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"Complex" Real Options - Title Page - MIT

"Complex" Real Options - Title Page - MIT

To generate this output,

To generate this output, it was assumed that all airlines and airframers were rationalagents that made decisions based on maximizing their net present value. Based on thisassumption, it was assumed that if planes were technically exactly the same, airlineswould buy them in equal numbers, but if the planes are different airlines would increasein likelihood of buying a plane that was expected to increase profitability. In the model,airlines can not know a priori what plane will maximize profits, as future uncertainty hasnot been resolved yet and the future conditions may change from when the plane wasordered.For example, if current fuel prices are low, airlines may forecast continued low fuelprices and buy planes that are lower in cost but less fuel-efficient. If the future changes,the airlines may be stuck with a fleet that has a high operating cost due to the low fuelefficiencyof the fleet. This example is shown in Figure 5-15 with a changing order ratefor two planes. Plane A is a low-cost, low efficiency plane and Plane B is a high-cost,high efficiency plane. At the start of the simulation, fuel prices are low and Plane Aoutsells Plane B. However, a sudden fuel price increase after a number of years causesthe ordering patterns of airlines to reverse, with Plane B outselling Plane A until the endof the simulation.Plane APlane BFuel PriceIncrease StartsTotalPlane BPlane AFigure 5-15 Ordering rate for two competing planes: Plane A is low-cost/low efficiencyand Plane B is high-cost/high efficiency. Fuel prices start low and increase after about 20years.186

5.2.5 MODEL VALIDATIONThe system dynamics model was validated in four ways. First, the structure of the modelwas seen as valid, given the similarities from expanding on the previously published andextensively used Weil model (Weil 1996). Second, the model was used to try andrecreate historical outputs for such driving factors as passenger demand and capacity. Acomparison of the historical passenger demand and aircraft capacity produced by themodel with historical data is shown in the two figures, Figure 5-16 and Figure 5-17.Historical data (all planes)Model data (all planes)Model data (wide bodies)Model data (narrow bodies)Figure 5-16 Comparison of historical data and model produced results for historicaldemand. Historical demand from 1984 – 2005 is shown in the figure.187

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    ACKNOWLEDGEMENTSThis dissertation i

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    students. I am sure I am missing pe

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    6.7 Enterprise and Institutional Ch

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    Table 8-8 Summary of existing mode

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    Figure 3-17 System management loop

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    Figure 5-13 Historical world annual

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    Figure 7-19 Decision path for ITS m

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    Figure 10-3 Summary of differences

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    1. A large commercial aircraft maki

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    made to the system are often not on

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    From the MIT Engineering Systems Di

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    enterprise, the enterprise itself m

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    system capable of coping with uncer

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    Ch. 2Ch. 3Ch. 4Ch. 7Ch. 5Ch. 8Ch. 6

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    applicability of the framework. Fin

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    Myers, S. (1977) Determinants of Ca

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    FindingsFigure 2-1 Research process

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    • Difficult to predict future beh

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    As is apparent in the literature, t

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    of these. Ideally, either with the

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    do not appear to be mutually exclus

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    The ability for a system to activel

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    price (the option price) for the fl

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    and the results can be easier to ex

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    For some real options this appears

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    there is value to waiting to see wh

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    2.5 REAL OPTION PROCESSESExisting p

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    option is then evaluated with a “

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    • Option to engage in exploration

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    elatively straight-forward and are

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    OptionComplexityReal option in syst

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    2.8 REFERENCESAllen, T. et. al. (20

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    Hayes, R. and D. Garvin. (1982) Man

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    Ross, A. (2006) Managing Unarticula

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    3 LIFE-CYCLE FLEXIBILITY (LCF) FRAM

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    3.1 OVERVIEW OF NEED FOR LIFE-CYCLE

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    Figure 3-3 Condensed version of the

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    level, the appropriate enterprise n

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    3.1.2.1 Conceiving an OptionThe abi

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    3.1.2.2 Design and Evaluation of Op

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    option holder can not exercise the

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    system’s underlying structure and

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    3.2.2 DECISION TO USE LCF FRAMEWORK

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    Figure 3-11 Integration of decision

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    ounded rationality is not an issue,

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    quantitative analysis chapters, Sec

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    meantime, the land now would have d

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    3.2.5 DESIGN STRATEGY FOR OPTION EX

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    anticipated that external political

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    Figure 3-16 illustrates how the str

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    3.2.6 MANAGING THE SYSTEMManaging t

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    System Management LoopFigure 3-17 S

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    System Management LoopSystemImpleme

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    Long-term Management Loop ofUnknown

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    Long-term Management Loop of Unknow

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    Enterprise Readiness is included as

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    Figure 3-23 Condensed LCF Framework

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    3.4 REFERENCESAllen, T. et. al. (20

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    4 FLEXIBILITY IN BLENDED WING BODY

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    4.1.1 THE EARLY YEARSAfter the firs

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    Figure 4-2 Sikorsky S-42 Flying Boa

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    The 1950’s saw aircraft shift fro

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    to the government for doing so, wou

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  • Page 149 and 150: With a bi-wing (or tri-wing) constr
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  • Page 155 and 156: Additional benefits of the BWB arch
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  • Page 159 and 160: lower costs, higher scales of econo
  • Page 161 and 162: Miller, B. (2005) A Generalized Rea
  • Page 163 and 164: 5 VALUE OF FLEXIBILITY IN BLENDED W
  • Page 165 and 166: This chapter is composed of three m
  • Page 167 and 168: this research were deemed necessary
  • Page 169 and 170: For clarity of discussion, a high l
  • Page 171 and 172: model, a better understanding of co
  • Page 173 and 174: An overview of each of these subsys
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  • Page 177 and 178: Figure 5-9 Airline finances and pro
  • Page 179 and 180: Figure 5-10 Airline profitability,
  • Page 181 and 182: Product design is based on a trade-
  • Page 183 and 184: The airframe manufacturer productio
  • Page 185: $70Inflation Adjusted Crude OilPric
  • Page 189 and 190: Forecast data (all planes)Model dat
  • Page 191 and 192: 5.3.1 INHERENT BENEFITSBWB technica
  • Page 193 and 194: minor differences between aircraft
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  • Page 197 and 198: derivative depends on corporate str
  • Page 199 and 200: Table 5-1 Number of derivatives lik
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  • Page 203 and 204: The results presented can be interp
  • Page 205 and 206: Compared to the Boeing 787, the dev
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  • Page 209 and 210: In the opposite case where the BWB
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  • Page 219 and 220: 5.4 REFERENCESAirbus. (2006) Annual
  • Page 221 and 222: 6 CHALLENGES OF FLEXIBILITY IN BLEN
  • Page 223 and 224: FindingsFigure 6-1 Case study analy
  • Page 225 and 226: Figure 6-2 Characteristics of case
  • Page 227 and 228: 6.1.3 INTERVIEWEE SELECTIONAs the i
  • Page 229 and 230: Table 6-2 ITS case study organizati
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  • Page 233 and 234: 2. If flexibility is used, can you
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    primarily through military and NASA

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    Figure 6-7 Delivery and market fore

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    to meet rising demand, the overall

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    Another option widespread in the ai

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    design, evaluate or manage flexibil

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    Interviewee views on flexibility ce

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    and evaluations are based around th

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    operating and maintenance costs by

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    when fuel costs increased substanti

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    options, such as cross-program deri

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    6.9 REFERENCESAirbus. (2007) Produc

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    7 FLEXIBILITY IN HOUSTON GROUNDTRAN

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    Figure 7-2 Characteristics of case

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    cases can be added to existing or n

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    7.2.2 STANDARD ITS TECHNOLOGIES AND

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    • increased opportunities for pri

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    for Inherently Low Emitting Vehicle

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    Marker 2005). This type of cross fu

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    Figure 7-4 Plastic pylon separated

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    ecause the network of sensors can t

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    operating conditions. Additional ro

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    DSRC based system would require a l

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    Houston has already deployed one of

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    Figure 7-13 Transit center location

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    Figure 7-15 Houston’s managed lan

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    as HOT or TOT lanes. This can be es

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    BuildtraditionalinfrastructureDelay

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    HOT / BRTlaneNon-flexibleTOT / BRTl

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    BuildtraditionalinfrastructureDelay

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    or improved safety functions could

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    Haning, C. and W. McFarland. (1963)

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    8 VALUE OF FLEXIBILITY IN HOUSTON G

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    attempt was made to completely repr

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    Figure 8-4 Quantitative analysis pr

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    8.2.1.1 Travel Demand ModelingThe t

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    ange of traffic analysis studies to

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    I-10 KatyFreewayI-610(innerloop)Bel

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    5 lanesFigure 8-10 Example of satel

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    Beltway 8(secondary loop)I-610 (inn

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    8.2.2.5 Major Modeling AssumptionsD

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    from a public agency that is intere

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    funding improvements that would pre

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    This is because of the low-cost of

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    From the analysis above, with the d

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    Figure 8-16 Addition of two general

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    capabilities are typically deployab

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    Table 8-5 Benefit-Cost Ratios for K

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    35%30%25%Probability20%15%10%5%0%$(

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    Figure 8-20 NPV density function, w

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    Table 8-6 Summary of flexibility to

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    Figure 8-23 Comparison of ITS/delay

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    vehicles would continue to gain fre

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    Figure 8-24 Value of time savings f

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    This illustrates the importance of

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    Table 8-10 Summary of ITS case stud

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    Similar to the above discussion of

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    9 CHALLENGES OF FLEXIBILITY IN HOUS

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    new challenges as well as increase

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    9.2 QUALITATIVE ANALYSIS PROCESSPre

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    The qualitative research methodolog

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    to be able to answer the research q

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    Table 9-1 Functional activities per

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    USDOT, Volpe Center, Officeof Syste

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    3. If flexibility is used, can you

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    • Increased data sources - The no

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    importance that Harris County plays

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    Figure 9-7 H-GAC area of responsibi

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    Figure 9-9 State level stakeholders

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    9.3.2.3 State Legislators and Gover

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    met with business interests before

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    The resulting plan forecasted more

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    Discussions with interviewees with

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    Currently, the cross section of the

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    Also of interest is another part of

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    y the Southern Pacific Railroad. In

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    9.6 PROCESSES FOR IDENTIFYING, DESI

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    The federal level interviewee conti

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    may not be tied to a physical proje

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    During the interview process, sever

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    Figure 9-15 Katy Freeway configurat

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    Monitor/ManageFigure 9-16 Summary o

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    company on a schedule to complete t

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    interviewees commented on the ongoi

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    facilities has created a lack of wi

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    eversible HOV lanes as a safety pre

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    the real option and the decision to

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    • Mechanism for creating pressure

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    9.9.2.2 Uncertainty as a Result of

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    option purchase price. This was bec

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    9.10 REFERENCESABC7. (2004) Chicago

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    Judd, D. and T. Swanstrom. (2004) C

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    10 FINDINGS AND CONCLUSIONSChapter

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    concerns the use of real options

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    Table 10-1 Summary of major researc

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    to a system. Rather, these options

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    future option exercise can prevent

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    Q1-2. The case studies provided a d

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    Currently, the Silver Line right-of

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    technical system as well as the soc

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    In the ITS case study, the transpor

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    system that the technical system is

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    option exercise unlikely (building

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    some future date. This type of wast

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    DesignPhaseEvaluationPhaseManagemen

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    ITS capabilities used to create the

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    technical and social components of

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    incorporated directly into the mode

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    As defined in Section 2.6, the diff

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    In the BWB case study, an enterpris

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    For “standard” real options it

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    “Standard” real options are des

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    From the research it was found that

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    d. Evaluating the option with quant

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    need for the system is, while simul

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    10.7 REFERENCESClemons, E. and B. G

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