MULTIMODAL INVESTMENT ANALYSIS METHODOLOGY PHASE ONE: THE CONCEPTUAL MODEL

PART VII: FREIGHT TRANSPORTATION

CHACTERISTICS

As explained by Coyle, Bardi and Novack (1), freight transportation demand is derived from demand by customers for the products carried. The cost of transportation then becomes part of the landed cost of the product, affecting both the demand for the product at a specific location as well as demand for the particular transportation service. The characteristics of freight transportation are time, capability, accessibility, reliability, and security.

Transit time is related to the cost of providing the transportation service and also to inventory carrying cost. For example, high-speed, high-cost transportation will permit lower average inventories; the trade-off of the cost increase in transportation must be compared with the potential savings in inventory carrying costs.

The capability of a transportation provider refers to matching the physical characteristics of the freight--size, weight, temperature and handling requirements--and market requirements, such as location monitoring and timely delivery.

Accessibility may be described by the connections between the origin and destination points via a particular mode. For example, most shippers have direct access to motor carriers but not to rail, water or air carriers; these would need intermodal transfers, resulting in added costs and transit time.

Reliability is the consistency of transportation time, or the ability to meet a pickup and delivery schedule. Both modal choice and carrier choice are affected by reliability (1, p. 37). Ballou relates how uncertainty in lead-time results in added safety stocks, thus increasing inventory carrying costs (2).

Security refers to the ability of a carrier to deliver freight in the condition expected. The effects of lost and damaged freight include reduced production and sales by the intended receiver of the freight, increased inventory carrying costs in attempting to avoid these stockout costs, and increased costs of handling loss and damage claims.

Quantitative measures of freight transportation generally are variables that include the value and weight of the freight, distance shipped, and transportation cost and speed. These variables are consistent with those used by Ralston, Tharakan, and Liu (3) in their Bangladesh Transportation Modeling System (BTMS); see Appendix V.B. The intermodal nature of the BTMS was introduced by Ralston et al. from their experience and observations of transport by ferryboats, and they used cost and time equations to explain the "logical links," which include loading or unloading and intermodal transfers. A generalized model may substitute fixed handling charges and time for the special ferry charges and ferry scheduled times.

The BTMS then computes a utility function, Uijkm (for each shipment of commodity k, between origin and destination i and j, on mode m; see Appendix V.B.), which becomes the basis for the modal share (probability of using mode m):

P(m|ijk) = exp(Uijkm)/ S exp(Uijkm)

Using the Ralston et al. model as a guide, the required inputs become, for each mode:

VC = variable cost (money per ton-km or ton-mile; money per passenger km)

S = speed (kmph or miles per hr.)

MFC = fixed facilities cost (money per ton or per passenger)

CFC = fixed facilities cost due to commodity characteristics (money per ton or per passenger)

MFT = loading or transfer time

CFT = time due to the commodity characteristics

Typical values for a portion of the required data is readily available and have been tabulated in Table V.B.1. While not industry-specific, these measures provide a starting point and default values that may be used in when more detailed data is not collected.

The modal share variable is one method of handling the multimodal nature of a shipment. For example, if a shipment traveled 50 miles by truck, to a rail transfer facility, and then 1700 miles by rail, finally completing its journey by being drayed 250 miles by truck, the modal share fractions would be .15 (i.e., 300/2000) and .85 (i.e., 1700/2000), respectively, for motor freight and railroad.

The tons and value of freight shipped may be related to the population and employment in the area by:

Tons = a * P b + c * E d

Value = e * P f + g * E h

Where P and E are population and employment, respectively, and a through h are coefficients to be determined.

 

TABLE V.B.1: PUBLISHED COSTS BY MODE

Variable Motor freight Railroad Airfreight Water Page ref.
Costs ($/mi.) $1.247       147
Capacity (tons per vehicle) 25 90 100 1,500 & up 143, 170, 226
Revenue ($/ton-mi.) .2438 .0266 .4634 .0075 226
Speed (m.p.h.) 45 20 453 7 141, 184, 204, 226-27
Fixed facilities cost ($/ton) $ $ $ $  
Loading, transfer time (min./ton) 4 2 4 10  
Modal share, ton-mi. (.0 to 1.0) .263 .374 .004 .274 132, 162, 192, 216
Modal share, cost (.0 to 1.0) .727       132
Ave. length of haul (miles) 391 650 1,397 441-1,974 201, 225

Source: Coyle, John J.; Edward J. Bardi, and Robert A. Novack, Transportation, 4th ed. (St. Paul: West Publishing Company, 1994).

 

IOWA FREIGHT SHIPMENTS

In the 1993 Commodity Flow Survey, Iowa recorded total shipments ("by establishments in mining, manufacturing, wholesale, and selected retail and service industries" (4) of $79.9 billion, weighing 164.5 million tons. These totals represented about 1 percent of the total U.S. value of shipments and 2 percent of the U.S. total weight. In other words, much of Iowa's shipments were high-weight, low-value commodities. The largest category by weight was farm products, which accounted for 33 percent of the volume, but 10 percent of the value. Other high-weight product categories were food or kindred products (24 percent), nonmetallic minerals (15 percent), clay, concrete, glass, or stone products (9 percent), and petroleum or coal products (6 percent). Several manufactured product categories contributed over 5 percent each of total shipment value: Food or kindred products; machinery, including computers; chemicals or allied products; electrical machinery, equipment, or supplies. Except for food or kindred products, the weights of each of these categories were less than 5 percent of the total and were grouped in with "other commodities" which shipped approximately 13 percent of the total weight.

By value, 35 percent of Iowa's shipments stayed in the state, as did 60 percent of the weight. As shown in Table V.B.2, bordering states received significant shares of the remaining shipments.

 

TABLE V.B.2. IOWA SHIPMENTS TO BORDERING STATES

Destination: Iowa border states Percent of value Percent of weight
Illinois 10.1 7.1
Minnesota 3.7 3.8
Missouri 3.7 2.7
Nebraska 3.9 3.3
Totals 21.3 16.9

 

Specific Product Example

An example may clarify the discussion of the conceptual model for manufactured products. One product category produced in Iowa and shipped to destinations both inside and outside the state is Standard Industrial Classification 36, Electrical machinery, equipment or supplies. The Commodity Flow Survey (4, p. 19) lists Iowa's shipments of SIC 36 at $4,215,000,000, with a total weight of 568,000 tons. Iowa’s SIC 36 shipments are compared with the state’s Farm Products and Total shipments in Table V.B.3, below. While significant in value, at one-half that of farm products, electrical machinery, equipment and supplies shipments were one percent of the weight of farm products and two percent of the ton-miles (because shipments of the former traveled four times the distance of the latter). Figures V.B.1 and V.B.2 (based on Tables V.B.4 and V.B.5) display the distances shipped for Iowa's total output compared with SIC 36 alone. While over one-half of Iowa's shipment (by value) travel less than 250 miles, the majority of SIC 36 shipments travel over 500 miles. Weight comparisons are similar: Over one-half of Iowa's total shipments stay within a 100 mile distance of their origin, but nearly one-half (48 percent) of SIC 36 products travel over 500 miles. The longer miles per shipment are one factor that would increase the likelihood that electrical machinery shipments would be containerized, requiring intermodal facilities. These differences support the logic of treating specific product categories separately, when data can be attained.

 

TABLE V.B.3. IOWA SHIPMENTS

Category Value Tons Ton-miles Mi/shipment

(STCC) ($ million) % (1,000) % (million) %

36 Elect. Mach. 4,215 5.3 568 .3 380 .8 713

01 Farm Products 8,254 10.3 54,394 33.1 21,632 42.9 141

All commodities 79,900 100 164,544 100 50,478 100 323

Source: Commodity Flow Survey, Table 6, Iowa 11.

 

TABLE V.B.4. ALL IOWA SHIPMENTS

Distance (mi.) Median % value accum % % weight accum%

Under 50 25 22.5 22.5 45.1 45.1

50 - 99 74.5 10 32.5 13.9 59

100 - 249 174.5 22.4 54.9 15.7 74.7

250 - 499 374.5 14.9 69.8 8.3 83

500 - 749 624.5 9.3 79.1 3.5 86.5

750 - 999 874.5 10 89.1 9.2 95.7

1000 - 1499 1249.5 7.3 96.4 3 98.7

1500 - 1999 1749.5 3.7 100.1 1.1 99.8

2000 - up 2500 0 100.1 0 99.8

 

TABLE V.B.5. IOWA SIC 36

Distance (mi.) Median % value accum % % weight accum %

under 50 25 12.8 12.8 11.4 11.4

50 - 99 74.5 4.2 17.1 5.6 17.1

100 - 249 174.5 14.1 31.1 16.7 33.8

250 - 499 374.5 15.1 46.2 18.1 51.9

500 - 749 624.5 17.3 63.5 17.3 69.2

750 - 999 874.5 17.0 80.5 15.1 84.3

1000 - 1499 1249.5 15.4 95.9 13.6 97.9

1500 – 1999 1749.5 4.0 99.9 1.9 99.8

2000 - up 2500 0.1 100.0 0.0 99.8

1

 

Mode Choice Matrix

The modes used for Iowa's originating shipments are shown in Table V.B.6 and are predominately truck. These figures differ from the U.S. averages: Iowa's originating shipment value and tons by truck and by rail are higher, largely because Iowa had air, water and pipeline shipments too small to be categorized (some of these are included in "all other"). The comparisons suggest that, in the absence of specific commodity shipment information, Iowa shipments have an 80 percent chance of being shipped by truck vs. a 73 percent chance for overall U.S. shipments. Also, nearly 75 percent of Iowa's originating tonnage will travel by truck, considerably higher than the 53 percent for the entire country. As shipment information for specific product categories becomes available, the modal prediction model will be refined. For example, the following discussion develops modal prediction for one particular product category.

TABLE V.B.6. USA AND IOWA SHIPMENTS VS MODE

USA Iowa USA Iowa USA

Mode Value Value Tons Tons Ton-miles

(%) (%) (%) (%) (%)

Parcel etc. 8.9 7.1 0.2 0.1 0.3

Truck 72.6 80.3 52.6 74.5 23.7

Air 2.4 0.0 0.1

Rail 4.0 6.5 12.7 15.6 26.0

Water 3.9 17.2 24.0

Pipeline 2.8 10.8 16.1

Truck and rail 1.3 0.4 0.3 0.1 1.2

Other intermodal 0.2 1.2 5.1

All other 3.9 5.7 5.0 9.7 3.6

 

MODAL SHARES

It is assumed the demand for transportation services for manufactured products is desired in ton-miles (or other weight and distance measurements) by mode. Figure V.B.XX displays a detailed model in diagram form, with the general process of breaking down national economic outputs into regional, and the regional economic model into manufacturing employment and output by industry. Use of input/output tables can further segregate manufactured products requiring transportation into final goods and intermediate goods. Final goods are then transported to a consumer or reseller and intermediate goods are transported to another manufacturer for additional processing or assembly prior to their becoming final goods. In both cases the volume of manufactured goods, measured by dollar amounts, is allocated to its next destination region, resulting in two origin/destination matrices, which are then aggregated to give overall value flows, from Origin Oij to Destination Dij. A product and weight matrix then allows the value for each product group to be estimated in Tons (or other weight-measure). Thus the transportation demand for product group X, on mode k, between Iowa and region Y, may be approximated.

The intermodal portions present a challenge for analysis. For example, it may be known that 15 percent of final goods in category Z are exported, and 92 percent of these exports are containerized (with the balance being trucked to port), with 40 percent of the exports departing from Seattle and 60 percent from the Port of Miami, Then rail ton-miles to the northwest will increase by .15 * .92 * 40 * Tons output * distance (to northwest). Rail ton-miles to the southeast will likewise increase by .15 * .92* .60 *Tons output * distance (to southeast). Road tons will be .15 * .08 * Tons.

 

FREIGHT RATES AND CLASSIFICATIONS

Background

Each freight movement, described by type and amount of product, between each origin and destination could have a unique price. This situation could result in billions of separate prices, an administrative problem for pricing individual loads of freight. The problem and approaches to solving it predate railroads. Taff reports that overseas operators of riverboats and canal boats classified commodities into a small number of groups, a practice that was later used in the United States and adopted by wagoners and the developing railroads (5). For example, a railroad simplified its freight rate quotations by classifying products as either heavy goods, which were charged on the basis of weight, or light goods, which paid for the space occupied.

Individual railroads refined their classifications by adding new groups, which led to a lack of uniformity and confusion when traffic was interlined. Lieb notes that regional classification systems came before 1900, after the ICC "prodded the railroads to streamline the classification system" (6). Three regional classifications resulted, beginning with the Official Classification of 1887 (east of the Mississippi River and North of the Ohio River), and followed by the Southern Classification (south of the Ohio River) and the Western Classification (Chicago and St. Louis to the West). The consolidated Freight Classification was published in 1919, which made the rules and regulations, and the description of products uniform; some ratings differences remained. The Uniform Freight Classification system (for rail freight) replaced the three regional systems for most use in 1952 (5, pp. 354-55).

The National Motor Freight Classification, filed with the Interstate Commerce Commission in 1936, used classification descriptions identical to those used in the rail system because, as explained by Taff, "the task of formulating completely new classifications was so formidable" (5, p. 407).

Ratings

The class rating system was developed to simplify the process of determining freight charges into a basic formula (7):

Freight charge = Weight X rate

The weight is expressed in hundred-pound units (CWT) and the freight rate is quoted as a cost per hundredweight. The rate is, in turn, based on the distance and the product being shipped. Distance has been simplified into a rate basis number, which is based on the distance between map segments, rather than the point-to-point distance for each particular shipment. As displayed in Figure 1, any origin or destination within a map segment is treated as being at the major shipping point of that segment (7, p. 273).

Reference to product attributes is simplified by giving each product a rating number, which is a percent of the first-class or standard product rating. Thus, a product with a rating of 100 would be charged the standard rate and a product with a rating of 50 would be charged one-half that rate. In the first Uniform Freight Classification, over 23,000 product descriptions were grouped into 31 classes, from 13 to 400. The classes are: 400, 300, 250, 200, 175, 150, 125, 110, 100, 92.5, 85, 77.5, 70, 65, 60, 55, 50, 45, 40, 37.5, 35, 32.5, 30, 27.5, 25, 22.5, 20, 17.5, 16, 14.5, and 13 (5, pp. 359.

The National Motor Freight Classification follows the pattern of the rail classification but uses 23 groups, which ranged between 35 and 500. The NMFC classes are: 500, 400, 350, 300, 250, 200, 175, 150, 125, 110, 100, 92.5, 85, 77.5, 70, 65, 60, 55, 50, 45, 40, 37.5, and 35. The lowest four classes were assigned to truckload (TL) freight only. The Coordinated Motor Freight Classification, in place by 1948 for shipments in New England, reduced the number of classes to five. Classes were determined by density, with no differentiation between less-than-truckload (LTL) and high volume shipments (5, pp. 362, 365).

Products are rated by factors including (6, pp. 217-218):

1. Shipping weight per cubic foot

2. Liability for damage

3. Liability for damage to other commodities with which it is transported

4. Perishability

5. Liability for spontaneous combustion or explosion

6. Susceptibility to theft

7. Value per pound in comparison with other articles

8. Ease or difficulty in loading or unloading

9. Stowability

10. Excessive weight

11. Excessive length

12. Care or attention necessary in loading and transporting

13. Trade conditions

14. Value of service

15. Competition with other commodities transported

16. Quantity offered as a single consignment.

The National Classification Committee, composed of up to 100 motor common carrier employees and owners, rates new commodities and acts on applications to reclassify existing commodities. Pugh emphasizes the revenue neutrality of the NCC: the transportation characteristics determine the rating; economic considerations "are reflected in the rate tariffs" of the carriers (9). While each of factors listed above may influence how a product is rated, the ICC has ruled that product density, stowability, handling, and liability are the four determining factors (1, p. 362). Bohman explains that the National Classification Committee relies strongly on its "Density Guidelines" (see Table V.B.7): "Now there may be circumstances in which other transportation characteristics might prompt the NCC to assign ratings higher or lower than called for in its density guidelines. . . don't underestimate the weight accorded to density in the rating determination" (10).

Table V.B.7. National Classification Committee's "Density Guidelines"

Class Min. Ave. Density

(Pounds Per Cubic Foot)

500 less than 1
400 1
300 2
250 3
200 4
175 5
150 6
125 7
110 8
100 9
92.5 10.5
85 12
77.5 13.5
70 15
65 30
60 30
55 35
50 50

Source: Ray Bohman, "Bohman on Pricing: Get to know the NCC guidelines," Traffic Management, Vol. 29 (January 1990), p. 25.

Liability, one of the "other" characteristics that may affect ratings, is partially a function of the value of the specific shipment. (Liability for damage to other commodities will depend on their particular valuations.) Values are conveniently compared by expressing them in dollars per pound. The NCC uses value density maximums, shown in Table V.B.8, as guidelines in assigning ratings. Extremely high-valued products ("property of extraordinary value") will not be accepted by common carriers as LTL shipments. Examples are bank bills; currency, other than coin; deeds, drafts, jewelry, other than costume or novelty jewelry; postage stamps; precious stones; revenue stamps; valuable papers of any kind (11). While density will be the factor that establishes the initial rating, Bohman explains that products with values higher than the maximums for that class might have a higher rating "to reflect the greater liability carriers would be exposed to in the event of loss or damage" (12).

Table V.B.8. National Classification Committee's Value Guidelines

Class Max. Ave. Value

(Per Pound)

500 $89.12
400 71.29
300 53.47
250 44.56
200 35.65
175 31.20
150 26.74
125 22.27
110 19.60
100 17.82
92.5 14.25
85 10.70
77.5 7.12
70 5.34
65 3.53
60 2.12
55 1.42
50 .71

Source: Ray Bohman, "Bohman on Pricing: How 'value' fits into the rating equation," Traffic Management, Vol. 30 (April 1991), p. 25.

Although no specific formulae are used to assign a commodity to a particular class, the four factors are considered in conjunction by a carrier classification committee. An individual carrier may establish a commodity classification that differs from the national classification; this individual carrier classification is termed an exception and takes precedence over the national classification.

 

Exception ratings and Commodity rates

The desire for freight charges different (i.e., lower, usually) from those calculated according to the class rate system may come from several fronts, such as shippers or potential shippers trying to match a competitor’s costs, or a carrier competing for freight. In addition to the exception ratings, shippers may protest to the classification committee that a product is rated too high, citing lower ratings for analagous products. Carriers may use the same strategy in protesting that a rating is too low (6, p. 218). Changed ratings resulting from protests apply to all shippers. Requests for exception ratings arise from specific competitive situations and tend to apply to a limited number of shippers (because of product or packaging description, shipment sizes, or area served), even though the exceptions are published in the calss rate tariffs.

Commodity rates (dollar amounts, not ratings, as above) are usually lower than the class rates and are for movements of a specific commodity from one stated point to another. One estimate is that commodity rates account for a majority of rail, truck and water tonnage (but not the number of shipments (6, p. 225). To the extent that more shipments would be made under commodity rates, the rate simplification objective of the class rate system has been defeated. This same comment would apply to contract pricing of transportation, further amplifying the complexity of transportation rates. As Lieb points out, "The shipper is legally entitled to the lowest published rate that might be applied to his traffic. That is, at any given time, only one legal rate applies to a specific shipment handled by a specific carrier" (6, p. 223).

Simplification attempts

With railroads moving away from less-than-carload shipments and toward contract rates, the NMFC became the dominant classification system. In 1977 (before the Motor Carrier Act of 1980), Snow criticized the rate structure for LTL freight as being "cumbersome and needlessly complex" and not based "on genuine cost differences" (13). Davis, also, had supported the use of more precise cost data in constructing rates. He noted that pricing for transporting containers was based on "the size of container or weight loaded rather than the standard classification of the product" (14).

Nearly two decades after deregulation of trucking, Foster called for "junking the old pricing system based on the NMFC, which no longer has any relevance to how LTL services are bought and sold." He proposed that rates be based "on simple variables such as cents per pound, density and distance moved," with a simple factor for liability. Both shippers and carriers would avoid existing costs of rating, and of payment and auditing services (15). Some carriers have begun testing a one-page, net rate pricing scheme, which has discounts and accessorial charges built-in and customized for the individual shipper. Cassidy reports that shippers have welcomed pricing simplification "when it promotes billing accuracy and provides savings" (16). Such simplification has been introduced in several ways for multimodal freight movements. For example, the "any commodity rate" and "freight-all-kinds" rate de-emphasize the shipment value and have been used for several piggybacking plans and for containerized imports (6, p. 226; p. 425).."

 

CONCLUSIONS FOR THE PROJECT

Freight charges are typically calculated by multiplying a rate times the weight, with the rates varying by product or product classification. Even with the faults some writers attribute it, the NMFC provides a reasonable starting point for describing freight. For the proposed model, a "typical" freight product would be a class 100 shipment, in terms of density and value. A simple multiplier may then adjust freight costs for shipments clearly unlike class 100 commodities. For example, a high-valued product, with a 400 rating, would have a multiplier of 4.

Multiple modes do not necessarily mean morecomplex freight charge calculations. There already exist freight rate schemes based on a container or weight unit and not on value of products carried. A recommended future modification may be to specify containerized shipments (expressed twenty-foot equivalent units, or TEUs). For example, one state transportation plan includes Containerized Cargo as one of eleven separate product categories (17).

 

REFERENCES

1. Coyle, John J.; Edward J. Bardi, and Robert A. Novack, Transportation, 4th ed. (St. Paul: West Publishing Company, 1994), pp. 34-36.

2. Ballou, Ronald H., Business Logistics Management, 3rd ed. (Englewood Cliffs, NJ: Prentice Hall, 1992), pp. 430-431.

3. Ralston, Bruce A.; George Tharakan; and Cheng Liu, "A Spatial decision support system for transportation policy analysis in Bangladesh," Journal of Transport Geography, Vol. 2, No. 2, 1994, pp. 101-110.

4. U.S. Department of Transportation, Commodity Flow Survey: Commodity Movements Originating in Iowa: 1993, www.bts.gov/programs/dfs/states/ia.html, p. 1.

5. Charles A. Taff, Management of Physical Distribution and Transportation, 7th ed. (Homewood, Ill.: Richard D. Irwin, Inc., 1984), pp. 353-54.

6. Robert C. Lieb, Transportation, 3rd ed. (Reston, Va.: Reston Publishing Company, 1985), p. 216.

7. James C. Johnson and Donald F. Wood, Contemporary Logistics, 6th ed. (Upper Saddle River, NJ: Prentice Hall, 1996), p. 210.

8. Based on: Donald F. Wood and James C. Johnson, Contemporary Transportation, 4th ed. (New York: Macmillan Publishing Company, 1993), p. 273.

9. William W. Pugh, "A Primer on the National Motor Freight Classification," Transport Topics, October 8, 1990, pp. 18-19.

10. Ray Bohman, "Bohman on Pricing: Get to know the NCC guidelines," Traffic Management, Vol. 29 (January 1990), p. 25.

11. Carl J. Ackerman, ed., Tariff Practice Book, 4th ed. (Atlanta: Southern Motor Carriers Rate Conference, 1961), p. 15.

12. Ray Bohman, "Bohman on Pricing: How 'value' fits into the rating equation," Traffic Management, Vol. 30 (April 1991), p. 25.

13. Paul W. MacAvoy and John W. Snow, eds., Regulation of Entry and Pricing in Truck Transportation (Washington: American Enterprise Institute for Public Policy Research, 1977), p. 18.

14. Bob J. Davis, "New Ideas in Ratemaking," I.C.C. Practitioners' Journal, Vol. 33 (June 1966), p. 793.

15. Tom Foster, "Viewpoint: Ring in the new LTL pricing system," Distribution, March 1997, p. 80.

16. William B. Cassidy, "Fleets Are Simplifying Their Rates," Transport Topics, No. 3096 (December 5, 1994), p. 23.

17. Louisiana, Statewide Intermodal Transportation Plan, March 1996, p. 83.

 

 

PART VI APPENDIX: EXPLANATION OF RALSTON ET AL. VARIABLES

Cost and time are related to distance and speed by the following:

Cost = L * VC * LCM * SCM

where:

L = length of link

VC = variable cost (money per ton-km or money per passenger km)

LCM = link's unique cost (multiplier nominally 1), reflecting link's state of repair

SCM = mode's seasonality cost (multiplier nominally 1)

Time = (L / S) * LTM * STM

where:

S = speed (kmph)

LTM = link's unique time (multiplier nominally 1), reflecting link's state of repair

STM = mode's seasonality time (multiplier nominally 1)

The following cost and time equations explain the "logical links," which include loading or unloading and intermodal transfers:

Cost = FFC * LCM * SCM

where:

FFC = fixed ferry charge (money per ton or per passenger)

and:

Time = FFT * LTM * STM

where:

FFT = known delays (i.e., fixed ferry time in hours)

Cost = (MFC + CFC) * NCM

where:

MFC = fixed cost (money per ton or per passenger)

CFC = fixed cost due to commodity characteristics (money per ton or per passenger)

NCM = node cost multiplier (nominally 1)

Time = (MFT + CFT) * NTM

where:

MFT = loading or transfer time

CFT = time due to the commodity characteristics

NTM = node time multiplier (nominally 1)

The utility function (for each shipment of commodity k, between origin and destination i and j, on mode m) is:

Uijkm = B1k Cijkm + B2k Tijkm Vk + B3k d1 + B4k d2

where:

V = value of commodity k (for passengers, V = 1)

d1 = toggle (1 if rail, 0 otherwise)

d2 = toggle (1 if water)

B1k = weight (to be determined, expected negative)

B2k = weight (to be determined, expected negative)

B3k = weight (to be determined, either sign)

B4k = weight (to be determined, either sign)

The modal share (probability of using mode m) is then:

P(m|ijk) = exp(Uijkm)/ S exp(Uijkm)

 

REFERENCES FOR APPENDIX

1. Ralston, Bruce A.; George Tharakan; and Cheng Liu, "A Spatial decision support system for transportation policy analysis in Bangladesh," Journal of Transport Geography, Vol. 2, No. 2, 1994, pp. 101-110.

Multimodal Investment Analysis: Phase 1 Contents

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