Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

VISUALIZATION OF HIERARCHICAL SYSTEM OF CITIES IN EAST CONSIDERING SUPPLY AND CONSUMPTION BEHAVIOR

Md. Kamrul ISLAM Hitoshi IEDA Assistant Professor Professor Department of Civil Engineering Graduate School of Engineering Dhaka University of Engineering and University of Technology (DUET), Gzipur 7-3-1, Hongo, Bunkyo-ku, Tokyo Gazipur-1700, Bangladesh 113-8656 Japan Fax: + 880-2-9204701-02 Fax: +81-3-5841-8506 E-mail: [email protected] E-mail: [email protected] [email protected] Kerati KIJMANAWAT Liqiang MA Transport Planning Department Research Associate Land Transport Division Asian Development Bank Institute Pacific Consultants International 7-5,Sekido 1-Chome, Tamashi Kasumigaseki Bdg.8F 3-2-5 Tokyo 206-8550,Japan Chiyoda-ku, Tokyo 100-6008 Fax: + 81-42-372-6353 Fax: +81-3-3593-4270 E-mail: [email protected] Email: [email protected]

Abstract: The most of countries’ city system has relatively small number of large cities and large number of small cities. Economy of scale can be enjoyed through cost reduction resulting form high demand within large cities. However, people of small cities would have to travel large cities to buy necessary goods and services paying travel cost. Thus, there exist a hierarchical dilemma between demand and supply within system of cities. The objective of this paper is to provide a survey on hierarchical system of cities in East Japan to understand how the consumption of urban goods/services affects the system of cities. A survey on household shopping behavior was conducted to estimate consumption rate. Limited simulations were performed and four levels of hierarchy were found. Another simulation was performed by changing consumption rate to observe the network change of system of cities. Finally, implications and directions of future research are discussed.

Key words: Hierarchical system of cities, consumption rate, goods and services

1. INTRODUCTION

Systems of cities are interacting networks of human economic activities. Economic theories of system of cities explain why production and consumption activities are concentrated in a number of urban areas of different size rather than uniformly distributed space (Abdel- Rahman,H.M. and Anas,A,2004). Casual observation shows that cities differ by their size as well as by the various types of economic activities which they carry on. Research in urban geography finds that larger cities provide more specialized goods and services to the local market and surrounding areas, function as a transportation and wholesale hub for smaller places, and accumulate more capital, financial service provision often concentrating administrative functions for the area in which they lie. People in the big cities enjoy better accessibilities to goods & services, while people in smaller cities have less access to goods & services. People who lived in small city have to travel from their town to larger cities to purchase the goods that do not available in their city. If there are only few cities provide low Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

consumption rate goods, the system can enjoy the reduction in costs due to economy of scale from concentrating the buyers to these few cities. However, people in this system will have to travel longer to do their shopping, thus increase the transportation costs to the whole society. In the contrary, if numerous cities provide all level of goods, the transportation costs can be reduced. But the supplier would face inefficiency from inadequate demand. Thus there exists a hierarchical dilemma within the system of cities and inter-urban transportation network configuration strongly affects the geographic structure of system of cities. In short, it can be said that the reason of existence of hierarchical system of cities as follows: 1. Difference in the needs of access frequency, for example, daily needs, unessential service, shopping, leisure, etc. 2. Difference in the level of economic of agglomeration.

Metropolis

Town

City

Figure 1 Symbolic presentation of Hierarchical System of Cities

This relation among places of different sizes is called the urban hierarchy. In this respect, what is probably the most striking feature of the space-economy is that cities form a hierarchical system exhibiting some regularity in terms of both their size and the array of goods they supply (Henderson, 1974). Growing concerns about system of cities lead to questions about how people congregate in settlements of different sizes and shapes and how these expanding centers of population are connected to each other over the surface of the earth. Most of researchers put their effort into modeling system of cities to explain the formation is of cities. These studies do not pointed out how consumption of goods and services and trade among cities affect large network of system of cities in real world situation. The objective of this study is to provide a survey in system of cities to understand vital questions: how the change in demand for urban service/activities affects the system of cities. To address these issues, as mentioned here, the hierarchical system of cites in East Japan analyzed macroscopically and empirically.

1.2 Study Scope In order to achieve the above objective, the literatures that so focused on analyzing and modeling of system of cities and hierarchical network solving problem were reviewed. To explain system of cities numbers of models have been developed. However, those models can deal with only relatively small number of nodes and do not consider multilevel hierarchy. No study to visualize the system of cities based on behavior of goods and services consumption was found. A methodology to deal with very large scale country wide generalized multilevel hierarchical network was developed by Kerati (2004). This methodology was applied in the estimation of hierarchical network of the system of cities in Japan. In this application study, types of goods and services were categorized in three groups (namely daily product, general products and luxury products) by intuition based on assumed consumption rate of those types of goods and services. This model provided a visualization of hierarchical system of cities in Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

Japan which showed what type of goods and services are provided in each city in there level of hierarchies. As mentioned here, however, to describe existing hierarchical system of cities in Japan, some parameters were assumed intuitively which leads suspicion about the accuracy of this visualization. The interest of this current study was to verify these intuitive assumptions of types of goods and services and consumption rate of those goods from as most as real concern which affect the model immensely. Based on above discussion the study scope of this research was as follows:

• Categorizing of goods and services from as most as real concern rather than intuitive assumptions based on their consumption frequency. A household shopping travel behavior survey was conducted in April, 2006. How many times and which type of goods and services people buy in a week, in a month, in a year or in several years were investigated. • Estimating consumption rate of categorized goods and services using statistical analysis. • Estimating the network of hierarchical system of cities using the categorized goods and services found from survey and consumption rate of those goods and services. • Conducting sensitivity analysis for hierarchical system of cities using different set of categorized goods and services and consumption rate.

This paper consists of several chapters, sections and subsections. The background and the objective of the study are presented in the first chapter. Additionally, the study scope is pointed out. Chapter 2 deals with formulation of the objective function for transport cost of consumers and cost of suppliers to determine the location of hub cities and allocation of non- hub cities to hub cities. Study area is shown in chapter 3. Chapter 4 describes about the survey namely “Household Shopping Behavior”. The preparation of data for the calculation and the data source are described in chapter 5. Chapter 6 demonstrates the simulation results. Subsequently, this chapter discussed the implication of results. Chapter 7 concludes the results from the analysis and its implications. Lastly, directions for future study are proposed.

2. FORMULATION OF OBJECTIVE FUNCTION FOR HIERARCHICAL NETWORK OF SYSTEM OF CITIES

In this Section, the formulation hierarchical network of system of inter-city trade is shown here. As explained earlier, people of small cities would have to travel large cities to buy necessary goods and services which are not available in their own cities paying travel cost. Therefore, there is trade-off relationship between demand and supply. Thus, hierarchical system of cities exists because of difference in the needs of access frequency, for example daily needs, unessential services, shopping, leisure, etc and difference in the level of economic of agglomeration.

2.1 Hierarchical System of Cities Network Formulation Notations

K = Level of hierarchies K ∈{}1,2,3,...Kmax , where Kmax is highest level in the hierarchy TITC = Total individual transport cost for trade Rk = Consumption rate of goods k Pi = Population in city i Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

Cii = Intra-city transportation cost in city i Cij Inter-city transportation cost from city i to city j,C ij usually proportional to the distance from city i to j and can be set to reflect cost of travel time, transport and other factors TSC = Total supplier cost i Uk = Average sales per trip of goods k sales in city i PMk = Profit margin of goods k CF = Annual fixed operation cost of suppliers K α1 = Retail economy of scale for goods k K K X ij = Nodal assignment variable. X ij is equal to 1 if node i is assigned to hub h at hierarchical level K and zero otherwise

NK : set of nodes at level K

H K : set of hubs at level K

2.2 Assumptions in the Formulation of Objective Function To formulate the objective function several assumptions were made. Those assumptions were related to people, transport and trade of goods and services are shown here: Assumptions for people: • People are only residing in cities • People do not migrate between cities Assumptions for transport: • Inter-city transport are connected by highway networks • Intra-city transport is served by local roads & public transport Assumptions for trade: • No distinction in prices of products among cities • The quality and variation of goods are equal everywhere • Cost is the only decision factor for people to choose which city to shop

2.3 Formulation of Objective Function The objective function formulation was to determine cities locations which are providing a certain level k goods. The formulation was comprised of two steps. At first, the hub cities location are determined to minimize the total individual transport cost and total supplier cost for all types of goods. And in the next step, the non-hub cities allocations were performed to the hub cities in objective to minimize the individual disutility of consumers. Each aggregate user will set their goal to only minimize their disutility. The assumption was the system will reach equilibrium when each user can no longer change their destination to improve their utility.

2.3.1 Hub cities location: Minimization of total individual transport cost and total supplier cost for all types of goods and services i) Minimization of total individual transport cost: The first objective of the formulation is to minimize the total individual transportation cost. This is to ensure the accessibility for consumers to their required products and services. Thus minimizing this function would give rise to the productivity and reduce energy consumption.

Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

The formulation of total individual transport cost (TITC) as follows, n n n (1) TITC = ∑ Rk Cii Pi X ii + ∑∑ Rk Cij Pj X ij i=1 i==11j

According to this formulation, since C ij >> C ii , the transportation cost would be minimized if all cities provide all level of goods and services. Thus, this is the push toward self-sufficient cities (no requirement for inter-city transport). ii) Minimization of total supplier cost for all types of goods: The second objective of the formulation was to minimize the total supplier cost for all types of goods. The supplier cost savings can be achieved thorough economic of scope and scale arise from large number of customers. The formulation of total supplier cost (TSC) as follows, σ k 2 i nn35 U ij k TSC=++ CFkiiikjij R PX R P X * (2) ∑∑ ∑ PM ik==11 j = 1 k According to this formulation, the total retailer revenue is dependent on the total number of n customers which described by, N = R k P i + ∑ R k P j . In practice, since the acquisition economy k k j =1 of scale (α2 ) is 01≤≤α2 , the greater the number of customer, the greater the profit.

The objective function can be formulated as the combination of the minimization total individual transportation cost for all people and the minimization the supplier costs of all types goods. The objective function formulation is described below.

F = Min ( δ * TITC + β * TSC ) (3) Subject to K 0 ≤ X ij ≤ 1 and integer for all i, j,K (4) K ∑ X ih = 1 for all i,K (5) h K K X ij ≤ X jj for all i, j,K (6) The first term in the objective function represent total cost for transportation. While the second term represents the total supplier cost. β and δ represent the parameter for relative importance, such that β + δ = 1.

2.3.2 Facility allocation: Minimization of individual disutility The objective of this function is to minimize the disutility of each aggregate user in selecting their shopping destinations. Their disutility consists of 2 factors which are the transportation cost and their retail purchase cost. The formulation for this objective function can be described as

σ −1 nnn1 i F =++Minγη** RPCk i ij RPCX k i ii ii RPCX k j ij ij * U k ()∑∑∑ (7) iij===111

Subject to K 0 ≤ X ij ≤ 1 and integer for all i, j,K (8) K ∑ X ih = 1 for all i,K (9) h Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

K K X ij ≤ X jj for all i, j,K (10) The first term in the objective function represent the individual cost of transportation. While the second term represents the retail purchase cost. γ and η represent the parameter for relative importance, such that γ + η = 1.

K K Constraints (4) & (8) restrict the value of X ij and X jj to 0 and 1. Constraints (5) & (9) ensure that the each node at each level is assigned to one and only one hub. Constraints (6) & (10) enforce that any node may not be assign to location j unless it is a hub of hierarchy K, any nodes at level K can connect to any hub from level K+1 to Kmax.

In order to solve this optimization problem, a hybrid heuristic algorithm between several well known heuristics was adopted, developed by Kerati (2004) to solve the formulation. A hybrid heuristic between Tabu Search and Genetic Algorithm namely M-GATS (Multilevel Genetic Algorithm Tabu Algorithm Search) algorithm to solve the network design problem is devised. The GA component determines the optimal number of hub cities as well as its location; while TS determines the TS determines the allocation of non-hub cities to the hub cities.

3. STUDY AREA

Among of eight regions of Japan (Hokkaido, Tohuku, Kanto, Chubu, Chugoku, Kinki, Shikoku and Kyushu) shown in Figure 2, the Kanto region is Japan's largest plain which lies in the southeastern part of Honshu Island. This region, which includes such key cities as Tokyo, , Kawasaki and , is the most populous region of Japan. The hub of the region—the Tokyo-Yokohama district—is the core of Japan's commerce and industry. The size of Greater Kanto area’s economy accounts for 40 % of total Japanese economy. The satellite suburbs, within about two hours' commuting distance from downtown Tokyo, are expanding, and resulting in the urbanization of a large portion of the Kanto region. Considering these stances, this study interest was focused on this region. Moreover, to observe the affect of Kanto region on the other region’s system of cities, and to observe others region’s affect on Kanto region, Chubu and Tohoku regions was also included in this study since these two regions are the adjacent of Kanto region. The study area divided into 90 life-activity cities or “Seikatsukan” as shown in appendix-4.

Hokkaido

Tohoku Tohoku

Chubu Chubu Chugoku Kanto Kanto

Kinki (Okinawa) Kyushu Shikoku

Figure 2 Regional division map of Japan Figure 3 Selected area of study

Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

4. THE SURVEY ON HOUSEHOLD SHOPPING BEHAVIOR (HSB)

Consumption rate of goods and services depend on necessity, accessibility and availability. For example, perishable goods such as vegetable, meat products and other groceries have the highest consumption rate. People travel to purchase these goods several times per week. Thus most cities have their own food and grocery stores. However, electronics goods, jewelry has low consumption rate and people travel to those cities where these kinds of goods are available. To find out the people’s behavior of shopping frequency a survey was conducted namely “Household Shopping Behavior (HSB) Survey”. Appendix-1 shows the framework of this survey. 4.1 Objective of Survey • To find out the shopping frequency of household: How many times and which type of goods and services people buy in a week, in a month, in a year or in several years

4.2 Usage of the Outcomes of this Survey • To categorize the types of goods and services (K)from real world situation rather than assumption • To calculate the consumption rate (Rk) of each categorized goods and services

4.3 Questionnaire Design and Preliminary Survey Keeping in the consideration the objective of the survey, a questionnaire was designed which was composed of 34 items of goods and services, scale of shopping frequency and shopping location. To check the design of questionnaire and survey procedure, preliminary survey was conducted at Ashikaga city of Tochigi prefecture, and Akabane city of Tokyo prefecture (Figure 5). Based on preliminary survey item of goods and services and scale of shopping frequency was revised and items of goods and services were reduced to 15 from 34 by grouping the goods of similar shopping frequency and shopping location. Appendix-2 shows the list of goods and services and appendix -3 shows the shopping frequency scale.

4.4 Selection of Survey Sites To select survey site a unique principle was set up on the basis of accessibility, population and distance from a large city as follows:

4.4.1 Accessibility To conduct this survey it was important to consider about accessibility to survey site in terms of time and cost to conduct survey.

4.4.2 DID Population To select survey site, DID (Densely Inhabitant District) population was considered to observe whether it affects shopping travel of household.

4.4.3 Distance from Tokyo To find out where and what types goods and services people buy, the location of cities was considered from Tokyo (considering Tokyo is the most influential city other cities).

Kanto region was selected for survey considering transportation cost to access the survey site since survey was conducted from Tokyo. To select survey site, many cities of Kanto region were considered based on DID population and distance from Tokyo (Figure 4), however, three of them were selected considering fictitious diagonal axis. Those are (1) “Ashikaga” Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

city of Tochigi prefecture, 96 km far from Tokyo with 91000 DID population, (2) “Kasama” city of Ibaraki prefecture , 125 km far from Tokyo city with 6000 DID population and (3) “” city of kawakawa Prefecture, 65 km distance from Tokyo with 185000 DID population.(Figure 5).

200000

Atsugi 160000 Kasama Noda Ashikaga Hadano (Ibaraki) (Tochigi) 120000 Chikusei Narita Ashikaga 80000 Isehara Hitachiota

DID Population Choshi 40000 Numata Fujioka Tokyo Moka Tateyama Atsugi Yuki Kasama Shimutsuma 0 Annaka (Kanagawa) 30 60 90 120 150 Distance from Tokyo (km) Figure 4 Selection of survey Figure 5 Location of selected sites

4.5 Survey Result This survey was conducted through direct interview of householder or the householder's spouse in each selected survey site by one group of interviewers. On average, lasted 20 minutes; all most, all of the interviews lasted between 15 and 25 minutes. Total 80 household were participated in this survey. Each survey site was divided into 5 areas for 5 interviewers after checking survey responses for correctness and making the data base of survey, shopping frequency of each goods and services is plotted in graph (Figure 6). In this figure all goods and services are arranged in horizontal axis in the descending order of corresponding average shopping frequency. Shopping frequency is shown in the vertical axis in the unit of times per year. The shopping frequency curve is drawn for each survey site. From graph, it was found that food and beverage have the highest frequency (average frequency is 220 times in a year) as these are perishable goods. And car, electronics goods etc. have lower frequency. Other goods and services like utensils, cloths, and ornaments have decreasing shopping frequency. It can be seen form the curve that the shopping frequency for goods and services are almost similar in all of three survey sites with negligible deviation.

4.6 Comparison with Kerati (2004) Research As it was found that shopping frequency of goods and services have similar trend for every survey site an average shopping frequency curve was drawn (Figure7) and compared with the value of Kerati (2004) research. Table 1 shows the intuitively categorized types of goods and services and assumed consumption rate for each type of goods in Kerati (2004) research. For food and beverage, survey result showed near about same shopping frequency (R = 0.7) with

Table 1Assumed Types of Goods and Consumption Rate (times/day) in Kerati (2004) model

K1 Daily Products (Vegetable, Meat & Poultry, Milk, Consumption Rate, R1=0.7 K2 General Products (Clothing & accessories, Consumption Rate, R2=0.02 K3 Luxury Products (Electronics, Car & parts, Consumption Rate, R3=0.04

Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

Kerati (2004). But for consumption rate of cloths, furniture, electronic goods and cars the assumed value in Kerati (2004) is quite higher than that found in the survey result as shown in Figure 7. ) 1000 1 Shopping Frequency Curve Atsugi Ashikaga Kasama according to Kerati (2004) 100 0.1 (times/day) 10 0.01 Average Shopping Frequency Curve

1 0.001 Shopping Frequency Shopping

0.1 0.0001 p s s t s s e, r, n e e r o s s y n s erage oks r s r, a o t Food v sho d dr tu seum parts rage nsils re es ver i r Bo l llover u e d to eum /pl s er a al rni Food ve l lo a t vi Be Utensilsb u puu M rnamecert/play BooksUt a r le s rm , F O n Television and Be u Mus cer nd pa a o s , pul ge Ornament Te a Bar C F ter Refrigerat Co a Furniture, on r ea Digital Carcamera, BarberC shopFormal dr efri C a

Shopping Frequency Shopping(times/year Frequency w eater R DigitalC camera, S w S Figure 6 Shopping Frequency Curve Figure 7 Comparison with Kerati (2004) research

4.7 Proposed Types of Goods and Services Based on the survey data, statistical t-test was conducted for every pair of goods with 95% confidence limit. Based on t-test results, types of goods and services were proposed to categorize into five groups in terms of consumption rate (shown in Figure 8 and Table 2). To observe, effect of the change in the consumption rate on the hierarchical network of cities, the types of goods and services again categorized into three groups by combining K2 and K3 into one group. K4 and K5 were combined into another group and consumption rate re-estimated. This re-categorization of types of goods and services are shown in Table 3.

1 R1 = 0.6 K1(Food, Beverage) 0.1 K (Books,Utensils) R2 = 0.04 2 (times/day) K (Cloths) 0.01 R3 = 0.012 3 K (Furnitrue,Ornament) 4 R = 0.005 0.001 4 Shopping Frequency Shopping K (Electronic,Car)R5 = 0.0002 0.0001 5 s s il s s , , y s s or ent a arts hop re res eum era, p ten s ture at am /pl Food Book r l d ni r t U a r cam Beverage be u ige Mus Orn and s Fur fr Television r Bar a e C Formal d R Conce igital Ca D weater, pullover S

Figure 8 Proposed types of goods and services and consumption t Table 2 Proposed types of goods and services (K) and consumption rate (Rk) K Types of good and services Consumption

rate(times/day/person)

K1 Food, Beverage R1=0.6

K2 Books, Utensils, Berber shop and beauty parlor R2=0.04

K3 Cloths, Sweater, pullover R3=0.012

K Furniture, Refrigerator, Ornaments, Museum R =0.005 4 4 K5 Electronic goods, car and parts R5=0.0002 Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

Table 2 Revised types of goods and services (K) and consumption rate (Rk) K Types of good and services Consumption rate(times/day)

K1 Food, Beverage R1=0.6 K2 Cloths , Utensils, Barber shop R2=0.1 K3 Furniture, Refrigerator, Electronic goods, car and R4=0.01 parts In this study, both the types of goods and services were used for calculation. The types of goods and services and consumption rate found by this survey, shown in Table 2, is recalled as “Set 1” of R and types of goods and services shown in Table 3 is recalled as “Set 2” of R in the later sections of this paper.

5. DATA PREPARATION

Before the calculation studies, there were several data availability issues needed to be addressed, the major source for data collection was from the Statistic Bureau, Ministry of Public Management, Home Affairs, Posts and Telecommunications, available at http://www.stat.go.jp/english/index.htm

1) Population in city i (Pi):This data was found in Japan Population Census available at http://www.stat.go.jp/english/index.htm. Appendix-5 shows the population distribution of East Japan.

2) Intra-city transportation cost in city i(Cii ) and Inter-city transportation cost from city i to

city j(Cij ) : The intra-city transportation cost is estimated at 500 yen per trip as suggested by Kerati (2004). As for inter-city transport, the travel distance and travel time was determined using highway and expressway network of Japan as described in Appendix-6.

3) Consumption rate of goods k ()Rk : For the consumption rate of goods k, in this study, a survey on Shopping Behavior was conducted and discussed earlier. k 4) Average sales per trip of goods k sales in city i (Ui ): The Average sales per trip of goods i Total annual sales( per year) 1 k sales in city i was calculated by U k = * 365* Pi Rk (trips per day) The total annual sales of retailers’ acquired from Japan Economic Census.

(5)Annual fixed operation cost of suppliers (CF): The annual fixed operation cost of suppliers can be formulated as the summation of the annual payroll, facility rent, debt, and utility costs. However, due to the limitation of data availability, the annual fixed operation cost was estimated as directly proportional to the annual payroll.

6. SIMULATION RESULTS

From the data preparation, calculations on system of cities in the study area were performed. The hierarchical network of system of cities were simulated using the ”Set 1” of R. “Set 2” of R was used for another calculation. The calculation results are shown schematically in Figure 9-10. Figure 9 represents that Kanto region is acting as very strong economic area than other Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

region which reflect the actual situation of East Japan’s system of cities. Four levels of hierarchies were found in this simulation, it was found that all cities provided by food and beverage. Eight cities (, Utsonomiya, Hachioji, , , , Toyota, and ) provided by f R2 types goods of Set 1. Yokohama, Chiba and Omiya of Kanto region provided by R3 types of goods of “Set 1”of R. R4 and R5 types of goods and services provided in the regional center of Tohuku, Kanto and Chubu namely , Tokyo and respectively. However, in this simulation any more hierarchy was not found. Calculation process was stepwise. Hierarchy can be generated until transport cost can be improved. In this optimization calculation, until fourth step, transport cost of calculation was less than the actual situation. In the fifth step i,e for R5 = 0.0002 , the transport cost became higher than the actual cost. It means that the possible number of level of hierarchies is four.

Set 1 of R R1=0.6 4 Levels of Hierarchies R2=0.04 2nd level cities=8 Morioka R3=0.012 3rd level cities=3 R4=0.005 4th level cities=3 R5=0.0002 Niigata Sendai

Kanazawa Nagano Utsonomiya

Omiya Toyota Hachioji Tokyo Nagoya Chiba yokohama Shizuoka Figure 9 Calculation results of system of cities using “Set 1” of R Figure 10 shows the calculation result of “Set 2” of R. In this calculation, 15 cities (, Morioka, , Utsonimya, , Hachioji, Numazu, Shizuoka, Niigata, Nagano, , Toyota, , Kanazawa, ) provided by R2 types of goods and services of “Set 2”. And R3 types of goods of “Set 2" are provided by 6 cities namely, Sendai, Omiya, Tokyo, Chiba, Yokohama, and Nagoya. In comparison with simulation result of “Set 2” and “Set 1” of R, it was found that some of 2nd level cities such as Hachinohe, Morioka,

Hachinohe Set 2 of R 3 Levels of Hierarchies Morioka R1=0.6 2nd level cities=15 Akita R2=0.1 rd R3=0.01 3 level cities=6 Niigata Sendai

Kanazawa Toyama Nagano Fukui Utsonomiya Omiya Toyota Hachioji Tokyo Nagoya Chiba Numazu Hamamatsu Shizuoka yokohama

Figure 10 Calculation results of system of cities using “Set 2” of R

Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

Akita, Maebashi, Numazuin, Hamamatsu, Fukui and Toyama of simulation for “Set 2” became 1st level cities in the simulation for “Set 1” showing more concentric nature of hierarchical system of cities. Moreover, Nagoya, Tokyo and Sendai become in the highest level of hierarchy in “Set 1” concentrating more consumers and minimizing supplier costs. Hence, system of cities has been pushed toward a system where all higher level of goods and services are only available in a single city.

Aomori

“R” assumed by Kerati (2004) 3 Levels of Hierarchies R1=0.6 2nd level cities=12 R2=0.02 3rd level cities=6 R3=0.04

Niigata

Sendai Kanazawa Toyama Nagano Fukui Utsonomiya Toyota Omiya Tokyo Nagoya Chiba Shizuoka yokohama

Figure 11 Calculation results of system of cities from Kerati (2004) research

Figure 11 shows the result of simulation performed by Kerati (2004). It can be observed that there are up to 12 cities that selling R2 types of goods of Table 1 and up to 6 cities providing R3 types of goods of Table1. Though, both of Figure 10 and Figure 11 show three levels of hierarchy, network of system of cities is found different due to difference in consumption rate of goods and services. In comparison between Figure 10 and Figure 11, it can be seen that some cities namely Hachinohe, Morioka, Akita, Hamatsu and Numazu become in lower level hierarchy (Figure 11) when consumption rate of R2 types of goods of “Set 2” of R lowered from 0.1 per capita per day to 0.02 per capita per day in Kerati’s (2004) simulation.

Table 4: Comparison of results among Set 1, Set 2 of R and Kerati (2004) result Hierarchy level Kerati (2004) result Set 2 Set 1 2nd level 12 cities 15 cities 8 cities 3rd level 6 cities 6 cities 3 cities 4th level ------3 cities

Table 4 compares the result found from simulation using Set 1 of R, Set 2 of R and result found from Kerati (2004) research. It is clear that when consumption rate of goods services is lower, system of city become concentric and vise versa. This is because; lower consumption means less number of customers. Supplier will not be interested to provide their goods services everywhere due to diseconomy of scale; they will be interested to locate in higher level of cities. Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

6.1 Implication of the Study This research was conducted to visualize how the hierarchy among cities affected by goods and services consumptions. It showed that destination of people of smaller cities to the higher cities, i.e., where people travel to buy their goods and services from their own city to nearest hub city. This kind tendency revealed the importance of the one region over other region which may play important role in the planning of administrative and regional division. Thus, this study has the implications as follows:

1) In the feasibility/appropriateness of block division in National Land Planning (Kokudo- Keisei Planning). As example, Japan government is considering the divisional re- organization of regions. This study has implication in this regards. East Japan can be divided in different three parts as shown in Figure 12. 2) In the reformation of governmental system (especially the prefecture division) in county system in Japan. 3) In problem of identity disappearance of goods and services provided in each local area and afterthought to the development after high-economic growth era up to now in Japan.

Morioka

Niigata Nagano Sendai Kanazawa Utsonomiya Omiya Toyota Hachioji Tokyo

Nagoya Chiba yokohama Shizuoka

Figure 12 Implication of system of cities of East Japan in appropriateness of block division

7. CONCLUSION

The main objective of this study was to visualize how the demand for goods and services consumption affects the system of cities. And also sensitivity analysis was performed by changing the parameter values. From Figure 9 to11, it can be clearly observed that the hierarchical relationships in East Japan’s system of inter-city trade and consumption of goods and service. In the category of food and beverage, the consumption rate is high but there is low economy scale. Thus the grocery stores would be readily available in most cities to reduce the travel cost of the society. These figures show that all cities have their own grocery stores and supermarket and the people mostly purchase goods in their own cities. Figure 9-11 also show that cloth and accessories is not available in all cities. This means that people who reside in small cities have to travel to larger cities to buy these products. Moreover, these figures show the per capita trade for luxuries products such as electronic goods, cars and parts etc. This clearly indicates the validity of assumptions of this study in hierarchical system of inter-city commerce. It can be seen that the purchase power become concentrate to only the major cities such as Sendai, Tokyo and Nagoya. The people from other region would have to travel to one of these cities to complete their shopping of R4 and R5 types of goods. It can Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007

also be observed that these trade centers are located along the Tokaido region where most people are concentrated. This scenario experiment demonstrates the applicability of the described model in prediction of changes in structure of system of cities after changes in consumption of goods and services.

At last, it can be concluded that, if demand for goods and services consumption become lower, the system of cities are concentric nature and shows more level of hierarchies, since suppliers’ profit maximized by concentric more people in city. Thus, this study showed the four level hierarchical levels in the study area which reflect the actual concentrated system of cities in East Japan.

7.1 Directions of Future Research The current study was the extension of Kerati (2004) research by using revised consumption parameter from the real world situation rather than intuitive assumption. However, there are more parameters which may affect the results significantly. The model can be improved by considering those factors which were neglected before. This study is suggesting the following direction of future research: • In the formulation of the objective function for hub cities locations, for supplier cost, economy of scale parameter is one vital factor. Research can be also extended in this case. • In the Kerati (2004) model migration of population, agglomeration of economy, price and quality of goods, consumer’s preference were not considered. In the future research these can be considered.

Moreover, the research on the system of cites can be extended using same solving methodology in the following way:

Š To incorporate the higher land price in big cities into the cost function. Š To incorporate the industrial production into the trade model.

REFERENCES

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APPENDICES Appendix-1 Framework of the survey Appendix-4 East Japan’s 90 Seikatsukan Survey Strategy Questionnaire Preliminary Main Set up Design Survey Survey

Necessity of Presurvey Survey Survey Selection of Location Site Types •Atsugi Required of goods and •Ashikaga information Services Survey •Kasama Method from survey Shopping Number Frequency Usage of survey Feedback from of Sample

data Shopping presurvey Analysis of Location Survey Data

Appendix-5 East Japan’s Appendix-2 Survey questionnaire Population distribution Types of Goods and Services Shopping Name of 50 Persons/Sq.km or under Shopping Frequency 50-100 Persons/Sq.km Location 100-200 Persons/Sq.km 101 Food(Vegetable,meat,fish) 200-300 Persons/Sq.km 300-500 Persons/Sq.km 102 Beverage(Soft drink,juice,alcohol) 飲 500-1000 Persons/Sq.km 103 Formal dress (Suit,dress shirt, 1000-5000 Persons/Sq.km 5000 Persons/Sq.km or above 104 Casual dress (T-shirt,casual slaks,) 105 Sweater, pullover 106 Utensils 107 Furniture,Refrigerator, 108 Books (Novels) 109 Television

goods 1.Consumer 110 Digital camera,DVD palyer ,Vedio 111 Ornament 112 Car and parts 201 Barber shop/Beauty parlor 202 Concert/play

2.Services 203 Museum Appendix-6 East Japan’s highway and Appendix-3 Scale of shopping frequency expressway network

Shopping Frequency

Every day 1time/year

1time/week 1time/month 1time/5 years 1time/5

years 1time/10 1time/2-3 years 1time/6 months1time/6 2-3 times /week 2-3 times 1time/2 months 1time/2 2-3 times/month 1 time/3 months