Modelling multiple occurrences of activities during a day: an extension of the MDCEV model

Abstract

The increased interest in time use among transport researchers has led to a search for flexible but tractable models of time use, such as Bhat's Multiple Discrete Continuous Extreme Value (MDCEV) model. MDCEV formulations typically model aggregate time allocation into different activity types during a given period, such as the amount of time spent working and shopping in a day. While these applications provide valuable insights into activity participation, they ignore disaggregate activity-episodes, that is the fact that people might split their total time spent working in multiple separate blocks, with breaks or other activities in between. Insights into this splitting into episodes are necessary for predicting trips and understanding time use satiation. We propose a modified MDCEV model where an activity-episode , rather than an activity type , is the basic choice alternative, using a modified utility function to capture the reduced likelihood of individuals performing a very large number of episodes of the same activity. Results from two large revealed preference datasets exhibit equivalent forecast accuracy between the traditional and proposed approach at an aggregate level, but the latter also provides insights on the number and duration of activity-episodes with significant accuracy.

Impact of the COVID-19 Pandemic on Activity Time Use and Timing Behavior in Switzerland

“…While for women this difference is rather uniform across activities, it is less pronounced for older individuals traveling. The signs for leisure and shopping coincide with findings of previous studies, while the results for work are contrary to these findings where men tend to work less (17,23,24). However, as a lower propensity to choose an activity does not imply anything about the duration, it might be that women pick fewer activities, but the overall activity durations are much longer.…”

“…In addition, they were able to demonstrate that people with lower workload tend to shop more often, and that men are more likely to participate in leisure activities, confirming results from prior research (23,24). Palma et al (24) found that men are also more likely to go shopping, but less likely to work.…”

“…In addition, they were able to demonstrate that people with lower workload tend to shop more often, and that men are more likely to participate in leisure activities, confirming results from prior research (23,24). Palma et al (24) found that men are also more likely to go shopping, but less likely to work. In a different study, Palma and Hess (15) observed that women tend to perform more out-of-home activities than men as well as a "significant complementarity between shopping and leisure activities".…”

Finite-Mixture Continuous Logit Model: Formulation and Application for Shopping Start Time Choice of Non-Commuters

“…Time use focuses on time allocation decisions, and capturing the interactions between duration, travel time, and activity-travel frequency. The fractional logit model, multiple discrete-continuous extreme value (MDCEV) model, and episode-based MDCEV model are mainly applied to the studies of time-use problems (9)(10)(11)(12)(13). Currently, the improvements proposed by Saxena et al (12) and Palma et al (13) for the episodebased MDCEV model are new advances in this field.…”

“…The fractional logit model, multiple discrete-continuous extreme value (MDCEV) model, and episode-based MDCEV model are mainly applied to the studies of time-use problems (9)(10)(11)(12)(13). Currently, the improvements proposed by Saxena et al (12) and Palma et al (13) for the episodebased MDCEV model are new advances in this field.…”