San Francisco International Airport and Quantum Secure's SAFE for Aviation System: Making the Business Case for Corporate Security

2013 ◽  
Author(s):  
Daniel Diermeier ◽  
Evan Meagher
Keyword(s):  
San Francisco ◽  
Business Case ◽  
Corporate Security ◽  
International Airport

San Francisco International Airport and Quantum Secure’s SAFE for Aviation System: Making the Business Case for Corporate Security

2017 ◽  
pp. 1-12
Author(s):  
Daniel Diermeier ◽  
Evan Meagher
Keyword(s):  
San Francisco ◽  
Net Present Value ◽  
Capital Expenditure ◽  
Green Light ◽  
Business Case ◽  
Internal Rate Of Return ◽  
Present Value ◽  
Corporate Security ◽  
International Airport ◽  
Spreadsheet Models

In 2008 San Francisco International Airport (known by its three-letter airport code, SFO) had announced a $383 million plan to renovate and reopen Terminal 2. Assistant deputy director of aviation security Kim Dickie and her team had selected Quantum Secure's SAFE software suite as the new Terminal 2 credentialing system, but she needed to develop a business case quickly that would convince senior management to give the green light to fund the purchase. The case describes a scenario that occurs frequently in the real world, in which a decision offers some real but qualitative value in ways that are difficult or impossible to quantify. The discussion and analysis gives students the opportunity to consider the factors that will drive the internal rate of return (IRR), net present value (NPV), and discounted payback period calculations without constructing comprehensive spreadsheet models. Analyzing the case suggests the limits of such approaches in cases where perceived value is difficult to quantify. The case prepares students to evaluate and justify purchasing requests when interacting with financial gatekeepers such as CFOs and CEOs by introducing a framework to analyze the quantifiable benefits of a capital expenditure while keeping in mind important intangible benefits.After analyzing the case, students should be able to: Understand how return on investment (ROI) calculations work, with an emphasis on identifying incremental effects Decide how to use results from similar entities making similar purchases to estimate the incremental benefit of a proposed solution Identify and use the best data available in making assumptions Justify the validity of benefits that are difficult to quantify in conjunction with the presentation of a traditional ROI analysis

Determinants of Customer Satisfaction at the San Francisco International Airport

2019 ◽  
Vol 08 (01) ◽  
Author(s):  
Ashok K. Singh ◽  
Myongjee Yoo ◽  
Rohan J. Dalpatadu
Keyword(s):  
Customer Satisfaction ◽  
San Francisco ◽  
International Airport

scholarly journals Characterization of ambient aerosols at the San Francisco International Airport using bioaerosol mass spectrometry

2006 ◽  
Author(s):  
Paul T. Steele ◽  
Erica L. McJimpsey ◽  
Keith R. Coffee ◽  
David P. Fergenson ◽  
Vincent J. Riot ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
San Francisco ◽  
Ambient Aerosols ◽  
International Airport ◽  
Bioaerosol Mass Spectrometry

Impacts on Vehicle Occupancy and Airport Curb Congestion of Transportation Network Companies at Airports

2018 ◽  
Vol 2672 (23) ◽  
pp. 52-58 ◽  
Author(s):  
Karina Hermawan ◽  
Amelia C. Regan
Keyword(s):  
Los Angeles ◽  
San Francisco ◽  
Public Transit ◽  
Transportation Network ◽  
Light Rail ◽  
International Airport ◽  
Using Data ◽  
Standard Service ◽  
Transportation Network Companies

How does the growth of transportation network companies (TNCs) at airports affect the use of shared modes and congestion? Using data from the 2015 passenger survey from Los Angeles International Airport (LAX), San Francisco International Airport (SFO), and Oakland International Airport (OAK), this research analyzes TNCs’ relationship with shared modes (modes that typically have higher vehicle-occupancy and include public transit such as buses and light rail, shared vans or shuttles) and the demand for their shared vs. standard service at the airport. Because TNCs both replace shared rides and make them possible, the research also measured the net effects at these airports. The results suggest that in 2015, TNCs caused 215,000 and 25,000 passengers to switch from shared to private modes at SFO and OAK, respectively. By 2020, the increase is expected to be about 840,000 and 107,000 passengers per year, respectively.

scholarly journals Forecast-Based Decision Support for San Francisco International Airport: A NextGen Prototype System That Improves Operations during Summer Stratus Season

2012 ◽  
Vol 93 (10) ◽  
pp. 1503-1518 ◽  
Author(s):  
David W. Reynolds ◽  
David A. Clark ◽  
F. Wesley Wilson ◽  
Lara Cook
Keyword(s):  
Decision Support ◽  
Traffic Flow ◽  
San Francisco ◽  
Research Effort ◽  
Federal Aviation Administration ◽  
Prototype System ◽  
International Airport ◽  
Marine Stratus ◽  
Probabilistic Forecasts ◽  
Ground Delay

During summer, marine stratus encroaches into the approach to San Francisco International Airport (SFO) bringing low ceilings. Low ceilings restrict landings and result in a high number of arrival delays, thus impacting the National Air Space (NAS). These delays are managed by implementation of ground delay programs (GDPs), which hold traffic on the ground at origination airports in anticipation of insufficient arrival capacity at SFO. In an effort to reduce delays and improve both airport and NAS efficiency, the Federal Aviation Administration (FAA) funded a research effort begun in 1995 to develop an objective decision support system to aid forecasters in the prediction of stratus clearing times. By improving forecasts at this major airport, the scope and duration of ground and airborne holds can be reduced. The Marine Stratus Forecast System (MSFS) issues forecasts both deterministically and probabilistically. Following transition to NWS operations in 2004, the system continued to provide reliable forecasts but showed no significant improvement in delay reduction. Changes to the FAA GDP issuance procedures in 2008 allowed them to utilize the improved forecasts, leading to quantifiable reductions in ground and airborne holds for SFO equating to dollars saved. To further reduce delays, a refined statistically based model, the Ground Delay Parameters Selection Model (GPSM) for selecting an optimal ground delay strategy has been developed, utilizing the available archive of objective MSFS probabilistic forecasts and accompanying traffic flow data. This effort represents one of the first systematic attempts to integrate objective probabilistic weather information into the air traffic flow decision process, which is a cornerstone element of the FAA's visionary NextGen program.

Ground motion at the San Francisco international airport from the Loma Prieta earthquake sequence, 1989

1991 ◽  
Vol 81 (5) ◽  
pp. 1923-1944
Author(s):  
A. McGarr ◽  
M. Çelebi ◽  
E. Sembera ◽  
T. Noce ◽  
C. Mueller
Keyword(s):  
Ground Motion ◽  
San Francisco ◽  
Epicentral Distance ◽  
Sedimentary Cover ◽  
Low Velocity ◽  
Near Surface ◽  
Loma Prieta Earthquake ◽  
International Airport ◽  
Bay Area ◽  
Loma Prieta

Abstract Following the Loma Prieta earthquake, the U.S. Geological Survey installed four portable digital seismic recorders at the San Francisco International Airport (SFO) for one week to study aftershock ground motion at this important Bay area “lifeline.” This study was motivated largely by the need to anticipate strong ground motion from future major earthquakes affecting the Bay area and, to a lesser extent, by the fact that SFO was shut down for 13 hours owing to damage from the Loma Prieta shock. Accordingly, the recording sites were chosen so as to elucidate the effects of varying thicknesses of low-velocity surficial alluvium on the ground motion. Three large aftershocks with magnitudes ranging from 4.2 to 4.5 each produced ground motion that was recorded at all four SFO stations. One of our stations was collocated with a permanent ground motion recorder that indicated a peak horizontal velocity of 29 cm / sec and a peak horizontal acceleration of 0.33 g during the 18 October mainshock. From the aftershock data and one mainshock record, it is possible to extrapolate approximately the mainshock ground motion to other locations at SFO and, more generally, to assess the effects of low-velocity sedimentary cover, including artificial fill material, on the character of the ground motion. The main-shock ground motion recorded at the permanent station was apparently typical for most of SFO where the near-surface alluvium resulted in peak horizontal ground velocity, in the frequency band 0.1 to 3 Hz, amplified by a factor of about 2.5 relative to that recorded at bedrock sites. Observations, in the epicentral distance range 59 to 95 km, including SFO, of the moho-reflected phases PmP and SmS from the aftershocks support the hypothesis, presented elsewhere, that the phase SmS accounted for much of the peak ground motion throughout most of the San Francisco Bay area.

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