Simultaneous estimation of residential, workplace location and travel mode choice based on nested logit model

An empirical model of joint decisions of where to live and work, how to get to workplace demonstrates that individuals make residential location, workplace location and mode choices by trading off wages, housing prices, and commuting cost, mainly commuting time. In the sense that its formulation is especially appealing because of its intuitive way of capturing even complex structures, a generalised extreme value model specified as Nested Logit (NL) are estimated in the joint residential, workplace location and travel mode choice context. Taken Beijing as a case study, results demonstrate that commuting time and commuters' socio-demographic characteristics have high correlation with this kind of joint choice with residential location as one of choice dimension and also reveals that commuters in Beijing make their residential and employment location and mode choice similarly to people in other cities but to slightly degree of magnitude.