## 2 Literature Review
### Disaggregate Demand Models on Transit Consideration and Mode Choice
#### 2.1.1 Research on Train Consideration  
Consideration models focus on the process of including an alternative in the choice set of many alternatives [18]. Consideration is affected by feasibility, availability, awareness, and compatibility with activity-travel patterns. These models are developed using either a latent variable approach or revealed choice data [17; 19; 20]. Such revealed data typically consists of binary variables about whether a particular mode was used within a specified time window [21; 22]. Among the two approaches, for existing modes, modeling the revealed outcome is often preferable, as it is easier for respondents to report, and the response is more precise than corresponding latent variable indicators. However, selecting an appropriate time window for measuring consideration is essential for robust model development. Measurements over very long time windows may lead to poor memory recall by respondents or may not accurately reflect recent travel patterns. On the other hand, consideration over just a few days may capture some rare or occasional trips but may not reflect regular patterns. Regardless of whether a latent or observed variable approach is used, almost all studies assume that consideration of a particular mode is a binary response variable. Hence, it is widely modeled using binary logit or probit models, and the main empirical findings are summarized below. In many such models, accessibility characteristics are found to strongly affect the propensity of individuals to consider trains. For example, high access and egress distances (or walk time) reduce the propensity to consider trains [10; 11]. [PERSON] et al. (2012) identified that individuals unwilling to walk for more than two minutes were unlikely to consider trains [17]. However, there is not enough understanding of how perceptions of footpath usability and the ease of walking access to train stations affect consideration. Furthermore, research on access and egress times for modes other than walking is scarce. In particular, the impact of intermediate public transport (IPT) modes,such as auto-rickshaws and shared autos (regular or ride-hailing), on train consideration is not well understood. This is especially important for Indian cities, where IPT modes carry a significant number of passengers to train stations daily. Vehicle ownership is often regarded as a major inhibitor to considering public transit. The literature reveals that vehicle ownership reduces the likelihood of considering trains [10; 11]. Another study illustrated that individuals who are captive to public transit due to vehicle unavailability have a higher propensity to consider trains [11]. However, the role of vehicle type, number, and degree of availability in train consideration has not received adequate attention. Notably, none of these studies explored whether the sensitivity to factors such as first- and last-mile connectivity, walkability, or perceptions towards train services varies across different market segments based on the availability of personal vehicles. Quantitative transit service attributes (e.g., travel time, cost) and the qualitative level of service for the train services (e.g., comfort, crowding) play a key role in deciding whether individuals include trains in their choice set [10]. [PERSON] et al. (2012) showed that individuals who perceived low comfort levels in transit were less likely to consider train services [17]. Additionally, those with a pro-transit attitude were more likely to consider the train. However, the influence of these factors could vary across market segments, which remains underexplored. For example, individuals owning a car may prioritize comfort over cost [23], whereas those owning a two-wheeler might be more sensitive to travel time. Empirical studies have also revealed the effect of socio-demographic variables on train consideration. For example, younger individuals, females, and high-income respondents were more likely to consider trains than other segments [17; 20].