Sustainable housing and railway developments over space and time

Railway is recognized to be an effective transport mode with high capacity that caters for the increasing travel demand in a developing area. While pure railway development is not sustainable financially for most practical cases, the development of housing near the railway stations has demonstrated to be a financially viable strategy which allows cross-subsidization between railway and housing, or referred to as joint housing and railway developments. Recently, such joint developments have been integrated with the public-private partnership (PPP) approach, which utilizes the strengths of both the public and the private sectors. With this approach, the ideal situation to be achieved is that; residents gain access to the new railway services and pay an affordable housing rent, railway operator and housing developer make reasonable returns on their investments and the government addresses the transport and housing demand without deploying public funds. This outcome, however, is not a natural occurrence, but requires an in-depth analysis on the distribution of costs and benefits of all the parties involved and their relations with each other. To this end, in this thesis, we examine three major issues; the first issue is to design the housing supply and railway service plan over space and time; the second issue is to consider the impacts on stakeholders according to their differential objectives; and the third issue is to reveal possible policy implications based on the results so as to balance the different objectives. Specifically, the spatial distribution of housing supplies is firstly considered, where the supply constraint is discussed as a policy measure. A time-dependent framework is then developed to analyze the development phasing, or timing plan, of housing and railway given fixed population and construction cost variations, so as to identify possible win-win situations. The framework is subsequently extended to evaluate various PPP models with risk sharing mechanisms, under uncertain population and construction cost. Finally, a global optimal solution algorithm is proposed to solve the optimization problems formulated.