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Appendix A Methodology
This appendix describes in more detail the methodology used to develop the scenarios presented in this report. We define scenario as a plausible combination of possible future developments. Scenarios support what-if thinking and lay the foundation for alternative strategies to reduce uncertainties in mid- and long-term planning (Gausemeier, Fink, and Schlake, 1998; Lempert, Popper, and Bankes, 2003; Mietzner I and Reger, 2005). Scenario planning is distinguished from forecasting in that scenario planning produces multiple potential futures, as illustrated in Figure A.1.
Scenarios can be developed using several approaches (Mietzner and Reger, 2005). Early scenario-planning techniques focused on the solely qualitative and narrative description of different futures and mostly used intuitive approaches to arrive at these pictures and strategic statements (Kahn and Pepper, 1979). Over the years, different process steps were strengthened and formalized to address the complexity of strategic issues. Consistency analyses began to be used to measure scenario quality and relevance. Results were documented in narratives with statements relating to key indicators. Today, scenarios are developed with more-quantitative approaches that rely on multiple model runs and computer tools, which enhance the ability to cope with system complexity and make the resulting scenarios less arbitrary (see, for example, Gordon and Hayward, 1968; Kane, 1972; Gausemeier, Fink, and Schlake, 1998; Lempert, Popper, and Bankes, 2003; Bryant and Lempert, 2010; Rozenberg et al., 2012; Schweizer and Kriegler, 2012; Gerst, Wang, and Borsuk, 2013). Our methodological approach (outlined in Chapter One and presented in more detail here) is representative of a more quantitative approach to scenario development.
In the rest of this appendix, we describe each of the six steps of the scenario approach in detail.
Step 1: Select Influencing Areas
In the first step, the team identified influencing areas and descriptors relevant to building the scenarios. Influencing areas are topics germane to the scenario context. The team drew on past work on German and U.S. transportation futures, as well as additional background research on China, to identify four influencing areas: demographics, economics, energy, and transportation supply and constraints. Next, we identified descriptors within each influencing area; these were also based on prior research of the study team. We define descriptors as indicators within an influencing area; they can be quantitative or qualitative.
For each influencing area, RAND experts produced a paper documenting past trends for each descriptor over a period of 20 years, or, if data were unavailable, discussing the descriptors anecdotally. (Chapter Two presents a summary of past trends.)
Step 2: Elicit Projections on Descriptors
We held four workshops, one for each influencing area. We held workshops on demographics and on economics in the RAND Washington office in December 2013. We held workshops on energy and on transportation supply and constraints at the Wenjin Hotel near the campus of Tsinghua University in Beijing in May 2014. Six to eight outside experts participated in each workshop, for a total of 28 people (see Appendix B for a list of the U.S. experts and the affiliations of the Chinese experts). In a facilitated discussion (held in English at the U.S. workshops and in Chinese at the Beijing workshops), we asked the experts to develop a projection for each descriptor in 2030. The projection could be qualitative or quantitative. Each expert estimated his or her upper- and lower-bound projection, followed by his or her best estimate. We asked each expert to provide reasons that a certain projection might be plausible and under what conditions. We also asked each to discuss any qualitative effect on travel behavior and mode choice.
Table A.1 shows all 24 descriptors and 47 projections developed during the four workshops. For some descriptors, the experts agreed on a single projection. For example, the demographic experts agreed that urbanization would reach 70 percent in 2030. For other descriptors, participants produced multiple projections. In some cases, this was because opinions varied; in others, it was because the experts agreed that the future value of the descriptor would vary depending on other factors. For example, labor-force participation might rise if retirement ages increase or if wages decline, or remain the same as today if relaxation of the one-child policy leads to more parents staying home with children. The experts determined how many projections to produce for each descriptor.
Table A.1. Influencing Areas, Descriptors, and Projections
DESCRIPTOR : PROJECTION
Influencing area: Economy
DESCRIPTOR ; PROJECTION
Influencing area: Transportation supply and constraints
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