A Copula-Based Sample Selection Model of Telecommuting Choice and Frequency

Abstract

The objective of this study is to contribute to the telecommuting literature by jointly examining the propensity and frequency of workers to telecommute, using a rich set of individual demographics, work-related and industry characteristics, household demographics, and commute trip/work location characteristics. The data are drawn from the Chicago Regional Household Travel Inventory, collected between 2007 and 2008. From a methodological standpoint, the current study adopts a copula approach that allows the testing of several types of dependency structures between the telecommuting choice and frequency behavioural processes. To our knowledge, this is the first formulation and application in the econometric literature of a copula approach for the case of a binary self-selection mechanism with an ordered-response outcome.The results clearly indicate that telecommuting choice and the frequency of telecommuting are governed by quite different underlying behavioral processes. For instance, women are less likely to telecommute relative to men, though there is no statistically significant difference in telecommuting frequency propensity between men and women telecommuters. Similarly, full-time employed individuals (≥ 30 hours per week) are more likely to have a telecommuting arrangement than those working part-time (< 30 hours per week). However, among those who telecommute, fulltime employed individuals telecommute less frequently than part-time employed individuals.Further, the results suggest that the analyst risks the danger of incorrect conclusions regarding dependency in the telecommuting choice and frequency behavioral processes, as well as inconsistent and inefficient parameter estimates, by imposing incorrect dependency structures or assuming independence between the two behavioral processes. Overall, the empirical results indicate the important effects of several demographic and work-related variables on telecommuting choice and frequency, with implications for transportation planning and transportation policy analysis.

On modeling telecommuting behavior: option, choice, and frequency

“…Individuals who have a flexible work start time are not only more likely to have the option to telecommute, but also more likely to choose to telecommute given the option (see Walls et al, 2007, andSener andBhat, 2010). Indeed, the effect of flexible work start time on having the option to telecommute is strong and highly statistically significant.…”

“…Indeed, the effect of flexible work start time on having the option to telecommute is strong and highly statistically significant. As suggested by Sener and Bhat (2010), individuals who value work flexibility will look for jobs that can provide them both temporal (work timing) and spatial (work location) flexibility. Our results here more directly support this hypothesis, because we model the "option" dimension explicitly, while Sener and Bhat (2010) could only speculate based on the effects of education on the "choice" and "frequency" dimensions.…”

The impact of the residential built environment on work at home adoption frequency: An example from Northern California

“…To our knowledge, only two studies (Popuri and Bhat 2003;Sener and Bhat 2010) have modeled the two decisions as separate but joint choices, while others have modeled them either together as one single choice or as unconnected choices. Table 6 compares the single-choice and two-choice approaches to modeling adoption and frequency.…”

On the Impacts of Telecommuting over Daily Activity/Travel Behavior: A Comprehensive Investigation through Different Telecommuting Patterns

“…In order to resolve this issue, some researchers suggested using the number of telecommuting days (either per week or per month) as a frequency index rather than ad hoc discrete categories (Popuri & Bhat, 2003;Sener & Bhat, 2011;Singh et al, 2012). Also, researchers did not distinguish between home-based workers (those who do not have or need a conventional office rather than home) and real telecommuters (those who have a fixed office but telecommute regularly).…”

“…Also, researchers did not distinguish between home-based workers (those who do not have or need a conventional office rather than home) and real telecommuters (those who have a fixed office but telecommute regularly). Hence, application of large sample sizes, usually at the national or statewide level (Drucker & Khattak, 2000;Yen, 2000;Popuri & Bhat, 2003;Wernick, 2004;Walls et al, 2006;Zhou, 2008;Sener & Bhat, 2011;Singh et al, 2012), along with providing clear definitions of telecommuters and their subcategories, could be named as major enhancements of models in the research background.…”