Study on Development and Application of MAS for Impact Analysis of Large-scale Shopping Center Development

ZJ. Shen, M. Kawakami, P. Chen

Kanazawa University, Japan

2006. DDSS

Contents

Introduction

Location Regulations for B-shops

Framework of Shopsim-MAS

Policy Scenarios Evaluation

Discussion and Further Research

Background

The commercial environment of many local cities in Japan is experiencing decline in their centre areas.Local governments have developed all kinds of city center generation policies to constrain this trend and revitalize the central city commercial environment.It is difficult to evaluate the potential impact of current policies on the city future due to the uncertainty inherent in urban system.MAS simulation is reconized as a tool to visualize impact of planning policies for presenting the complexity of the urban system.

Introduction

Picture of center area in metropolitan

prosperous commercial street in Osaka

Introduction

Pictures of center area in local city

Decline of commercial environment

Introduction

Pictures of large-shopping mall

In suburban area

Contents

Introduction

Location Regulations for B-shops

Framework of Shopsim-MAS

Policy Scenarios Evaluation

Discussion and Further Research

Location Regulations for B-shops

Urbanization

Control Area

White Land

•Commercial district•Quasi –industrial district•Industrial distinct•2nd residential district•Quasi-residential district•Neighborhood commercial district

•1st low-rise exclusive residential district•2nd low-rise exclusive residential district•1st mid-high rise exclusive residential district•2nd mid-high rise exclusive residential district•1st residential district•Exclusive industrial distinct

X

Urban planning area

X

Land use zone

Urbanization

Promoting Area

B-shops are not permitted to locate in these land zoning district

B-shops can be permitted to locate in these land zoning district

In principle, any development are prohibit in Urbanization Control Area

Permitting state

Planning regulations on location of large-scale shopping center

(B-shop)

Location Regulations for B-shops

Land use zoning

Location Regulations for B-shops

Bylaw regarding location and floor space

Location Regulations for B-shopsPrinciple scenarios for shopping center location as Decision table for

developer agent (Bylaw regulations and land use zonings)

C1 Scenario

C2Location is incenter N Y Y

C3Location matcheszone type N / / N / N

C4

Location isconsistent withbylaw N / / / N / / N /

C5

Distance toexisting shops isappropriate Y N / / / / Y N / / / Y N / /

A1Set potentiallocation Y / / / / / Y / / / / Y / / /

A2Set floor spaceup-limit N / / / / / 10000 / / / / 3000 / / /

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15

Y

Y

Center Activation

Y

Neighborhood Commerce Promoting

Y

Y

N

Railway Station Development

Y

Y

N

Location Regulations for B-shops

The location alternatives are limited in the possible areas according to land use zonings regulation and bylaw regarding large-scale shopping mall.

These location alternatives reflect the different scenarios of commercial development.

Contents

Introduction

Location Regulations for B-shops

Framework of Shopsim-MAS

Policy Scenarios Evaluation

Discussion and Further Research

Framework of Shopsim-MAS

provincial city of Japan Mono central

> urban sprawl > suburb house development > large suburban shopping mall

Poly central > declination in inner city > Policy change -> location regul

ations of lager shopping mall

Framework of Shopsim-MAS --- Shop choice (percolation model)

Percolation model for getting spatial patternPercolation probability Ps or Pb

Pb for shopping in B-shop

Ps for shopping in S-shop

Pb + Ps = 1

If Pb > 0.5 then percolation phenomenon will occur.

To keep the S_shop market share, Ps should be more than 0.5 B-shop

S-shop

Framework of Shopsim-MAS --- Shop choice (percolation model)

A random utility model for shopping Probability in Percolation model

Agents’ (Household) shop choice of B_shop or S_shop Chose B_shop if Uib > Uis Chose S_shop if Uis > Uib

B-shop

S-shop

ijijij VU

Framework of Shopsim-MAS----Shop choice (percolation model)

A random utility model for household shop choice:

The random factor can be used to adjust percolation probability, which will generate diverse spatial patterns

TCXfV ijkijk

jij )(

)()(22

yyxxTC jijiiij

ijijij VU

Framework of Shopsim-MAS----shop choice model

According to local regulations of large scale shopping mall,

influence factors of percolation probability should be set as location (set as decision table )and floor area.

Xkij is the kth attribute describing store j attracting household i., price: X1j =Pj and

floor space: X2j =Sj (Price Pj is added by authors)

distance: Cij is a measure of the disutility of travel between site of household i and site of shop j. (Cij is added by authors)

Shopping choice in simulation based on utility is deterministic process, as random factor to control individual choice.

ij

Framework of Shopsim-MAS --- Shop choice (percolation model)

Cij is a measure of the disutility of travel between site of household i and site of shop j.

Percolation probability become unstable in this case, however it is relative to its spatial position.

B-shop

S-shop

H

H →　 B-shop　distance

H →　 S-shop　distance

)()( BhBh yyxx

)()( ShSh yyxx

TCXfV ijkijk

jij )(

Framework of Shopsim-MAS --- Shop choice (percolation model)

percolation probability is shifted if household position is near ot far away from a shop.

B-shop

S-shop

H

To S-shopCij shorter Ps(Sj,Pj,Cij) larger

To S-shopCij longer Ps(Sj,Pj,Cij) smaller

H

Framework of Shopsim-MAS----spatial pattern (percolation model)

random value was set to translate the probability of random utility model into simulation in Uib, 10000in Uis, 10000Rate of shoping in B_shop=0.08 in S_shop=0.92

price in S 300, in B 200

travel cost 120/cell

Framework of Shopsim-MAS----spatial pattern (percolation model)

random value was set to translate the probability of random utility model into simulation in Uib, 10000in Uis, 5000Rate of shoping in B_shop=0.5 in S_shop=0.5

price in S 300, in B 200

travel cost 120/cell

Framework of Shopsim-MAS----spatial pattern (percolation model)

random value was set to translate the probability of random utility model into simulationin Uib, 5000in Uis, 5000Rate of shopping in B_shop=0.94 in S_shop=0.06

price in S 300, in B 200

travel cost 120/cell

Framework of Shopsim-MAS----spatial pattern (percolation model)

random value was set to translate the probability of random utility model into simulationin Uib, 2000in Uis, 2000Rate of shopping in B_shop=0.16 in S_shop=0.84

price in S 300, in B 200

travel cost 120/cell

Framework of Shopsim-MAS----spatial pattern (percolation model)

random value was set to translate the probability of random utility model into simulation in Uib, 500in Uis, 500(critical point)Rate of shoping in B_shop=0.24 in S_shop=0.76

price in S 300, in B 200

travel cost 120/cell

Framework of Shopsim-MAS ---shop choice model

Therefore, percolation Probability of B_shop or S_shop is decided by Pj, Sj and Cij. For translating probability of random utility model into agent’s individual behavior, a random variable is defined.

If percolation probability changed gradually, the spatial pattern of percolation will be changed gradually. This phenomenon can be used in the market share simulation using MAS.

However, how about fitness of Individual shopping choice based on ramdam utility and percolation probability in simulation is still a further study.

Framework of Shopsim-MAS----uban space and agents

Urban Space

Agents Planner Developer Shop

S-shop B-shop

Household

Framework of Shopsim-MAS----object model

Framework of Shopsim-MAS----Simulation Process

1. The user of Shopsim-MAS defines a policy scenario to be implemented. -> decision table

2. The planner agent sets the spatial structure and initiates the scenario.

3. S-shop agents and existing B-shop agents are created in the urban space. Household agents are created and distributed to the whole central city urban planning area.The developer agent places the new B-shop in urban space according to defined scenarios.

4. The user sets the initial values of parameters .For clear simulation results, random value is set as 500 under critical point.

5. Households then decide where to go shopping until their demands are fulfilled (demands of each household=50).

Contents

Introduction

Location Regulations for B-shops

Framework of Shopsim-MAS

Policy Scenarios Evaluation

Discussion and Further Research

Policy Scenarios Evaluation----Define four cases of scenario

Base Scenario No new B-shop are permitted to develop

Centre Activation(CA) B-shop can only locate in the centre commercial area without up

per limitation for floor space.

Railway Station Development (RSD) B-shop can only be opened near the station, with an upper limit

ation of 10000 m2.

Neighbouring Commerce Promotion (NCP) B-shop can only locate in neighbour commercial area, with an up

per limitation of 3000 m2.

Policy Scenarios Evaluation----Analysis of CA scenario

3000m2

Market share of existing B-shop

Market share of the new B-shop

Market share of S-shop

5000m2 20000m215000m210000m28000m2

Sale statistics in CA scenario

The spatial effects of CA scenario as shown in figures.

It can be see that CA scenario do have effect in improving the market performance of the city centre, but may do severe harm to the centre S-shops at the same time if there is no limitation on B-shop’s scale.

Floor space =

Policy Scenarios Evaluation----Compare scenarios

Sale statistics of Center shops and S-shops

Market share of existing B-shop

Market share of S-shop

Base CA NCP

RSD

To compare three scenarios, the floor space of the new B-shop is set same as 3000m2.

Both Figures show that in RSD and NCP scenario, the loss of market share of S-shops caused by the new B-shop is more than in CA scenario .

Both Figures also indicate that CA scenario might be the only effective to improve center commerce among three scenarios.

Contents

Introduction

Location Regulations for B-shops

Framework of Shopsim-MAS

Policy Scenarios Evaluation

Discussion and Further Research

Discussion and Further Research

The use of MAS for impact analysis of large scale shopping center development regulations is proposed in this paper. By introducing real urban land use zoning to form agent’s behavior constraints, the Shopsim-MAS simulate the virtual urban space in a more practical way in the context of urban planning. Percolation model and random utility model are employed in this simulation and spatial pattern of the market share influenced by urban bylaw and planning regulations can be visualized.The simulation results of four possible policy scenarios indicate that to develop new B-shop in the city center might be an effective measure to improve commercial activity of city centre.

However, how about the behavior of households (random factors in this simulation that will influence the spatial pattern of market share) ?