2015 Survey of Commute Patterns among Queen's University Employees

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Collins, Patricia; Agaewal, Ajay, 2019, "2015 Survey of Commute Patterns among Queen's University Employees", https://doi.org/10.5683/SP2/51LDXX, Borealis, V1, UNF:6:pgMyyuSZGPvtdP0fDoV2UA== [fileUNF]

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Description	The objective of this survey was to investigate commute patterns among Queen's employees and to assess whether transit improvements have stimulated interest and willingness among Queen's employees to take Kingston Transit to commute to work. The survey data collected here will also serve as a baseline for subsequent surveys that will assess change in commute patterns to Queen's over time. The findings from this research will offer insights to researchers interested in the impacts of public transit as population health interventions, as well as to Queen's University in terms of understanding how members of their community could make better use of a key public resource in Kingston.
Subject	Social Sciences
Keyword	Commuting, Kingston Transit, Public transit
Related Publication	Collins PA, Bowie A. “Shifting Commute Patterns of Queen’s University Employees: 2013-2017.” 2019. Kingston, ON: Queen’s University. Agarwal, Ajay, and Patricia Collins. "Opportunities and barriers to promoting public transit use in a midsize Canadian city." Canadian Journal of Urban Research, vol. 25, no. 2, 2016, p. 1+. Collins, Patricia A., and Ajay Agarwal. “Impacts of Public Transit Improvements on Ridership, and Implications for Physical Activity, in a Low-Density Canadian City.” Preventive Medicine Reports 2 (2015): 874–879. PMC. Web. 1 June 2017. Collins, Patricia A., and Ajay Agarwal. “Survey of Commute Patterns of Queen’s Employees: Preliminary Summary Report”, Queen’s University. School of Urban and Regional Planning, Kingston, Ontario, Canada.
License/Data Use Agreement	CC-BY 4.0

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	2013-2017-CommutePatterns-UserGuide.pdf Adobe PDF - 797.6 KB Published Apr 25, 2019 20 Downloads MD5: 07b187c19e088efd98ba2c08078ec959 User Guide Documentation	Preview "2013-2017-CommutePatterns-UserGuide.pdf" Access File File Access Public Download Options Adobe PDF Download Metadata Data File Citation EndNote XML RIS BibTeX
	2015-QueensCommuteSurvey-Codebook.pdf Adobe PDF - 2.2 MB Published Apr 25, 2019 7 Downloads MD5: ee978eb5d8965e04cf930d87c0c9c296 Codebook Documentation	Preview "2015-QueensCommuteSurvey-Codebook.pdf" Access File File Access Public Download Options Adobe PDF Download Metadata Data File Citation EndNote XML RIS BibTeX
	2015-QueensCommuteSurvey-SurveyInstrument.pdf Adobe PDF - 77.6 KB Published Apr 25, 2019 8 Downloads MD5: 48be90b120c294b7fccb158a53899be1 Survey Instrument Documentation	Preview "2015-QueensCommuteSurvey-SurveyInstrument.pdf" Access File File Access Public Download Options Adobe PDF Download Metadata Data File Citation EndNote XML RIS BibTeX
	2015-QueensCommuteSurveyPublic.sps SPSS Syntax - 24.6 KB Published Apr 25, 2019 4 Downloads MD5: 8b3676657d69ceebd7a14d78ad34a8c1 Syntax (command code) file Documentation	Access File File Access Public Download Options SPSS Syntax Download Metadata Data File Citation EndNote XML RIS BibTeX
	2015-QueensCommuteSurveyPublic-1.tab Tabular Data - 463.8 KB Published Apr 25, 2019 150 Downloads 101 Variables, 1963 Observations UNF:6:5NgsZ33nJGUlYrpoLY6hwg== Data file - SPSS Data	Access File File Access Public Download Options SPSS Binary (Original File Format) Tab-Delimited RData Download Metadata Variable Metadata Data File Citation EndNote XML RIS BibTeX Explore Options Data Explorer
	2015-QueensCommuteSurveyPublic.dat Fixed Field Text Data - 3.2 MB Published Apr 25, 2019 8 Downloads MD5: 7a0ae33d778bee75cb8b3bd3d0dcd16e Data file - ASCII Data	Access File File Access Public Download Options Fixed Field Text Data Download Metadata Data File Citation EndNote XML RIS BibTeX
	2015-QueensCommuteSurveyPublic.tab Tabular Data - 833.5 KB Published Apr 25, 2019 113 Downloads 101 Variables, 1963 Observations UNF:6:oc9elSywlZSE0zLM1Xee9w== Data file - CSV Data	Access File File Access Public Download Options Comma Separated Values (Original File Format) Tab-Delimited RData Download Metadata Variable Metadata Data File Citation EndNote XML RIS BibTeX Explore Options Data Explorer

Citation Metadata

Persistent Identifier	doi:10.5683/SP2/51LDXX
Publication Date	2019-04-25
Title	2015 Survey of Commute Patterns among Queen's University Employees
Author	Collins, Patricia (Queens University. Department of Geography and Planning) Agaewal, Ajay (Queens University. Department of Geography and Planning)
Point of Contact	Use email button above to contact. Data Services (Queen's University Library)
Description	The objective of this survey was to investigate commute patterns among Queen's employees and to assess whether transit improvements have stimulated interest and willingness among Queen's employees to take Kingston Transit to commute to work. The survey data collected here will also serve as a baseline for subsequent surveys that will assess change in commute patterns to Queen's over time. The findings from this research will offer insights to researchers interested in the impacts of public transit as population health interventions, as well as to Queen's University in terms of understanding how members of their community could make better use of a key public resource in Kingston.
Subject	Social Sciences
Keyword	Commuting Kingston Transit Public transit
Related Publication	Collins PA, Bowie A. “Shifting Commute Patterns of Queen’s University Employees: 2013-2017.” 2019. Kingston, ON: Queen’s University. Agarwal, Ajay, and Patricia Collins. "Opportunities and barriers to promoting public transit use in a midsize Canadian city." Canadian Journal of Urban Research, vol. 25, no. 2, 2016, p. 1+. Collins, Patricia A., and Ajay Agarwal. “Impacts of Public Transit Improvements on Ridership, and Implications for Physical Activity, in a Low-Density Canadian City.” Preventive Medicine Reports 2 (2015): 874–879. PMC. Web. 1 June 2017. Collins, Patricia A., and Ajay Agarwal. “Survey of Commute Patterns of Queen’s Employees: Preliminary Summary Report”, Queen’s University. School of Urban and Regional Planning, Kingston, Ontario, Canada.
Language	English
Producer	Collins, Patricia (Queen's University. Department of Geography and Planning) Agarwal, Ajay (Queen's University. Department of Geography and Planning)
Production Date	2014
Production Location	Queen's University. Kingston, Ontario, Canada
Distributor	Data Services (Queen's University Library) http://library.queensu.ca/search/data-statistics
Depositor	Collins, Patricia
Deposit Date	2018-10-29
Date of Collection	Start Date: 2015-11-10 ; End Date: 2015-11-27
Data Type	Survey data
Series	Commute Patterns among Queen's University Employees

Geospatial Metadata

Geographic Coverage	Canada, Ontario, Kingston
Geographic Unit	Forward Sortation Area (FSA)

Social Science and Humanities Metadata

Unit of Analysis	Individual
Universe	Queen's University employees (e.g., staff, faculty, postdoctoral fellows, adjunct professors) that had active email addresses.
Data Collector	Office of Institutional Research and Planning, Queen's University
Sampling Procedure	The objective was to establish a census of the commute patterns of all Queen's employees that reside roughly within a 100 kilometre radius of Queen's University. Based on eligible postal codes, invitations to complete the survey were issued to Queen's employees.
Collection Mode	Respondents' employee NetID was used to access the survey, and to prevent non-employees from completing it. The 2013-2016 surveys were administered using the Fluid Surveys platform; Qualtrics was used for the 2017 survey. Once access to the survey was closed, the dataset was stripped of identifying information (i.e., names and email addresses), and then passed along to the study researchers.
Response Rate	47.1% (4375 employees invited; 2059 surveys completed)

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Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Creative Commons Attribution 4.0 International License. CC-BY 4.0

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Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Creative Commons Attribution 4.0 International License. CC-BY 4.0

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