Commuting to work remains the most important travel segment contributing to the growing congestion in major metropolitan regions. The traditional approach is to focus on a “typical” urban commuter, who is a full time worker with fixed workplace and who commutes every workday according to a fixed schedule in the peak periods. The paper investigates evolution of alternative work arrangements such as part-time work, self-employment, working from home, telecommuting, and flexible and/or compressed work schedules in travel modelling. Alternative work arrangements have already reached 30%-40% of workers in major metropolitan regions in the US and Israel. The paper presents three sub-models of the regional Activity-Based Model (ABM) developed for Jerusalem:

• Strategic long-term model for main individual work arrangements that predicts employment type (owner/self-employed or hired), full-time vs. part-time worker status, number of jobs (to account for specifics of multiple-job holders), and usual workplace location (home vs. outside). Some components of this model that relate work from home have been already incorporated in ABMs in practice. The other components have not been endogenized yet.

• Long-term workplace location choice model for those whose usual workplace is outside home. This model is a routine part of any ABM system but in our case it incorporates many more explanatory variables that relate to the strategic work arrangements.

• Mid-term model that relates to usual commuting frequency and flexibility. Commuting frequency choice incorporates the possibility of a compressed work week. It is combined with possible telecommuting frequency when the worker does not go to work but spends a substantial amount of time working from home. Two other dimensions relate to work schedule flexibility that is categorized by fixed schedule, some flexibility (±30 min in arrival at work), high flexibility (±2 hours in arrival at work), and full flexibility, and usual commuting hours (outbound and inbound).

All choice models were estimated based on the recent Household Travel Survey in Jerusalem. Behavioral insights are discussed along with the model application to predict shifts in usual work arrangements as the result of long-term trends as well as possible travel demand management policies.