The Telecommuting Adoption Process: Conceptual Framework and Model Development
Jin-Ru Yen and Hani S. Mahmassani, University of Texas at Austin, August 1994, 186 pp.
The substitution of travel by telecommunication has long been advocated as an approach that might alleviate congestion on transportation facilities and thereby reduce fuel consumption and air pollutant emissions. With increasing penetration of telecommunications in individual homes and businesses, coupled with the widespread availability of computing equipment, facsimile capabilities and the like, there is renewed interest in exploring and encouraging telecommuting arrangements. These include work-at-home schemes and workplace decentralization with satellite work centers, as well as many other non-traditional approaches to structure workplace activities and worker responsibilities.
The aim of this report is to propose a comprehensive framework of the interactions between telecommuting and travel behavior, and to develop a mathematical model of the telecommuting adoption process. The framework identifies two principal actors in the decision process, the employee and the employer. The employee faces a decision of whether to participate in a telecommuting program given the program features and his/her personal and household characteristics and circumstances. The employer decides whether to offer a telecommuting program to employees and the features of such a program, given the employer’s mission, activities and management concerns. Discrete choice models are employed to formulate the adoption process of both employee and employer.
The derived choice models are based on the ordered-response theory and the normality assumptions of the disturbances, known as the ordinal probit model. While existing ordinal probit models are limited by assumptions of deterministic utility thresholds and identical and independent disturbances of the latent variable, the generalized ordinal probit model derived in this research allows stochastic thresholds and a general variance covariance structure of the disturbances, which enables the model to analyze panel data with serial correlations or auto-correlations. The models are calibrated using stated-preference survey data from three Texas cities.
Keywords: Telecommuting, Traffic Congestion, Air Pollution, Travel Behavior, Suburban Mobility
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