Surface transportation has evolved through technology advancements using parallel
knowledge areas such as machine learning (ML). However, the transportation industry has …

Understanding choice behavior regarding travel mode is essential in forecasting travel
demand. Machine learning (ML) approaches have been proposed to model mode choice …

Abstract Background Discrete choice models (DCMs) for moral choice analysis will likely
lead to erroneous model outcomes and misguided policy recommendations, as only some …

In this paper, we present an optimization method to analyze the simultaneous decisions on
dynamic pricing and ordering quantities for seasonal products, by a retailer in monopolistic …

Ride-sourcing services have had a disruptive impact on urban mobility. However, the
perceived risk of contracting the COVID-19 virus while using these services has negatively …

Modeling and prediction of mode choice are essential to support more sustainable and safer
transportation decisions. There is plenty of literature in this decade showing that machine …

How to promote air traveler repurchasing has become an important marketing strategy in
airlines. However, because of the growing concern over user privacy, effectively and …

Recently, there has been a growing interest in comparing machine learning models and
Discrete Choice Models. However, no studies have been conducted on image choice …

The methodology discussed in this paper aims to enhance choice models'
comprehensiveness and explanatory power for forecasting choice outcomes. To achieve …

Accurate classification of mode choice datasets is crucial for transportation planning and
decision-making processes. However, conventional classification models often struggle to …