Combining Disparate Surveys across Time to Study Satisfaction with Life

In 2011, the United Nations General Assembly passed a resolution recognizing happiness and well-being as a fundamental human goal, and followed this up in 2013 by establishing an official International Day of Happiness. These actions attracted much attention from the international community, and especially from those within academia, generating a surge of popular news and academic pieces on well-being and its variants. However, psychologists and social scientists have been studying happiness and subjective well-being (SWB) for decades based on large-scale longitudinal surveys. large-scale longitudinal studies have allowed researchers to model the effects of general variables such as demographic characteristics, and selected values and behaviors on SWB. However, because these longitudinal surveys are broad in nature, they do not facilitate the examination of SWB within specific contexts or with the help of more diverse explanatory variables. As a result, researchers within assorted fields have taken to studying SWB using cross-sectional surveys, which are more commonly available and facilitate investigation from specific perspectives (e.g., effects of health, occupation, etc. on well-being). A number of scholars have used cross-sectional surveys to examine the impacts of transportation, especially commuting, on well-being (Mokhtarian, 2019, De Vos et al., 2013; Dickerson et al., 2014; Lorenz, 2018; Martin et al., 2014; Smith, 2017; Sweet and Kanaroglou, 2016). In this proposed study, the research team plans to combine the longitudinal and cross-sectional approaches to studying well-being, creating a fused dataset that includes common variables from five travel-behavior-oriented cross-sectional surveys conducted across a 27-year period. The PI of this study was heavily involved in all five of these surveys, while a co-PI was heavily involved in the most recent three. Accordingly, each survey includes an identical SWB question, as well as numerous other common variables across the individual datasets. Since these surveys were originally designed to serve travel behavior modeling purposes, the development of this fused dataset will allow a unique examination of SWB within a transportation context. This project aims to (1) combine the common variables from multiple surveys conducted across a range of times (nearly 30 years) and places (within California) to obtain a large repeated cross-sectional sample; (2) use the combined sample to analyze changes in self-reported subjective well-being (satisfaction with life) across time and differences related to geography and demography; (3) assess the influence of transportation-related variables on subjective well-being; and (4) assess whether respondents recruited via commercial online opinion panels are notably different in their satisfaction with life than other, more randomly-sampled, respondents.

    Language

    • English

    Project

    • Status: Active
    • Funding: $164249
    • Contract Numbers:

      69A3551747116

    • Sponsor Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      Center for Teaching Old Models New Tricks

      Arizona State University
      Tempe, AZ  United States  85287
    • Performing Organizations:

      Georgia Institute of Technology, Atlanta

      School of Civil and Environmental Engineering
      790 Atlantic Drive
      Atlanta, GA  United States  30332-0355
    • Principal Investigators:

      Mokhtarian, Patricia

      Circella, Giovanni

      Watkins, Kari

    • Start Date: 20191001
    • Expected Completion Date: 20211001
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers Program

    Subject/Index Terms

    Filing Info

    • Accession Number: 01754996
    • Record Type: Research project
    • Source Agency: Center for Teaching Old Models New Tricks
    • Contract Numbers: 69A3551747116
    • Files: UTC, RiP
    • Created Date: Oct 20 2020 7:50PM