A

CONCEPTUAL APPROACH TO DESIGN THE

K

NOWLEDGE

B

ASED

U

RBAN

D

EVELOPMENT

(KBUD)

USING

A

GENT

B

ASED

M

ODELLING

European Real Estate Society (ERES) conference paper

Rengarajan Satyanarain* & HO, Kim Hin / David

Department of Real Estate School of Design and Environment National University of Singapore *Email: [email protected]

Introduction: what are knowledge based urban developments?

Contents of the paper

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

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

Background : Influence of design on knowledge based work

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 ; Interaction with peers  F2F  Productive/innovative

Background: Workspace design / Urban scale designs

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

Research problem

Designs have been Ad-hoc and experimental.

Euclidian (single land use) Mixed use zoning

vs.

3.

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.

The research question

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

Knowledge interactions

Social Environmental Economic Transportation

3.

Knowledge/information interactions

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).

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

Knowledge/information interactions

Intra-cluster interactions

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

Literature review – Current design practices

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

Literature review – Current design practices

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

Literature review - Knowledge interaction determinants

Spatial proximity maybe necessary

Mixed land uses Not sufficient

Other dimensions of proximity ..

Literature review - Knowledge interaction determinants

Proximity factors Key dimension Proximity

Too little Too high

Institution Organizational Trust (based on common institutions) Control

Opportunism Network disruption Lock-in Bureaucracy

Knowledge base Cognitive base Base gap Knowledge gap

Lack of common base Physical barrier for fertilisation Misunderstanding Unintended spillovers

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

Source: Boschma (2005)

Theoretical criteria of a knowledge interactive urban design

Interaction level (I) 0 Proximity 1 Lock-in Knowledge base Institutional Organizational Cognitive Lock-in

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

A 3.

E.g. Illustration of Design “lock-in effects” in a KBUD A) “Institutional lock-in” B) “Cognitive lock-in” B

*Illustrative purpose only

Methodology

Theoretical Model of design ‘Optimal’ design =(

Design criteria , Spatial constraints, Actors [Number & Distribution] )

Theoretical model of design (AGM) Design

Methodology- Land use design models in planning

Urban Planning literature Single objective Multiple objective

Land use design optimization problems

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

Multiple land use : Kenneth (1965)

;Barber (1976); Arad and Berechman (1978); Williams and Revelle (1996); Makowski (1997); Janssen et al (2008); Regular grid (non-overlapping) No explicit representation of space Multiple objective Multiple land use Spatially explicit Overlapping Linear Programming methodology

3.

Methodology- Agent based modeling

Typical Land use design model (MAS)

Decision function Self select Agents criteria zones S constraint s Unsatisfied 3 4 2 1

Physical definition (conceptual/real) Actor classification Constraints (limits of the system) Operational objective functions (evaluation)

Source:Ligtenberg et al, (2004)

Actors in the KBUD

Size 100-500 hectares Embedded

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 j k Agents l m

Theoretical model of design

Land use design Quantity variables Quality variables Location variables Space constraints Types of land uses Zonal interaction Source: Adapted from Kenneth Schlager,1965

Where,

Theoretical model of design

Quality variable Quantity variables

Optimal design algorithm

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

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

Spatial constraints

1. Plot ratio 2. Land parcels (no.) 3. Minimum requirements (setbacks, accessory etc in sq m) Economic forecasts

AIP

Agents

KI criteria KBUD system

Subsidiary land use I) Planning ratios

Design Type

1. Knowledge bases 2. Institutional 3. Organizational 4. Cognitive

Future work

Case study :One north KBUD system

Data

1.

2.

3.

4.

Land use plans Planning ratios Plot ratio, Set backs etc Land use designs Source: JTC

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

Organizational composition

 Research institution  Technology firm  University (learning)  misc

Model output

Input data

1) Agent Identification 2) Coordinate map 3) Rules 4) Planning ratio ( i.e. minimum requirements)

Output data

1)Land use composition 2)Plot Ratios 3) Subsidiary land uses 4) Zonal maps (2-D)

Research Contribution

Agent based modeling literature Land use design models in planning KBUD Literature

Linear programming

Knowledge interaction criteria (KIC) Planning practice

KBUD Theoretical model of urban design (Our contribution)

Governance , Institutional planning models , Planning metrics

Urban design

1 2 3

Have not paid attention to the role of urban design in KBUD literature No theoretical basis on how to effectively mix land uses .

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

3.

Conclusion

 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.

The End

Thank you for listening Q&A

Case study :One north KBUD system

Data

1. Land use plans 2. Planning ratios 3. Plot ratio, Set backs etc 4. Land use designs Source: JTC

Design Parameter assumptions

Agents

Technology Firm Research institution Educational (university) Service firm

              

Assumptions

Unit of occupation: Firm Minimum number of persons/firm: 20 Space per person: 70 sq ft Space per firm: 1500 sq ft Unit of occupation: Department/firm Minimum number of persons department/firm: 20 Space per person: 70 sq ft Space per Department: 1500 sq ft Unit of occupation: Department MnoD : 10 departments Space per department: 2000 sq ft 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 person

Housing



80 sq m per person

Recreational



3 sq m per person

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

Model output

Input data

1) Agent Identification 2) Coordinate map 3) Rules 4) Planning ratio ( i.e. minimum requirements)

Output data

1)Land use composition 2)Plot Ratios 3) Subsidiary land uses 4) Zonal maps (2-D)

Theoretical model of design

O

NE NORTH

-B

IOPOLIS

B

ASELINE

(AIP)

Type Work Live Learn Play Total Percentage Space needed (GFA) in Sq ft.

48% 40% 9% 3%

285,600 130,400

38,250 122(meters)

Characteristics Representative unit Agents 285 Dept./firm Research institution/firms Housing

Apartment unit Department

Educational [university, school etc] Green space (80 %) Sports & recreation (20%) N.A

D D

D 41250.64 [meters] 100% Source: One north masterplan,2008

Theoretical model of design

B

ASELINE SCENARIO

-2-D

IMENSIONAL

Knowledge base Composition-Analytical (Biomedical sciences) Retail Research Institutions Housing Green space Screenshots

Phase 1 & 2-Biopolis-Land use distribution

Total population Knowledge base Composition

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

Land use design –Institutional base Institutional Composition Subsidiary land uses

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

Organizational composition

 Research institution  Technology firm  University (learning)  misc

Fully populated model by institutional-Sample design

Design Type

Knowledge base – High Institutional-High Public Private

Model output

Input data

1) Agent Identification 2) Coordinate map 3) Rules 4) Planning ratio ( i.e. minimum requirements)

Output data

1)Land use composition 2)Plot Ratios 3) Subsidiary land uses 4) Zonal maps (2-D)

Summary of the paper

The paper provides a theoretical criteria to help design KBUD.

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

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

A flexible approach reduces reliance on long term designs.

The ‘Lock-in’ design phenomenon

Institutional ‘Lock-in’ Knowledge base ‘Lock-in’ Organizational ‘Lock-in’

Why is it important?

   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.

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

Research problem 2 : The design process

Actor i ) (T 0, T n i є [ University, public, private research institutes, firms, service companies etc]

3.

Urban design criteria Defined land area divided into a set of N land parcels KI Urban design 2 3 1

Uncertainty of participants Static urban designs Design Criteria for knowledge interaction

Zoning guidelines Spatial Constraints {a,b…z} є N