National Academies Press: OpenBook

Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging (2011)

Chapter: Chapter 5 - The Self-Tagging Decision-Making Tool User Guide

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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Suggested Citation:"Chapter 5 - The Self-Tagging Decision-Making Tool User Guide." National Academies of Sciences, Engineering, and Medicine. 2011. Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging. Washington, DC: The National Academies Press. doi: 10.17226/14470.
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Overview This report includes two spreadsheet tools to support the decision-making process: an Assess- ment Tool and a Simulation Tool. These tools address the subjective, qualitative aspects and the objective, quantitative aspects of the implementation of self-tagging. The Assessment Tool guides the user through the different subject areas and specific items that will need to be addressed in an implementation. This tool organizes the prerequisites taken into account by the reference airports and enables the user to determine which are relevant to their airport. The tool will rank and pri- oritize the different elements, which can help determine the complexity of the implementation and scope of the project for the airport. The Simulation Tool enables the users to input their own specific data to determine the impact of self-tagging on space, flow, and resource requirements. These impacts can be quantified and evaluated as part of a cost/benefit analysis. The purpose of the Assessment Tool is to provide the user with the qualitative information required to understand the scope of the potential self-tagging initiative. It allows the user to input data that describes the airport’s unique characteristics, business drivers, and operating environ- ment and provides an Assessment Report that details the appropriate strategies, prerequisites to implementation, and pros and cons of self-tagging. This report is built by the ranking and pri- oritization of the multiple prerequisites identified in the airport site visits and industry surveys. The full list of Assessment Report content is included as Appendix C. The user can use the Assess- ment Tool to run reports on different implementation strategies, for example a pilot trial, single market, or full airport installation. This qualitative assessment report can be used to help scope the implementation requirements. Figure 7 shows the opening screen of the Assessment Tool. The purpose of the Simulation Tool is to provide the user with the quantitative information required to forecast the impact of the self-tagging initiative on passenger processing. It allows the user to input data that describes the specific passenger processing environment to be simu- lated, including processor throughput times, resource availability, flight information, passenger demographics, and physical space allocation. This data is used to create a throughput and queue model, which shows the demand versus the capacity for processor resources over time, and a space model, which shows the variances between the current space allocation and the space requirements for the simulated environment. The model can be used to calculate the resources and space required for self-tagging and traditional check-in, as well as kiosk, rework, and bag drop-off. The user can input multiple scenarios to illustrate the impact and support a cost/ benefit analysis. The Simulation Tool is not intended to provide design-level output and does not address optimum layout for improving passenger flow and congestion. Variables such as pas- senger dwell time, entrance points, physical obstructions, counter configurations, queue dimen- sions, and baggage system induction points will all affect the layout design and are beyond the scope of this product. In addition, this tool does not address the impact of passenger self-tagging 23 C H A P T E R 5 The Self-Tagging Decision-Making Tool User Guide

on downstream processes. In particular, concessions and the security checkpoint are likely to be affected by any significant changes in passenger throughput. It is important for the TSA and con- cessionaires to be included in the planning stages in order to be prepared for the changes they are likely to experience. Figure 8 shows the opening screen of the Simulation Tool. As outlined in Figures 7 and 8, the following two sections represent User Guides for both com- ponents of the Decision-Making Tool. Assessment Tool—User Guide User Identification The User Identification worksheet, as shown in Figure 9, is for documentation purposes. This sheet allows the user to input the name of airport that is being assessed, the date of assessment, the person leading the effort, and the contributors, including respective company and department affil- 24 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 7. Self-Tagging Assessment Tool outline. Figure 8. Self-Tagging Simulation Tool guide contents.

iations for each individual. This information is used to create the title page to the Assessment Report, which is discussed later in this Guide. The user shall type in data as appropriate. Airport Profile The Airport Profile worksheet, as shown in Figure 10, is designed to capture the unique mix of characteristics that make up the subject airport, namely, the airport being assessed. This sheet allows the user to select criteria from a range of categories that best describe the airport. This information is used to identify the appropriate self-tagging pros and cons for that airport. The user shall select “yes” in the drop down box for each characteristic that accurately describes the subject airport. Business Driver Assessment The Business Driver Assessment worksheet, as shown in Figure 11, is designed to identify the appropriate self-tagging strategy for the subject airport based on its primary business drivers. This sheet allows the user to rank a set of predefined business drivers as high, medium, or low priority. This information is used to provide the user with a description of the self-tagging strate- gies that will provide the biggest benefit and have the highest level of success. The user shall select the appropriate priority level from the drop down box next to each business driver. The Self-Tagging Decision-Making Tool User Guide 25 Figure 9. User Identification worksheet.

Commercial Impact Assessment The Commercial Impact Assessment worksheet, as shown in Figure 12, is designed to identify the commercial prerequisites to implementation that must be addressed to achieve a successful self-tagging program. This sheet allows the user to select the appropriate answer to a set of key questions. This information is used not only to determine the prerequisites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. 26 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 10. Airport Profile worksheet. Figure 11. Business Driver Assessment worksheet.

Facility Impact Assessment The Facility Impact Assessment worksheet, as shown in Figure 13, is designed to identify the facility prerequisites to implementation that must be addressed to achieve a successful self-tagging program. This sheet allows the user to select the appropriate answer to a set of key questions. This information is used to determine not only the prerequisites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. Legal/Financial/Risk Impact Assessment The Legal/Financial/Risk Impact Assessment worksheet, as shown in Figure 14, is designed to identify the legal, financial, and risk prerequisites to implementation that must be addressed to achieve a successful self-tagging program. This sheet allows the user to select the appropriate answer to a set of key questions. This information is used to determine not only the prerequi- The Self-Tagging Decision-Making Tool User Guide 27 Figure 12. Commercial Impact Assessment worksheet. Figure 13. Facility Impact Assessment worksheet.

sites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. Operational Impact Assessment The Operational Impact Assessment worksheet, as shown in Figure 15, is designed to identify the operational prerequisites to implementation that must be addressed to achieve a successful 28 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 14. Legal/Financial/Risk Impact Assessment worksheet. Note: BHS = baggage handling system; BRS = baggage reconciliation system. Figure 15. Operational Impact Assessment worksheet.

self-tagging program. This sheet allows the user to select the appropriate answer to a set of key questions. This information is used to determine not only the prerequisites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. Regulatory/Security Impact Assessment The Regulatory/Security Impact Assessment worksheet, as shown in Figure 16, is designed to identify the regulatory and security prerequisites to implementation that must be addressed to achieve a successful self-tagging program. This sheet allows the user to select the appropriate answer to a set of key questions. This information is used to determine not only the prerequi- sites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. Technical Impact Assessment The Technical Impact Assessment worksheet, as shown in Figure 17, is designed to identify the technical prerequisites to implementation that must be addressed to achieve a successful self- tagging program. This sheet allows the user to select the appropriate answer to a set of key ques- tions. This information is used to determine not only the prerequisites that must be met, but also to return a breakdown of the basis for the issue, the impact it will have, the resulting action that is required, and the cost elements associated with it. The user shall select either “yes” or “no” from the drop down box next to each question. Assessment Report The Assessment Report is the comprehensive result of each of the individual assessments. It will define the self-tagging pros and cons for the specific subject airport, the appropriate self-tagging strategies, and the prerequisites for implementation that must be met to achieve success. The Assessment Report is preformatted for printing and is automatically generated using macros. As such, when the Assessment Tool is opened, the user must select the option to enable macros. After completing each of the assessments, the user must press the “Create Assessment Report” button on the “Self-Tagging Assessment Tool Outline” tab to generate the report. Figure 18 shows a sample cover page of this report. The Self-Tagging Decision-Making Tool User Guide 29 Figure 16. Regulatory/Security Impact Assessment worksheet.

30 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 17. Technical Impact Assessment worksheet. Figure 18. Self-Tagging Assessment Report cover page.

Simulation Tool—User Guide Prerequisites A set of prerequisite tasks are required in order to obtain the necessary information that will enable the user to develop useful simulation models. When possible, accurate data reflecting the specific subject airport, airlines, and passengers should be used to provide the most accurate results. Sample values, identified through case studies and from the ACRP Report 25: Airport Pas- senger Terminal Planning and Design, are included as Appendix B for cases in which accurate data cannot be obtained (Transportation Research Board, 2010). The following steps should be per- formed by the user to identify the necessary information: Step 1. Perform an audit of passenger processing throughput at each step of the check-in process by physical observation (Check-in Counter, Check-in Kiosk, Agent-Assisted Bag Drop and Rework). a. Document the time to process each party in seconds. b. Note the party size (1, 2, 3, 4+). c. Note any exceptions or reasons for significant delays. d. Calculate average processing times in seconds for each party size at each step. Step 2. Obtain resource information for the subject area. a. Agent work schedule for all of the Check-In Counter and Bag Drops for a day with peak activity. b. Number of Self-Service Check-In Kiosks. Step 3. Obtain flight information for all airlines serviced by the subject area on the same day for which resource information was identified. a. Identify airline, flight number, destination, and aircraft model for reference pur- poses only. b. Identify departure time in 24-hour format (hh:mm). c. Identify the amount of time prior to departure that check-in closes. d. Identify the amount of time prior to departure that check-in opens on-sight. e. Identify the number of seats available for sale. Step 4. Obtain passenger profile information for each of the flights input in the flight profile. a. Identify the percentage of seats occupied on each flight. b. Identify the percentage of passengers on each flight that are not originating at the subject airport. c. Identify the percentage of local boarding passengers on each flight that are part of a party of 1, 2, 3, and 4 or more. The total must equal 100%. d. Identify the percentage of local boarding passengers that arrive during each of the following check-in time segments. The total must equal 100%. i. The earliest 1⁄3 of the available duration. ii. The midrange 1⁄3 of the available duration. iii. The latest 1⁄3 of the available duration. e. Identify the percentage of local boarding passengers that utilize each of the avail- able check-in resources. The total must equal 100%. i. Traditional Check-In Counter. ii. Web or Mobile Check-In with No Bags (passengers who go directly to the security check-point). iii. Web or Mobile Check-In with Bags. iv. Self-Service Check-In Kiosk with No Bags (not self-tagging). v. Self-Service Check-In Kiosk with Bags (not self-tagging). f. Identify the number of local boarding passengers that require rework. The Self-Tagging Decision-Making Tool User Guide 31

Step 5. Obtain resource quantities and the breakdown of space in square feet allocated to each. a. The number of Check-In Counter Positions and the area required for the agent workspace, the counter, and the passenger workspace. b. The area allocated for Check-In Counter Queuing only. c. The number of Check-In Kiosks and the area required for the passenger workspace. d. The area allocated for Check-In Kiosk Queuing only. e. The number of Agent-Assisted Bag Drop Positions and the area required for the agent workspace, the counter, and the passenger workspace. f. The area allocated for Agent-Assisted Bag Drop Queuing only. g. The total area for Non-Processing purposes, including walking traffic lanes, secu- rity, airport administration, and concessions. Once the prerequisite information has been gathered, the user is prepared to enter the initial data into the five Input Components (Processor, Resource, Flight, Passenger, and Space). After the data entry has been completed by the user, the Simulation Tool will build two models (Queue and Space) of the current environment. As optional tools, the user can also run varying simula- tions by changing input values. Processor Throughput Input (Figure 19) 1. Enter the average calculations for each party size in the appropriate cell for each check-in step. 2. For Self-Tag Kiosk, Self-Tag Application, and Self Bag Drop, use the industry average num- bers from Appendix B. Resource Profile Input (Figure 20) 1. Enter the total number of agents staffing the Check-In Counters and Bag Drop Counters dur- ing each hour throughout the day. 2. Enter the total number of Self-Service Check-In Kiosks (not self-tagging). Flight Profile Input (Figure 21) 1. Enter the flight data for each flight. Passenger Profile Input (Figure 22) 1. Enter the passenger profile data for each flight. 32 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 19. Processor Throughput Input.

The Self-Tagging Decision-Making Tool User Guide 33 Figure 20. Resource Profile Input. Figure 21. Flight Profile Input.

Space Profile Input (Figure 23) 1. Enter the current quantity and space breakdown information for each resource. At this point the data entry by the user is finished. As mentioned earlier, the following two models are automatically generated by the Simulation Tool based on the input by the user. 34 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 22. Passenger Profile Input. Figure 23. Space Profile Input.

Figure 24. Demand vs. Capacity Over Time summary table. Queue Model The Queue Model illustrates the demand versus the capacity for passenger processing at each of the check-in mediums, in terms of minutes and based on the values entered in the profile input sheets. The cumulative queue times are based on the difference between the resource capacity and processing demand as they accumulate and are resolved over time. A summary table, as shown in Figure 24, is used to identify the average queue buildup, average resources per hour during the queue, average wait time per passenger during the queue, average number of passengers in queue, maximum queue buildup, available resources during maximum queue, maximum wait time per passenger, and maximum number of passengers in queue. Charts, as shown in Figures 25 through 30, are included to provide a graphical depiction of the data. The queue model is preformatted for printing. Space Model The Space Model, as shown in Figure 31, illustrates the current space allocation versus the sim- ulated space requirements for each of the passenger processing resources in terms of square feet, based on the values entered in the profile input sheets. A summary table is used to identify the current square footage and the simulated square footage for each resource. As various simula- tions are tested to achieve the queue results desired, the space model will update to illustrate the space required to provide the necessary resources. Charts are included to provide a graphical depiction of the data. The space model is preformatted for printing. Simulations After the current models have been developed, the user is prepared to run simulations to see the impact that adding self-tagging resources will have on the airport. Perform the following The Self-Tagging Decision-Making Tool User Guide 35

36 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 25. Total Demand vs. Capacity Over Time. Figure 26. Check-In Counter/Bag Drop Demand vs. Capacity Over Time.

The Self-Tagging Decision-Making Tool User Guide 37 Figure 27. Agent-Assisted Bag Drop Demand vs. Capacity Over Time. Figure 28. Check-In Kiosk Demand vs. Capacity Over Time.

38 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging Figure 29. Self-Tag Kiosk Demand vs. Capacity Over Time. Figure 30. Self-Tag Bag Drop Demand vs. Capacity Over Time.

steps individually to see the impact they have on the current model. Once an understanding has been established as to the impact of individual changes, develop different simulations by com- bining various changes as desired. Step 1. Modify throughput times as desired to see the effect they have on queue times and space requirements. Step 2. Enter values for agent staffing of the Self-Tag Bag Drop and the Self-Tag Kiosks based on estimates of need. Step 3. Modify all resources as desired to see the effect they have on queue times and space requirements. Step 4. Add additional flights with generic data to see the effect that growth will have on queue times and space requirements. Step 5. Modify the Check-In Medium data to include self-tagging. a. Add a small percentage of Self-Tag Kiosk users. b. Reduce the “Traditional Check-In Counter” and “Self-Service Check-In Kiosk with Bags” accordingly to maintain a total of 100% across all resources. c. Observe the effect that migration to self-tagging will have on queue times and space requirements. Step 6. Modify other passenger profile information to simulate different trends. a. Modify load factors to simulate general increases or decreases in air travel. b. Modify percentage breakdowns of party sizes to simulate seasons of either greater business travel or leisure travel. c. Modify percentage breakdowns of arrival times to simulate passengers trending toward arriving later as they recognize processing times dropping. d. Modify rework percentages to simulate an increase in rework requirements upon initial implementation of self-tagging and a decrease in rework requirements as passengers learn the process. The Self-Tagging Decision-Making Tool User Guide 39 Figure 31. Space Model: Current Space Allocation vs. Simulated Space Requirements.

Step 7. Enter the required space in square feet for each of the resources. a. Check-In Counter Positions—square footage per check-in position including standing room for passengers. b. Check-In Counter Queuing—square footage per person in check-in counter queue line. c. Check-In Kiosks—space per kiosk including room for passengers. d. Check-In Kiosk Queuing—square footage per person in kiosk queue line. e. Agent-Assisted Bag Drop Positions—square footage per agent assisted bag drop position including standing room for passengers. f. Agent-Assisted Bag Drop Queuing—square footage per person in agent assisted bag drop queue line. g. Self-Tag Kiosks—space per kiosk including room for passengers. h. Self-Tag Kiosk Queuing—square footage per person in kiosk queue line. i. Self-Tag Bag Drop Positions—square footage per bag drop position, including standing room for passengers. j. Self-Tag Bag Drop Queuing—square footage per person in bag drop queue line. k. Non-Processing Area—square footage for non-processing functions. 40 Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging

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TRB’s Airport Cooperative Research Program (ACRP) Report 41: Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging provides the information and tools, included on and accompanying CD-ROM, necessary for an airport or airline to determine the appropriateness of pursuing passenger self-tagging should it be allowed in the United States in the future.

The tools, in an Excel Spreadsheet format, allow for the input of airport-specific information, such as facility size and passenger flows, while also providing industry averages to assist those airports and airlines that haven’t yet collected their individual information. The decision-making tools provide both qualitative and quantitative information that can then be used to assess if passenger self-tagging meets organizational needs or fits into their strategic plan.

Appendix A to ACRP 41 was published online as ACRP Web-Only Document 10: Appendix A: Research Documentation for ACRP Report 41.

The CD-ROM included as part of ACRP Report 41 is also available for download from TRB’s website as an ISO image. Links to the ISO image and instructions for burning a CD-ROM from an ISO image are provided below.

Help on Burning an .ISO CD-ROM Image is available online.

Download the .ISO CD-ROM Image.

(Warning: This is a large file that may take some time to download using a high-speed connection.)

A errata for the printed version of this document is available online. The errata material has been incorporated into the electronic version of the document.

View information about the February 9, 2010 TRB Webinar, which featured this report.

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