Integrated Demand Supply Models Sample Clauses

Integrated Demand Supply Models. Integrated demand supply models refer to a set of regression equations where three fundamental measurements (or at least the first two) are modeled simultaneously. They include: 1) Demand (transit ridership), 2) Service supply, and 3) The inter-route relationships. The methodology was founded on the assumption that transit riders were responding to service changes while transit planning was responding to ridership changes (endogeneity effect between demand and supply). In other words, transit patronage and service supply were highly interrelated. It was also noticed that transit riders transfer from route to route, the introduction of new service might draw some riders from the existing routes, which implied that transit patronage on a route was also affected by other parallel and intersecting routes. In this regard, analytic tools were developed to examine these complex relationships in the transit system (Xxxx 1994, Xxxx and Xxxxxx 1995, Xxxx et al. 1997, Xxxxxxxx et al. 2002, Xxx 2004, Xxxxxxxxx and Xxxxxxxxx 2008). Peng 1994 used Tri-Met data from Portland/Oregon to develop the simultaneous demand/supply model based on buffered socio-demographic variables, park-and-ride capacity, competing route attributes, and employment density, etc. A three stage least square method (3SLS) was applied where both ridership values and total seat supply were used as endogenous variables which account for the cause/effect interrelationships between the two parameters. Five different models were developed for different time-of-day sections: AM Peak, Mid-day, PM Peak, Evening, and Night. Xxxxxxxx et al. (2002) described the basics of a Regional Transit Feasibility Analysis and Simulation Tool (known as RTFAST) by developing an integrated demand supply equation system. In a Bus Rapid Transit (BRT) study in Bogotá, Colombia, Xxxxxxxxx and Xxxxxxxxx (2008) applied a 2SLS regression model to predict station boardings. In addition to considering the demand/supply endogeneity, researchers incorporated four latent environmental factors into account, namely walking supports, barriers to car use, low safety and insecurity, and connectivity.