ReMoTe-S. Residential Mobility of Tenants in Switzerland: an agent-based model

Accounting for a fourth of the CO2 emissions and total energy consumption in Switzerland (IEA, 2018), housing plays a crucial role in the transition towards the sustainability of urban systems. Although new technologies have been developed to tackle the environmental burden of the residential sector, technical solutions alone are not sufficient to achieve the transition, as their success depends on how they can be reconciled with the present and future needs of households. Residential mobility offers the perfect ground to understand the matching of and recursive effect between households needs and dwellings. A wide range of models simulating residential dynamics exists; however, the specificities of the Swiss rental market require to consider factors influencing the decision to move and the selection of the new dwelling that are tenure- and context-specific, and which have not been modeled so far. In our presentation, we introduce ReMoTe-S, an agent-based model of the residential mobility of tenants in Switzerland. The model results from the interdisciplinary scientific collaboration of social, environmental and computer scientists. Based on exploratory qualitative and quantitative research, ReMoTe-S accounts for the complexity of tenants’ and buildings’ life course. The former includes changes in household (e.g. a new child), housing (e.g. an offer on the market), and work trajectories (e.g. a promotion), the corresponding triggers to move, and the consequent adjustment of residential preferences. The latter considers the construction, renovation and demolition of dwellings and buildings of two types of Swiss multifamily housing providers: cooperatives and asset managers. The matching between household- and dwelling-agents is determined by preferences and constraints. Preferences are simulated as desired housing functions (e.g. a shelter, a status symbol); their correspondence with the function fulfilled by the dwelling is used to determine households’ satisfaction, and thus the relocation behavior. While the desired function is specific to each household type (e.g., ‘young single’), the dwelling function is computed from the dwelling, building and neighborhood characteristics (e.g., ‘proximity to public transports’). Constraints are set based on rules specific to the Swiss rental market (e.g., occupancy rules, salary-rent proportion). The model simulates an open market, where in- and out-migration are responsible for the variation in dwellings’ vacancy rate. To check for plausibility and robustness of the baseline scenario, calibrate the model and run experiments, the effect of the variation of several parameters were explored. Our presentation shows the results of the OFAT or One-Factor-at-a-time sensitivity analysis, where, to account for the stochastic variation of parameter values and estimate long term behaviours independent of initial patterns, each simulation run was repeated 100 times over a time span of 30 years (or 360 time-steps). In