Beyond Information. Intelligence.
Established 1960
Database Marketing
Economic & Social Impact Studies
Evaluations
Research
Modeling/Forecasting BASIC DATA SERIES
DOMESTIC IN-FLIGHT SURVEY, 2016 SMS
1042 Fort Street Mall Suite 200 Honolulu, HI 96813 Ph: (808) 537-3356 Documentation Report Toll Free (877) 535-5767 E-mail: [email protected] Website: www.smshawaii.com
Prepared for:
The Hawai‘i Tourism Authority July 2017 CONTENTS
INTRODUCTION ...... 1 PURPOSE AND OBJECTIVES OF THE RESEARCH ...... 1 POLICIES PERTAINING TO PROJECT RESPONSIBILITIES ...... 1 DATA ACQUISITION PROCEDURES ...... 3 SURVEY INSTRUMENT ...... 3 DISTRIBUTION OF FORMS ...... 3 DATA COLLECTION ...... 7 LOGGING AND PREPARATION ...... 8 PRE-SCANNING RULES ...... 8 SCANNING IN-FLIGHT FORMS ...... 9 EVALUATION ...... 9 VERIFICATION ...... 10 SCANNING AND VERIFICATION RULES ...... 10 COMMITMENT ...... 11 NAMING CONVENTIONS OF BDS SAV FILES ...... 11 HTA VSAT LABELS ...... 11 DATA PROCESSING ...... 11 FILE MERGER...... 12 DATA CLEANING ...... 12 ZIP CODE CLEANING ...... 17 LENGTH OF STAY (LOS) CLEANING ...... 17 ASCRIPTION ...... 18 CONSISTENCY CHECKS ...... 18 NEW VARIABLES AND VALUES ...... 18 NON-MMA COUNTRY ASSIGNMENT ...... 19 APPEND ZIP CODE DATA ...... 19 ELIMINATION OF INVALID RECORDS ...... 19 DATA WEIGHTING ...... 20 MONTHLY WEIGHTS ...... 20 TABULATION & REPORTS ...... 21 MONTHLY REPORTS ...... 21 DELIVERABLES ...... 22 END-OF-YEAR PROCEDURES ...... 22 ANNUAL WEIGHTS ...... 22 ANNUAL DATA TABULATION ...... 22 DISPOSAL OF MATERIALS ...... 23 APPENDIX ...... 24 APPENDIX A: SURVEY FORMS ...... 25 APPENDIX B: CODEBOOK ...... 28 APPENDIX C: VALUES OF GENERATED VARIABLES ...... 64
INTRODUCTION1
PURPOSE AND OBJECTIVES OF THE RESEARCH
Per Act 156, SLH 1998, the Hawai‘i Tourism Authority (HTA) is responsible for collecting visitor counts, characteristics (party size, length of stay, visitor status, purpose of trip and island visitations by major market areas), expenditure and other tourism related data for the State of Hawai‘i. The HTA’s Tourism Research program supports four core data collection surveys: Domestic In-Flight Survey, International Departure Survey, Island Departure Survey, and Cruise Visitor Survey. These projects are inter-related and the data are critical to the state’s economic analysis. The objective is to collect, process, and report statistics from a representative sample of visitors across all markets and the six major islands (O‘ahu, Hawai‘i, Maui, Molokaʻi, Lānaʻi, and Kauaʻi). The number of visitors who came by out-of-state cruise ships to Hawai‘i is added to counts from visitors who came by air to calculate total visitor data for Hawai‘i. These visitor statistics are published monthly in the HTA visitor news releases and annually in the HTA’s Visitor Research Reports. In addition to the four surveys, the HTA conducts a post-trip visitor satisfaction and activity survey to measure visitors’ satisfaction levels with Hawai‘i as a vacation destination.
POLICIES PERTAINING TO PROJECT RESPONSIBILITIES
This project involves collecting, processing, and reporting basic characteristics data from visitors arriving to Hawai‘i on domestic flights. The survey instrument is the In-Flight form. The contractor must pick up the forms from the DOA office at the Daniel K. Inouye International Airport (formerly known as the Honolulu International Airport) and accept deliveries of forms from DOA offices on the Neighbor Islands. For data processing, the contractor must be equipped with high speed image scanners capable of scanning a minimum of 250,000 forms a month (3,000,000 forms a year) in six different languages.
The contractor is required to apply statistical, sampling, and weighting techniques using SPSS to generate monthly tabulations and reports to the HTA. Those reports include the following items:
❖ a daily log of airline information (carrier name, arrival date, number of passengers, flight number, and port of entry)
❖ a port-of-entry report by island to include party size, airline, and number of completed survey forms
❖ SPSS and Excel files containing visitor counts, island visitation, length of stay, and other characteristics of domestic visitors for individual major market areas, by state and metro areas.
1 Material in this section was provided by the HTA as the official project description and has been inserted here verbatim. The remainder of the manual was provided by SMS Research & Marketing Services, Inc. (SMS).
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 1 © SMS July 2017 The contractor is required to generate image files of visitors’ names and addresses and SPSS files containing basic demographic information on the visitors selected for the satisfaction survey and provide them to the HTA on a weekly basis. These files are forwarded to the contractor conducting the Visitor Satisfaction Survey.
Data for the Basic Data Series, 2016 are collected, processed, stored, and analyzed according to the procedures described in this manual. Data are collected using a self-administered survey instrument distributed among passengers aboard flights arriving from domestic cities. The instrument is optically scanned into the basic data files. Data are weighted and balanced to reflect party size and airline passenger counts (landings).
An important feature of the BDS is the time series information it provides: comparisons to previous periods and a historical foundation for projections. Proposed changes in the procedures for this survey must be weighed against the cost of disrupting the continuity of the data series.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 2 © SMS July 2017 DATA ACQUISITION PROCEDURES
SURVEY INSTRUMENT
The survey instrument was prepared by SMS in consultation with and with the approval of the HTA. The data collection form contained 15 questions and was printed in six languages, English, Japanese, Modern Mandarin Chinese, Korean, Tagalog, and Spanish (see Appendix A). The survey instrument is printed on the reverse side of the State of Hawai‘i, Department of Agriculture, Plants and Animals Declaration Form. Airlines arriving from domestic U.S. airports are required by Hawai‘i State law to distribute and collect the agricultural form from their passengers.
Many different survey forms have been used in the last 20 years of In-Flight data collection. A new version of the form has been created and assigned a unique number each time minor changes in the content or format of the survey were requested in order to track variations from one form to the next. Each time a new form was introduced into the field, old forms could be terminated. Ideally, only one version of the form would be used in the field at a time, however, there were still copies of older forms being stored and used by individual airlines at individual airports in North America. At times during the last two decades as many as five forms were simultaneously used in the system. The In-Flight syntax was developed to recognize and process more than one survey version at a time.
In 2016, there were four forms being used, versions 6, 7, 8, and 9 (form numbers 61618, 39997, 24661, and 58844 respectively). Version 6 was put into service in 2005, Version 7 was put into service on 05-15-2012, and Version 8 has been in use since 04-23-2013. Differences introduced in new forms have typically been very small. For example, the only difference between Forms 7 and 8 was the introduction of the respondent’s e-mail address.
In 2016 the newest form was introduced. The form label was HTA Form Rev. 02-01-2016 and the TELEform ID was 58844 (Form 9). However the form was not put into active use until April 2016. The changes in Form 9 from Form 8:
❖ Question 9 on the HTA side of the form added two new response categories: o Private Room in Private Home o Shared Room/Space in Private Home
DISTRIBUTION OF FORMS
The In-Flight form has two sides: 1) the HTA visitor survey form and 2) the Department of Agriculture’s (DOA) Plants and Animals Declaration Form which all visitors are required by law to complete. Approximately 7,5000,000 forms were printed in 2016. Twice a month (On the 1st and the 15th), In-Flight forms were delivered in batches of 312,480 forms to the DOA Honolulu Plant Quarantine Office, located at the Daniel K. Inouye International Airport (formerly known as the Honolulu International Airport). Each batch was packaged in reams of 310 forms: (280 forms in English; 10 forms in Chinese; 5 forms each in Japanese, Korean, Tagalog and Spanish). There were 16 reams per carton and 63 cartons per batch.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 3 © SMS July 2017 Representatives from airlines with domestic flights to the Hawaiian Islands (i.e., Alaska, Allegiant, American, Delta, Hawaiian, United, U.S. Airways, Omni Air, and Virgin America) picked up these forms from the DOA Honolulu Office, and distributed them to their stations in Hawai‘i and on the mainland. In-Flight forms were distributed by airline crews to passengers (1 form per party) on domestic flights to Hawai‘i.
Compliance with the request to complete the HTA side of the form was voluntary. One form was to be completed by each traveling party (including visitors, intended residents, and returning resident traveling parties).
Flight crews collected the completed forms and packaged them in manila envelopes labeled “IMPORTANT”. The following information was provided on each envelope:
❖ Name of Carrier ❖ Flight Number ❖ Arrival Date ❖ Arrival Time ❖ Number of Passengers ❖ Number of Crew ❖ Port of Origin ❖ Last Port of Departure
Upon arrival, the packet of forms is given to a DOA Inspector for review. Once inspections were completed, these forms were available to SMS staff for pick up for scanning and data processing. In 2016, there were 3,611,279 forms scanned.
Figure 1 is a flow chart of activities required to conduct the Basic Data Series Domestic In-Flight Survey, 2016. The flow chart shows monthly processing activities. The remainder of this manual will describe these procedures. Figures 2 and 3 are additional flowcharts detailing a component of scanning and processing procedures in further detail.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 4 © SMS July 2017 Figure 1: In-Flight Processing Flow Chart, Overview
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 5 © SMS July 2017 Figure 2: In-Flight Processing Flow Chart, Scanning Detail
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 6 © SMS July 2017 Figure 3: In-Flight Processing Flow Chart, Processing and Weighting Detail
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 7 © SMS July 2017 DATA COLLECTION
For flights that arrive at the Daniel K. Inouye International Airport (formerly known as the Honolulu International Airport), SMS drove to the airport and picked-up forms from the Department of Agriculture office. Forms from the other islands were sent by the Department of Agriculture to SMS via FedEx.
Honolulu: SMS staff members picked up forms at the Department of Agriculture's break room at the Daniel K. Inouye International Airport (formerly known as the Honolulu International Airport) Agricultural Office baggage claim area G Monday through Friday afternoons at 12:00 pm. The afternoon pick-up time allowed airport personnel to organize forms from the prior day. The Monday pickup included forms collected from Friday afternoon through Sunday night. Some excess forms organized after 12:00 pm on Monday were picked up and processed Tuesday afternoon.
Other Islands: Forms arriving at Kahului, Kona, Hilo, and Līhu‘e airports were collected by the Department of Agriculture and sent by FedEx to SMS weekly or as soon as their boxes filled up, whichever happened first. The DOA was requested to make a final delivery by the 5th of the month following arrival. There were no In-Flight forms collected from Lāna‘i or Moloka‘i because there are no direct flights to these islands.
Logging and Preparation
Forms were taken out of the “IMPORTANT” envelopes and processed by first removing blocks of blank forms sometimes included in the envelopes. Forms marked “CREW” were removed. Forms that were crumpled, food encrusted, or otherwise damaged to the point that they could not be properly scanned and any forms completed in a shade of ink that could not be read properly by the scanner were removed from the stack and processed separately. Their contents were transferred onto blank survey forms exactly as they appeared on the original and they were scanned on the same day.
SMS logged the information on the “IMPORTANT” envelopes and generated a daily passenger counts report (known as PAX counts). The report is e-mailed to the Hawai‘i Department of Business, Economic Development and Tourism (DBEDT) and the HTA no later than 3:00 pm each day.
Pre-Scanning Rules
1. Remove forms marked as “CREW” 2. Remove packs of blank forms 3. Remove, re-enter, and replace damaged forms and forms completed in colors unreadable by the scanner 4. Arrange forms in order by flight number and assign batch numbers
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 8 © SMS July 2017 Scanning In-Flight Forms
Arriving In-Flight forms were separated according to day, airline, and flight number. The arrival date, port of entry, airline, and flight number were recorded in a logbook. These numbers were also entered to the TELEform software (to be described later in this section) as custom fields prior to scanning.
Batches were fed into one of two Panasonic KV-S2055 L High Speed Scanners capable of duplex scanning at 3,000 sheets per hour. These scanners are highly sensitive reading and recoding devices capable of reading bubbled items regardless of the nature of the mark. They also read numbers entered into boxes and text clearly written in prescribed spaces. The scanners were maintained regularly throughout the year, with monthly recalibration and adjustment.
Completed survey forms from a single flight were arranged in one to three batches for input to the scanners. Batches were organized by batch number (a unique and sequential numbering system assigned by TELEform) and then scanned in. As batches were read in, the scanner counted the number of forms scanned. That number was included in the scanned data file. In 2016, there were 3,611,279 forms scanned. It was also transferred manually to a project log for internal record-keeping and for delivery to the DBEDT as part of the project deliverables each day. The software read each form and created images of each survey in a data file. Those images were labeled and made ready for evaluation.
The scanning process was designed and managed using a software package called TELEform Enterprise Edition2, Version 10.1. Three of our staff worked regularly with this edition and were familiar with HTA programming. TELEform was used for the processing of scanned data because of its ability to convert information written on paper forms into electronic data and permit necessary quality control functions during the conversion process. TELEform was used to formulate the survey instrument, as well as read marks into the system during scanning and interpret them as data during evaluation. It also provided the instruction to operators during the verification procedure. All of these procedures are described below.
Evaluation
The evaluation process was carried out using the TELEform software. The images were read and interpreted according to a template developed in tandem with the survey instrument. Interpretation is a process by which marks on the image documents were compared with locations on the template and interpreted as data. Those data were then transferred to digital files containing the survey information for each batch scanned.
Variables were checked for accuracy. In the process of evaluation, the software determined if data were readable and transferred accurately according to the template. Specifically, marks that appear in specific locations on the scanned forms were interpreted as data for a specific variable. Those data were recorded in the output file. As part of that process, the TELEform software also estimated the certainty that the data were recorded accurately. For every data point in the file, the measure of certainly was reported as a percentage from 0 percent to 100 percent. For all projects scanned by SMS, including In-Flight, the certainty percentage at which scanners were set was 90 percent. If the measure of certainty for a specific variable was less
2 The Enterprise Edition is the professional package for full-scale operations.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 9 © SMS July 2017 than 90 percent, the data point involved was flagged for verification. Flagged data were handled in the data verification step of the scanning procedure.
Batches were checked for accuracy. At the end of each batch scan, the operator was alerted to the readability status of the batch. If the scanned images did not match the template, the operator was then informed of an error. If an error did occur the forms and software settings were checked and problems (if any) were fixed, and then the batch data file was discarded, surveys were rescanned, and the logbook entries updated. Once all forms were successfully scanned, the operator was informed that the batch was ready for verification.
Verification
During the verification process, each form that was written to the evaluation output file was checked for the presence of any flagged data point (see description of data flagging in the previous section). If no data were flagged, the file was released to the commitment file. If any flags were found, the survey image was transferred to an operator’s verification screen. Flagged items were marked in yellow on the operator’s screen, showing both the respondent’s marks and the data written to the file during evaluation. The operator determined if the data file were an accurate representation of the respondent‘s mark and either passed the data or changed the data to match the respondent’s mark. After dealing with all flagged items in a single case, the case is released to the commitment file.
The verification rates for select written responses were set at 100 percent (Question 14 Other, and Question 15 E-mail Address). Handwritten responses for Question 9 Other and Question 10 Other were not verified. Therefore, if any handwritten information appeared on these lines the TELEform brings up that image and the operator must confirm that the data are correct or retype the text. In 2016 the operators had to verify and re-enter most of the E-mail addresses.
For bubbled items, the rate was 90 percent. Verification focused on residence and length of stay (LOS). Zip codes for US, Japan and Canada were extracted from the visitor survey side of the form, and the U.S. zip code was pulled from the DOA side
The script used in TELEform for reading, evaluation, and verification is modified each time a new version of the survey instrument is introduced. The evaluation software reads the version number for the form and applies the appropriate processing code. In this manner, the input from six different forms can be treated as if it were from a single output format.
Scanning and Verification Rules
1. 90% verification of bubbled (radio button) items 2. 100% verification of zip code data 3. 100% verification of all written data including E-mail addresses
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 10 © SMS July 2017 Commitment
After verification, TELEform software committed or exported the verified data into SPSS format. The TELEform software also produced a file of images of each form scanned. Each image was systematically named by the TELEform software. The image name was also a part of the data exported for each record. This data was renamed, organized by month, and backed up. The resulting data file was transferred to the team responsible for cleaning and processing procedures.
Naming Conventions of BDS SAV Files
DOM -- (domestic) 122410 – (MMDDYY) date file was created 4 – (Series form number) DEC02 – (Processing month and year)
Example: dom122410_4_DEC10.sav
The file name indicates that this file was created from BDS domestic data on December 24, 2010 from series 4 surveys forms collected for flights arriving in the month of December of the year 2002.
HTA VSAT Labels
The BDS In-Flight Survey completed forms were also used by the HTA as a sampling frame for HTA Visitor Satisfaction Survey (VSAT) (SMS was not the research vendor for this project in 2016). The VSAT required the name, mailing address, and E-mail address of visitors. This information was used to send out VSAT questionnaires directly to the visitor. Therefore the TELEform software was also programmed to clip an image of the name and address section (lower half) of the DOA side of the form and saved as a tiff file (VSAT Labels).
The VSAT Labels file, a file of all In-Flight forms and a corresponding verified data file were saved to portable computer storage (flash) drives and picked up by an authorized representative from the VSAT vendor from SMS’ Downtown offices on Wednesday of each week. The flash drive included data and image files of all forms verified for the previous week
DATA PROCESSING
Data processing for the Basic Data Series Domestic In-Flight Survey is a complex process. The surveys were distributed to groups of visitors from widely different backgrounds using a self- administered survey technique. Millions of forms were collected each year. The process of making a rational, reliable database out of their myriad responses required thousands of lines of processing code. The code was developed over the years to eliminate as much human error as possible in interpreting raw data collected on the planes.
In 2016, the processing code was contained in the 25 syntax files listed in Figure 4. The files are listed in order by the five major processing tasks. They were applied to the processing flow in the order of the syntax file number. All syntax files were submitted as project deliverables and became part of the annual record.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 11 © SMS July 2017 Figure 4: Data Processing Syntax Files Used in 2018
Processing Syntax File Applied Function File Merger 1_01d_readnew&old_2015_withForm8.sps Data Cleaning 3_04A_Dom_Cleaning_2015_NoMSA.sps Weighting 2_03d_weights_2015.sps 4_04C_Dom BDS weights.sps 4a_DOM weights for Island Survey_2015_to Portia.sps 4b_weights_cumulativemerge.sps Tabulate 5a_Revised 04D_HLJan15 by Island Visitation.sps Highlights 6_hl_airline_flightno_C_2015_PNC.sps 6_Revised 04D_HL_airline_flightno_2015.sps 7_Revised 04D_HL_c_2015.sps 7a_Revised 04D_HL_c_2015.sps 21_04D_HL_Original_c_2104Revised0216014.sps Tabulate 8_Revised 05D Banners1 (MMA)_2013.sps Banners 9_Revised 05D_Banners2 (USRegion&States)_2015 10_Revised 05_Banners3 (CBSA)_2013.sps 11_Revised 05_Banners4 (Japan Prefecture)_2015.sps 12_Revised 05_Banners5 (Canadian Province)_2015.sps 13_Revised 05_Banners6 (Island_CBSA)_2013.sps 14_Revised 05_Banners7 (Accommodation)_2013.sps 15_Revised 05_Banners8 (Purpose of Trip)_2013.sps 16_Revised 05_Banners9 (1st timeRepeat, Organized Tour Group, Package Trip, and Length of Stay)_2013.sps 17_Revised 05_Banners10 (Age & Sex of Party Head, PS, and Lifestage)_2013.sps 18_Revised 05_Banners11 (Visitor and Resident and HI City)_2013.sps 19_Revised 05_Banners12 (Airline)_2013.sps 20_Revised 07D_RETRES_c_2013.sps
File Merger
The fundamental procedures for processing the scanned data have been in effect since 2003. The first step was to merge all files for each day and each island port of entry into a monthly data file. After the forms were merged into one master file, the syntax containing code to clean the data was applied. Syntax focused on cleaning data related to length of stay (LOS) and zip codes as these are key variables used to segment the data for analyses.
Data Cleaning
The second processing task was to clean the data. That is, to review each data item, check it for face validity (fix multiple response issues, out-of-range codes, contingency patterns, etc.) and internal consistency (within range relative to other data in the survey). The extent of coding required to complete this task is reported each year at the end of the project, line for line, word for word. The results of the process are presented here in two exhibits. One (Figure 5) is for the variables taken directly from the survey. The other (Figure 6) is for the most important variables generated from survey data for use in data tabulations. Note also that more specific information on variables and their characteristics are included in the appendix to this manual.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 12 © SMS July 2017 Figure 5: Rule for Processing Questions on the Survey Form:
Q. Value/Issue Procedure . Q1. Total number of people (including yourself) covered by this form is..? >10 set to 11 multiple response choose the highest marked value blank ascribe3
Used in PS (Party size)
Q2. I am a: O visitor to Hawai‘i O intended resident moving to Hawai‘i for at least one year. (Answer q. 11 to 14 only) O returning Hawai‘i resident multiple response consistency checks [ Q2a, Q4, Q5, Q14a] blank ascribe
Used in Total (Length of Stay for entire trip)
Q2a. (For returning Hawai‘i residents) Number of nights away from Hawai‘i. (Write in) Blank if returning resident, ascribe; if not, blank Zero ascribe Number >0 if not returning resident, blank
Used in Total (Length of Stay for entire trip)
Q3. The trip is my (1st 2nd 3rd 4th 5th 6 to 10th More than 10th)
multiple response choose highest value blank if visitor to Hawai‘i, ascribe; else blank
Q4. Altogether, I/we will be in the Hawaiian Islands for: O a few hours only (STOP HERE). O one night or more multiple response if further questions answered, mark “one night or more” blank if further questions answered, mark “one night or more” if visitor and (q4a>1) mark “one night or more”
Q4a Number nights in Hawaiian Islands (Write in)
>365 if not visitor, blank; if visitor, consistency checks 0 if visitor, ascribe >0 if not visitor, blank
Q5. Please mark the places you plan to visit and the number of nights you plan to stay at that place (Write 0 if day-only trip).
Plan to visit (O‘ahu, Maui, Molokai, Lāna‘i, Kona, Hilo, Kaua‘i). no marks ascribe Number of nights (Write in) No marks ascribe Does not match Q4a consistency checks
3 Ascription is described in detail following the presentation of by-item rules for the In-Flight Survey beginning on page 18.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 13 © SMS July 2017
Q6. [Answer if you plan to visit O‘ahu, otherwise skip to Q.7.] Are you or any member of your party planning on attending any events at the Hawai‘i Convention Center? (Yes/No)
blank ascribe multiple responses mark “Yes”
Q7. On this trip, I am a member of an organized tour group: (Yes/No)
blank ascribe multiple responses mark “Yes”
Q8. I am on a pre-paid package trip that includes at least airfare and lodging: (Yes/No)
blank ascribe multiple responses mark “Yes”
Q9. Where will you stay while in Hawai‘i? (mark all that apply)4
blank ascribe
Q10. The main reason for this trip is (Residents – mark purpose of your trip) (mark all that apply)5
Blank ascribe
Q11. What is your age: (Write in)
blank ascribe (within party size, Q1 – Q11). <18 Eliminate the case
Q12. Gender
blank ascribe both marked consistency checks
Q13. Of the people covered by this form (NOT including yourself), how many are: (Write in for 6 age groups and 2 genders plus total males and females).
blank ascribe does not match PS consistency checks Σmales ≠ Total males consistency checks Σfemales ≠ Total females consistency checks
4 The final option, “Other” includes an instruction “please specify” with a space for a write-in response. Those responses were not processed in the 2016 system. 5 The final option, “Other” includes an instruction “please specify” with a space for a write-in response. Those responses were not processed in the 2016 system.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 14 © SMS July 2017
Q14. I am a resident of Q14a Countries
blank a. Decide based on postal codes b. Decide based on address (on side 1) c. ascribe multiple response a. Decide based on postal codes b. Decide based on address (on side 1) c. ascribe
Used in MMA (Major Marketing Area)
Q14b. USA (provide Zip Code Below) (Write in)
blank a. decide based on address (on side 1) b. ascribe does not match country a. recheck country codes code b. decide based on address (on side 1) c. ascribe
Used in MMA (Major Marketing Area)
Q14c. USA (provide Zip Code Below) (fill in bubbles)
blank a. decide based on Q14b, USA only b. decide based on address (on side 1) does not match country a. recheck country codes code b. decide based on address (on side 1)
Used in MMA (Major Marketing Area)
Q14d. Canada (provide postal code below) (Write in)
blank a. decide based on address (on side 1) does not match country a. recheck country codes code b. decide based on address (on side 1)
Used in MMA (Major Marketing Area)
Q14e. All other countries (provide postal code below) (Write in)
blank a. decide based on address (on side 1) does not match country a. recheck country codes code b. decide based on address (on side 1)
Used in MMA (Major Marketing Area)
Q15. E-mail Address (to participate in a follow-up survey):
No processing
These variables taken directly from the survey instrument were used in many of the tabulations that appear in monthly, quarterly, and annual tabulations delivered.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 15 © SMS July 2017 Figure 6: Generated Variables
Q. Value/Issue Procedure .
Isvis: Number of Islands Visited on this trip
multiple response accepted non-match other data recalculate as Island with non-zero LOS (include day trips) blank ascribe
Compares with LOS, Island LOS, visitation by island, O‘ahu/NI, Island-only indicators
LOS: Length of stay in days
All LOS days = LOS nights + 1 LOS = O, blank use sum of island LOS LOS =1 use sum of island LOS Sum of Is LOS<1 ascribe >365 use sum of island LOS; ascribe if necessary LOS NE. Sum Isle LOS consistency checks
Compare: Isviv, island LOS, day trip indicators, returning residents days away, isle sum, visitor days, average visitor census
ACCOM: Visitor accommodations indicators
All accom = 0, blank ascribe
Compare: total accommodations used, accommodations types, indicator of accommodation (1,0), hotel or condo, one accommodation only indicator.
POT: Purpose of Trip Indicators
All blank ascribe
Compare: Individual purpose indicators: pleasure (honeymoon, wedding, vacation), “honeywed” (honeymoon or wedding), mci (meeting, convention, or incentive)
RptVis: First time or repeat visitor (developed from number of trips)
NumTrip = 11 num trip = more than 10. NumTrip = 0, blank ascribe
Compare number of trips, cardinal number of trip
Geog: States, Nations, countries and Major Market Areas (MMAs)
Postal code, country = 0, blank ascribe Postal code, country don’t match consistency checks
Compare: See Appendix A, for a complete list of states, countries, and MMAs and some other geographic indications generated from these data.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 16 © SMS July 2017
Zip code cleaning
Survey forms asked for a zip code to be entered at three different points: one on the agricultural side of the form, one in bubbles on the visitor survey side of the form, and another printed zip code right above the bubbles. All three were subject to 100-percent verification during data entry which ensured that all of the zip code data were scanned as entered.
Postal codes for US, Japan, and Canada were extracted from both the visitor survey side and from the DOA side if they were provided there. The routine begins with the bubble zip code as the target – the temporary “real zip code.” It was first compared with a list of postal codes used by the United States Postal Service in 2016. If no match was found, the postal code target was discarded and the written postal code from the survey was used as the target for comparison with the official postal code file for the U.S., Canada, and Japan. If no match was found, the DOA side postal code was used as a target for comparison. The remaining “no match” cases, those for which no usable postal code information was supplied, the zip code was set to “missing”, and ascription was applied.
Length of Stay (LOS) cleaning
The cleaning procedure used internal consistency checks to make decisions about unclear data. For example, the routine might check total trip LOS against the sum of LOS for each island visited to clear up issues with the overall LOS. Other routines used information from the scanning process itself to identify entry errors that frequently appear in scanned data. A seven- day LOS might have been entered as 7, as 07, or as 007. The routine can easily change those to “7.”
Verification thresholds were set at 90 percent accuracy by contract (i.e., if TELEform is at least 90 percent confident, it has chosen the correct number; it is not verified by a human operator). The 90 percent allowed for some data errors to slip through. Those errors were mostly systematic and were corrected in the cleaning syntax. The cleaning syntax did not check for all types of errors; it checked for the most common ones generated in the scanning process (thinking a 2 is an 8, or a 7 is a 1, for instance).
The rest of the LOS cleaning reconciled the LOS and the sum of LOS for each island visited. If there were differences, then a decision was made to adjust either the total or the island LOS. For visitors to more than one island, visitor days rarely summed to the total LOS for the State. That was because some may visit more than one island per day on multi-island tours.
The syntax set up a few variables related to LOS and balanced them. Islands visited was calculated in two forms – total islands visited and total islands visited for overnight or longer stays, that is, eliminating day trips. Second, differences between total LOS and the sum of island LOS were reconciled. Third, one day was added to the total LOS to change that figure from nights to days. Then the extra day was allocated to the island on which the visitor party spent the majority of its visitor days. If a case had no data for islands visited, then the total LOS was allocated to the port of entry island.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 17 © SMS July 2017 Ascription
If certain key variables had missing values, ascription was applied to estimate a replacement value. The so called “nearest neighbor” method has been used for ascription since 1995. The method involves selecting a value for the missing one from a randomly ordered set of cases with similar characteristics (MMA, month, party size, purpose of trips, etc.).
Ascription is currently applied to the following variables:
Q1 Party size Q2 Visitor status Q3 Number of trips to Hawai‘i Q5 Island visitation and length of stay Q7 Group tour vs. Free and Independent travelers Q8 Package Tour vs. self-arranged tour Q9 Visitor accommodations (ascribed as a set) Q10 Purpose of trip variables (ascribed as a set) Q11 Age Q12 Gender
The ascription produced new, ascribed variables with post-ascription distributions that are very similar to pre-ascription distributions. It is, however, a univariate technique that ignores associations between ascribed variables and other variables in the dataset.
Consistency Checks
“Consistency Checks” is a term used to describe a series of operations needed to assign or adjust a survey variable such that it is consistent with other data in the survey record. If, for example, a respondent did not fill in his or her country code and we knew that person’s zip code, we could assign the accurate country code. If they said they visited O‘ahu, Maui, and Lāna‘i, and elsewhere indicated the number of islands they visited was one, we could use internal data to determine which answer was correct. The exact data used, types of tests applied, and calculations needed to get the answer were unique for nearly every variable. Consistency checks were used frequently throughout data processing, as can be seen in Figures 5 and 6.
New Variables and Values
As mentioned earlier, in 2016 a new form (Form 9) was introduced that included additional response categories for Question 9 (Accommodations). Two new variables were created for the responses:
❖ Q9k: Private Room in Private Home ❖ Q9l: Shared Room/Space in Private Home
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 18 © SMS July 2017 Effective September 1, 2016, values for variable q14 were added or adjusted:
❖ Afghanistan is now 149 “Middle East” previously it was 123 “Other Asia” ❖ Czech Republic is coded as 176 (new value) ❖ Cyprus is now 147 “Other Europe” previously it was 123 “Other Asia” ❖ Greece is coded as 177 ❖ Hungary is coded as 178 ❖ Poland is coded as 179 ❖ Portugal is coded as 180 ❖ Turkey is now 181
Non-MMA Country Assignment
On the Domestic In-Flight form, Question 14 (q14) asked respondents to indicate where they live. The information in this variable was used to assign respondents to MMAs.
Respondents from the U.S. and Canada provided their postal codes in designated fields in q14. Respondents from countries other than the U.S. and Canada indicated their country of origin either by selecting it from a list of 16 countries or by handwriting their postal code in a designated space in q14. If a respondent provided a postal code in the handwritten field, that respondent’s data were included in a variable coded as “q14_oth” in the In-Flight dataset.
During the use of Form 6, the data from q14_oth was committed to the In-Flight data file in alphanumeric format. When Form 7 was adopted, q14_oth was committed to the data file in numeric format. In order to merge the data files from Forms 6 and 7 together, processing required that the variable q14_oth in each dataset had the same format (i.e., either numeric or alphanumeric). In order to preserve the alphanumeric data that was captured in the data for Form 6, the syntax was revised to convert data in q14_oth on Form 7 from numeric to alphanumeric. All subsequent forms were also adjusted.
Append Zip Code Data
Assigning the U.S. state, county or metropolitan area for each visitor is done by recoding the U.S. zip code. This is quickly accomplished by conducting a look up function that matches the zip code in a record to the record in the Zip code Look Up table (ZipMSA2016.sav), then the data from that record is appended to the record in the In-Flight dataset. The zip code source data is provided by the HTA every year. The variables added to each record include: state, county, and MSA.
If a record has a zip code that does not appear in the ZipMSA2016.sav, then it is coded as Other Foreign (unknown origin).
Elimination of Invalid Records
Finally, any records that were coded as “Other Foreign (unknown origin)” or had a length of stay greater than 365 days were eliminated. The surviving records are saved as Preliminary Data Set- CHECK 2 save valid zipcodes and countries. The total number of valid records for 2016 was
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 19 © SMS July 2017 DATA WEIGHTING
In-Flight Survey data were weighted to bring them into correspondence with population parameters for airline visitors arriving in Hawai‘i aboard domestic carriers each month.
Monthly Weights
By the 12th day of the month following the month to be processed, HTA provided SMS with the number of passengers disembarking6 all domestic air carriers in the month to be processed. The data is presented as a value for each Port of Entry (O‘ahu, Kaua‘i, Maui, Kona, Hilo); known as “domestic weights,” these data were based on monthly reporting filed by each airline and submitted to the Hawai‘i Department of Transportation (DOT), Airports Division and the Department of Business, Economic Development and Tourism (DBEDT). These data were used to develop the numerators (Nij) in the equation to calculate In-Flight data weights.
In general, weights take the form:
Wij = Nij / nij , where
th 7 th Wij = the weight for the i Port of Entry and the j month of arrival, i = 1 to 5, j = 1 to 12;
th Nij = the number of passengers disembarking from domestic air carriers for the i Port of Entry and the jth month of arrival, i = 1 to 5, j = 1 to 12; and
th th nij = the number of completed survey forms collected for the i Port of Entry and the j month of arrival, i = 1 to 5, j = 1 to 12.
The calculation of the weighting values was done in the syntax file labeled 2_03d_weights_2014.sps.
First, the monthly In-Flight data file was weighted (w) by party size (q1), to reflect the number of passengers represented by one record (The domestic landings file describes all passengers while the In-Flight data file contains one record per party). Second, the number of forms (n) for each Port of Entry is calculated by aggregating the records by Port of Entry (dummy). Third, SMS enters in the Domestic Weight values for the five Port of Entry into the syntax file. The variable is called USwt. Finally the weights were calculated and then assigned to each In-Flight data file record.
Weights delivered on a monthly basis were considered preliminary until all DOT reports were collected and verified by DOT Airports Division; usually by April of the following year. A verified set of weights was provided for annual processing.
6 This count does not include transients, those continuing on to other destinations on the same day (i.e., do not leave the airport). 7 In the actual syntax the variable is named DUMMY where 1=HNL, 2=LIH, 3=OGG, 4=KOA, 5=ITO.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 20 © SMS July 2017 TABULATION & REPORTS
The majority of the processing syntax was devoted to tabulations (Figure 4). Highlights Reports were a standard set developed to provide monthly, quarterly, and annual data in similar formats across years. Data from individual variables were produced for visitors from each MMA, to each island, and for a series of special purpose tables. Banners were a much larger set of tabulations designed to exploit the survey data and anticipate all possible queries that might be put to the data. Highlights and banners were delivered monthly and annually as SPSS8 output files.
In the process of developing tabulations, further revisions were sometimes made to the data and recoding was done to expand or collapse the response sets to fit the purpose of specific data tables.
Monthly Reports
The Monthly Highlights report was produced after receiving the domestic landings report from HTA. The Highlights for any given month were delivered by the 15th of the following month. Monthly Highlights is a report on visitors to Hawai‘i for a given month this year, the same month last year, percentage change between a given month this year and the same month last year, year-to-date counts for this year, and year-to-date counts for last year. Reported visitor characteristics include visitor counts and days (which is the total number of days stayed by all visitors in a given month), islands visited, accommodations, purpose of trip, and travel status.
Note that the Highlights reports do not report all of the variables on the In-Flight survey, but rather a subset of all available variables. A complete list of In-Flight survey variables is shown in Appendix B to this document.
Monthly Banners were generated as SPSS output files and included all questions in the survey. The banner files generated included:
❖ Highlights banner: Contained the key variables and formats used in the monthly highlights. ❖ Highlights by island visitation banner: Same as the highlights banner, but with a layer in each table for each island (including all visitors to any island) and island only (including only visitors who only visited a single island). ❖ Highlights extra banner: A set of tables HTA used regularly set forth in a special banner. ❖ HCC banner: Contained detailed analysis of visitors who went to the Hawai‘i convention center and indicated that a conference or convention was a purpose of their trip. ❖ Party type banner: Number of visitors by party type based on party composition and visitation patterns. ❖ Returning resident banner: Detailed tables on returning residents to Hawai‘i ❖ Big banner: Has over 200 detailed tables. ❖ Flight number banner: Has detailed analysis of visitors by airline flight number.
8 IBM SPSS (IBM Statistical Package for the Social Sciences) is the statistical package SMS uses for all In-Flight statistical analyses in order to produce data and output files that are compatible with the software in use at HTA.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 21 © SMS July 2017 In 2016, in addition to the SPSS output files (Highlights Reports and Monthly Banners), SMS was also requested to produce a set of Excel spreadsheets to be used for an Access database, referred to as the Highlights Database (HLDB). The HLDB imported domestic and international tables from the monthly output files to generate the monthly reports that were published by the HTA.
First, SMS converted select tables from the SPSS output files into Excel spreadsheet templates and sent them to the HTA. These Excel sheets and also similar sheets that were provided by the International data processing vendor were imported into the HLDB. The HTA also entered additional data on air seats and load factors into the HLDB interface. The database’s interface featured buttons that selected and imported the correct data relevant to each report. Imported data included major or MMA highlights, highlights for each island, highlights for regions, and highlights for CBSA (core-based statistical areas). The HDLB then exported reports as Excel spreadsheets.
Deliverables
Highlights and banners were delivered monthly and annually as SPSS output files. The SPSS syntax files and the data files from which the tabulations were generated, were delivered at the same time. Both were delivered in SPSS formats. Highlights, banners, and state and nation reports were also delivered in Excel format ready for import into the database.
END-OF-YEAR PROCEDURES
Annual Weights
The weighting process was repeated once more following the close of the calendar year. This enabled the collection of all survey forms from flights for the entire year which included any forms that were turned in late after the monthly processing deadline. The HTA reviewed all DOT carrier reports and confirmed any mistakes or omissions to obtain final weights. Data that became available during the course of the year were used to refine monthly data weights.
Annual Data Tabulation
The HTA provided SMS with revised monthly domestic landing weights for the 2016 year by the beginning of June 2016. Utilizing the same process as for monthly tabulations as outlined above, each month's data were re-weighted using final landings counts.
Annual tables and banners had the same content and format as monthly reports and were produced using nearly identical procedures. Formats changed slightly, mostly by providing more month-by-month information. Three major sub-products were prepared and delivered: Final Tabulations and Banners which nearly duplicated the monthly tables and banners, a set of banners and tables used to produce the Annual Research Report; and the Data Book Tables to be used by the Department of Business, Economic Development and Tourism to produce the annual Hawai‘i Data Book.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 22 © SMS July 2017 Banner points for tabulation are defined as follows:
❖ Visitors to Hawai‘i ❖ Purpose of Trip - True Independent (net) ❖ Repeat Visitor ❖ U.S. States and Regions of U.S.A ❖ Total United States ❖ Country of Residence
DISPOSAL OF MATERIALS
All hard copy materials were stored securely at SMS for three months after data processing. After three months, and after completion and delivery of all banners and reports, all documents were destroyed by a bonded agent. SMS first confirmed through an e-mail to the HTA that they have authorization to destroy the scanned In-Flight forms.
Backup data files in electronic form were sent to the HTA with the monthly and annual deliverables. Another set was maintained in a fireproof storage in SMS's care. An additional copy was kept in a safety deposit box in a local bank. Since June 2013, a cloud backup copy was also maintained.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 23 © SMS July 2017
APPENDIX
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 24 © SMS July 2017
APPENDIX A: SURVEY FORMS
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 25 © SMS July 2017
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 26 © SMS July 2017
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 27 © SMS July 2017 APPENDIX B: CODEBOOK9 convent Purpose of trip is Value BATCHNO convention or conference Batch Number Value Label convention Standard Label BatchNo Type Numeric Standard Attributes Type Numeric Format F1 Attributes Format F10 meeting Purpose of trip is a Q1txt Value Value business meeting Label q1 Label corporate meeting Standard Standard Type String Type Numeric Attributes Attributes Format A3 Format F1 1 1 incent 2 2 Purpose of trip is an Value 3 3 incentive reward 4 4 Label incentive travel Standard 5 5 Type Numeric Attributes Valid Values 6 6 Format F1 7 7 Other Business 8 8 Other Business Value 9 9 Label other business Standard 10 10 Type Numeric Attributes >10 >10 Format F1 Q10 Visit Friends, relatives Value Purpose of trip is to visit Value Label q10 friends and relatives Standard Type String visit friend, Attributes Label Format A72 Standard relatives honey Attributes Type Numeric Purpose of trip is Format F1 Value honeymoon Government Label honeymoon Purpose of trip is Standard Type Numeric government or military Value Attributes Format F1 business government, married Label Standard military Purpose of trip is get Value Attributes Type Numeric married or attend a wedding Format F1 Label get married Standard Type Numeric School Attributes Purpose of trip of to attend Format F1 Value school. Label attend school Standard vacation Type Numeric Attributes Purpose of trip is vacation Value Format F1 Label vacation Standard Sport Type Numeric Purpose of trip is to attend Attributes Value Format F1 a sports event Label sports event Standard Type Numeric Attributes Format F1 9 This codebook specifies the characteristics of each Other purpose variable in the In-Flight dataset including variable type Purpose of trip is “other” Value (numeric or alphanumeric), variable labels (the name of Label other each variable as it appears in the output files), and value Standard Type Numeric labels (indication of what each numerical response for a Attributes categorical variable signifies). Format F1
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 28 © SMS July 2017 m2 Q11 Males 13 to 17 Value Respondent’s age in years Value Label Males 13 to 17 Standard Label q11 Type Numeric Standard Attributes Type Numeric Attributes Format F2 Format F2 m3
f7 Males 18 to 24 Value Total females in party Value Label Males 18 to 24 Label q13f_total Standard Standard Type Numeric Type Numeric Attributes Attributes Format F2 Format F2 m4
f1 Males 25 to 40 Value Females 12 or under Value Label Males 25 to 40 Label Females Under 13 Standard Standard Type Numeric Type Numeric Attributes Attributes Format F2 Format F2 m5
f2 Males 41 to 59 Value Females 13 to 17 Value Label Males 41 to 59 Label Females 13 to 17 Standard Standard Type Numeric Type Numeric Attributes Attributes Format F2 Format F2 m6
f3 Males 60 or older Value Females 18 to 24 Value Label Males 60 or older Label Females 18 to 24 Standard Standard Type Numeric Type Numeric Attributes Attributes Format F2 Format F2 Q14_OTHE
f4 Country: Other, specify Value Females 25 to 40 Value Label q14_other Label Females 25 to 40 Standard Standard Type String Type Numeric Attributes Attributes Format A30 Format F2 Canada code
f5 Canadian postal code Value Females 41 to 59 Value Label q14b Label Females 41 to 59 Standard Standard Type String Type Numeric Attributes Attributes Format A6 Format F2 Japanese code
f6 Japanese postal code Value Females 60 or older Value Label q14c Females 60 or Standard Label Type String older Attributes Standard Format A7 Attributes Type Numeric Q2 Format F2 Q2, Type of traveler Value m7 Label Type of traveler Total males in par ty Value Standard Type Numeric Label q13m_total Attributes Standard Format F1 Type Numeric Attributes 1 visitor Format F2 Valid Values 3 returning resident m1 4 intended resident Males 12 or under Value Q2A Label Males Under 12 Standard Visitor to Hawai‘i Value Type Numeric Label q2a Attributes Standard Format F2 Type Numeric Attributes Format F3 Q3
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 29 © SMS July 2017 Returning Resident Value Q5B5 Label q3 Visited Kona Value Standard Type Numeric Label q5b5 Attributes Standard Format F1 Type Numeric 1 A few hours only. Attributes Valid Values Format F3 2 One night or more. Q5B6 Visited Hilo Value
Label q5b6 Standard Type Numeric Q4 Attributes Number times to Hawai‘i Value Format F3 Label times to Hawai‘i Standard Type Numeric Q5B7 Attributes Format F1 Visited Kaua‘i Value 1 1 Label q5b7 Standard Type Numeric 2 2 Attributes 3 3 Format F3 Valid Values 4 4 POE 5 5 Port of Entry Value 6 6 to 10 times Label q6 Standard 7 11 or more Type Numeric Attributes q3a Format F1 1 Yes First time to Hawai‘i Value Valid Values Label q4a 2 No Standard Type Numeric G roup Attributes Format F3 Member of a tour group Value Member of Tour Label Q5A Standard Group Visited Any Island Value Attributes Type Numeric Format F1 Label q5a Standard 1 yes Type String Valid Values Attributes 2 no Format A42 Package Q5B1 Here on a package tour Value Visited O‘ahu Value Air and Lodging Label Label q5b1 Standard Package Standard Type Numeric Attributes Type Numeric Attributes Format F3 Format F1 1 yes Q5B2 Valid Values Visited Maui Value 2 no Label q5b2 Q9 Standard Type Numeric Accommodations used Value Attributes Label q9 Format F3 Standard Type String Q5B3 Attributes Visited Molokai Value Format A50 Label q5b3 H otel Standard Type Numeric Stayed at a hotel Value Attributes Label Hotel Format F3 Standard Type Numeric Q5B4 Attributes Format F1 Visited Lāna‘i Value Valid Values 1 Label q5b4 Standard C ondo Type Numeric Attributes Stayed at a condominium Value Format F3 Label Condo Standard Type Numeric Attributes Format F1 Valid Values 1
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 30 © SMS July 2017 Rental House Other Accommodation Stayed at a rental house Value Stayed at other accom. Value Label Rental House Label other Standard Standard Type Numeric Type Numeric Attributes Attributes Format F1 Format F1 Valid Values 1 Valid Values 1 T imeshare SUSPENSE FILE Stayed at a timeshare unit Value And IDS number Value Label Timeshare Label Suspense_File Standard Standard Type Numeric Type String Attributes Attributes Format F1 Format A30 Valid Values 1 ZIP
Zip Code Value
Label Zip Bed and Breakfast Standard Type String Stayed at a B&B Value Attributes Label Bed and Breakfast Format A5 Standard Type Numeric Q5A1 Attributes Format F1 Nights on O‘ahu Value Valid Values 1 Label q5a1 Standard C ruise Type Numeric Attributes Stay on a cruise ship Value Format F1 Label Cruise ship Standard Q5A2 Type Numeric Attributes Nights on Maui Value Format F1 Label q5a2 Valid Values 1 Standard Type Numeric Friends or Relatives Attributes Format F1 Stayed w friends. Relatives Value
Label Friends, relatives Q5A3 Standard Type Numeric Nights on Molokai Value Attributes Format F1 Label q5a3 Standard Valid Values 1 Type Numeric Attributes Format F1
Hostel Q5A4 Stayed at a hostel Value Nights on Lāna‘i Value Label hostel Standard Label q5a4 Type Numeric Standard Attributes Type Numeric Format F1 Attributes Format F1 Valid Values 1
C amp Q5A5 Nights in Kona Value Stayed at a camp grounds Value Label q5a5 Label camping Standard Standard Type Numeric Type Numeric Attributes Attributes Format F1 Format F1 Valid Values 1 Q5A6 Privtrm Nights in Hilo Value Stayed at Private Room Value Label q5a6 Standard Label Private Room Type Numeric Standard Attributes Type Numeric Attributes Format F1 Format F1 Q5A7 Valid Values 1 Nights on Kaua‘i Value
Sharerm Label q5a7 Standard Stayed in a shared room Value Type Numeric Label Shared Room Attributes Standard Format F1 Type Numeric Attributes Format F1 Valid Values 1
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 31 © SMS July 2017 3.00 Mar LANGUAGE BUBBLE 4.00 Apr Language on form Value 5.00 June Label lang_bbl 6.00 Jun Standard Type Numeric Attributes 7.00 Jul Format F1 8.00 Aug 1 1 9.00 Sep 2 2 10.00 Oct 3 3 Valid Values 11.00 Nov 4 4 12.00 Dec 5 5 day 6 6 Day of then month Value Old or New Form Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 32 © SMS July 2017 Lāna‘i Ages of females in party Value LOS Lāna‘i Value Label
17.00 South Pacific (SP) Age of female respondent Labeled Values United Airlines Age of female respondent Value 18.00 (UAL) Age of female Label World Airways head 19.00 Standard (WOA) Attributes Type Numeric 20.00 Air New Zealand Format F8.2 21.00 EVA (BR)
self1 22.00 Orion Respondent gender Value Philippine Airlines Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 33 © SMS July 2017 Hawai‘i American 35.00 Flight number Value Cruises Label Flight Number Standard Type Numeric Attributes Ports of Format F8.2 36.00 Call/Skyworld P ort (POC) Port of entry Value 37.00 Harmony Air (HQ) Label
Flight Number WhitePopulation
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 34 © SMS July 2017 Zip code with population Value AverageHouseValue Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 35 © SMS July 2017 CityType Zip code CSA Value Zip code city type Value Label
DayLightSaving ZAip code DLST code Value Label
MSA13
Zip code MSA Value Label
Zip code PMSA Value
Label
CSA Here follows 45 additional characteristics of the
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 36 © SMS July 2017 zip code area that include the respondent’s home 47.00 N. Carolina zip code. Many of those are addresses that might 48.00 S. Carolina be used to contact the respondent. 49.00 Virginia numstate 50.00 West Virginia State code Value 51.00 Puerto Rico Label Standard 53.00 Hawai‘i Type Numeric Attributes Format F8.2 54.00 Virgin Islands 1.00 Alaska 2.00 California G uam 3.00 Oregon Guam marker Value 4.00 Washington Label Guam Standard Type Numeric 5.00 Arizona Attributes 6.00 Colorado Format F8.2 7.00 Idaho Pr 8.00 Montana Puerto Rico marker Value 9.00 Nevada Label Puerto Rico Standard Type Numeric 10.00 New Mexico Attributes 11.00 Utah Format F8.2 12.00 Wyoming V i 13.00 Iowa Virgin Islands market Value 14.00 Kansas Label Virgin Islands Standard Type Numeric 15.00 Minnesota Attributes 16.00 Missouri Format F8.2 17.00 Nebraska US Region 18.00 N. Dakota Region code Value 19.00 S. Dakota Label
46.00 Maryland
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 37 © SMS July 2017 Asia Can Visitor from Asia Value Label Asia Visitor from Canada Value Standard Label Canada Type Numeric Standard Attributes Type Numeric Format F8.2 Attributes Format F8.2 Labeled Values 1.00 (net) Labeled Values 1.00 Canada Asctry Province Asian country code Value Canadian Province Value Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 38 © SMS July 2017 South Africa South American country Value Visitor from Africa Value South American Label Africa Label Standard Standard Country Type Numeric Attributes Attributes Type Numeric Format F8.2 Format F8.2
1.00 Argentina middle 2.00 Bolivia Visitor from Middle East Value 3.00 Brazil Label Middle East 4.00 Chile Standard Type Numeric 5.00 Colombia Attributes Format F8.2 6.00 Ecuador Labeled Values US 7.00 Peru Visitor from US Value 8.00 Uruguay Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 39 © SMS July 2017 region testsum Area of the World Value Scratch variable Value Label Area of World Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 40 © SMS July 2017 islands Format F8.2 # of Islands Visited Value mcounty Number of islands Label Visited Maui County Value Standard visited Label Maui County Standard Attributes Type Numeric Type Numeric Attributes Format F8.2 Format F8.2 islevis ni sle Visited 1 or 2+ Islands Value Visited a Neighbor Island Value Label Islands visited Standard Visited a Neighbor Type Numeric Label Attributes Standard Island Format F8.2 Attributes Type Numeric 1.00 1 only Labeled Values Format F8.2 2.00 2 or more mco oao Visited Maui County Only Value Visited O‘ahu Only Value Label Maui County only Label O‘ahu only Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2
isletype mao NI Only or NI and O‘ahu Value Visited Maui Only Value Neighbor - only or Label Maui only Label Standard Standard plus O‘ahu Type Numeric Attributes Attributes Type Numeric Format F8.2 Format F8.2 Neighbor island 1.00 only kao Labeled Values Neighbor islands Visited Kaua‘i Only Value 2.00 Label Kaua‘i only and O‘ahu Standard Type Numeric accomm Attributes Format F8.2 Accommodations Value Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 41 © SMS July 2017 Hotel & Condo Value Labeled Values 1.00 Label Hotel and Condo Pac Standard Type Numeric Visited Pacific Region Value Attributes Format F8.2 Label Pacific Region Standard otheracc Type Numeric Attributes Other Accommodations Value Format F8.2 Other USPAC Label Standard accommodations Visited US Pacific Region Value Attributes Type Numeric Label
Net, honeymoon or Label USMONT get married Standard Mountain Region States Value Attributes Type Numeric Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 42 © SMS July 2017 WSth 32.00 Connecticut From W. S. Central Region Value 33.00 Maine W. South Central 34.00 Massachusetts Label Labeled Values Standard Region 35.00 New Hampshire Attributes Type Numeric 36.00 Rhode Island Format F8.2 37.00 Vermont USWSTH ESC W. S. Central States Value From E. S. Central Region Value Label
USENC SA E. N. Central States Value From S. Atlantic Region Value Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 43 © SMS July 2017 UScon1 Format F8.2 From US Value USsat United States From A. Atlantic Value Label Mainland Label South Atlantic Standard Standard &Territories Type Numeric Attributes Attributes Type Numeric Format F8.2 Format F8.2 USpgv
UScon5 From PR, Guam, VI Value From Other Foreign Value Puerto Rico, Label Other Foreign Label Standard Standard Guam, Virgin Islands Type Numeric Attributes Attributes Type Numeric Format F8.2 Format F8.2 USpac1 state01 From Pacific Region Value Alaska Value Label Pacific Region Label Alaska Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 USmtn state02 From Mtn. Region Value California Value Label Mountain Region Label California Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 state03 Oregon Value USwnc Label Oregon From W. N. Central Value Standard Type Numeric Label West North Central Attributes Standard Format F8.2 Type Numeric Attributes sta te04 Format F8.2 Washington Value USwsc Label Washington From W. S. Central Value Standard Type Numeric West South Attributes Label Format F8.2 Standard Central Attributes Type Numeric state05 Format F8.2 Arizona Value Label Arizona USenc1 Standard Type Numeric From E. N. Central Value Attributes Format F8.2 Label East North Central Standard Type Numeric state06 Attributes Format F8.2 Colorado Value Label Colorado Smat Standard Type Numeric From Mid-Atlantic Value Attributes Format F8.2 Label Mid Atlantic Standard Type Numeric state07 Attributes Format F8.2 Idaho Value Label Idaho USeng Standard Type Numeric From New England Value Attributes Format F8.2 Label New England Standard Type Numeric state08 Attributes Format F8.2 Montana Value Label Montana USesc1 Standard Type Numeric From E. S. Central Value Attributes Format F8.2 Standard Label East South Central Attributes Type Numeric state09
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 44 © SMS July 2017 Nevada Value Format F8.2 Label Nevada state20 Standard Type Numeric Arkansas Value Attributes Format F8.2 Label Arkansas Standard Type Numeric state10 Attributes Value Format F8.2 Label New Mexico state21 Standard Type Numeric Louisiana Value Attributes Format F8.2 Label Louisiana Standard Type Numeric state11 Attributes Utah Value Format F8.2 Label Utah state22 Standard Type Numeric Oklahoma Value Attributes Format F8.2 Label Oklahoma Standard Type Numeric state12 Attributes Wyoming Value Format F8.2 Label Wyoming state23 Standard Type Numeric Texas Value Attributes Format F8.2 Label Texas Standard Type Numeric state13 Attributes Iowa Value Format F8.2 Label Iowa state24 Standard Type Numeric Illinois Value Attributes Format F8.2 Label Illinois Standard Type Numeric state14 Attributes Kansas Value Format F8.2 Label Kansas state25 Standard Type Numeric Indiana Value Attributes Format F8.2 Label Indiana Standard Type Numeric state15 Attributes Minnesota Value Format F8.2 Label Minnesota state26 Standard Type Numeric Michigan Value Attributes Format F8.2 Label Michigan Standard Type Numeric state16 Attributes Missouri Value Format F8.2 Label Missouri state27 Standard Type Numeric Ohio Value Attributes Format F8.2 Label Ohio Standard Type Numeric state17 Attributes Nebraska Value Format F8.2 Label Nebraska state28 Standard Type Numeric Wisconsin Value Attributes Format F8.2 Label Wisconsin Standard Type Numeric state18 Attributes North Dakota Value Format F8.2 Label N. Dakota state29 Standard Type Numeric New Jersey Value Attributes Format F8.2 Label New Jersey Standard Type Numeric state19 Attributes South Dakota Value Format F8.2 Standard Label S. Dakota state30 Attributes Type Numeric New York Value
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 45 © SMS July 2017 Label New York state41 Standard Type Numeric Tennessee Value Attributes Format F8.2 Label Tennessee Standard Type Numeric state31 Attributes Pennsylvania Value Format F8.2 Label Pennsylvania state42 Standard Type Numeric Washington D.C. Value Attributes Format F8.2 Label Washington D.C. Standard Type Numeric state32 Attributes Connecticut Value Format F8.2 Label Connecticut state43 Standard Type Numeric Delaware Value Attributes Format F8.2 Label Delaware Standard Type Numeric state33 Attributes Maine Value Format F8.2 Label Maine state44 Standard Type Numeric Florida Value Attributes Format F8.2 Label Florida Standard Type Numeric state34 Attributes Massachusetts Value Format F8.2 Label Massachusetts state45 Standard Type Numeric Georgia Value Attributes Format F8.2 Label Georgia Standard Type Numeric state35 Attributes New Hampshire Value Format F8.2 Label New Hampshire state46 Standard Type Numeric Maryland Value Attributes Format F8.2 Label Maryland Standard Type Numeric state36 Attributes Rhode Island Value Format F8.2 Label Rhode Island state47 Standard Type Numeric North Carolina Value Attributes Format F8.2 Label N. Carolina Standard state37 Type Numeric Attributes Vermont Value Format F8.2 Label Vermont state48 Standard Type Numeric South Carolina Value Attributes Format F8.2 Label S. Carolina Standard Type Numeric state38 Attributes Alabama Value Format F8.2 Label Alabama state49 Standard Type Numeric Virginia Value Attributes Format F8.2 Label Virginia Standard Type Numeric state39 Attributes Kentucky Value Format F8.2 Label Kentucky state50 Standard Type Numeric West Virginia Value Attributes Format F8.2 Label West Virginia Standard Type Numeric state40 Attributes Mississippi Value Format F8.2 Label Mississippi state51 Standard Type Numeric Puerto Rico Value Attributes Format F8.2 Standard Label Puerto Rico
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 46 © SMS July 2017 Attributes Type Numeric Finland Value Format F8.2 Label Finland Standard state52 Type Numeric Attributes Guam Value Format F8.2 Label Guam europe10 Standard Type Numeric Attributes Austria Value Format F8.2 Label Austria Standard state54 Type Numeric Attributes Virgin Islands Value Format F8.2 Label Virgin Islands europe11 Standard Type Numeric Attributes Belgium Value Format F8.2 Label Belgium Standard europe01 Type Numeric Attributes United Kingdom Value Format F8.2 Label U.K. europe12 Standard Type Numeric Attributes Ireland Value Format F8.2 Label Ireland Standard europe02 Type Numeric Attributes Germany Value Format F8.2 Label Germany europe13 Standard Type Numeric Attributes Spain Value Format F8.2 Label Spain Standard europe03 Type Numeric Attributes France Value Format F8.2 Label France europe1 4 Standard Type Numeric Attributes Netherlands Value Format F8.2 Label Netherlands Standard europe04 Type Numeric Attributes Italy Value Format F8.2 Label Italy europe15 Standard Type Numeric Attributes Russia Value Format F8.2 Label Russia Standard europe05 Type Numeric Attributes Switzerland Value Format F8.2 Label Switzerland europe16 Standard Type Numeric Attributes Other Europe Value Format F8.2 Label Other Europe Standard europe06 Type Numeric Attributes Norway Value Format F8.2 Label Norway Standard asia01 Type Numeric Attributes Japan Value Format F8.2 Label Japan Standard europe07 Type Numeric Attributes Sweden Value Format F8.2 Label Sweden Standard asia02 Type Numeric Attributes Korea Value Format F8.2 Label Korea Standard europe08 Type Numeric Attributes Denmark Value Format F8.2 Label Denmark Standard asia03 Type Numeric Attributes China Value Format F8.2 Standard Label China europe09 Attributes Type Numeric
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 47 © SMS July 2017 Format F8.2 Label El Salvador Standard Type Numeric asia04 Attributes Taiwan Value Format F8.2 Label Taiwan camer3 Standard Type Numeric Guatemala Value Attributes Format F8.2 Label Guatemala Standard Type Numeric asia05 Attributes Hong Kong Value Format F8.2 Label Hong Kong camer4 Standard Type Numeric Honduras Value Attributes Format F8.2 Label Honduras Standard Type Numeric asia06 Attributes Indonesia Value Format F8.2 Label Indonesia camer5 Standard Type Numeric Panama Value Attributes Format F8.2 Label Panama Standard Type Numeric asia07 Attributes Philippines Value Format F8.2 Label Philippines camer6 Standard Type Numeric Mexico Value Attributes Format F8.2 Label Mexico Standard Type Numeric asia08 Attributes Singapore Value Format F8.2 Label Singapore camer7 Standard Type Numeric Nicaragua Value Attributes Format F8.2 Label Nicaragua Standard Type Numeric asia09 Attributes Thailand Value Format F8.2 Label Thailand camer8 Standard Type Numeric Other Central America Value Attributes Format F8.2 Other Central Label asia10 Standard America Malaysia Value Attributes Type Numeric Label Malaysia Format F8.2 Standard Type Numeric samer01 Attributes Format F8.2 Argentina Value Label Argentina asia11 Standard Type Numeric India Value Attributes Label India Format F8.2 Standard Type Numeric samer02 Attributes Format F8.2 Bolivia Value Label Bolivia asia12 Standard Type Numeric Other Asia Value Attributes Label Other Asia Format F8.2 Standard Type Numeric samer03 Attributes Format F8.2 Brazil Value Label Brazil camer1 Standard Type Numeric Costa Rica Value Attributes Label Costa Rica Format F8.2 Standard Type Numeric samer04 Attributes Format F8.2 Chile Value camer2 Standard Label Chile El Salvador Value Attributes Type Numeric
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 48 © SMS July 2017 Format F8.2 Bermuda Value samer05 Label Bermuda Standard Colombia Value Type Numeric Attributes Label Colombia Format F8.2 Standard Type Numeric Attributes caribb5 Format F8.2 Jamaica Value samer06 Label Jamaica Standard Ecuador Value Type Numeric Attributes Label Ecuador Format F8.2 Standard Type Numeric Attributes caribb6 Format F8.2 Dominican Republic Value samer07 Dominican Label Peru Value Standard Republican Label Peru Attributes Type Numeric Standard Type Numeric Format F8.2 Attributes Format F8.2 caribb7 samer08 Haiti Value Uruguay Value Label Haiti Standard Label Uruguay Type Numeric Standard Attributes Type Numeric Format F8.2 Attributes Format F8.2 caribb8 samer09 Other West Indies Value Paraguay Value Label Other West Indies Standard Label Paraguay Type Numeric Standard Attributes Type Numeric Format F8.2 Attributes Format F8.2 occtry1 samer10 Australia Value Venezuela Value Label Australia Standard Label Venezuela Type Numeric Standard Attributes Type Numeric Format F8.2 Attributes Format F8.2 occtry2 samer11 New Zealand Value Other S. America Value Label New Zealand Standard Other South Type Numeric Label Attributes Standard America Format F8.2 Attributes Type Numeric occtry3 Format F8.2 American Samoa Value caribb1 Label American Samoa Standard Caribbean Value Type Numeric Attributes Label Caribbean Format F8.2 Standard Type Numeric Attributes occtry4 Format F8.2 Western Samoa Value caribb2 Label Western Samoa Standard Bahamas Value Type Numeric Attributes Label Bahamas Format F8.2 Standard Type Numeric Attributes occtry5 Format F8.2 Tahiti Value caribb3 Label Tahiti Standard Barbados Value Type Numeric Attributes Label Barbados Format F8.2 Standard Type Numeric occtry6 Attributes Format F8.2 Value caribb4 Standard Label Fiji
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 49 © SMS July 2017 Attributes Type Numeric 1.00 Mexico Format F8.2 Labeled Values 2.00 Brazil occtry7 3.00 Argentina Otr Oceania & PI Value HTAnz Other Oceania and Oceania Value Label Standard Pacific Islands Label Oceania Standard Attributes Type Numeric Type Numeric Attributes Format F8.2 Format F8.2 1.00 Australia CONus Labeled Values From US Value 2.00 New Zealand United States of HTAother Label Standard America Other Country Value Attributes Type Numeric Label Other Standard Format F8.2 Type Numeric Attributes United States of Format F8.2 Labeled Values 1.00 America Labeled Values 1.00 Other HTAus HTAasiaT US East vs US West Value Other Asian Country Value Label US Label Other Asia Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 US West Labeled Values 1.00 Total 1.00 Labeled Values (Pacific/Mountain) HTAeurT 2.00 US East Europe Visitor Value HTAeur Label Europe Standard Europe Value Type Numeric Attributes Label Europe Format F8.2 Standard Type Numeric Labeled Values 1.00 Total Attributes Format F8.2 HTAlataT 1.00 United Kingdom Latin American Visitor Value 2.00 France Label Latin America Standard Labeled Values 3.00 Germany Type Numeric Attributes 4.00 Italy Format F8.2 5.00 Switzerland Labeled Values 1.00 Total HTAjapan HTAnzT Japan Value Oceania Visitor Value Label Japan Label Oceania Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 Labeled Values 1.00 Japan Labeled Values 1.00 Total HTAasia ps Asian Country Value Party Size Value Label Other Asia Number of people in Standard Label Type Numeric Standard party Attributes Format F8.2 Attributes Type Numeric 1.00 Taiwan Format F8.2 2.00 Hong Kong visitor3 Labeled Values 3.00 Korea Visitor Type Value 4.00 China Label Type Standard 5.00 Singapore Type Numeric Attributes Format F8.2 1.00 Visitor destined to HI HTAlatam 2.00 Travel beyond HI Labeled Values Latin American Country Value 3.00 Returning resident Label Latin America 4.00 Intended Resident Standard Type Numeric Attributes numtrip2 Format F8.2
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 50 © SMS July 2017 San Francisco-Oakland- First Time Visitor Value 2.00 Label Number of trips Hayward CA Standard Type Numeric Seattle-Tacoma-Bellevue Attributes 3.00 Format F8.2 WA 1.00 First 4.00 San Diego-Carlsbad CA Labeled Values 2.00 Second or more San Jose-Sunnyvale- 5.00 numtrip_r Santa Clara CA Portland-Vancouver- # of Trips to Hawai‘i Value 6.00 Number of trips to Hillsboro OR-WA Label New York-Newark-Jersey Standard Hawai‘i 7.00 Attributes Type Numeric City NY-NJ-PA Sacramento--Roseville-- Format F8.2 8.00 1.00 1 Arden-Arcade CA Phoenix-Mesa-Scottsdale 2.00 2 9.00 3.00 3 AZ Chicago-Naperville-Elgin Labeled Values 4.00 4 10.00 5.00 5 IL-IN-WI Riverside-San 6.00 6 to 10 times 11.00 Bernardino-Ontario CA 7.00 11 or more Dallas-Fort Worth- 12.00 bothGP Arlington TX Group/Pkg Tour Value Washington-Arlington- Label Both Grp and Pkg Standard 13.00 Alexandria DC-VA-MD- Type Numeric Attributes WV Format F8.2 Denver-Aurora-Lakewood 14.00 Labeled Values 1.00 CO portx Houston-The Woodlands- 15.00 Port of Entry Value Sugar Land TX Label Port of Entry Standard Las Vegas-Henderson- Type Numeric 16.00 Attributes Paradise NV Format F8.2 Minneapolis-St. Paul- 17.00 1.00 O‘ahu Bloomington MN-WI 2.00 Maui 18.00 Anchorage AK Labeled Values 3.00 Kona Oxnard-Thousand Oaks- 19.00 4.00 Kaua‘i Ventura CA 5.00 Hilo Boston-Cambridge- 20.00 xfile Newton MA-NH Atlanta-Sandy Springs- Scratch variable Value 21.00 Label X File Roswell GA Standard Type Numeric Philadelphia-Camden- Attributes Format F8.2 22.00 Wilmington PA-NJ-DE- 1.00 Yes MD Labeled Values 2.00 No 23.00 Salt Lake City UT Totalx 24.00 Santa Rosa CA Detroit-Warren-Dearborn Westbound Total Value 25.00 Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 51 © SMS July 2017 33.00 Stockton-Lodi CA Attributes Type Numeric Spokane-Spokane Valley Format F8.2 34.00 WA 1.00 1-6 2.00 7-12 35.00 Tucson AZ Labeled Values San Antonio-New 3.00 13-30 36.00 Braunfels TX 4.00 31 or more days 37.00 Fresno CA O‘ah u_D 38.00 Boise City ID Days on O‘ahu Value Santa Maria-Santa Label Days on O‘ahu 39.00 Standard Barbara CA Type Numeric Attributes 40.00 Provo-Orem UT Format F8.2 41.00 Ogden-Clearfield UT Maui1 42.00 Reno NV Days on Maui-Category Value 43.00 Bremerton-Silverdale WA Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 52 © SMS July 2017 Mac_D 4.00 31 or more days Days on Maui County Value Kona_D Label Days on Maui County Days in Kona Value Standard Type Numeric Label Days on Kona Attributes Standard Format F8.2 Type Numeric Attributes Mac1 Format F8.2 Days on Maui Cty Category Value Big_D Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 53 © SMS July 2017 Molo2 O‘ahud Days on Molokai Value O‘ahu Day Trip Value Label Molokai Label O‘ahu one day or less Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 1.00 ....Day Trip Labeled Values Mauid 2.00 ....2 or more Maui Day Trip Value Lani2 Label Maui one day or less Standard Days on Lāna‘i Value Type Numeric Label Lāna‘i Attributes Standard Format F8.2 Type Numeric Attributes Format F8.2 Molod 1.00 ....Day Trip Molokai Day Trip Value Labeled Values 2.00 ....2 or more Label Molokai one day or less Standard Type Numeric Mac2 Attributes Days on Maui County Value Format F8.2 Label Maui County Lanid Standard Type Numeric Lāna‘i Day Trip Value Attributes Format F8.2 Label Lāna‘i one day or less Standard 1.00 ....Day Trip Type Numeric Labeled Values Attributes 2.00 ....2 or more Format F8.2 Kaua‘i 2 Macd Days on Kaua‘i Value Maui County Day Trip Value Label Kaua‘i Standard Maui County one day or Type Numeric Label Attributes Standard less Format F8.2 Attributes Type Numeric 1.00 ....Day Trip Labeled Values Format F8.2 2.00 ....2 or more Kaua‘i d BIG2 Kaua‘i Day Trip Value Days on Hawai‘i Island Value Label Kaua‘i one day or less Label Big Island Standard Standard Type Numeric Type Numeric Attributes Attributes Format F8.2 Format F8.2 1.00 ....Day Trip BIGd Labeled Values 2.00 ....2 or more Hawai‘i Island Day Trip Value Hilo2 Label Big Island one day or less Standard Type Numeric Days in Hilo Value Attributes Label Hilo Format F8.2 Standard Type Numeric Attributes res_d Format F8.2 Rtn. Resident Days Away Value 1.00 ....Day Trip Returning resident # of Labeled Values Label 2.00 ....2 or more Standard days away Kona2 Attributes Type Numeric Days in Kona Value Format F8.2 Label Kona Standard q13sum Type Numeric Attributes Scratch variable Value Format F8.2 Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 54 © SMS July 2017 Males 13 to 17 Value Format F8.2 Label Males 13 to 17 Standard Type Numeric allages Attributes Format F8.2 All Ages Value Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 55 © SMS July 2017 Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 56 © SMS July 2017 6.00 Big Island Kaua‘i_vd 7.00 Maui Visitor Days Kaua‘i Value 8.00 Molokai Label Visitor days Kaua‘i 9.00 Lāna‘i Standard Type Numeric Attributes 10.00 Kaua‘i Format F8.2 11.00 Military Base hilo_vd 99.00 Unknown Visitor Days Hilo Value zipoa Label Visitor days Hilo O‘ahu Zipcode Value Standard Type Numeric Label O‘ahu Attributes Standard Format F8.2 Type Numeric Attributes kona_vd Format F8.2 Visitor Days Kona Value Labeled Values 1.00 O‘ahu Label Visitor days Kona rres Standard Type Numeric Returning Resident Value Attributes Label Returning Resident Format F8.2 Standard Type Numeric total_vd Attributes Format F8.2 Visitor Days Total Value Labeled Values 1.00 Returning Resident Label Visitor days Total Standard ires Type Numeric Attributes Intended Resident Value Format F8.2 Label Intended Resident Standard big_vd Type Numeric Attributes Visitor Days BI Value Format F8.2 Label Visitor days Big Isle Labeled Values 1.00 Intended Resident Standard Type Numeric POT Attributes Format F8.2 Scratch variable Value mac_vd Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 57 © SMS July 2017 Purpose: Convention 5.00 Six or more Visited HCC and had 2.00 vsatisle Other Purpose of Trip O‘ahu, NI, or Both Value Did not visit HCC, but Label Island Visitation 3.00 Standard Purpose was Convention Type Numeric Did not visit HCC, had Attributes 4.00 Format F8.2 other Purpose of Trip 1.00 O‘ahu Only s elf 2.00 Neighbor Island Only Labeled Values Age of Party Head Value Neighbor Island Plus 3.00 Label Age of party head O‘ahu Standard Type Numeric Attributes ttl Format F8.2 Scratch variable Value 1.00 0-12 Label Total Standard 2.00 13-17 Type Numeric Attributes 3.00 18-24 Format F8.2 Labeled Values 4.00 25-40 Labeled Values 1.00 5.00 41-59 tatpak 6.00 60+ TAT Pkg or Not Value ptycomp1 Label TATPAK Standard Type Numeric Adults with Kids Value Attributes Adults traveling with Format F8.2 Label 1.00 Pak Standard children Attributes Type Numeric Labeled Values 2.00 TAT Format F8.2 3.00 Non-TAT ptycomp2 w_ni Elderly Party Members Value NI Weight Value Visited NI for EXP Label All members over 60 Label Standard Standard weights Type Numeric Attributes Attributes Type Numeric Format F8.2 Format F8.2 ptycomp3 .00 O‘ahu only Labeled Values Single Male Value 1.00 Neighbor island Label Single male Standard w_nio Type Numeric Attributes NI Only Weight Value Format F8.2 Visited NI ONLY for EXP Label ptycomp4 Standard weights Single Female Value Attributes Type Numeric Label Single female Format F8.2 Standard .00 O‘ahu Type Numeric Labeled Values Attributes 1.00 Neighbor island only Format F8.2 vd ptycomp5 Visitor Days Value Total # of Adults Value Label
Visitor Days Weight Value ps_r Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 58 © SMS July 2017 Labeled Values 1.00 1 Newfoundland and 5.00 Y ear Labrador Visit Year Value 6.00 Northwest Territories Label
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 59 © SMS July 2017 Label Tohoku Format F8.2 Standard Type Numeric Attributes jkanto Format F8.2 Kanto Regions Value 1.00 Aichi Label Kanto Standard 2.00 Akita Type Numeric Attributes 3.00 Aomori Format F8.2 4.00 Chiba 1.00 Aichi 5.00 Ehime 2.00 Akita 6.00 Fukui 3.00 Aomori 7.00 Fukuoka 4.00 Chiba 8.00 Fukushima 5.00 Ehime 9.00 Gifu 6.00 Fukui 10.00 Gumma 7.00 Fukuoka 11.00 Hiroshima 8.00 Fukushima 12.00 Hokkaido 9.00 Gifu 13.00 Hyogo 10.00 Gumma 14.00 Ibaragi 11.00 Hiroshima 15.00 Ishikawa 12.00 Hokkaido 16.00 Iwate 13.00 Hyogo 17.00 Kagawa 14.00 Ibaragi 18.00 Kagoshima 15.00 Ishikawa 19.00 Kanagawa 16.00 Iwate 20.00 Kochi 17.00 Kagawa 21.00 Kumamoto 18.00 Kagoshima 22.00 Kyoto 19.00 Kanagawa 23.00 Mie 20.00 Kochi Valid Values 24.00 Miyagi 21.00 Kumamoto 25.00 Miyazaki 22.00 Kyoto 26.00 Nagano 23.00 Mie 27.00 Nagasaki Labeled Values 24.00 Miyagi 28.00 Nara 25.00 Miyazaki 29.00 Nigata 26.00 Nagano 30.00 Oita 27.00 Nagasaki 31.00 Okayama 28.00 Nara 32.00 Okinawa 29.00 Nigata 33.00 Osaka 30.00 Oita 34.00 Saga 31.00 Okayama 35.00 Saitama 32.00 Okinawa 36.00 Shiga 33.00 Osaka 37.00 Shimane 34.00 Saga 38.00 Shizuoka 35.00 Saitama 39.00 Tochigi 36.00 Shiga 40.00 Tokushima 37.00 Shimane 41.00 Tokyo 38.00 Shizuoka 42.00 Tottori 39.00 Tochigi 43.00 Toyama 40.00 Tokushima 44.00 Wakayama 41.00 Tokyo 45.00 Yamagata 42.00 Tottori 46.00 Yamaguchi 43.00 Toyama 47.00 Yamanashi 44.00 Wakayama jjkan to 45.00 Yamagata Total Kanto Value 46.00 Yamaguchi Standard Label Total Kanto 47.00 Yamanashi Attributes Type Numeric jjchubu
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 60 © SMS July 2017 TotalChubu Value 46.00 Yamaguchi Label Total Chubu 47.00 Yamanashi Standard Type Numeric jjkinki Attributes Format F8.2 Total Kinki Value j chubu Label Total Kinki Standard Type Numeric Chubu Regions Value Attributes Label Chubu Format F8.2 Standard Type Numeric Attributes Format F8.2 jkinki 1.00 Aichi Kinki Regions Value 2.00 Akita Label Kinki Standard 3.00 Aomori Type Numeric Attributes 4.00 Chiba Format F8.2 5.00 Ehime 1.00 Aichi 6.00 Fukui 2.00 Akita 7.00 Fukuoka 3.00 Aomori 8.00 Fukushima 4.00 Chiba 9.00 Gifu 5.00 Ehime 10.00 Gumma 6.00 Fukui 11.00 Hiroshima 7.00 Fukuoka 12.00 Hokkaido 8.00 Fukushima 13.00 Hyogo 9.00 Gifu 14.00 Ibaragi 10.00 Gumma 15.00 Ishikawa 11.00 Hiroshima 16.00 Iwate 12.00 Hokkaido 17.00 Kagawa 13.00 Hyogo 18.00 Kagoshima 14.00 Ibaragi 19.00 Kanagawa 15.00 Ishikawa 20.00 Kochi 16.00 Iwate 21.00 Kumamoto 17.00 Kagawa 22.00 Kyoto 18.00 Kagoshima Labeled Values 23.00 Mie 19.00 Kanagawa 24.00 Miyagi 20.00 Kochi 21.00 Kumamoto 25.00 Miyazaki Labeled Values 26.00 Nagano 22.00 Kyoto 27.00 Nagasaki 23.00 Mie 28.00 Nara 24.00 Miyagi 29.00 Nigata 25.00 Miyazaki 30.00 Oita 26.00 Nagano 31.00 Okayama 27.00 Nagasaki 32.00 Okinawa 28.00 Nara 33.00 Osaka 29.00 Nigata 34.00 Saga 30.00 Oita 35.00 Saitama 31.00 Okayama 36.00 Shiga 32.00 Okinawa 37.00 Shimane 33.00 Osaka 38.00 Shizuoka 34.00 Saga 39.00 Tochigi 35.00 Saitama 40.00 Tokushima 36.00 Shiga 41.00 Tokyo 37.00 Shimane 42.00 Tottori 38.00 Shizuoka 43.00 Toyama 39.00 Tochigi 44.00 Wakayama 40.00 Tokushima 45.00 Yamagata 41.00 Tokyo 42.00 Tottori
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 61 © SMS July 2017 43.00 Toyama 40.00 Tokushima 44.00 Wakayama 41.00 Tokyo 45.00 Yamagata 42.00 Tottori 46.00 Yamaguchi 43.00 Toyama 47.00 Yamanashi 44.00 Wakayama jjchugok 45.00 Yamagata Total Chugoku Value 46.00 Yamaguchi Label Total Chugoku 47.00 Yamanashi Standard Type Numeric jjshikok Attributes Format F8.2 Total Shikoku Value jchugoku Label Total Shikoku Standard Type Numeric Chugoku Regions Value Attributes Label Chugoku Format F8.2 Standard Type Numeric Attributes jshikoku Format F8.2 Shikoku Regions Value 1.00 Aichi Label Shikoku Standard 2.00 Akita Type Numeric Attributes 3.00 Aomori Format F8.2 4.00 Chiba 1.00 Aichi 5.00 Ehime 2.00 Akita 6.00 Fukui 3.00 Aomori 7.00 Fukuoka 4.00 Chiba 8.00 Fukushima 5.00 Ehime 9.00 Gifu 6.00 Fukui 10.00 Gumma 7.00 Fukuoka 11.00 Hiroshima 8.00 Fukushima 12.00 Hokkaido 9.00 Gifu 13.00 Hyogo 10.00 Gumma 14.00 Ibaragi 11.00 Hiroshima 15.00 Ishikawa 12.00 Hokkaido 16.00 Iwate 13.00 Hyogo 17.00 Kagawa 14.00 Ibaragi 18.00 Kagoshima 15.00 Ishikawa 19.00 Kanagawa 16.00 Iwate Valid Values 20.00 Kochi 17.00 Kagawa 21.00 Kumamoto 18.00 Kagoshima Valid Values 22.00 Kyoto 19.00 Kanagawa 23.00 Mie 20.00 Kochi 24.00 Miyagi 21.00 Kumamoto 25.00 Miyazaki 22.00 Kyoto 26.00 Nagano 23.00 Mie 27.00 Nagasaki 24.00 Miyagi 28.00 Nara 25.00 Miyazaki 29.00 Nigata 26.00 Nagano 30.00 Oita 27.00 Nagasaki 31.00 Okayama 28.00 Nara 32.00 Okinawa 29.00 Nigata 33.00 Osaka 30.00 Oita 34.00 Saga 31.00 Okayama 35.00 Saitama 32.00 Okinawa 36.00 Shiga 33.00 Osaka 37.00 Shimane 34.00 Saga 38.00 Shizuoka 35.00 Saitama 39.00 Tochigi 36.00 Shiga
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 62 © SMS July 2017 37.00 Shimane 34.00 Saga 38.00 Shizuoka 35.00 Saitama 39.00 Tochigi 36.00 Shiga 40.00 Tokushima 37.00 Shimane 41.00 Tokyo 38.00 Shizuoka 42.00 Tottori 39.00 Tochigi 43.00 Toyama 40.00 Tokushima 44.00 Wakayama 41.00 Tokyo 45.00 Yamagata 42.00 Tottori 46.00 Yamaguchi 43.00 Toyama 47.00 Yamanashi 44.00 Wakayama jjkyush 45.00 Yamagata Total Kyushu Value 46.00 Yamaguchi Label Total Kyushu 47.00 Yamanashi Standard Type Numeric Attributes Format F8.2 jjhokaid jkyushu Total Hokido Value Label Total Hokaido Kyushu Regions Value Standard Label Kyushu Type Numeric Standard Attributes Type Numeric Format F8.2 Attributes Format F8.2 jjokinaw 1.00 Aichi Total Okinawa Value 2.00 Akita Label Total Okinawa Standard 3.00 Aomori Type Numeric Attributes 4.00 Chiba Format F8.2 5.00 Ehime visitor2 6.00 Fukui Type of Traveler Value 7.00 Fukuoka Label Type of traveler Standard 8.00 Fukushima Type Numeric Attributes 9.00 Gifu Format F8.2 10.00 Gumma 1.00 Visitor Labeled Values 11.00 Hiroshima 2.00 Resident 12.00 Hokkaido 13.00 Hyogo 14.00 Ibaragi 15.00 Ishikawa 16.00 Iwate Valid Values 17.00 Kagawa 18.00 Kagoshima 19.00 Kanagawa 20.00 Kochi 21.00 Kumamoto 22.00 Kyoto 23.00 Mie 24.00 Miyagi 25.00 Miyazaki 26.00 Nagano 27.00 Nagasaki 28.00 Nara 29.00 Nigata 30.00 Oita 31.00 Okayama 32.00 Okinawa 33.00 Osaka
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 63 © SMS July 2017 APPENDIX C: VALUES OF GENERATED VARIABLES
Island visitation variables numisle number of islands visited islesum1 sum(oahu, maui, molokai, lanai, kona, hilo, kauai). oahu, maui, molokai, lanai, kona, hilo, kauai LOS in the island oa, ka, ma, mo, la, bi, ko, hi island visitation indicator (1 or 0) mcounty indicator for visiting Maui couty nisle indicator for visiting a neighbor island oao, kao, mao, moo, lao, bio, biho, biko, mco one island only indicators Islands Number of islands visited
Length of stay variables isletot , sum2, isleadd sum(q5b1, q5b2, q5b3, q5b4, q5b5, q5b6, q5b7). dif2 q3a-sum2 total q3a oahu1, manui1, molo1, Lani1, kauai1, hilo1, kona1, big1, total_1 island LOS categories mac1 maui county LOS oahu2, manui2, molo2, Lani2, kauai2, hilo2, kona2, big2, total_2 indicator of one day trip (1) or more days (2) oahuD, manuiD, moloD, LaniD, kauaiD, hiloD, konaD, bigD, total_D indicator of one day or less (1) dayoa, dayma, daymo, dayla, dayko, dayhi, dayka indicator of day-trippers (1) res_d returning residents # days away islesum sum(oahu, maui, molokai, lanai, hilo, kona, kauai). oahu_vd. Maui_vd, molo_vd, lanai_vd, Kauai_vd, hilo_vd, kona_vd, total_vd, big_vd, mac_vd visitor days
Accomodation variables accom count of accomodations hotel, condo, rhouse, timeshare, cruise, friendacc, bedb indicator of accommodation (1 or 0) otheracc other accommodation, hostel, camp hotcon hotel and condo hotelo condoo tshareo rentalo one accommodation indicators
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 64 © SMS July 2017 Purpose of trips variables honey, married, vacation, convention, meeting, incentive indicator of purpose of trip pleasure honeymoon, wedding, or vacation honeywed honeymoon or wedding mci meeting, convention or incentive
Other Misc variables use for HL and banners NumTrips Number of trips to Hawaii numtrip2 First trip (1) or Second or more trips (2)
RptVisit Frist time or repeat visitors (1 or 2)
Group indicator of group tour (1 or 2) Package indicator of package tour (1 or 2) BothGP indicator of group and package trip (1) indep True indepndent (not group and not package)
TotalX WB record (1) Visitor WB visitor (1) visitor3 type of visitor (Q2)
prtytype type of party 0 'Unknown' 1 'Single' 2 'Couple' 3 'Young Couple' 4 'Couple, 40 to 59 years old' 5 'Couple, Seniors' 6 'Family with young children' 7 'Family with teenagers' 8 'PS = 3 or 4, no kids' 9 'Large Party (5+ members)' type2 type of party 1 ' ' 3 'Young Couple' 4 'Couple, 40 to 59 years old' 5 'Couple, Seniors' 6 'Couple, unknown age'. portx Port of entry … 1 "Oahu" 2 "Maui" 3 "Kona" 4 "Kauai" 5 "Hilo".
US States and Regions State 2-char state code from Zipcode file matched with data using Zipcode var NumState numeric State code ("AK"=1) ("CA" = 2 ) ("OR" =3) ("WA"= 4) ("AZ"= 5) ( "CO" = 6 ) ("ID"=7) ("MT" = 8 ) ("NV" =9) ("NM"= 10) ("UT"= 11) ( "WY" = 12 ) ("IA" =13) ("KS" = 14) ("MN" =15) ("MO"= 16) ("NE"= 17) ( "ND" = 18 ) ("SD"=19) ("AR" = 20) ("LA" =21) ("OK"= 22) ("TX"= 23) ( "IL" = 24 ) ("IN" = 25) ("MI" = 26 ) ("OH"=27) ("WI"= 28) ("NJ"= 29) ( "NY" = 30 ) ("PA"= 31) ("CT" = 32) ("ME"=33) ("MA"= 34) ("NH"= 35) ( "RI" = 36 ) ("VT"= 37) ( "AL" = 38) ("KY"=39) ("MS"= 40) ("TN"= 41) ( "DC" = 42 ) ("DE"=43) ( "FL" = 44) ("GA"=45) ("MD"= 46) ("NC"= 47) ( "SC" = 48 ) ("VA"=49) ( "WV"= 50) ("PR"=51) ("GU"= 52) ("HI"= 53) ("VI" = 54) USregion 1 "Pacific Region" 2 "Mountain Region" 3 "West North Central" 4 "West South Central" 5 "East North Central" 6 "Mid Atlantic" 7 "New England" 8 "East South Central" 9 "South Atlantic" USPAC 1 " Alaska" 2 " California" 3 " Oregon" 4 " Washington" USMONT 5 " Arizona" 6 " Colorado" 7 " Idaho" 8 " Montana" 9 " Nevada" 10 " New Mexico" 11 "Utah" 12 'Wyoming". USWNTH 13 " Iowa" 14 " Kansas" 15 " Minnesota" 16 " Missouri" 17 " Nebraska" 18 " N. Dakota" 19 " S. Dakota" . USWSTH 20 " Arkansas" 21 " Louisiana" 22 " Oklahoma" 23 " Texas" . HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 65 © SMSUSENC 24 " Illinois" 25 " Indiana" 26 " Michigan" 27 " Ohio" 28 " Wisconsin" . July 2017 USMA 29 " New Jersey" 30 " New York" 31 " Pennsylvania" . USNEW 32 " Connecticut" 33 " Maine" 34 " Massachusetts" 35 " New Hampshire" 36 " Rhode Island" 37 " Vermont" . USESC 38 " Alabama" 39 " Kentucky" 40 " Mississippi" 41 " Tennessee". USSA 42 " Washington D.C." 43 " Delaware" 44 " Florida" 45 " Georgia" 46 " Maryland" 47 " N. Carolina" 48 " S. Carolina" 49 " Virginia" 50 " West Virginia" . USTa 1 " Guam" 2 " Puerto Rico" 3 " Virgn Islands". Pac, MONT, WNRTH, WS, ENC, MARG, NEWE, ESC, SA, USTa indicator of US region (1) numstate 1 " Alaska" 2 " California" 3 " Oregon" 4 " Washington" 5 " Arizona" 6 " Colorado" 7 " Idaho" 8 " Montana" 9 " Nevada" 10 " New Mexico" 11 "Utah" 12 "Wyoming" 13 " Iowa" 14 " Kansas" 15 " Minnesota" 16 " Missouri" 17 "Nebraska" 18 "n. Dakota" 19 'S. Dakota" 20 "Arkansas" 21 " Louisiana" 22 "Oklahoma" 23 "Texas" 24 " Illinois" 25 " Indiana" 26 " Michigan" 27 " Ohio" 28 " Wisconsin" 29 " New Jersey" 30 " New York" 31 " Pennsylvania" 32 "Connecticut" 33 "Maine" 34 " Massachusetts" 35 " New Hampshire" 36 " Rhode Island" 37 " Vermont" 38 " Alabama" 39 " Kentucky" 40 " Mississippi" 41 " Tennessee" 42 " D.C." 43 " Delaware" 44 " Florida" 45 " Georgia" 46 " Maryland" 47 " N. Carolina" 48 " S. Carolina" 49 " Virginia" 50 " West Virginia" 51 " Puerto Rico" 52 " Guam" 53 " Hawaii" 54 "Virgin Islands".
US States and Regions State 2-char state code from Zipcode file matched with data using Zipcode var NumState numeric State code ("AK"=1) ("CA" = 2 ) ("OR" =3) ("WA"= 4) ("AZ"= 5) ( "CO" = 6 ) ("ID"=7) ("MT" = 8 ) ("NV" =9) ("NM"= 10) ("UT"= 11) ( "WY" = 12 ) ("IA" =13) ("KS" = 14) ("MN" =15) ("MO"= 16) ("NE"= 17) ( "ND" = 18 ) ("SD"=19) ("AR" = 20) ("LA" =21) ("OK"= 22) ("TX"= 23) ( "IL" = 24 ) ("IN" = 25) ("MI" = 26 ) ("OH"=27) ("WI"= 28) ("NJ"= 29) ( "NY" = 30 ) ("PA"= 31) ("CT" = 32) ("ME"=33) ("MA"= 34) ("NH"= 35) ( "RI" = 36 ) ("VT"= 37) ( "AL" = 38) ("KY"=39) ("MS"= 40) ("TN"= 41) ( "DC" = 42 ) ("DE"=43) ( "FL" = 44) ("GA"=45) ("MD"= 46) ("NC"= 47) ( "SC" = 48 ) ("VA"=49) ( "WV"= 50) ("PR"=51) ("GU"= 52) ("HI"= 53) ("VI" = 54) USregion 1 "Pacific Region" 2 "Mountain Region" 3 "West North Central" 4 "West South Central" 5 "East North Central" 6 "Mid Atlantic" 7 "New England" 8 "East South Central" 9 "South Atlantic" USPAC 1 " Alaska" 2 " California" 3 " Oregon" 4 " Washington" USMONT 5 " Arizona" 6 " Colorado" 7 " Idaho" 8 " Montana" 9 " Nevada" 10 " New Mexico" 11 "Utah" 12 'Wyoming". USWNTH 13 " Iowa" 14 " Kansas" 15 " Minnesota" 16 " Missouri" 17 " Nebraska" 18 " N. Dakota" 19 " S. Dakota" . USWSTH 20 " Arkansas" 21 " Louisiana" 22 " Oklahoma" 23 " Texas" . USENC 24 " Illinois" 25 " Indiana" 26 " Michigan" 27 " Ohio" 28 " Wisconsin" . USMA 29 " New Jersey" 30 " New York" 31 " Pennsylvania" . USNEW 32 " Connecticut" 33 " Maine" 34 " Massachusetts" 35 " New Hampshire" 36 " Rhode Island" 37 " Vermont" . USESC 38 " Alabama" 39 " Kentucky" 40 " Mississippi" 41 " Tennessee". USSA 42 " Washington D.C." 43 " Delaware" 44 " Florida" 45 " Georgia" 46 " Maryland" 47 " N. Carolina" 48 " S. Carolina" 49 " Virginia" 50 " West Virginia" . USTa 1 " Guam" 2 " Puerto Rico" 3 " Virgn Islands". Pac, MONT, WNRTH, WS, ENC, MARG, NEWE, ESC, SA, USTa indicator of US region (1) numstate 1 " Alaska" 2 " California" 3 " Oregon" 4 " Washington" 5 " Arizona" 6 " Colorado" 7 " Idaho" 8 " Montana" 9 " Nevada" 10 " New Mexico" 11 "Utah" 12 "Wyoming" 13 " Iowa" 14 " Kansas" 15 " Minnesota" 16 " Missouri" 17 "Nebraska" 18 "n. Dakota" 19 'S. Dakota" 20 "Arkansas" 21 " Louisiana" 22 "Oklahoma" 23 "Texas" 24 " Illinois" 25 " Indiana" 26 " Michigan" 27 " Ohio" 28 " Wisconsin" 29 " New Jersey" 30 " New York" 31 " Pennsylvania" 32 "Connecticut" 33 "Maine" 34 " Massachusetts" 35 " New Hampshire" 36 " Rhode Island" 37 " Vermont" 38 " Alabama" 39 " Kentucky" 40 " Mississippi" 41 " Tennessee" 42 " D.C." 43 " Delaware" 44 " Florida" 45 " Georgia" 46 " Maryland" 47 " N. Carolina" 48 " S. Carolina" 49 " Virginia" 50 " West Virginia" 51 " Puerto Rico" 52 " Guam" 53 " Hawaii" 54 "Virgin Islands".
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 66 © SMS July 2017 Countries Can indicator of Canada (1) Province 1 " British Columbia" 2 " Alberta" 3 " Saskatchewan" 4 " Manitoba" 5 "Ontario" 6 " Quebec" 7 " Maritime Provinces" 8 " Northwest Territories" 9 " Yukon Territories". Euro indicator of Europe (1) europe 1 " U.K." 2 " Germany" 3 " France" 4 " Italy" 5 " Switzerland" 6 " Norway" 7 " Sweden" 8 " Denmark" 9 " Finland" 10 " Austria" 11 " Belgium" 12 " Ireland" 13 " Spain" 14 " Netherlands" 15 " Russia" 16 " Other Europe". asia indicator of Asia (1) asctry 1 "Japan" 2 "Korea" 3 "China" 4 "Taiwan" 5 "Hong Kong" 6 "Indonesia" 7 "Philippines" 8 " Singapore" 9 " Thailand" 10 " Malaysia" 11 " India" 12 " Other Asia" CAmerica indicator of Central America (1) Central 1 " Costa Rica" 2 " El Salvador" 3 " Guatamala" 4 " Honduras" 5 " Panama" 6 " Mexico" 7 "Nicaragua" 8 " Other Central America" SAmerica indicator of South america (1) South 1 " Argentina" 2 " Bolivia" 3 " Brazil" 4 " Chile" 5 " Colombia" 6 " Ecuador" 7 " Peru" 8 " Uruguay" 9 " Paraguay" 10 " Venezuela" 11 "Other South America" Carib indicator of Caribbean (1) Caribb 1 " Caribbean" 2 " Bahamas" 3 " Barbados" 4 " Bermuda" 5 " Jamaica" 6 " Dominican Republican" 7 " Haiti" 8 " Other West Indies" oceania indicator of Oceania (1) Occtry 1 ' Australia' 2 ' New Zealand' 3 ' American Samoa' 4 ' Western Samoa' 5 ' Tahiti' 6 ' Fiji' 7 ' Other Oceania and Pacific Islands'. Africa indicator of Africa (1) middle indicator of Middle East (1) US indicator of USA (1) Cana indicator of Canada (1) FORE indicator of Other foreign country (1) 1 "United States Mainland &Territories" 2 "Other US, unknown zip" 3 "Other US-APO" 4 "Canada" 5 "Other Foreign" 6 CON "Other Foreign (unknown origin)"
MMA CONus 1 'United States of America' HTAus 1 'US West (Pacific/Mountain)' 2 'US East'. HTAeur 1 ' United Kingdom' 2 ' France' 3 ' Germany' 4 ' Italy' 5 ' Switzerland' HTAeurT Europe total HTAjapan 1 'Japan' HTAasia 1 ' Taiwan' 2 ' Hong Kong' 3 ' Korea' 4 ' China' 5 ' Singapore'. HTAasiaT Asia total HTAlatam 1 ' Mexico' 2 ' Brazil' 3 ' Argentina' . HTAlataT Latin America total HTAnz 1 'Australia' 2 'New Zealand'. HTAnzT Oceania total HTAother 1 'Other'.
HTA BDS Domestic In-Flight Survey Documentation Report 2016 Page 67 © SMS July 2017