sub-orbital space tourism: predictions of the future ... · sub-orbital space tourism: predictions...

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SpaceWorks Engineering, Inc. (SEI) www.sei.aero 1 Mr. A.C. Charania Senior Futurist SpaceWorks Engineering, Inc. (SEI) [email protected] Dr. John R. Olds CEO SpaceWorks Engineering, Inc. (SEI) [email protected] Mr. Dominic DePasquale Systems Engineer SpaceWorks Engineering, Inc. (SEI) [email protected] SUB-ORBITAL SPACE TOURISM: Predictions of the Future Marketplace Using Agent-Based Modeling IAC-06-E3.4.01 57 th International Astronautical Congress (IAC) 02-06 October 2006, Valencia, Spain Revision A 04 October 2006

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Page 1: SUB-ORBITAL SPACE TOURISM: Predictions of the Future ... · SUB-ORBITAL SPACE TOURISM: Predictions of the Future Marketplace Using Agent-Based Modeling ... -Simulation can represent

SpaceWorks Engineering, Inc. (SEI)www.sei.aero

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Mr. A.C. CharaniaSenior FuturistSpaceWorks Engineering, Inc. (SEI)[email protected]

Dr. John R. OldsCEOSpaceWorks Engineering, Inc. (SEI)[email protected]

Mr. Dominic DePasqualeSystems EngineerSpaceWorks Engineering, Inc. (SEI)[email protected]

SUB-ORBITAL SPACE TOURISM:Predictions of the Future Marketplace Using Agent-Based ModelingIAC-06-E3.4.0157th International Astronautical Congress (IAC)02-06 October 2006, Valencia, Spain

Revision A04 October 2006

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Contents

Firm OverviewOverview of Agent-Based Modeling NESC Model OverviewSample NESC Model Simulations

SpaceWorks Engineering, Inc. (SEI)www.sei.aero

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Firm Overview

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SpaceWorks Engineering, Inc. (SEI)www.sei.aero

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Introduction to SpaceWorks Engineering, Inc. (SEI)

Overview:- Engineering services firm based in Atlanta (small business concern)- Founded in 2000 as a spin-off from the Georgia Institute of Technology- Averaged 130% growth in revenue each year since 2001 - 85% of SEI staff members hold degrees in engineering or science

Core Competencies:- Advanced Concept Synthesis for launch and in-space transportation systems- Financial engineering analysis for next-generation aerospace applications and markets- Technology impact analysis and quantitative technology portfolio optimization

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Practice AreasSpace Systems Analysis | What is the System?Conceptual Level Engineering AnalysisConceptual Level Engineering DesignLife Cycle AssessmentCost EngineeringAdvanced / Robust Design Processes

Technology Prioritization | What are the Implications? Technology AnticipationTechnology Benefit AssessmentsTechnology Prioritization

Financial Engineering | Is the Project Viable?Business DesignFuture Venture Due DiligenceReal Options Analysis

Future Market Assessment | What is Next?Scenario PlanningMarket ForecastingMarket Analysis

Policy and Media Consultation | How to Express the Vision?Government InitiativesPolicy ConsultationTelevision, Film, Radio, Internet Presence

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From Vision to Concept

Including:- Engineering design and analysis- New concept design- Independent concept assessment- Full, life cycle analysis- Programmatic and technical analysis

Including:- Storyboards- Technical concept illustrations (marker and pastel in B&W and color)- 2-D line engineering drawings with technical layouts and dimensions- 3-D engineering CAD models of concept designs- High-resolution computer graphics imaging (renders) - Concept / architecture summary datasheets and single page handouts / flyers

SpaceWorks Engineering, Inc. (SEI)www.sei.aero

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Including:- 2nd, 3rd, and 4th generation single-stage and two-stage Reusable Launch Vehicle (RLV) designs (rocket, airbreather, combined-cycle)- Human Exploration and Development of Space (HEDS) infrastructures including Space Solar Power (SSP)- Launch assist systems- In-space transfer vehicles and upper stages and orbital maneuvering vehicles- Lunar and Mars transfer vehicles and landers for human exploration missions- In-space transportation nodes and propellant depots- Interstellar missions- In-space and surface human habitats

Concepts and Architectures

Image sources: SpaceWorks Engineering, Inc. (SEI), Space Systems Design Lab (SSDL) / Georgia Institute of Technology

SpaceWorks Engineering, Inc. (SEI)www.sei.aero

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Recent Exploration Experience

Including:- NASA Exploration Systems Mission Directorate (ESMD) Concept Exploration and Refinement (CE&R) Study Subcontractor- NASA Exploration Systems Mission Directorate (ESMD) Economic Development of Space (EDS) Project- NASA MSFC exploration architecture trade studies (launch vehicles, in-space stages, lunar landers)- NASA MSFC Prometheus follow-on study: Nuclear Electric Propulsion (NEP) mission to Pluto/Kuiper Belt- NASA LaRC Lunar Lander Preparatory Study Phases 1 and 2 Concept Design for NASA JSC - Rocketdyne propulsion technology assessment on lunar exploration architectures- Mission Scenario Analysis Tool (MSAT) architecture optimization tool development- Moonraker in-space stage and habitat sizing tool development- In-space trajectory tool development- Lunar exploration economic and life cycle cost analysis

Image sources: NASA

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Sample Economic Analyses

Human Exploration Cost Estimates Scenarios of Reusable Launch Vehicle (RLV) Price Sensitivity

500

1,500

2,500

3,500

4,500

25% 50% 75%Turn-Around-Time Reduction

Pric

e Pe

r Pou

nd P

aylo

ad [$

/lb]

20

40

60

80

100

120

140

Flig

ht R

ate

[Flig

hts

Per

Yea

r]

Price Per Flight [$/lb]

Flight Rate [Flights/Year]

500

1,500

2,500

3,500

4,500

25% 50% 75%Turn-Around-Time Reduction

Pric

e Pe

r Pou

nd P

aylo

ad [$

/lb]

20

40

60

80

100

120

140

Flig

ht R

ate

[Flig

hts

Per

Yea

r]

Price Per Flight [$/lb]

Flight Rate [Flights/Year]

1,0002,0003,0004,0005,0006,0007,0008,0009,000

10,000

25% 50% 75%Turn-Around-Time Reduction

Pric

e Pe

r Pou

nd P

aylo

ad [$

/lb]

20

25

30

35

40

Flig

ht R

ate

[Flig

hts

Per

Yea

r]

Price Per Flight [$/lb]

Flight Rate [Flights/Year]

1,0002,0003,0004,0005,0006,0007,0008,0009,000

10,000

25% 50% 75%Turn-Around-Time Reduction

Pric

e Pe

r Pou

nd P

aylo

ad [$

/lb]

20

25

30

35

40

Flig

ht R

ate

[Flig

hts

Per

Yea

r]

Price Per Flight [$/lb]

Flight Rate [Flights/Year]

Oper

atio

ns C

ost R

educ

tion

DDT&E AND TFU COST REDUCTION25% 75%

25%

75%

Components of LCC (FY06)

Other (Robotic/ISS/Shuttle)

CEV/CM

CLV

LSAM

CaLV-HLLV

EDS + CEV/SM

Technology Maturation Surface Systems

Facilities, Operations, and Flight Tests

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Year

$M

$111.3 B (2006-2018) $53.4 B (2019-2025)$164.7 B

NASA FY06 Exploration-Related Budget

See: http://www.sei.aero/library/technical.html for more information and technical papers on above analyses

Space Tourism Economic Modeling International Space Station (ISS) Support Market

-100M

-50M

0M

50M

100M

0 2 4 6 8 10 12

Disc

ount

ed C

umul

ative

Ca

sh F

low

(US

$)

Project Year

Effect of Competition

Higher-End Operator

In Competition with Higher-End

Lower-End Operator

Effect of Market Entry Date

0 2 4 6 8 10 12Project Year

-40M-20M

0M20M40M60M80M

-60M-80M 2 Year Market Delay

4 Year Market Delay

Higher-End Operator

Lower-End Operator

5 Commercial Competitors + min. 2 CEV/Yr + Russian Competition

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SEI’s Background Related to Economics of Emerging Commercial Space Transportation

Sample Economic Analysis Tools:- NESC (Nodal Economic Space Commerce Model, agent-based space market simulation financial tool) - CABAM (Cost and Business Analysis Model, general space transportation)

- LMNoP (Launch Markets for Normal People, tourism model)

Recent Projects:-Economic Development of Space (EDS)sponsored by NASA Langley Research Center-Simulating Emerging Space (SES) Industries with Agent-Based Modeling sponsored by NASA Marshall Space Flight Center

Recent Papers (www.sei.aero):-Charania, A., Kanamori, H., "Extensions of NASA's Exploration Architecture: Performance Capabilities and Market Economics of a Lunar Propellant Production Facility," ISTS-2006-k-13, 25th International Symposium on Space Technology and Science (ISTS), Kanazawa City, Ishikawa Prefecture, Japan, June 4-11, 2006.-Charania, A., DePasquale, J., "Agent-Based Modeling of the Space Tourism Market," ISDC 2006-355, 25th International Space Development Conference, Los Angeles, California, May 4-7, 2006.-Charania, A., Bradford, J. E., Olds, J. R., "Economic Development of Space: Examination and Simulation," IAC-05-E3.3.08, 56th International Astronautical Congress, Fukuoka, Japan, October 17-21, 2005.-Charania, A., DePasquale, D., "Simulating the Dynamic Marketplace: An Introduction to the Nodal Economic Space Commerce (NESC) Model," AIAA-2005-6617, Space 2005, Long Beach, California, August 30 - September 1, 2005.

Sample Clients and Partners:

NESC ModelSub-orbital Public Space Flight Market

NESC ModelCommercial Support of the

International Space Station (ISS)

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Overview of Agent-Based Modeling

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Trying to Model the World (or even a small piece of it)

Source: Stephen Eubank, “Social Networks and Epidemics,” Basic and Applied Simulation Sciences, Los Alamos National Laboratory

The world is complex

Complex group interactions

Simple individual/agent behaviors

Conditions change -> agent behaviors change

Microsoft Excel – strains to model complexity

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Nodal Economic Space Commerce (NESC) Model

The Nodal Economic Space Commerce (NESC) model is a dynamic, agent-based space market simulation and financial engineering tool

Agent-Based Modeling (ABM): allows heterogeneous agents with varied and dynamic behavior

- Qualities: emergent phenomena, natural description of system, flexible- Simulation can represent plants and animals in ecosystems, vehicles in traffic, people in crowds, or

autonomous characters in animation and games

Modeling space capitalism in NESC- Between competitors, includes current and future competitors (expendable and reusable)- Entrance of new competitors within existing and new markets - Explore variations in customer preferences- Current markets: sub-orbital space tourism and ISS support- Use available data (Futron, etc.) on demand and estimate supply

Companies compete for customers with the goal of maximizing revenues

- Each company autonomously decides its pricing strategy given its unique capacity, costs, and vehicle characteristics

- Model outputs financial health of each company- Model differences in products/services

Based Upon “REcursive Porous Agent Simulation Toolkit”RePast Sources: http://www.duncanrobertson.com/research/simulation.htm, http://sourceforge.net/projects/repast/, http://complexityworkshop.com/cw/tutorial/RePast/index.html

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Users of Agent-Based Modeling (ABM)

P&G to understand the impact of alternative shipment and payment terms on retail in stock positions and company inventory

Macy’s to generate new store layout options for maximizing customer satisfaction and spending

Hewlett Packard to understand the effect on organizational performance by a change in hiring practices

NASDAQ to understand what happen when the “tick size” changes from 1/8 of a dollar to 1/100 of a dollar

U.S. Department of Defense to conduct war games predicting battlefield outcomes in a networked information environment

Pricewaterhouse Coopers to predict CD sales in the Japanese pop (J-Pop) market using 75,000 agents (correlation coefficients of actual and predicted sales between 0.8 and 0.9)

Electronic Arts (EA) and their “The SIMS” game

Sources: “Agent-based Modeling: A valuable new weapon for Chief Marketing Officers in the fight of their lives,” EMM Group, Inc., 2004, http://www.red3d.com/cwr/ibm.html

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NESC Model Overview

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Context: “Emerging” Space Products and ServicesSpaceWorks Engineering, Inc. (SEI)

www.sei.aero

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NESC Dynamics: Space Tourism

Company A

Has unique:Costs

Vehicle CharacteristicsDiscount rate

Desires to maximize:Profits = Sales - Cost

3

Limited information sharing:• Price from prior year• Vehicle characteristics

Company BSame logic as Company

A but with different product

Company CSame logic as Company

A but with different product

Company adjusts pricing strategy:• Stay at current• Higher• Lower• Match competitor

4

4

4

1Price offering per year Customers purchase

21

2

orSpace Tourism Market

P

QQ*

P*

Potential Market Multipliers

Use Aggregate Market Curve Model Individual Customers

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One at a Time: A Sub-Orbital Space Tourism Customer “Agent”

Used to make purchase choices

Willingness to Pay (Wealth Surveys)Interest

Behaviors

Dependent on company offering

Reliability (linear)Appeal (linear)

Windows (LMNoP- Georgia Tech model)Seat Belt Freedom (Futron Study)

Company Interest Factors

Changes with time

Pioneer or Imitator

Diffusion Interest Factors

Constant with time

Base interest in suborbital

Base Interest Factors

Who is the Customer?

Does the customer want

to buy?

Who does the customer want to buy from?

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NESC Company/Customer/Market Agent Interaction

Evaluate pricing optionsRemain at current priceRaise priceLower price

Alter price if desired

Make offer to market

Calculate financial metrics

Examine profit

Estimate price for desired ROI

Make offer to market

Initial Price

Subsequent Price

Pass company offers to customers

Match customer demand to supply

Return number sold

MARKET AGENTS

Evaluate company offers

Rank companies in preferred order

Decide to buy or not

CUSTOMER AGENTS

COMPANY AGENTS

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Quality and Quantity of Space Tourists

Since sub-orbital space tourism is a new industry, little data is available from actual sales and company revenues

Data on customer characteristics and behaviors must be determined from market surveys, inferred from other industries, or deduced using intelligent assumptions

One such source is the Space Tourism Market Study conducted by Futron Corporation in cooperation with Zogby International

- The market study involved telephone interviews of 450 people with household income of at least US$250,000 annually or net worth greater than US $1 million to examine the size, growth potential, and customer characteristics of the suborbital and orbital tourism markets

The number of customers for the NESC sub-orbital model simulation is estimated to be around 53,000 for calendar year 2006. This is the number of customers who are interested in purchasing a sub-orbital experience and able to do so (financially and physically). It is derived by the following parameters:

- Number of Millionaires in World- Take proportion who have requisite net worth (assume willing to spend 1.5% of net worth)- Apply percent interested in participating (somewhat, very, and definitely likely) from Futron survey- Reduce for fitness requirements (split between those over and under age of 65)

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High Net Worth Individuals (HNWI) Population by Region, 2003 – 2005 (In Millions)

Source: Merrill Lynch and Capgemini, Source: http://www.us.capgemini.com/worldwealthreport06)* 2004 numbers have been refined and minimally restated, as every year more accurate and recent data or sourcesof information are gathered.Note: All chart numbers are rounded.Source: Capgemini Lorenz curve analysis, 2006

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Potential Customers at Various Prices (Source: Futron Space Tourism Market Study)

Cumulative % of Potential

Customers Willing to Pay at the

Indicated Price or Lower

0%

10%

20%

30%

40%

50%

60%

$0 $50 $100 $150 $200 $250 $300Price Per Consumer ($K)

$0 $50 $100 $150 $200 $250 $300Price Per Consumer ($K)

Experience: Sub-Orbital Space Tourism

The percentage of potential customers willing to pay for a suborbital tourism experience levels out at higher price points

The additional potential customers gained by decreasing price from $200 thousand to $150 thousand is small (a four percent increase) by comparison to the additional customers gained by decreasing price from $100 thousand to $50 thousand (a twelve percent increase)

This suggests that the market for suborbital space tourism is relatively inelastic at high prices, but elastic at low prices

Futron Suborbital Demand (extrapolated)

0200400600800

1,0001,2001,4001,6001,8002,000

$0 M $200 M $400 M $600 M $800 M $1,000 MTicket Price (US$ K)

2006

2008

2010

Annual Passenger Rate

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NESC: Sub-Orbital Space Tourism

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NESC: Sub-Orbital Space Tourism Model Visual Interface - Inputs

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Sample NESC Model Simulations

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Top Level Assumptions

Company input information based upon available public data- Since incomplete information for these companies, results are to be taken as

representative of industry as a whole and not specific to any one company

Sub-orbital space tourism companies make decisions based upon impact on financial bottom line and not other “human”desires

- Examined from the perspective of other capital investment projects and not as a hobby or altruistic venture

Several case studies are presented here as examples of the capabilities of the NESC sub-orbital space tourism model:

- Case A: One firm- Case B: Two firms (same start times)- Case C: Three firms (same start times)

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Overview of Firm Inputs

202020Maximum Flights Per Vehicle Per Year

0.250.250.25Debt-to-Equity Ratio

435Perceived Vehicle Appeal (Qualitative 1-5)

$1.0 M / Flight$0.2 M / Flight$0.5 M / FlightVariable Operating Cost Per Flight ($M FY2006)

$25 M / Year$8 M / Year$20 M / YearFixed Operating Cost Per Year ($M FY2006)

626Passenger Capacity

10.91Window Quality (Shared=0.25, Small=0.9, Large=1, Ceiling=1.25)

151715Risk Premium

334Perceived Reliability (Qualitative 1-5)

1.4811.48Vehicle Freedom (Belts=1, No Belts=1.48)

$10 M$9 M$10 MVehicle Production Cost ($M FY2006)

$20 M$10 M$50 MDevelopment Cost ($M FY2006)

535Number of Vehicles in Fleet

Firm 3Firm 2Firm 1Item

Customers: 53,000 potential sub-orbital space flight consumers over a 15 year project period with 1) the financial means to pay, 2) physical condition to fly, and 3) the interest in suborbital flight have been categorized into over 20,000 “agent types” based on personal characteristics such as: pioneer vs. imitator, influence of perceived vehicle reliability, willingness to pay at various ticket prices, influence of cabin freedom (e.g. seat belt requirements), influence of perceived vehicle uniqueness/intrinsic appeal, etc.Providers: A user-defined number of sub-orbital passenger vehicle developer/operators can be included in any simulation: Each provider has a realistic business model including development and production costs, operating costs, vehicle capacity, perceived reliability, etc. Each ‘CEO agent’ can adjust its market price for a ticket from year to year in an effort to improve profitability. Firms select their initial prices based upon ROI.Growth rate: 6% per yearPrice Ceiling: $500k/passenger maximum amount that can be charged

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Sample Simulation Results: Sub-Orbital Space Tourism Market

Case AOne Firm

Case BTwo firms (same start times)

Case CThree firms (same start times)

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Sub-Orbital Space Tourism Market: Preliminary Observations

Sub-orbital public space flight market can allow two companies to beprofitable over time

- A third competitor, competing with the top-tier operator, struggles to maintain viability- Can the first firms in the marketplace have enough capacity to capture total annual market?- Based upon results shown here and other sensitivity analyses previously performed- Caveat 1: Given current consumer and company modeling assumptions- Caveat 2: Need to re-examine in terms of higher fidelity NESC model (almost complete)

Optimal pricing strategy must take advantage of “pioneer” and “imitator” effects

- Initial prices should start higher (around $300k/ticket in simulations) than some initial “public” rates, companies could then decrease (to close to $150-200k/ticket) to maximize profit

- “Virgin Galactic has, in the near term, been focusing on what it calls the ‘Founders’, its group of the first 100 customers who have paid their full $200,000 ticket price up front. With the Founders group now filled up, Virgin is now promoting two other groups of passengers: Pioneers and Voyagers. The Pioneers will be the next 400 passengers, paying a deposit of between $100,000 and $175,000, while the Voyagers will follow the Pioneers, putting down a deposit of 10 percent of the ticket price, or no more than about $20,000.” (Source: http://www.thespacereview.com/article/717/1, Monday, October 2, 2006)

Future work will include enhancement and additional analysis- Include the effect of failure (cost and downtime) upon market demand and suppliers (Monte Carlo

analysis)- Better pricing determination- Enhance financing model to include injection of venture capital and mezzanine financing, including

stocks/warrants (beyond current debt-to-equity ratio formulation)

NESC capability is ready to be applied by SEI for commercial ventures

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www.sei.aero

Business Address:SpaceWorks Engineering, Inc. (SEI)1200 Ashwood ParkwaySuite 506Atlanta, GA 30338 U.S.A.

Phone: 770-379-8000Fax: 770-379-8001

Internet:WWW: www.sei.aeroE-mail: [email protected]