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Spatial economies in distribution transports
OMEGA, The Int. JI of Msmt Sci., Vol. 5, No. 1, 1977. PergamonPress.Primed in Great Britain
Spatial Economies in Distribution Transports R LAULAJAINEN Helsinki School of Economics (Received June 1976; in revised form August 1976)
Unit costs of distribution transport (depot ~ customer) are studied using a simulator. Petroleum companies with four spatial distribution parameters---size ( = market share), market area, depot pattern and customer structure--are used as observations. Relevant combinations of the parameters are evaluated with real world data. The unexpectedly small differences between alternatives appear to be due to the dominance of a single urban agglomeration.
PROBLEM IT IS a well established economic doctrine that company unit costs decline as a function of increased scale of operations. The decrease is customarily attributed to production technology and most empirical evidence is related to it. Other aspects such as financing and marketing, with the subdisciplines of advertising, sales promotion, R&D and physical distribution, have received far less attention in this context. Nevertheless, the possibilities offered for savings, e.g. by changes in the spatial intensity of distribution, are obvious. Intensity need not, of course, be the only spatial dimension of unit costs of distribution. In this paper an attempt is made to measure the significance of various spatial distribution strategies for the unit costs of distribution transports. 1 The attempt is based on data on shipments, orders and delivery costs from actual operations. The most crucial spatial aspects of distribution transports, apart from the intensity of operations, are probably the location and extent of delivery areas ( = market area), the number and location of depots and the location and size of customers within delivery areas. Customer size as a spatial concept depends on the observation that, on average, the largest orders with lowest unit costs originate from the largest customers in locations with the largest sales potential. t Distribution transports are defined as shipments from depot to customers. In the narrow meaning they cover only transports in which the vehicle load is, in principle, delivered to several destinations.
67
LaulajainenmSpatial Economies in Distribution Transports The delivery areas and the depots depend on specific decisions made by the company. Specific decisions may also be made as to the size and 'quality' of customers even if there is an element of chance in the actual outcome of sales activity. Consequently, a suitable combination of delivery areas, depots and a priori customers should result in a minimization of company unit costs. Because of the hypothetical internal economies of scale, the combination is viewed against the company size. This approach tells little about company profits, of course. It is possible, for example, that the strategies adopted by several companies may be directed towards the same locations resulting in price competition and decline of profits. The partial nature of the discussion is further stressed by the fact that the study is restricted to a very limited area. This restriction is imposed purely for practical reasons of data collection and analysis. It has the unfortunate result that many of the delivery areas are truncated. Because of the partial nature of the discussion, there appears to be little reason to seek out a minimum cost strategy. Instead, the unit costs of actual distribution strategies or alternative strategies worthy of serious consideration are discussed. The latter in addition to the random dement in customer structure, implies that actual accounting data from existing companies has to be rearranged. This is done using a Monte Carlo simulator, the primary analytical device of the study.
SIMULATOR The Monte Carlo simulator is used here to produce unit cost data on companies using various distribution strategies. Due to heavy resource requirements, the simulator has not been tested with historical data but relies solely on the critical assessments of the staff of distribution companies. The simulator is static in the sense that an order set is generated in tote before it is delivered and that it is delivered completely before a new set is generated (Fig. 1). Spatial location in the Study Area is approximated by a square net. The simulator's road net is based on this square net. The flowchart of the simulator needs comment: in the customer generator the probability of the company having customers in a square equals the total sales volume of the square for all companies. The company market share must fall within certain bounds tied to the total market share of the company. The bounds get narrower as the total sales volume for all companies within the square grows. In squares with very small sales the indivisibility of customers is accounted for by assuming a market share of 100 ~ in every n 'h square selected. Two types of customers are used. For one (service stations) a certain threshold size in a square is required. 68
Omega, Vol. 5, No. 1
ROUTE CONSTRUCTOR
CUSTOMER GENERATOR
ORDER GENERATOR
TMS
=
TOTAL MARKET SHARE EMPLOYS RANDOM NUMBER GENERATOR
FIG. 1. Flowchart of the simulator.
In the order generator the total market share allocated by the customer generator is rounded so that the subsequent order volume is an exact multiple of the loading capacity of a large truck (see below). The square selection is proportional to the company sales potential in the square allocated by the customer generator. The order size is a function of the total sales volume of the square for all companies and the type of customer served. All orders originating from a particular square are aggregated to a whole. It is assumed that these orders are of equal size. Variation in order size results thereafter only from the variation between squares (with varying shares of the type of customers). All orders are assumed to be multiples of 1.5 m 3. This simplification obviates the need to consider the vehicle loading problem with different product qualities. For every company five customer sets and for every customer set five order sets are generated. All input values for a particular customer set and order set are identical except for the seed numbers of random number generators. Every 69
Laulajainen--Spatial Economies in Distribution Transports customer set represents the outcome of fictitious sales activity and every order set a normal working day. The route constructor attempts to minimize the total unit costs of delivery trucks. It is based on the following principles derived from actual trucking rates: I. no partially loaded trucks are allowed; 2. travel covered by trucks shall be minimized; 3. unit costs of a large truck are usually lower than those of a small truck (half the size of the large truck); 4. unit costs of a small truck can, however, be lower if deliveries are small and made close to the depot. Orders from a square are delivered by as many large trucks as the order volume allows. If the remaining volume is sufficient to load a small truck fully and, in addition, if the square is sufficiently close to the depot, within what is called here a critical distance, a route is also formed for this. The Clarke-Wright savings criterion is applied for the remaining orders and squares. These routes will be driven by a large truck if a single square on the route is beyond the critical distance. Otherwise a small truck is used. Both sizes of truck are available in sufficient numbers but only loaded trucks are included in cost calculations.
CASE The case to be studied has been selected from distribution transports of petroleum products in Finland--'clean' products in particular. The selection is conditioned by the fact that in Finland the continued operation of companies dealing primarily in clean products depends decisively on transportation economies. In addition, delivery of clean products implies typical distribution transports. Central Finland functions as the Study Area (Fig. 2). It has been selected for the following reasons: 1. Central Finland's share in the total sales of clean products is approx 5 ~o and as such is of marginal significance to coastal operations. In addition, since there are no small coastal depots because greater economy is achieved by reducing the number of depots than by reducing their size, 2 the discussion can start from the gates of oil refineries and coastal depots and at the same time maintain reasonable correspondence with actual cost calculations; 2. Central Finland is a sufficiently extensive area to allow for measurable differences in unit costs between spatially differentiated companies; 3. Central Finland is sufficiently far from the coast for the existence of an inland depot to be a relevant possibility. z This opinion is substantiated by most of the statements made by the staffs of distribution companies. 7O
Omega, Vol. 5, No. 1
i KOKKOLA
•> ,,\ \ \x
(3 '~'x
JYV~SK' ! I,"
t
r
i
i l/ "',, //¢ ¢/ / POR¥O0 INKI
0
K~
• REFINERY • DEPOT --RAILROAD - - - ROAD - ' - CENTRAL F I N L A N D
1(~0
FIe. 2. Central Finland in the Finnish petroleum transportation system in the early
1970's. In the early 1970's, the period under discussion, there were ten companies operating in Central Finland. Their market shares varied roughly between 5 and 2 5 ~ . As suggested above, the three spatial distribution parameters-market area, depots and customer structure--were, at least partly, a function of market share, here used as a proxy for company size, a factor with embedded spatial dimension. All the companies operated in the whole of Central Finland. Only half a decade earlier, however, two of the small companies had restricted their operations to the southern parts of the region. Four of the companies, the largest and the oldest ones, had depots in Jyv~iskyl~i (40 ~ of regional sales). They and four other companies also had depots in Helsinki and Kokkola-in Kokkola probably only rented storage space. The two smallest companies had depots in Helsinki only. The smallest companies either had no or only a few service stations among their customers, the virtue of the service stations being their large order size and 45 ~ share of the total market. In total, there was a notable variety in distribution strategies. It seems a priori clear that the internal economies of scale arising from high spatial intensity of operations favor companies with a large market share. To achieve a high spatial intensity it is not imperative, however, to have a large 71
Laulajainen--Spatial Economies in Distribution Transports overall market share. It is sufficient to have a large share in a limited area with reasonable sales potential, as exemplified by some of the small companies in the late 1960's. So, the relevant question is more the absolute magnitude o f the internal economies than their qualitative existence. The answer serves as a clue to the intriguing problem o f freedom o f entry to the market. The selection o f the depots used also appears obvious in the qualitative sense. A limited scale o f operations was not sufficient to cover the fixed costs o f running a depot in Jyv~iskyl~i or in Kokkola. Again, the relevant question is the quantitative impact o f deleting these locations and, in the case o f Jyviiskyl~i, o f variable depot throughput. The first question becomes relevant e.g. for a growing c o m p a n y which up to now has operated only in the southern part o f Central Finland from a depot in Helsinki. F o r a c o m p a n y having a depot in Jyv~iskyl~i the P o r v o o refinery offered a low-cost alternative source for between depot transfers, a The outcome o f customer structure is straightforward in the sense that, on average, service stations place larger orders than 'other customers', thus implying a lower unit cost. Unfortunately they usually require some kind o f financial involvement by the supply company, which probably offsets the saving in distribution costs. The choice whether to supply the service stations or not applied only to a small c o m p a n y , however. They could not be neglected by larger companies. This discussion is consolidated into five types o f companies to be simulated (Table 1). They represent the range o f spatial distribution strategies applied or TABLE 1. ALTERNATIVE DISTRIBUTION STRATEGIES
Company Market share Thruput type input output I of Jl/i % % 1
2 3 4 5
10 15 20 25 30 5 10 10 20 20 30 30
8.4 13-9 19-5 23.9 27-8 2-8 8.4 8.4 19.5 16"7 27.8 29-0
0 0 0 0 0 0 0 0 100 140 100 140
Market area Central Finland Central Finland Central Finland Central Finland Central Finland Jl~i with surr. Central Finland Central Finland Central Finland Central Finland Central Finland Central Finland
Depots
Unit cost a Customers 2 (Fmk/m 3)
Hki, Kla Hki, Kla Hki, Kla Hki, Kla Hki, Kla Hki Hki, Kla Hki Hki, Kla, Jl~i Hki, Kla, Jl~i Hki, Kla, Jl~i Hki, Kla, Jl/i
1, 2 1, 2 1, 2 1, 2 1, 2 2 2 2 1, 2 1, 2 1, 2
1, 2
25.97 25.72 25'49 25.05 25.04 25.22 26.39 29.14 28-67 28.90 26.41 27.91
i Output shares with identical input shares may vary due to rounding by the order generator. 2 1 = service stations, 2 = other types of customer. 3 Only company averages are given. a Because the prices of domestic products are maintained level with those of imports, domestic and imported products can be considered substitutes. 72
Omega, 1Ioi. 5, No. 1 applicable in the early 1970's and shortly before. Type 1 measures the impact of mere company size. Type 2 challenges the undifferentiated economies of scale with a concentrated market area and consequent depot selection. Type 3 compared with type 4 approximates the significance of the Kokkola depot while type 5 compared with the equal-sized companies of type 1 evaluates the Jyv~iskyl5 depot. Lastly, type 3 compared with the equal-sized company of type 1, measures the outcome of not supplying service stations. No simulated company is a strict replica of an actual company, of course. However, only those of type 1 with an input market share of 20-30~ are completely fictitious, though plausible companies. Quantitative evaluation of the strategies is based on cost data from delivery transportation and such transfer and storage costs as a~e necessary to compare the alternatives. By taking the refinery/coastal depot gate as a source, two alternative transport chains are obtained: 1. Porvoo refinery Aail ~ Jyv~iskyl~idepot road~ customer. 2. Helsinki/Kokkola depot ro~d ~-customer. The transportation rates apply for road and rail shipments in 1973. Trucking rates are assumed valid for both owned and rented trucks. Preliminary simulations suggested that to minimize trucking costs only one truck size (large) should be used. Additional sea freight to Kokkola and the capital cost for winter storage there can be safely estimated. At the Jyv~iskyl~tdepot only costs variable at 2-3 months' notice, for example wages, are taken into account. The empirical data basis of the customer generator, 1800 deliveries in 1963, is calibrated to correspond approximately to one working day in the early 1970's. Data for the order generator, 2500 orders in 1970 and 1971, are considered valid as such. The route constructor necessitates advance determination of depot delivery areas. The border between Helsinki and Kokkola is, in principle, equidistant from both depots. To allow for additional sea freight and winter storage, distances from Kokkola are, however, increased by 20 km. The optional Jyv~iskyl~i delivery area comprises as many squares as necessary as close to Jyv~iskyl~i as possible so that the desired depot throughput is reached.
RESULTS The spatially undifferentiated scale economies exemplified by type 1 change linearly and are of the order of 4 ~o in the 10--30~ range of input market share (Table 1 and Fig. 3). By concentrating operations to the parts of central Finland with the largest sales potential and most 'coastal' location, an overall input market share of 5 ~ by type 2 gives the same unit cost as the undifferentiated company with a share of 20-25 ~. The overall market share of 5 ~ corresponds 73
Laulajainen--Spatial Economies in Distribution Transports
MK/CU.M 30
x
2.5
'
~
160 IO
TYPE I II 2
X
~
x
'
260 2'0
• TYPE 3 O II 4
CU.MI DAY 3'0
°/o MARKET SHARE
• TYPE SilO0 A , 51140
FIe. 3. Unit cost as a function of the four spatial competition parameters. Only company averages are indicated.
to a local share of 10-12 %. The cost of distribution transport does not seriously deter entry to the petroleum market. The existence of a depot in Kokkola is a strong asset for a company of type 3 operating all over Central Finland, as the unit cost of type 4 is 10 ~o higher. The higher cost cannot be completely avoided, however. When a small company of type 2 grows larger it must, at some phase, extend its market area. Unless the extension takes pla~ simultaneously on the west coast and in Central Finland there is inevitably a period during which shipments to northern Central Finland are not yet sufficient to support depot operations on the west coast. The unexpected outcome of the study is the high unit cost of type 5 companies, particularly bearing in mind that no fixed costs for the Jyviiskyl~ depot are included and that alternative strategies of type 1 with 5-10 ~o lower unit costs were not employed in actual operations. The relatively high rail freight to the Jyv[iskylii depot, in fact two-thirds of the corresponding trucking rate, is the major reason for the cost level in type 5. The hypothetical remedy, scale economy from larger throughput at Jyv~iskyli~, is lost through the costs of delivering to a wider market. One argument for the existence of type 5 can be found in the length of the planning period. For example, since 1973 the road freight rates have increased compared to rail rates and the cost drawback of the Jyv~iskylii depot has almost disappeared. The Jyviiskyl~ depot also derives direct benefit from two other factors which are, however, more difficult to express in money terms, i.e. shorter delivery time implying better service to customers and the fact that deliveries are made within the normal working day of truck drivers. The last question, that of customer structure, proves relatively insignificant 74
Omega, Vol. 5, No. 1
in the sense of distribution unit cost. The unit cost of type 3 is less than 2 higher than that of an equalsized company of type 1. In general, differences between the alternatives are probably smaller than expected. The major reason seems to be the relative importance of Jyviiskyl~i as a potential market with the result that it is included in all distribution strategies and it clearly dominates them. The dominant role of urban agglomerations, also being a factor elsewhere in Finland, as it is in many other countries as well, the concept of relative insignificance of the unit cost of distribution transports to alternative spatial distribution strategies can probably be extended beyond the borders of Central Finland.
CONCLUSION In this paper an attempt was made to measure the significance of various spatial distribution strategies to the unit cost of distribution transports. The main analytical device was a simulator. Transportation of clean petroleum products in Central Finland in the early 1970's was used as the framework of the simulations and as the empirical data basis, Differences in unit cost between relevant distribution strategies were at most 10 ~o. Even then the high-cost companies could be shown to represent a transitory phase or to benefit from items not included to the calculations. In particular, the small size of a company was not necessarily a barrier to low-cost distribution transport. The heavy concentration of market potential to a single location was probably the decisive reason for the conclusions and a factor of general relevance.
ACKNOWLEDGEMENT Acknowledgement is made to the Petroleum Companies operating in Central Finland for supplying the necessary data. The computer staff of The Helsinki School of Economics was of invaluable help in several phases of designing the simulator. Professors Pertti Jiirvinen, Tampere; Olli Lokki, Helsinki; and Yrj6 Sepp~tl~i, Helsiaki have commented on the general setting of the study. The figures were drawn by Mrs. Eeva Kallioniemi. This particular paper, being part of a larger project, was supported by The Neste Foundation and The Niilo Helander Foundation.
REFERENCES 1. BAINJS (1965) Barriers to New Competition. Harvard University Press, Cambridge. 2. CLARK~G and WRIOrlTJW (1964) Scheduling of vehicles from a central depot to a number of delivery points. Ops Res. 12(4), 568-581. 75
Laulajainen--Spatial Economies in Distribution Transports 3. DOLLCL (1973) A preliminary simulation study of the delivery problem in an urban area. Centre of Transportation Studies, Working paper No. 10, The University of British Columbia, Vancouver. 4. DUGUZDAM and Moss CG (1971) Reorganizing of sales and distribution system. Opl Res. 22, 77-92. 5. EILON S, WATSON-GANDYCDT and CHRISTOFIDESN (1971) Distribution Management: Mathematical Modelling and Practical Analysis. Griffin, London. 6. GRILICHESZ and RINGSTADV (1971) Economies of Scale and the Production Function, an Econometric Study of Norwegian Manufacturing Establishment Data. North-Holland, Amsterdam. 7. LAULAJAINENR (1973) An entrepreneurial view of transportation. Geografiska Annaler 55B(2), 106-120. 8. SILBERSTONA 0973) Economies of scale in theory and practice. In Readings in Applied Microeconomics. (Eds. WAGNERL and BALTAZZISN). Open University Press, London. 9. SUSSAMSJE (1971) Efficient Road Transport Scheduling. Gower, London. ADDRESS FOR CORRESPONDENCE:
Professor R Laulajainen, Topeliuksenkatu 7A4, 00250
Helsinki 25, Finland.
76
Spatial Economies in Distribution Transports R LAULAJAINEN Helsinki School of Economics (Received June 1976; in revised form August 1976)
Unit costs of distribution transport (depot ~ customer) are studied using a simulator. Petroleum companies with four spatial distribution parameters---size ( = market share), market area, depot pattern and customer structure--are used as observations. Relevant combinations of the parameters are evaluated with real world data. The unexpectedly small differences between alternatives appear to be due to the dominance of a single urban agglomeration.
PROBLEM IT IS a well established economic doctrine that company unit costs decline as a function of increased scale of operations. The decrease is customarily attributed to production technology and most empirical evidence is related to it. Other aspects such as financing and marketing, with the subdisciplines of advertising, sales promotion, R&D and physical distribution, have received far less attention in this context. Nevertheless, the possibilities offered for savings, e.g. by changes in the spatial intensity of distribution, are obvious. Intensity need not, of course, be the only spatial dimension of unit costs of distribution. In this paper an attempt is made to measure the significance of various spatial distribution strategies for the unit costs of distribution transports. 1 The attempt is based on data on shipments, orders and delivery costs from actual operations. The most crucial spatial aspects of distribution transports, apart from the intensity of operations, are probably the location and extent of delivery areas ( = market area), the number and location of depots and the location and size of customers within delivery areas. Customer size as a spatial concept depends on the observation that, on average, the largest orders with lowest unit costs originate from the largest customers in locations with the largest sales potential. t Distribution transports are defined as shipments from depot to customers. In the narrow meaning they cover only transports in which the vehicle load is, in principle, delivered to several destinations.
67
LaulajainenmSpatial Economies in Distribution Transports The delivery areas and the depots depend on specific decisions made by the company. Specific decisions may also be made as to the size and 'quality' of customers even if there is an element of chance in the actual outcome of sales activity. Consequently, a suitable combination of delivery areas, depots and a priori customers should result in a minimization of company unit costs. Because of the hypothetical internal economies of scale, the combination is viewed against the company size. This approach tells little about company profits, of course. It is possible, for example, that the strategies adopted by several companies may be directed towards the same locations resulting in price competition and decline of profits. The partial nature of the discussion is further stressed by the fact that the study is restricted to a very limited area. This restriction is imposed purely for practical reasons of data collection and analysis. It has the unfortunate result that many of the delivery areas are truncated. Because of the partial nature of the discussion, there appears to be little reason to seek out a minimum cost strategy. Instead, the unit costs of actual distribution strategies or alternative strategies worthy of serious consideration are discussed. The latter in addition to the random dement in customer structure, implies that actual accounting data from existing companies has to be rearranged. This is done using a Monte Carlo simulator, the primary analytical device of the study.
SIMULATOR The Monte Carlo simulator is used here to produce unit cost data on companies using various distribution strategies. Due to heavy resource requirements, the simulator has not been tested with historical data but relies solely on the critical assessments of the staff of distribution companies. The simulator is static in the sense that an order set is generated in tote before it is delivered and that it is delivered completely before a new set is generated (Fig. 1). Spatial location in the Study Area is approximated by a square net. The simulator's road net is based on this square net. The flowchart of the simulator needs comment: in the customer generator the probability of the company having customers in a square equals the total sales volume of the square for all companies. The company market share must fall within certain bounds tied to the total market share of the company. The bounds get narrower as the total sales volume for all companies within the square grows. In squares with very small sales the indivisibility of customers is accounted for by assuming a market share of 100 ~ in every n 'h square selected. Two types of customers are used. For one (service stations) a certain threshold size in a square is required. 68
Omega, Vol. 5, No. 1
ROUTE CONSTRUCTOR
CUSTOMER GENERATOR
ORDER GENERATOR
TMS
=
TOTAL MARKET SHARE EMPLOYS RANDOM NUMBER GENERATOR
FIG. 1. Flowchart of the simulator.
In the order generator the total market share allocated by the customer generator is rounded so that the subsequent order volume is an exact multiple of the loading capacity of a large truck (see below). The square selection is proportional to the company sales potential in the square allocated by the customer generator. The order size is a function of the total sales volume of the square for all companies and the type of customer served. All orders originating from a particular square are aggregated to a whole. It is assumed that these orders are of equal size. Variation in order size results thereafter only from the variation between squares (with varying shares of the type of customers). All orders are assumed to be multiples of 1.5 m 3. This simplification obviates the need to consider the vehicle loading problem with different product qualities. For every company five customer sets and for every customer set five order sets are generated. All input values for a particular customer set and order set are identical except for the seed numbers of random number generators. Every 69
Laulajainen--Spatial Economies in Distribution Transports customer set represents the outcome of fictitious sales activity and every order set a normal working day. The route constructor attempts to minimize the total unit costs of delivery trucks. It is based on the following principles derived from actual trucking rates: I. no partially loaded trucks are allowed; 2. travel covered by trucks shall be minimized; 3. unit costs of a large truck are usually lower than those of a small truck (half the size of the large truck); 4. unit costs of a small truck can, however, be lower if deliveries are small and made close to the depot. Orders from a square are delivered by as many large trucks as the order volume allows. If the remaining volume is sufficient to load a small truck fully and, in addition, if the square is sufficiently close to the depot, within what is called here a critical distance, a route is also formed for this. The Clarke-Wright savings criterion is applied for the remaining orders and squares. These routes will be driven by a large truck if a single square on the route is beyond the critical distance. Otherwise a small truck is used. Both sizes of truck are available in sufficient numbers but only loaded trucks are included in cost calculations.
CASE The case to be studied has been selected from distribution transports of petroleum products in Finland--'clean' products in particular. The selection is conditioned by the fact that in Finland the continued operation of companies dealing primarily in clean products depends decisively on transportation economies. In addition, delivery of clean products implies typical distribution transports. Central Finland functions as the Study Area (Fig. 2). It has been selected for the following reasons: 1. Central Finland's share in the total sales of clean products is approx 5 ~o and as such is of marginal significance to coastal operations. In addition, since there are no small coastal depots because greater economy is achieved by reducing the number of depots than by reducing their size, 2 the discussion can start from the gates of oil refineries and coastal depots and at the same time maintain reasonable correspondence with actual cost calculations; 2. Central Finland is a sufficiently extensive area to allow for measurable differences in unit costs between spatially differentiated companies; 3. Central Finland is sufficiently far from the coast for the existence of an inland depot to be a relevant possibility. z This opinion is substantiated by most of the statements made by the staffs of distribution companies. 7O
Omega, Vol. 5, No. 1
i KOKKOLA
•> ,,\ \ \x
(3 '~'x
JYV~SK' ! I,"
t
r
i
i l/ "',, //¢ ¢/ / POR¥O0 INKI
0
K~
• REFINERY • DEPOT --RAILROAD - - - ROAD - ' - CENTRAL F I N L A N D
1(~0
FIe. 2. Central Finland in the Finnish petroleum transportation system in the early
1970's. In the early 1970's, the period under discussion, there were ten companies operating in Central Finland. Their market shares varied roughly between 5 and 2 5 ~ . As suggested above, the three spatial distribution parameters-market area, depots and customer structure--were, at least partly, a function of market share, here used as a proxy for company size, a factor with embedded spatial dimension. All the companies operated in the whole of Central Finland. Only half a decade earlier, however, two of the small companies had restricted their operations to the southern parts of the region. Four of the companies, the largest and the oldest ones, had depots in Jyv~iskyl~i (40 ~ of regional sales). They and four other companies also had depots in Helsinki and Kokkola-in Kokkola probably only rented storage space. The two smallest companies had depots in Helsinki only. The smallest companies either had no or only a few service stations among their customers, the virtue of the service stations being their large order size and 45 ~ share of the total market. In total, there was a notable variety in distribution strategies. It seems a priori clear that the internal economies of scale arising from high spatial intensity of operations favor companies with a large market share. To achieve a high spatial intensity it is not imperative, however, to have a large 71
Laulajainen--Spatial Economies in Distribution Transports overall market share. It is sufficient to have a large share in a limited area with reasonable sales potential, as exemplified by some of the small companies in the late 1960's. So, the relevant question is more the absolute magnitude o f the internal economies than their qualitative existence. The answer serves as a clue to the intriguing problem o f freedom o f entry to the market. The selection o f the depots used also appears obvious in the qualitative sense. A limited scale o f operations was not sufficient to cover the fixed costs o f running a depot in Jyv~iskyl~i or in Kokkola. Again, the relevant question is the quantitative impact o f deleting these locations and, in the case o f Jyviiskyl~i, o f variable depot throughput. The first question becomes relevant e.g. for a growing c o m p a n y which up to now has operated only in the southern part o f Central Finland from a depot in Helsinki. F o r a c o m p a n y having a depot in Jyv~iskyl~i the P o r v o o refinery offered a low-cost alternative source for between depot transfers, a The outcome o f customer structure is straightforward in the sense that, on average, service stations place larger orders than 'other customers', thus implying a lower unit cost. Unfortunately they usually require some kind o f financial involvement by the supply company, which probably offsets the saving in distribution costs. The choice whether to supply the service stations or not applied only to a small c o m p a n y , however. They could not be neglected by larger companies. This discussion is consolidated into five types o f companies to be simulated (Table 1). They represent the range o f spatial distribution strategies applied or TABLE 1. ALTERNATIVE DISTRIBUTION STRATEGIES
Company Market share Thruput type input output I of Jl/i % % 1
2 3 4 5
10 15 20 25 30 5 10 10 20 20 30 30
8.4 13-9 19-5 23.9 27-8 2-8 8.4 8.4 19.5 16"7 27.8 29-0
0 0 0 0 0 0 0 0 100 140 100 140
Market area Central Finland Central Finland Central Finland Central Finland Central Finland Jl~i with surr. Central Finland Central Finland Central Finland Central Finland Central Finland Central Finland
Depots
Unit cost a Customers 2 (Fmk/m 3)
Hki, Kla Hki, Kla Hki, Kla Hki, Kla Hki, Kla Hki Hki, Kla Hki Hki, Kla, Jl~i Hki, Kla, Jl~i Hki, Kla, Jl~i Hki, Kla, Jl/i
1, 2 1, 2 1, 2 1, 2 1, 2 2 2 2 1, 2 1, 2 1, 2
1, 2
25.97 25.72 25'49 25.05 25.04 25.22 26.39 29.14 28-67 28.90 26.41 27.91
i Output shares with identical input shares may vary due to rounding by the order generator. 2 1 = service stations, 2 = other types of customer. 3 Only company averages are given. a Because the prices of domestic products are maintained level with those of imports, domestic and imported products can be considered substitutes. 72
Omega, 1Ioi. 5, No. 1 applicable in the early 1970's and shortly before. Type 1 measures the impact of mere company size. Type 2 challenges the undifferentiated economies of scale with a concentrated market area and consequent depot selection. Type 3 compared with type 4 approximates the significance of the Kokkola depot while type 5 compared with the equal-sized companies of type 1 evaluates the Jyv~iskyl5 depot. Lastly, type 3 compared with the equal-sized company of type 1, measures the outcome of not supplying service stations. No simulated company is a strict replica of an actual company, of course. However, only those of type 1 with an input market share of 20-30~ are completely fictitious, though plausible companies. Quantitative evaluation of the strategies is based on cost data from delivery transportation and such transfer and storage costs as a~e necessary to compare the alternatives. By taking the refinery/coastal depot gate as a source, two alternative transport chains are obtained: 1. Porvoo refinery Aail ~ Jyv~iskyl~idepot road~ customer. 2. Helsinki/Kokkola depot ro~d ~-customer. The transportation rates apply for road and rail shipments in 1973. Trucking rates are assumed valid for both owned and rented trucks. Preliminary simulations suggested that to minimize trucking costs only one truck size (large) should be used. Additional sea freight to Kokkola and the capital cost for winter storage there can be safely estimated. At the Jyv~iskyl~tdepot only costs variable at 2-3 months' notice, for example wages, are taken into account. The empirical data basis of the customer generator, 1800 deliveries in 1963, is calibrated to correspond approximately to one working day in the early 1970's. Data for the order generator, 2500 orders in 1970 and 1971, are considered valid as such. The route constructor necessitates advance determination of depot delivery areas. The border between Helsinki and Kokkola is, in principle, equidistant from both depots. To allow for additional sea freight and winter storage, distances from Kokkola are, however, increased by 20 km. The optional Jyv~iskyl~i delivery area comprises as many squares as necessary as close to Jyv~iskyl~i as possible so that the desired depot throughput is reached.
RESULTS The spatially undifferentiated scale economies exemplified by type 1 change linearly and are of the order of 4 ~o in the 10--30~ range of input market share (Table 1 and Fig. 3). By concentrating operations to the parts of central Finland with the largest sales potential and most 'coastal' location, an overall input market share of 5 ~ by type 2 gives the same unit cost as the undifferentiated company with a share of 20-25 ~. The overall market share of 5 ~ corresponds 73
Laulajainen--Spatial Economies in Distribution Transports
MK/CU.M 30
x
2.5
'
~
160 IO
TYPE I II 2
X
~
x
'
260 2'0
• TYPE 3 O II 4
CU.MI DAY 3'0
°/o MARKET SHARE
• TYPE SilO0 A , 51140
FIe. 3. Unit cost as a function of the four spatial competition parameters. Only company averages are indicated.
to a local share of 10-12 %. The cost of distribution transport does not seriously deter entry to the petroleum market. The existence of a depot in Kokkola is a strong asset for a company of type 3 operating all over Central Finland, as the unit cost of type 4 is 10 ~o higher. The higher cost cannot be completely avoided, however. When a small company of type 2 grows larger it must, at some phase, extend its market area. Unless the extension takes pla~ simultaneously on the west coast and in Central Finland there is inevitably a period during which shipments to northern Central Finland are not yet sufficient to support depot operations on the west coast. The unexpected outcome of the study is the high unit cost of type 5 companies, particularly bearing in mind that no fixed costs for the Jyviiskyl~ depot are included and that alternative strategies of type 1 with 5-10 ~o lower unit costs were not employed in actual operations. The relatively high rail freight to the Jyv[iskylii depot, in fact two-thirds of the corresponding trucking rate, is the major reason for the cost level in type 5. The hypothetical remedy, scale economy from larger throughput at Jyv~iskyli~, is lost through the costs of delivering to a wider market. One argument for the existence of type 5 can be found in the length of the planning period. For example, since 1973 the road freight rates have increased compared to rail rates and the cost drawback of the Jyv~iskylii depot has almost disappeared. The Jyviiskyl~ depot also derives direct benefit from two other factors which are, however, more difficult to express in money terms, i.e. shorter delivery time implying better service to customers and the fact that deliveries are made within the normal working day of truck drivers. The last question, that of customer structure, proves relatively insignificant 74
Omega, Vol. 5, No. 1
in the sense of distribution unit cost. The unit cost of type 3 is less than 2 higher than that of an equalsized company of type 1. In general, differences between the alternatives are probably smaller than expected. The major reason seems to be the relative importance of Jyviiskyl~i as a potential market with the result that it is included in all distribution strategies and it clearly dominates them. The dominant role of urban agglomerations, also being a factor elsewhere in Finland, as it is in many other countries as well, the concept of relative insignificance of the unit cost of distribution transports to alternative spatial distribution strategies can probably be extended beyond the borders of Central Finland.
CONCLUSION In this paper an attempt was made to measure the significance of various spatial distribution strategies to the unit cost of distribution transports. The main analytical device was a simulator. Transportation of clean petroleum products in Central Finland in the early 1970's was used as the framework of the simulations and as the empirical data basis, Differences in unit cost between relevant distribution strategies were at most 10 ~o. Even then the high-cost companies could be shown to represent a transitory phase or to benefit from items not included to the calculations. In particular, the small size of a company was not necessarily a barrier to low-cost distribution transport. The heavy concentration of market potential to a single location was probably the decisive reason for the conclusions and a factor of general relevance.
ACKNOWLEDGEMENT Acknowledgement is made to the Petroleum Companies operating in Central Finland for supplying the necessary data. The computer staff of The Helsinki School of Economics was of invaluable help in several phases of designing the simulator. Professors Pertti Jiirvinen, Tampere; Olli Lokki, Helsinki; and Yrj6 Sepp~tl~i, Helsiaki have commented on the general setting of the study. The figures were drawn by Mrs. Eeva Kallioniemi. This particular paper, being part of a larger project, was supported by The Neste Foundation and The Niilo Helander Foundation.
REFERENCES 1. BAINJS (1965) Barriers to New Competition. Harvard University Press, Cambridge. 2. CLARK~G and WRIOrlTJW (1964) Scheduling of vehicles from a central depot to a number of delivery points. Ops Res. 12(4), 568-581. 75
Laulajainen--Spatial Economies in Distribution Transports 3. DOLLCL (1973) A preliminary simulation study of the delivery problem in an urban area. Centre of Transportation Studies, Working paper No. 10, The University of British Columbia, Vancouver. 4. DUGUZDAM and Moss CG (1971) Reorganizing of sales and distribution system. Opl Res. 22, 77-92. 5. EILON S, WATSON-GANDYCDT and CHRISTOFIDESN (1971) Distribution Management: Mathematical Modelling and Practical Analysis. Griffin, London. 6. GRILICHESZ and RINGSTADV (1971) Economies of Scale and the Production Function, an Econometric Study of Norwegian Manufacturing Establishment Data. North-Holland, Amsterdam. 7. LAULAJAINENR (1973) An entrepreneurial view of transportation. Geografiska Annaler 55B(2), 106-120. 8. SILBERSTONA 0973) Economies of scale in theory and practice. In Readings in Applied Microeconomics. (Eds. WAGNERL and BALTAZZISN). Open University Press, London. 9. SUSSAMSJE (1971) Efficient Road Transport Scheduling. Gower, London. ADDRESS FOR CORRESPONDENCE:
Professor R Laulajainen, Topeliuksenkatu 7A4, 00250
Helsinki 25, Finland.
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