[Paper Review] On the Factors Influencing the Choices of Weekly Telecommuting Frequencies of Post-secondary Students in Toronto

Khandker Nurul Habib, Ph. D.+1 more|arXiv (Cornell University)|Apr 9, 2020

Advanced MIMO Systems Optimization3 citations

TL;DR

This study investigates factors influencing weekly telecommuting frequency among post-secondary students in Toronto using a large-scale travel survey and multiple econometric models. It finds that 80% of students telecommute at least once a week, with car ownership and greater distance from campus increasing telecommuting frequency, while bicycle use is associated with the lowest likelihood of telecommuting.

ABSTRACT

The paper presents an empirical investigation of telecommuting frequency choices by post-secondary students in Toronto. It uses a dataset collected through a large-scale travel survey conducted on post-secondary students of four major universities in Toronto and it employs multiple alternative econometric modelling techniques for the empirical investigation. Results contribute on two fronts. Firstly, it presents empirical investigations of factors affecting telecommuting frequency choices of post-secondary students that are rare in literature. Secondly, it identifies better a performing econometric modelling technique for modelling telecommuting frequency choices. Empirical investigation clearly reveals that telecommuting for school related activities is prevalent among post-secondary students in Toronto. Around 80 percent of 0.18 million of the post-secondary students of the region, who make roughly 36,000 trips per day, also telecommute at least once a week. Considering that large numbers of students need to spend a long time travelling from home to campus with around 33 percent spending more than two hours a day on travelling, telecommuting has potential to enhance their quality of life. Empirical investigations reveal that car ownership and living farther from the campus have similar positive effects on the choice of higher frequency of telecommuting. Students who use a bicycle for regular travel are least likely to telecommute, compared to those using transit or a private car.

Motivation & Objective

• To identify socioeconomic and geographic factors affecting telecommuting frequency among post-secondary students in Toronto.
• To assess the impact of commuting mode, travel time, and residential proximity on telecommuting behavior.
• To evaluate the performance of different econometric models in predicting telecommuting frequency choices.
• To contribute empirical evidence on telecommuting patterns in higher education, a topic underexplored in transportation literature.

Proposed method

• Utilized a large-scale travel survey dataset from four major universities in Toronto.
• Applied multiple alternative econometric modeling techniques to analyze discrete choice behavior in telecommuting frequency.
• Employed models such as ordered probit and negative binomial regression to handle count data on weekly telecommuting trips.
• Controlled for variables including distance from campus, car ownership, and primary commuting mode.
• Used statistical inference to compare model fit and select the best-performing model for telecommuting frequency prediction.
• Analyzed the marginal effects of key predictors on telecommuting frequency using estimated coefficients.

Experimental results

Research questions

• RQ1 What factors significantly influence the frequency with which post-secondary students in Toronto telecommute?
• RQ2 How does distance from campus affect the likelihood of higher telecommuting frequency?
• RQ3 What is the role of car ownership in shaping telecommuting behavior among university students?
• RQ4 How do different commuting modes (e.g., transit, bicycle, private car) relate to telecommuting frequency?
• RQ5 Which econometric model performs best in predicting telecommuting frequency among students?

Key findings

• Approximately 80% of post-secondary students in Toronto telecommute at least once per week, with around 36,000 daily trips attributed to telecommuting.
• Students who own a car are significantly more likely to telecommute frequently, indicating a strong positive correlation between car ownership and telecommuting frequency.
• Greater distance from campus is associated with higher telecommuting frequency, suggesting that long commutes incentivize remote participation.
• Students who regularly use bicycles for commuting are the least likely to telecommute, compared to those using transit or private vehicles.
• The study identifies the negative binomial regression model as the best-performing econometric technique for modeling telecommuting frequency due to its superior fit with count data.
• On average, 33% of students spend over two hours per day traveling to campus, highlighting the potential quality-of-life benefits of telecommuting.