Table of Contents for Appendix E

Appendix E
E.1 Market Assessment/Analysis
E.1.1 Contacts
E.1.2 Business Model/Detailed Analysis
E.1.2.1 First Approach
E.1.2.2 Second Approach
The Full Section Index is at the end of this Section

Commercial Space Transportation Study


Appendix E Transportation Appendix

E.1 Market Assessment/Analysis

E.1.1 Contacts

During the performance of the Space Tourism study, contact was initiated with a number of cruise lines and others.

CSTS Contact
Telephone Notes:Jerry Mallett
Jim Pierson
Adventure Tourism Society
Date17 December 1993
Alliance Member:William T. Boardman
McDonnell Douglas Aerospace

Yesterday, 16 December 1993, I sent an introductory letter and a brochure to the Adventure Tourism Society. This group was referred to us by the US Travel Data Center. Today I received a call from the Society's president, Mr. Jerry Mallett and his partner, Mr. Jim Pierson.

They had just read the material and were quite enthusiastic about the prospect of space tourism. I explained that the Alliance consisted of six aerospace and that any meeting would contain representatives from more than one company and that the information would be shared with all. They expressed an interest in meeting with the Alliance.

They are of the opinion that there is a real market for space tourism. The numbers of people that are interested in being among the first to take unusual trips is growing rapidly. They also believe that the demographics in the early 21st century are good. A few of the facts that they mentioned are:

  1. Tourism is the largest industry in the world. It amounts to between 5 and 6% of the world's GDP.
  2. A permit to climb Mount Everest now costs $50K and there is a long waiting list.
  3. The Russians opened one of their ice breakers at $19K for trips into the Arctic circle. They are sold out.
  4. In the Denver area, NASA offered rides in a flight simulator at $1500 per hour. The demand was so great that additional time was provided.
These two gentlemen have met with groups from around the world. They mentioned two international organizations:

  1. World Travel Organization located in Madrid.
  2. World Tourism and Travel Council located in Brussels.
They volunteered to send me some material and further said that they would call me again early next year to set up a time for us to get together.

E.1.2 Business Model/Detailed ROI Analysis

As part of the analysis of the financial viability of Space Tourism, the CSTS Team conducted two similar "Bottoms Up" analyses. The results of these two analyses are summarized in section 3.5.6 of this report. The details of these alternate approaches is contained in this appendix.

E.1.2.1 First Approach

To determine the magnitude of the money available to develop space tourism, a model of worldwide personal income was developed. This assumes, as in other forms of tourism, that the sustained operations (including the costs of purchasing transportation hardware) are funded by the discretionary spending of interested individuals, and not subsidized in any significant way by a government.

There are other analogies that suggest governments may be interested, for a number of reasons, in helping to subsidize the initial procurement of new systems; this will be discussed later as one approach to enhancing the probability that space tourism will be realized.

The simplicity of the equations used permitted the model to be effectively implemented on a spreadsheet. An example page of input/output is shown as Figure E.1.2.1-1.

Parameters in the boxes are input values, other numbers are calculated. The first line is an input of personal income level in CY92 dollars. This number was parametrically varied from $50,000 per year to $2,000,000 per year.

This number is projected forward, and shown in the next line, at 2.337% per year (extrapolated from recent average growth trends) to the year 2005, which was selected as a representative date for the commencement of space tourism flights.



Figure E.1.2.1-1. Example of Spreadsheet Model

Next, a simplified representation of income distribution was made by obtaining data on the United States' population's income. Typically, the US personal wealth accounts for one-quarter of the worldwide figure; therefore the distribution was multiplied by four. Assuming the population of the world grows at an average rate of 0.8% per year until the year 2005, a histogram of number of people versus annual income was developed.

It was further assumed that anyone with an income greater than the selected level would also buy a ticket commensurate with the price set by the population at the selected level. That is to say, by analogy, a wealthy person would buy a $500 airline ticket even though he or she could easily afford a more expensive ticket. The histogram was "integrated" to arrive at an equation that represents the number of people worldwide with personal incomes in excess of income level "IL":

people = ex
where x = (.2599197 * ln(IL)^2 - 8.405613 * ln(IL) + 79.14591)

The third line of Figure E.1.2-1-1 is the output of this equation. Figure E.1.2.1-2 graphically portrays the number of individuals worldwide with incomes greater than or equal to a given income level.



Figure E.1.2.1-2. Model of Individuals With Incomes Greater Than or Equal to "IL"

The next input line, "Discretionary Spending Factor", is an estimate of how much the average person would spend for a ticket as a percentage of their annual income. This discretionary spending factor was parametrically varied from 5% to 20% (from a family vacation to a trip-of-a-lifetime). The "Interested Travelers" input parameter represents an estimate of what fraction of the population would avail themselves to a space trip if they had the financial means to do so.

Not everyone may wish to travel to space, and discretionary income for a space vacation has to compete with other travel destinations and consumer goods.

Previous studies have indicated that younger adults (those with less disposable income) are more likely to want to travel to space than older adults. Therefore, there is probably a 20 to 30 year period within an individual's lifetime where both the desire and the means to consider space tourism are present.

Within that period, it would be unlikely that the average individual would actually take more than one spaceflight. To account for all these considerations, the fraction of interested travelers within any given year was parametrically varied between .005 (1 in 200) and .0001 (1 in 10,000). Figure E.1.2.1-3 compares this range of interested travelers in combination with the range of discretionary spending with the often cited Society Expeditions market model (corrected for 1992 dollars and population).

Point "A" represents the interest in space tourism, as indicated by monetary deposits made towards the Society Expeditions/Phoenix venture (Ref. A-1).


Figure E.1.2.1-3. Range of Parametric Investigation of Space Tourism Elasticity

The next input is labeled "Transportation Fraction" and is an acknowledgment that not all of the ticket price goes to paying for the transportation. As in terrestrial tourism "packages", the amount of the tour price that pays for the airline ticket can vary significantly, depending on the nature of the trip. In the case of the "Joy Ride" scenario, the transportation fraction would be relatively high; in the case of an unsubsidized lunar resort, transportation costs are relatively small.

This parameter was varied from 25% to 75%. The focus of this report is on the transportation elements; and does not assess whether the remaining revenue is consistent with the development and manufacture of other tourism assets (such as an orbital hotel).

The "Mission + Turnaround Time" input is fairly self-explanatory. The parameter was varied between 2 and 90 days to account for different mission types as well as technology/operations assumptions. In reality, mission + turnaround time is not independent of the "transportation fraction", but for this model, they were left as discreet inputs.

Finally, an input of "Vehicle Capacity" is made. Without the benefit of a specific design, it is still necessary to know how many passengers one vehicle can accommodate in order to determine the fleet size. Inputs ranged from 10 passengers to 250 passengers.

The output section contains several values which describe the characteristics of one solution to space tourism transportation. The first line of the output is the total annual passengers, simply calculated by multiplying the "Interested Travelers" fraction with the number of individuals with incomes in excess of the selected income level. From this, the next line shows the number of annual flights, a rounding up of the annual passengers divided by the vehicle capacity.

One significant assumption is that the transportation vehicles are reusable and feature essentially infinite life (no accounting for spares or attrition). This is perhaps optimistic in that it is presumed that expendable vehicles, or limited lifetime reusable concepts, will cost more and would make the realization of space tourism less likely. With this caveat, the fleet size is calculated by rounding up the annual flights multiplied by the mission + turnaround time input, divided by 365.25 days per year.

The "Ticket Price" (in 2005 dollars) output is simply the product of the selected income level and the "Discretionary Spending Factor". This ticket price is multiplied by the vehicle capacity, the "Transportation Fraction", and a postulated 0.97 load factor (to account for last minute glitches, illness, gratis flights, etc.) to arrive at the "Transportation Revenue/Flight" output. Load factors on commercial airlines typically average 0.6 to 0.7 across an entire fleet and route structure.

Specialized air travel, such as the Concorde, experience similar load factors. Anecdotally, a common mistake with new airlines is basing economic projections based on load factors approaching 1.0; lending institutions have learned to be cautious with these optimistic projections. Our justification for selecting a high load factor is based on the idea that, for a first generation space tourism industry, scheduling will be flexible enough to only launch when 'all the tickets have been sold' in the manner of a charter operation rather than a scheduled airline flight.

The "Transportation Revenue/Flight" can be thought of as similar to the cost/flight parameter typically associated with space launchers.

Finally, at this point in the output, a value for $/lb is shown (assuming 300 lbm/person including baggage). Although this metric has been used extensively in comparing launch vehicles, it is arguably of secondary interest to the space tourism operator: transportation revenue/flight is a more useful management measurement. As predicted by previous studies, these values do tend to be small compared to conventional launch vehicles.

Results of Parametric Analysis. At this point, it is possible to begin to bracket the range of possible solutions. Varying the input parameters as described resulted in the generation of several thousand individual cases. Understanding the output is not as simple as a single graph. Remember, any individual case must answer the following, multi-part question: Can one build a safe, reliable vehicle that carries N people paying $X each, is operable for $Y/flight, and can be developed and manufactured (M vehicles) for $Z? Before answering the last question, what can we exclude on the basis of violating the first part of the question?

Some restrictions on the range of interest are immediately apparent (Fig. E.1.2.1-4). There is a lower limit on practical cost/flight that can be realized. Spaceflight will never be as inexpensive as other forms of transportation; fundamentally, there are large differences in the amount of energy stored and expended as well as the necessary complexity required to operate in hostile environments.

All solutions below some agreed upon minimum (say for argument, $2M/flight) can be eliminated from further consideration. Specifically in this case, vehicles smaller than 100 passengers are only valid if one selects customers with income levels in excess of $500,000/year as the target market.



Figure E.1.2.1-4. Example Model Output for Transportation Revenue per Flight Versus Vehicle Capacity

Likewise, in the related graph of
Figure E.1.2.1-5, a lower bound for vehicle size could be set by considering the cost involved in manufacturing such large fleets. {The Concorde has an average of 80-90 persons/flight and 12 vehicles in the active fleet.}

Fleet sizes of one vehicle are unlikely as well - maintenance or failure would stop all revenue and would not be good business practice. Referring to the previous finding for this example, the same target market would seem to be best served by a 'fleet' of two vehicles sized in the 50-100 passenger range.



Figure E.1.2.1-5. Example Model Output for Fleet Size Versus Vehicle Capacity

For the most promising cases, the spreadsheet analysis was carried further to estimate the size of the initial capital that could be invested, based on the amount of money for payments that could be generated as part of the revenue earned per flight. In an analogy to airplane transports, a portion of the ticket price (roughly half) is allocated to pay back the loan for the purchase of the airline's aircraft.

Figure E.1.2.1-6 depicts an example case from one spreadsheet run with parameters related to the case shown in Figures E.1.2.1-4 and -5. The data that comes from the previous analysis is shown as the "Annual Income Level" entry; this number is simply the transportation revenue/flight multiplied by the number of annual flights and a parametrically varied percentage that represents the amount of the revenue allocated to amortization.

One can also parametrically vary the period of time for amortization ("Years of return") and the "Rate of return". For a first pass, escalating to account for the exact year of introduction was ignored. The line labeled "max Capital" is the amount that can be amortized at the beginning of revenue operations. Finally, the "Init. Value" is calculated, using the variable 'Development Years"; this value represents the money available to develop the vehicle and to buy the fleet, or the amount of the loan from the lender.

The total money available is related to the annual flights, which is in turn a function of the selected target income level of the customer market. After accounting for development, the funds available for manufacturing the vehicles would set the maximum likely fleet size.

This example, then, shows a ridiculously unlikely scenario; even without considering how many production units there are, there is only millions to tens of millions of dollars available for developing and building a new, reusable manned launch system. Using these calculations, one could subjectively screen out the cases where development is under funded to the point of questionable credibility.

Within the entire parametric trade space depicted in Figure E.1.2.1-3, there are no credible solutions! There is nowhere near enough revenue to pay back lenders for the true costs of development and manufacture of a new, single purpose space tourism transportation system.

Figure E.1.2.1-6 yields other useful data. Large vehicles imply the fleet size is small; this is desirable in that larger fleets must be manufactured for roughly the same amount of money as a smaller fleet. Of course, larger vehicles are costlier to develop and build than smaller ones.

On the other hand, large vehicles imply lower ticket pricing to enable the fleet to fly efficiently; lower ticket revenues result in the requirement for extremely low cost/flight. Is there an answer to this enigma? There are solutions, but only if one can separate the cost of developing and building the system from the technical and operational challenges, which many believe can be met.



Figure E.1.2.1-6. Example Worksheet for Calculating Initial Investment

E.1.2.2 Second Approach

Income Distribution. Space travel for purposes of entertainment will remain only within the domain of the rich or high income households for only they could afford the cost. As a general rule, the lower the cost per pound to orbit, the larger the segment of the world population that can afford to travel to space, given that they had the inclination to do so. Thus, there are two huddles that the operators of a space destination resort must overcome in finding customers: first, the costs must be low enough that a sufficient number of people can afford the trip and second, there must be sufficient attraction so that people would want to go.

The first huddle to the prospective space traveler is affordability. A trip to space is likely to financed similar to any high cost purchase with monthly payments spread over time. The travel agent, actively attempting to solicit business, would have to offer financing for such a 5 day vacation at the space destination resort. The prospective customers who file for a bank loan would be screened based on their ability to make monthly payments, not unlike financing for a new automobile or home.

The financial rule of thumb for a customer to qualify for purchasing a house, considered a once in a life time purchase, is that the loan not exceed three times the household's current gross income, and amortized over 30 years. The financial rule of thumb for a customer to qualify for purchasing a new car, is that the loan should not exceed one-third the household's current gross income, and amortized over 5 years.

Applying similar financial rules of thumb, customers can be qualified for purchase of space resort tickets based on their annual income. Since the decision to purchase space travel tickets is a consumable purchase, it is more like an expensive vacation or perhaps an automobile. Thus, the appropriate financial rule of thumb is that household income should be at least three times greater then the purchase cost. Thus, if the household cost for a 5 day vacation at the space resort is $25,000, then to qualify for financing, the household income should exceed $75,000.

Income distributions have been collected by households from the three sources shown in Figure 3.5.6.3-1: (1) 1990 census data, (2) the 1989 Adjusted Gross Income Tax Statistics, and (3) the 1992 Statistical Abstract of the United States. The income statistics used in this study was the one for households with adults aged 25 to 55. Below this age band, it is assumed that the average household income is insufficient to finance a trip into space, and above the age band, the physical condition of the average individual will severly limit their ability to take advantage of the opportunity.

Worldwide income distributions were estimated by aggregating the populations of countries with per capita incomes similar to that of the United States. For the remaining, less wealthy world population, five percent was assumed to have upper income levels similar to the United States. These statistics were obtained from the World Almanac with populations adjusted to the year 2020. From this information, the number of households worldwide with income levels comparable to USA standards is 4 to 5 times greater than just USA statistics alone. Specifically, the USA income distribution statistics was multiplied by a factor of 4.62 to arrive at the worldwide households with equivalent income levels.

The number of worldwide households with incomes above a specified level is shown in Table 3.5.6.3-1. World wealth is growing at an uninflated rate of roughly 2% a year compounded. Thus, by the 2020, these population statistics could grow by another 67%. This has not been incorporated into this paper. The distinction between households and people is that for each of the 94 million households in the United Stated in 1991 there was an average of 2.63 people.

A major unknown in this study is the visitation rate to the space resort. In this study visitation rate was assumed to depend on two factors: 1) affordability and 2) propensity to consume (inclination to spend scare household resources on consumables such as vacations). To estimate the effect of affordability on visitation rate, the statistics on household income distribution was used to identify the number of households who could afford trip.

The rule of thump on affordability was that only those households with an income three times greater than the cost of the trip were financially "qualified" to do so. As the statistics in the section of this report demonstrates, there are plenty of households that could afford to take the trip to the space resort. The primary issue is how many households would elect to do so and how often?

The cost of a five day vacation at the space resort will be a major expense for most households. Even the most optimistic economic scenario assumed in this paper, with space transportation costs at $25 a pound, the household cost of a 5 day space resort vacation is $25-35,000 or equivalent to the purchase of a luxury car - a BMW, Lexus, or Mercedes.

Even at this comparatively low cost for a 5 day vacation at the space resort, there are simply too many economic choices competing for the consumer's money. For instance, a household could elect to spend a vacation in Paris, France and still purchase a luxury car (albeit a less exotic model) for the same cost as a trip to the space resort.

To estimate the effect of consumption propensity (willingness to spend scare economic resources on high priced consumables such as a 5 day vacation at the space destination resort) on visitation rate, the following rules of thumb were established. First, for those households with an inclination to visit the space resort, the trip was assumed to be a once in a lifetime experience.

Since only households headed by adults between the ages of 25 to 55 were considered in our income statistics, a lifetime for a household is assumed to be 30 years for purposes of this study. Second, only one household in ten is assumed to have an inclination to visit the space resort.

These rules of thumb are arbitrary and therefore debatable. In their defense, one could claim that they are not unreasonable, provide a measure of the economic viability of space tourism based upon demand, and more importantly, they produce visitation rates that make the space resort economically viable.

Thus, the visitation rates assumed in this study could be viewed as those required to make the commercial venture feasible rather then a prediction of how many households will actually visit. Visitation rates lower than those calculated in this report will tend to make space tourism and space entertainment considerable less economically viable. Likewise, higher visitation rates higher will make these market segments more attractive.

The actual visitation rate is difficult to predict because a visitation at the space destination resort is not currently an option. If surveyed, most people would probably consider a visit to a space destination resort as an absurd notion. But in the future, as space travel by ordinary people becomes safer and more common place, the notion will not seem as far fetched. In fact, once the space resort is in place, with its potential for extensive entertainment and adventures, it may become the one-of-a-kind place and experience that everyone will want to visit at least once in their lives.

An all-space television channel, broadcasting people and activities in space and watched periodically by most of the people who inhabit the planet will stimulate demand even more. The larger the space resort facility becomes and the more it is promoted from the all-space broadcasting channel on television, the more people who will want to experience the phenomena themselves.

Thus, as space becomes more familiar and routine, it will become a focal point in people's lives. Something that must be experienced in one's lifetime. As space becomes a natural place to visit, space as a destination and experience, will take on a unique appeal unrivaled by anything on Earth. Households will begin to serious consider the trip to the space resort in the same way they consider the purchase an automobile, "Should we purchased tickets this year or next?"

In the model shown in Figure 3.5.6.3-2, if household income level is at least three times greater than the estimated cost (the affordability rule), then the baseline visitation rate to the space resort is assumed to be one-tenth of once-in-a-lifetime or 1 in 300 per year. However, the baseline visitation rate is adjusted to account for incomes that are above or below the affordability rule.

Thus, for each income group, the baseline visitation rate was multiplied by an adjustment factor, or multiplier, to account for the fact that as income increases relative to cost, a household unit is more likely to make the trip or at least not be discouraged because of its cost.

Thus, the demand curve for space tourism is the product of the baseline visitation rate and the affordability multiplier. The affordability multiplier has the effect of increasing or decreasing the visitation rate for households whose incomes lie above and below the level considered to be affordable (an income three times the cost).

The logic of the affordability multiplier is that as the income-to-cost ratio gets larger, the cost is easier to absorb in the household discretionary budget. In the reverse, the smaller the income-to-cost ratio, the more difficult a household would have in justifying such an expensive expenditure, not only to themselves but to a financing loan officer. In other words, prosperity boosts the "propensity to consume" which rises and falls with household income levels.

The following example is intended to clarify the affordability multiplier. If the cost of the vacation at the space resort was $75,000, then the baseline demand is 1 in 300 for households whose income is three times the cost or $225,000. If the household income is greater than three times the cost, the demand is increased directly proportional to the higher income. The logic for this increase in affordability multiplier is that higher income households are less intimidated by the cost.

Thus, a household with an income of $300,000 would have an affordability multiplier of 1.33 (calculated by the ratio: income-to-cost ratio divided by 3 or $300,000/$75,000/3). This factor has the effect of increasing by one fourth the baseline demand for households in the $300,000 income level. A household with an income of $750,000 would have a affordability multiplier of 3.33.

For households with less income than three times the cost, $150,000 for example, the demand is decreased. In fact, to reduce demand even faster for lower income households, I have elected to decrease the demand as the square of the income-to-cost ratio divided by three. For example, the affordability multiplier for households with an income of $150,000 and cost is $75,000 is only .44 (calculated as follows: ($150,000/$75,000/3)^2). The rationale for taking the ratio ( which is less than one) and squaring it is to sharply reduce the demand as the income-to-cost ratio falls below three to account for affordability.

The overall effect of the affordability multiplier is as follows:

  1. To increase the demand for space tourism higher than what would have prevailed if a straight multiplier of the baseline value of 1/300 was applied to all households with an income above three times the cost;
  2. To decrease the demand rapidly for space tourism instead of cutting demand to zero for household's whose income is less than three times the cost; and
  3. To set demand for space tourism at zero for household incomes less than the cost.

In summary, the visitation rate to the space resort is based on the following factors: 1) USA household income distribution statistics multiplied by a factor of 4.62 to account for worldwide population, 2) the baseline visitation rate is applied only to households with an income above the ticket price and an income-to-cost ratio of three, 3) a baseline visitation rate of 1 in 300, and 4) an adjustment to the baseline visitation rate to account for higher and lower income-to-cost ratios.

The resultant household demand for a 5 day vacation at the space resort as a function of price is shown in Figure E.1.2.2-6 To adjust this demand curve from household to individual, the demand was divided by 2.63, the number of people in a household. To adjust this demand curve from a 5 day vacation in space to a one day ride cruise on a space ship, the demand was divided by 3 to reflect the relative value of a 5 day vacation at the space resort compared to a one day cruise on a launch vehicle. Both of these are also shown in Figure E.1.2.2-6.

PriceAnnual Demand for a 5 Day Vacation at the space resort for a HouseholdAnnual Demand for a 5 Day Vacation at the space resort for an IndividualAnnual Demand for a One Day Ride into Space for an Individual
$25,000170,00065,00022,000
$50,00067,00025,0008,300
$100,00020,0007,6002,500
167,0005,9002,200700
$250,0003,1001,200400
$500,00070027090
Figure E.1.2.2-6. Five and One Day Demand for Different Ticket Prices

References

A-1 Space Expeditions, Project Space Voyage, Society Expeditions, Seattle, 1987.

Back to top

Appendix E Transportation Appendix

Back to top