraints

Unsatisfied

1

2

3

4

Decision function

Typical Land use design model (MAS)

Source:Ligtenberg et al, (2004)

Actors in the KBUD

Size 100-500 hectares

Agents

Firm (high tech, service, business etc.)University department (i)Public research institute (PRI)Private institute (PVRI)Misc (Retail, commercial, housing etc)

Classification

J= Institution K=Organization L =Knowledge base (Asheim et al,2007)M= Cognitive field

Agents

kj l mEmbedded

Location variables

Theoretical model of design

Quality variablesQuantity variables

Space constraintsTypes of land

uses

Source: Adapted from Kenneth Schlager,1965

Land use design

Zonal interaction

Theoretical model of designWhere,

Quality variable

Quantity variables

Agent rules

Start Define space [e.g. plot ratio, parcel size, road length etc] Initiate agents (AIP). Occupy random position in space. Minimize the mean distance between ‘related’ agents. [KI – Design

criteria]

Upon reaching equilibrium, locate to the nearest available block. If KI is unsatisfied, re-define space and repeat step 2. If KI is satisfied. Initiate subsidiary agents (i.e. service ratio requirements). End

Optimal design algorithm

KBUD system

Agents

Economic forecasts

Design Type

1. Knowledge bases2. Institutional3. Organizational4. CognitiveSubsidiary land use

I) Planning ratios

Spatial constraints1. Plot ratio2. Land parcels (no.)3. Minimum requirements (setbacks,

accessory etc in sq m)

AIP

KI criteria

Agent base land use model (AGB-LUM)’s architecture

Future work

Case study :One north KBUD system

Data

1. Land use plans2. Planning ratios3. Plot ratio, Set backs

etc4. Land use designs

Source: JTC

Organizational composition

Research institution

Technology firm

University (learning)

misc

Phase 1 & 2-Biopolis-Land use distribution (by organization)

Output data

1)Land use composition2)Plot Ratios3) Subsidiary land uses4) Zonal maps (2-D)

Input data

1) Agent Identification2) Coordinate map3) Rules4) Planning ratio ( i.e. minimum requirements)

Model output

3.Research Contribution

1 Have not paid attention to the role of urban design in KBUD literature

2 No theoretical basis on how to effectively mix land uses .

3 Previous urban design models have predominantly used linear programming methodology (LPM).

Governance , Institutional planning

models ,Planning metrics

Urban design

KBUD Theoretical model of urban design

(Our contribution)

Land use design models in planning

KBUDLiterature

Linear programming

Knowledge interaction criteria (KIC)

Agent based modeling literature

Planning practice

Land use design models in planning

Our paper addresses the issue of urban design for knowledge based urban development.

Urban designs emphasizing spatial proximity (density) and diversity alone may not favor interactive environments.

Propose a theoretical framework for a design tool using ABM approach.

Conclusion

Thank you for listeningQ&A

The End

Data

1. Land use plans2. Planning ratios3. Plot ratio, Set

backs etc4. Land use designs

Source: JTC

Case study :One north KBUD system

Agents Assumptions

Technology Firm Unit of occupation: Firm Minimum number of persons/firm: 20 Space per person: 70 sq ft Space per firm: 1500 sq ft

Research institution Unit of occupation: Department/firm Minimum number of persons department/firm: 20 Space per person: 70 sq ft Space per Department: 1500 sq ft

Educational (university)

Unit of occupation: Department MnoD : 10 departments Space per department: 2000 sq ft

Service firm Unit of occupation: Firm (Mno)persons/firm: 20 Space per person: 50 sq ft Space per firm: 2000 sq ft

Sub-Agents Subsidiary land use specifications

Green space Regional ratio of 6 sq m per person (entire development)Retail 3 sq m per personHousing 80 sq m per personRecreational 3 sq m per person

Source: Authors,2013 & One north masterplan (2008)

Design Parameter assumptions

Output data

1)Land use composition2)Plot Ratios3) Subsidiary land uses4) Zonal maps (2-D)

Input data

1) Agent Identification2) Coordinate map3) Rules4) Planning ratio ( i.e. minimum requirements)

Model output

ONE NORTH-BIOPOLIS BASELINE (AIP)

Type Percentage Space needed (GFA) in Sq ft.

Characteristics Representative unit

Agents

Work48% 285,600 Research institution/firms

Dept./firm 285

Live40% 130,400 Housing

Apartment unitD

Learn9% 38,250 Educational [university,

school etc]

DepartmentD

Play3% 122(meters) Green space (80 %)

Sports & recreation (20%)

N.AD

Total100%

41250.64 [meters]

Source: One north masterplan,2008

Theoretical model of design

BASELINE SCENARIO -2-DIMENSIONAL

Screenshots

Research Institutions

Retail

Housing Green space

Knowledge base Composition-Analytical (Biomedical sciences)

Theoretical model of design

Total population Knowledge base Composition

Phase 1 & 2-Biopolis-Land use distribution

Land use design –Institutional base

Subsidiary land uses

Institutional Composition

Phase 1 & 2-Biopolis-Land use distribution (by instituition)

Organizational composition

Research institution

Technology firm

University (learning)

misc

Phase 1 & 2-Biopolis-Land use distribution (by organization)

Fully populated model by institutional-Sample design

Public Private

Design TypeKnowledge base –HighInstitutional-High

Output data

1)Land use composition2)Plot Ratios3) Subsidiary land uses4) Zonal maps (2-D)

Input data

1) Agent Identification2) Coordinate map3) Rules4) Planning ratio ( i.e. minimum requirements)

Model output

Summary of the paper

The paper provides a theoretical criteria to help design KBUD.

Towards a more scientific and dynamic approach in designing mixed use developments.

A flexible approach reduces reliance on long term designs.

Proposes an new methodology (AGM) to aid land use planning.

Institutional ‘Lock-in’

Organizational ‘Lock-in’

Knowledge base ‘Lock-in’

The ‘Lock-in’ design phenomenon

Design goals (criteria) are important for physical planning to take shape over time.

Effective zoning can help actors share resources efficiently. It can prevent land use conflicts arising from different actors.

Why is it important?

E.g. Housing Estates •Reduce commuting costs less pollution. •Make amenities accessible by walk Schools ,parks,retail etc.) •Social goals fostering sense of community

3. Research problem 2 : The design process

Defined land area divided into a set of N

land parcels

Actori

Spatial Constraints

{a,b…z} є N

i є [ University, public, private research institutes, firms, service companies etc]

(T0,Tn )

Urban design criteria

Zoning guidelines1 Uncertainty of participants

Static urban designs

Design Criteria for knowledge interaction

2

Urban design

KI

3