Addressing Uncertainty about Future Airport Activity Levels in Airport Decision Making (2012)

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128 This appendix summarizes research identifying, describing, and evaluating methodologies for recognizing and accom- modating unforeseen events and developments in plans that rely on airport activity level forecasts. The research involved a combination of a literature review and sourcing information from airport planners, managers, and other industry experts. Literature Review A review of previous research was undertaken in order to better understand methods and procedures for recognizing uncertainty and accommodating it into the airport planning process, and to gain insight into how uncertainties and risks can be incorporated into the airport planning process. In total, nearly 50 studies were reviewed. Most documents were retrieved from peer-reviewed academic or industry journals and other publications. Other materials were the product of government-related commissions or public–private policy institutes, theses or working papers, or airport and transpor- tation planning textbook chapters. Industry Review In addition to the literature review, information was obtained from the following members of the wider airport community (information correct at the time of research): • Lloyd McCoomb, CEO, Greater Toronto Airport Authority. • Dr. Richard de Neufville, Professor of Engineering Systems and Civil and Environmental Engineering, MIT. • Dr. Romano Pagliari, Course Director, MSc in Airport Planning and Management, Cranfield University. • Michael Matthews, Project Director of the Vancouver International Airport 2007-27 Master plan. • Paul Wessels, Director, Master Planning and Studies and Gerard van der Veer, Director Architectural Planning and Engineering, NACO, Netherlands Airport Consultants B.V. • Dr. Guillaume Burghouwt, SEO Economic Research. Dr. Burghouwt has written on flexible planning concepts and conducted a detailed case study of the planning pro- cess at Amsterdam Schiphol Airport. • Jan Kwakkel, PhD student, Delft University of Technol- ogy. At the time the research for ACRP Project 03-22 was conducted, Mr. Kwakkel was undertaking PhD research into adaptive airport strategic planning. • U.S. Transportation Security Administration (TSA). Pro- vided insight into the impact of security requirements on flexible airport planning. The findings from both elements of the research have been blended into a single discussion on industry best practice for recognizing unforeseen events and accommodating them into airport planning. Flexible Frameworks for Airport Planning Given the shortcomings of the traditional airport master plans and the traffic uncertainties facing airports, a num- ber of academics and researchers have proposed alterna- tive, more adaptable approaches to airport planning. A key element of these proposed approaches is to try to build far greater flexibility into the planning process. McConnell notes that while many definitions of flexibility exist, all of them share the common premise that flexibility allows a system to undergo change with greater ease or lower costs than if no flexible options were considered (McConnell, 2007). Different authors have proposed slightly different steps and procedures or variations, which can be identified as follows: • Dynamic strategic planning (e.g., de Neufville and Odoni, 2003), • Flexible strategic planning (Burghouwt, 2007), and A p p e n d i x e Flexible Approaches to Airport Planning and Real Options

129 • Reduce the uncertainty in the system; • Increase system robustness; and • Incorporate flexibility into the system (de Neufville, 2004). De Neufville notes that while not all aspects of uncer- tainty can be eliminated or mitigated, it is possible to reduce or mitigate some uncertainties through demand manage- ment techniques (i.e., uncertainties that are caused by mar- ket fluctuations) (de Neufville, 2004). The author suggests adjusting the price or the quality of a service provided by a system at different times and thereby making it possible to increase or decrease demand. As such, airport planners can influence the nature of the airport traffic (e.g., they can impede certain traffic types or facilitate others) (de Neufville and Odoni, 2003). De Neufville and Odoni use the following examples to clarify their point (de Neufville and Odoni, 2003): • Kansas City International Airport, where the passenger terminal was impractical to serve transfer traffic. Thus, the planning team encouraged the locally based airline to establish a hub at another airport. • London Luton Airport, where airport planners consciously targeted price-sensitive passengers and built airport facili- ties accordingly to keep costs low. • Singapore Changi Airport, which developed its airport facilities for premium services and became a major hub for business travelers. Flexible Strategic Planning This approach to planning, outlined by Burghouwt, draws heavily on the dynamic strategic planning approach of de Neufville and Odoni. However, it places additional empha- sis on proactive planning in the face of a broader range of uncertainties than just those inherent in traffic development (e.g., competitive positioning relative to other airports, influ- ence on regulatory changes) (Burghouwt, 2007). Burghouwt contrasts the differences between traditional master planning and flexible strategic planning as shown in Table E-1. Adaptive Airport Strategic Planning Adaptive airport strategic planning (AASP) (Kwakkel et al., 2008; Kwakkel et al., 2010) draws on ideas from the con- cept of adaptive policymaking as well as the two airport plan- ning approach described previously. Adaptive policymaking (Walker, 2000; Walker et al., 2001) is a generic approach for all kinds of organizations and uncertainties. Adaptive poli- cymaking attempts to create a base for future actions that is adaptable over time as future conditions and developments become manifest. • Adaptive airport strategic planning (Kwakkel, Walker, and Marchau, 2010). As the names suggest, these three approaches are fundamen- tally very similar, although they differ in detail, as discussed in the following. It should be noted that these approaches are largely conceptual, although based on real-world experience, and have not been fleshed out into detailed planning pro- cedures. In addition, the project team is not aware of these approaches being applied in practice, although there are exam- ples of airport planning that have, coincidently, used some ele- ments of these approaches. Each approach is discussed in further detail in the following. Dynamic Strategic Planning De Neufville and Odoni outline a dynamic strategic plan- ning concept in their airport systems book. They emphasize that dynamic strategic planning is compatible with the basic elements of traditional airport planning (i.e., master planning and strategic planning), and they consider dynamic strategic planning as “a marriage of the best elements of both master and strategic planning” (de Neufville and Odoni, 2003, p. 81). One of the ways dynamic strategic planning differs from traditional master planning is that rather than have most of the planning developed around a single forecast, the plan con- siders a range of forecasts. The approach allows for plans that can be relatively easily adjusted over time as events unfold and conditions change. De Neufville and Odoni compare a good airport planner with a chess player who thinks many moves ahead, chooses an immediate move that positions him/ her to respond well to whatever happens next, rethinks the issue after seeing what happens in the next phase, and finally adjusts his/her moves correspondingly. De Neufville and Odoni outline the following elements for development of the dynamic strategic plan: • Inventory of existing conditions; • Development of a forecast range of future traffic, includ- ing possible scenarios for major components (e.g., inter- national, domestic, transfer); • Determination of facility requirements suitable for several possible levels and types of traffic; • Development of several alternatives for comparative analysis purposes; and • Selection of the most acceptable initial development—the one that enables flexible responses to possible future condi- tions (de Neufville and Odoni, 2003). Discussing the management of uncertainty in engineering systems generally, de Neufville identifies three basic strategies to cope with uncertainties:

130 5. The implementation step involves the continual man- agement and adjustment of the plan based on the sign- posts and triggers set out in step 4. Four types of remedial actions are identified: a. Defensive: to protect the plan and preserve its benefits; b. Corrective: adjust the plan to meet unfolding events and conditions; c. Capitalizing: to take advantage of opportunities that arise and that will improve the performance of the basic plan; and d. Reassessment: when the analysis and assumptions crit- ical to the plan’s success have clearly lost validity. Kwakkel et al. also explore the use of exploratory modeling (EM) as a means to improve flexibility in the airport planning process (Kwakkel et al., 2010). EM is an operational research technique developed by the RAND Corporation. It involves the use of computer models to conduct experiments on the system of interest. In EM, the results of a model run are not viewed as a prediction or forecast of the future but rather as one possible outcome from the system under a given set of circumstances. By adjusting the inputs and behavior of the model, the analysis can build up a picture of the range of out- comes from the system. It can be seen as a form of scenario analysis involving greater technical analysis (“scenario analy- sis on steroids”). The authors developed a model of Amster- dam Airport Schiphol that incorporates a wide range of risk factors, including demand growth, technology, weather, and population. The model was used to assess the performance of the traditional master plan versus a flexible, adaptive plan. The model output provided not just financial and traffic per- formance but also noise impacts and emissions. AASP is designed to be a synthesis of the approaches above. As Kwakkel et al. state: The central idea of AASP is to have a plan that is flexible and over time can adapt to the changing conditions under which an airport must operate. AASP offers a framework and stepwise approach for making such adaptive or flexible plans. (Kwakkel et al., 2010, p. 1) The framework for adaptive airport strategic planning is illustrated in Figure E-1. The framework is made up of five steps: 1. Analyze existing conditions and specific goals for future development. 2. Specify the basic plan for achieving these goals, given exist- ing conditions. 3. Build in plan robustness through specification of: a. Mitigating actions to reduce certain adverse impacts of the plan; b. Hedging actions to reduce the risk or impact of uncer- tain adverse effects; c. Seizing actions to seize certain opportunities when they arise; and d. Shaping actions to reduce the chance that an uncertain external condition or event will make the plan fail, or increase the chance of an external condition or event making the plan succeed. 4. Contingency planning: specify signposts to be tracked in order to determine whether the plan is achieving its con- ditions for success. Critical values (i.e., triggers) are also specified that indicate when remedial action should be taken to keep the plan on track. Traditional Master Planning Flexible Strategic Planning Passive, reactive, adaptive Re-adaptive, pro-active Once-and-for-all anticipation/adjustment to change Continuous anticipation/adjustment to change Supply driven Demand driven Forecasts as predictions of the future Backcasting: Scenarios as guidelines of what may happen in the future Single-future robustness of plan and projects Multi-future robustness of plan and projects Long-term and short-term commitments Short-term commitments, long-term strategic thinking Preferred analytical tools: forecasting and net present value analysis Preferred analytical tools: scenario planning, decision analysis and real options, contingent road maps, scanning, experimenting Preferred alternative is optimal solution for a specific future Preferred alternative is best alternative across a range of possible future scenarios Risk implicitly ignored or risk aversion Think risk culture; risk as an opportunity Top-down/inside-out Top-down/bottom-up, inside-out/outside-in Reprinted by permission of the publishers from Airline Network Development in Europe and its Implications for Airport Planning by Guillaume Burghouwt (Farnham: Ashgate, 2007), p. 208. Copyright 2007. Table E-1. Characteristics of flexible planning.

131 As such, options are particularly useful in risky situations (de Neufville and Odoni, 2003). The real options concept applies this approach in the real, physical world rather than the financial world (although real options still have financial implications). The concept started to develop in the 1970s and 1980s as a means to improve the valuation of capital-investment programs and offer greater managerial flexibility to organizations. Trigeorgis (1996) identifies a number of common real options available to organizations: • Option to defer: A form of call option where, for example, an organization may hold the lease on some land but defer building a plant on the land until market conditions are right. • Staged investment: Staging investment as a series of out- lays, which allows abandonment of the project if conditions Real Options One concept that appears frequently in the literature on flexible or adaptive airport planning is real options. The concept of real options is based on, and developed from, financial options. In a financial context, options allow investors the right to acquire or to sell an asset (e.g., stock) at a specified price during a specified time frame. In short, an option is the right but not the obligation to take a certain course of action. There are two types of options: put options (the right to sell, generally to take advantage of good situation) and call options (the right to buy, to get out of a bad situation). As noted by de Neufville and Odoni, a remarkable feature of options is that their value increases with risk, which is the opposite of most other forms of assets. (Riskier assets generally have a lower value.) Source: Kwakkel et al., 2010, p. 5. Figure E-1. The steps of adaptive airport strategic planning.

132 Real options can also be applied to the mix of traffic as well as its volume. ACRP Report 25 describes the use of swing gates and space—a system of movable walls and internal pas- sageways allowing gates to be switched between domestic and international traffic, on a day-to-day basis [or to switch between different types of international traffic (e.g., U.S. ver- sus other international in Canada, or Schengen versus non- Schengen in Europe)]. The use of swing gates is becoming more common. Belin lists 29 airports worldwide using these gates, and the number is probably considerably larger over 10 years later (Belin and de Neufville, 2002). The overall layout of the airport also has real options implications. Where possible, a linear terminal layout is preferable to other layouts since it is the most easily expand- able in different directions (de Neufville and Odoni, 2003). Similarly, a modular design approach that includes repeat- able modules provides benefits regarding flexibility since it allows for an incremental airport development process that can be matched to traffic development (Landrum & Brown, 2010). Airport planners have to assume that airport facilities will acquire different uses over their lifetimes. Based on the literature review and the project team’s expe- rience, Table E-2 provides a summary of airport planning and design options that can be characterized as real options approaches. Real Options “on” Versus “in” a System De Neufville and Wang (2006) and de Neufville and Car- din (2009) distinguish between real options on versus real options in an infrastructure system. Whereas real options on a system focus on managerial flexibility such as abandon- ment and growth, real options in a system require technical and engineering knowledge (de Neufville and Wang, 2006; de Neufville and Cardin, 2009). As such, real options on a system are basically financial options taken on technical items where the technology itself is treated as a black box. Real options in a system are created by changing the physical design of the technical system. Chambers defines four primary maneuvers that can be done with real options on a system (Chambers, 2007): • Buy the system, • Sell the system, • Expand the size of the system, or • Contract the size of the system. These can be seen as broadly equivalent to the defer, scale, and abandon options set out by Trigeorgis (1996). Each maneuver keeps the ability open to delay important invest- ment decision on the system until the required information is change. Each stage is an option on the value of subsequent stages. • Option to alter scale: The ability to accelerate or expand if conditions are favorable, or contract if conditions are less favorable. At the extreme is the ability to halt production and restart later. • Option to abandon: If market conditions decline severely, options can be abandoned and equipment and land sold off. • Option to switch: Develop a facility in such a way that it can change the output mix produced (alternatively, change the input mix). • Growth options: An early investment (e.g., in land, in R&D) that opens up future growth opportunities. • Multiple interacting options: Projects often involve a col- lection of put and call options in combination. Their com- bined value may differ from the sum of the separate values. Realization of Real Options at Airports The use of real options and associated analytical techniques is not prevalent as a concept in airport planning and design. However, some of the design choices made for airports do encapsulate the ideas behind real options. For example, de Neufville and Odoni list a number of examples (de Neufville and Odoni, 2003, p. 816): • Reserving land for future development (land banking); • Preserving right-of-ways for public transport to airports; • Facilities designed for shared use between airlines; and • Glass or other non-load-bearing walls dividing domestic and international areas allowing the option to expand either area. Common examples of real options are shared-use facili- ties and equipment designed to serve many users, which allows the option of allocating space to different functions (e.g., domestic and international traffic, as needed) (Belin and de Neufville, 2002; Landrum & Brown, 2010). This also has direct financial implications since shared-use facilities increase the utilization of facilities and equipment and reduce the overall space required. Belin and de Neufville estimate that shared facilities could reduce capital expenditures by as much as 30%. Similarly, CUTE allows the airport to reassign gates and check-in counters without having to address individual air- lines’ computer systems (Landrum & Brown, 2010). It also eliminates the need for each airline to individually own equipment and reduces the overall space requirements of the terminal. CUSS kiosks can be installed around the airport as well as off-site (e.g., transit stations, parking lots), thus reducing space requirements and allowing greater flexibility in airport design.

133 available. By contrast, in real options are more equivalent to the staged investment and option to switch defined by Trigeor- gis (1996). The broad categories of on and in real options are summarized in Figure E-2. Real options in the system tend to involve greater tech- nical complexity and can be more difficult to identify. Fur- thermore, decisions to implement a real option in a system will most likely have an impact on other design decisions and therefore create interdependencies (Chambers, 2007). To illustrate, de Neufville and Cardin describe an office building development in Chicago designed to enable phased vertical expansion (i.e., the real option to build more stories on to the building once office space demand warrants it) (de Neufville and Cardin, 2009). The building plan involved careful design of the elevator shafts, columns, and footings in order to allow future expansion. Chambers offers the example of the 25 de Abril Bridge, which spans the Tagus River outside of Lisbon, Portugal. The bridge was originally constructed as a four- lane roadway that could be retrofitted in order to support both a highway and a railroad. As a result, bridge designers made engineering decisions internal to the bridge design that allowed for future retrofits. In an airport setting, the practice of land banking can be considered a real option on a system. Land banking helps to ensure that an airport can be built or expanded in the future or the land can be sold again or used for non-aviation prod- ucts. Thus, the decision is not irreversible, and the option to defer important investment decisions until the information required becomes available helps to protect against uncer- tainty and risk (Chambers, 2007). On the other hand, real options in a system cannot be applied to a system without consideration of the system’s design. Therefore, real options in a system require an appro- priate level of engineering knowledge (Chambers, 2007). Category Possible Real Option Implementations Common-Use Facilities/Equipment CUTE CUSS Common gates, terminals, lounges Swing spaces, swing gates Incremental Development Options Modular design approach Land banking Room to expand in all directions Linear terminal design – more easily expandable and can be combined with centralized check-in, security, and retail areas Self-propelled people movers (e.g., buses) rather than fixed transit systems – easier to expand, contract, and redirect Multiple ground transportation systems and rights-of-way Tug-and-cart baggage systems Multi-Functionality Swing spaces, swing gates Gates accommodating different aircraft types Lounges accommodating different passenger types Transverse transition zones Source: InterVISTAS based on diverse authors. Table E-2. Examples of real option approaches. Source: InterVISTAS representation based on diverse authors. Figure E-2. On and in real options.

134 The NPV is calculated using the following formula: NPV= F r n n t n 10 +( )=∑ Where r is defined as the discount rate, n is the number of periods, and Fn determines the revenue in each period. Calculating the NPV of each option allows for a simple ranking of different options. (Favorable options have higher NPV compared to less favorable options.) • Cost–Benefit Analysis CBA is typically used to analyze large infrastructure proj- ects such as airport developments. CBA determines a rank- ing of different options by calculating its ratio of benefits and costs: Cost Benefit Benefits Costs = ∑ ∑ As with NPV, future benefits and costs are discounted. Unlike NPV, CBA can also consider noncash factors (e.g., impacts on local communities, environment), although this is often controversial since it requires establishing monetary values for these factors. Chambers argues that CBA allows for a fairer ranking of projects than NPV, espe- cially projects of different sizes (Chambers, 2007). • Value at Risk VAR is a widely used risk measure in the financial industry that measures the potential loss in value on a risk asset over a defined period for a given confidence interval. Thus, if the VAR on an asset is $100 million at one week with a 95% confidence level, there is only a 5% chance that the value of the asset will drop more than $100 million over any given week. The same approach can also be applied to gains (value at gain). In the airport context, VAR could be used to apply a confidence level to an expected gain or loss associated with a project or an element of the project. A well designed, flex- ible option would decrease the project’s maximum loss (or increase its maximum gain) (Chambers, 2007). Application of the Analysis De Neufville, Scholtes, and Wang propose a simple spread- sheet analysis to estimate the value of real options in engi- neering systems (de Neufville, Scholtes, and Wang, 2006). The spreadsheet approach is based on the tools discussed previously. Their proposed spreadsheet approach for analyz- ing real options consists of three steps: 1. The spreadsheet is set up to represent the most likely pro- jections of future costs and revenues of the specific project. Swing spaces could be considered as real options in a system since they offer multi-functionality. Swing spaces can be con- nected in different ways (e.g., escalators or passages) and thus allow easy adjustment to traffic shifts. However, they can have knock-on implications for other aspects of the airport design. Valuing Real Options The greater flexibility that real options offer can have sig- nificant value for a decision maker. However, real options often (but not always) impose a cost. The trade-off between the real option’s value and cost will determine whether to go ahead with the option. Consider the example of a build- ing designed for staged vertical development. Designing the building in this way will likely impose greater engineering and construction costs than if the building was built in an non-expandable form. If the second stage of the building is never initiated, the remaining building will be more expen- sive than a standard building built to the same height. Simi- larly, if the second stage is built, then the final building will be more expensive than if it had been built to that height originally. However, before construction, the developer does not know with certainty what the future level of demand for office space will be. The benefits of the real option of staged devel- opment are the ability to avoid having an under-occupied building if demand is low (which may not cover the financing and operating costs) plus the ability to achieve greater returns if demand is high. The monetary value of that real option will depend on how well it performs over a range of outcomes in the local office market and the likelihood of those outcomes. As a result, various sophisticated analytical approaches have been developed to evaluate and value real options (for example, see Trigeorgis, 1996). There is now also a small body of literature on the application of these and other techniques to real options (and flexibility in general) in the airport plan- ning context. These analytical approaches are: • Net Present Value (Also Known as Discounted Cash Flow) NPV calculation is one of the most common methods to evaluate the financial value of diverse investments (Chambers, 2007). NPV is a means of producing a single monetary value for an option based on the future cash flow stream (both incoming and outgoing, hence net). Future cash flows are converted to a present value using a discount rate, which reflects the time value of money— money today has a greater value than money in the future. This is not due to inflation (NPV generally uses real val- ues) but rather the opportunity cost associated with the project (money invested in the project could have made returns elsewhere) and its risk profile (money in the future is less certain).

135 Thereby, the design that maximizes the NPV serves as a base case against which other flexible solutions are compared. 2. Possible scenarios are simulated to examine the implica- tions of uncertainty and risks and thereby determining an ENPV and the VAR. In other words, the probabilities of worst-case scenarios occurring. 3. The effects of various ways to provide flexibility (by changing the costs and revenues) are analyzed to reflect the design alternatives. The difference between the result- ing best ENPV and the NPV of the base case is the value of flexibility. Computer-based spreadsheets (such as Micro- soft Excel) can provide the needed tools for this procedure (de Neufville, Scholtes, and Wang, 2006). De Neufville and Cardin identify a need for analytical tools specifically to evaluate real options in a system. In their paper, the authors discuss some of the research issues involved in developing this field and suggest some tools (de Neufville and Cardin, 2009). These include: • Direct Interaction This approach involves direct interactions (e.g., discus- sions, brainstorming) with designers and planners to iden- tify and examine real options in a technical system. This technique provides a high-level approach to consider real options. However, the direct interaction approach is not very well structured (de Neufville and Cardin, 2009). • Design Structure Matrix (DSM) Design structure matrices (or variations of) are used to identify real options in a system and are considered an indirect approach to identifying real options. A DSM is a complex matrix where the rows and columns contain design components of the system, and entries describe the relationship between the components and thereby analyze all real options in the system. DSM methods are difficult to use since a lot of effort and resources are required to develop and examine them (Neufville and Cardin, 2009). • Screening and Simulation Models These methods help identify the real options that are most likely to add the most value and flexibility to a project. Possible methods include screening models and simula- tion models (de Neufville and Wang, 2006; de Neufville et al., 2008) to identify desirable real options for engineering systems. Screening models are computerized models that depict a conceptually simplified presentation of the system (only reflecting its most critical issues) and provide an ana- lytical base for determining which options are potentially most valuable. The simulation model is a more detailed means to validate critical considerations (e.g., robustness and reliability of the design options).