Despite the fact that everyone has the right to adequate housing, this fundamental human right has become a critical manner in several European Union (EU) nations, especially in the Netherlands (OHCHR, 2009; Rosenfeld, 2015; European Parliament, 2020). Despite being the largest social sector in Europe, accounting for approximately 30% of the Dutch housing market, recent research suggests that housing associations are unable to properly handle their social responsibilities in the current environment in the Netherlands (Penders, 2020). First of all, recent changes in the housing market demonstrate that the demand for social housing has not only expanded but also diversified its target audience (Madsen & Ghekière, 2021). Recent studies indicate that aside from the poor and vulnerable, also the elderly, young adults (starters), and middle-income families, along with vulnerable and special groups are becoming increasingly interested in this housing aid (OECD, 2020; Madsen & Ghekière, 2021). In order to meet the rising social housing demand, housing associations are expected to construct more than 25,000 new social houses each year until 2035, with the number of dwellings that must become more sustainable gradually increasing from 25,000 to over 60,000 (Penders, 2020; Madsen & Ghekière, 2021). According to Penders (2020), approximately €116 billion is required for all investments up to and including 2035, however, around €30 billion in social tasks (nearly 25% of the total amount) will not be accomplished since housing associations’ expenditures (interest, taxes, maintenance, and management) are rising faster than their income, namely rentals. In the Netherlands, the creation and management of social housing is the responsibility of social housing associations. However, the different actions that these housing associations can take in order to fulfil their social obligations depend mainly on the housing policies that the Dutch policymakers implement. As a result, it has recently come to light that a significant portion of the social housing stock in the Netherlands is unfit for habitation. One in five of all social rental dwellings in the Netherlands, which is estimated to be home to 312,500 households, are expected to be energy-poor, according to recent studies (P. Mulder et al., 2021; Aw, 2021). In addition, according to current Autoriteit woningcorporaties (Aw) data, the housing associations themselves provided about 80,000 social rental houses in (very) poor conditions (De Regt & Bunskoek, 2021). Given that the Dutch social housing is currently struggling to meet its social obligations due to a paradox of rising demand and constrained financial means. More legislative actions will be required to alleviate the current housing crisis through the social housing market. Therefore, this study aims to answer the following research question: What policy strategy could Dutch policymakers put in place to assist social housing providers to ensure that there are enough adequate rental properties available to meet the rising housing demand? In this study, this research question will be answered by means of a simulation modelling approach. It was decided to investigate the underlying mechanisms in the social sector in the Haaglanden urban region by conducting various analyses (including uncertainty analysis and policy analysis) using the system dynamics (SD) simulation model, the Dutch Social Housing Model, which was created during the execution of this study. Contrary to the conventional SD approach, this study is accomplished by combining the SD approach with the Exploratory Modeling and Analysis (EMA) methodology – which employs computer experiments to support decision-making under uncertainties. Given the dynamic complexity and deep uncertainty linked to the researched system, this method was performed to draw valid conclusions regarding the Dutch social housing market under deep uncertainty (Adams, 2011; Le Roux et al., 2011; Jonsson et al., 2021; Kwakkel & Pruyt, 2015). First of all, the results show that up to and including 2050 there will be a housing shortage in both the social housing market (hereinafter referred to as SGEI) and the housing market for middle-low-income households (hereinafter referred to as Non SGEI) in the Haaglanden urban region. In particular, the shortage of SGEI homes will remain at around 60,000 homes from now until 2050, while the shortage of Non SGEI homes will continue to rise to about 20,000 homes. This can be explained by the difficult financial situation of the social housing associations, which cannot meet their social obligations. Despite the anticipated gradual increase in the social housing associations’ financial sources, this study shows that these corporations will only have enough financial resources to invest in the social housing market. Due to this, it is expected that the housing quality of SGEI houses will improve, while that of the Non SGEI houses is expected to deteriorate. The reason being, that if the housing association has sufficient financial resources for a particular house (in this case the SGEI houses), it can ensure that the homes in question can undergo maintenance, which improves the housing quality. Given that the main purpose of this study is to identify policies that will enhance the system behaviour of the social housing market, it was decided to examine the following social housing regulations: Increase Average Rent, More Subsidy for Social Housing, More Planning Capacity for Social Housing, Lower Interest Rate, and Eliminate Landlord Levy. This is due to the fact that the policies Increase Average Rent, More Subsidy for Social Housing, and Eliminate Landlord Levy all improve the cash flow of social housing associations, with Eliminate Landlord Levy lowering the expenditures while the other two policies increase the income of the social housing associations. The expectation is that improved income flow will put social housing businesses in a stronger financial position, allowing them to make more investments to address the housing shortage and quality. Furthermore, More Planning Capacity for Social Housing guarantees more land at the disposal of housing associations compared to the current situation for the construction of new social housing to ensure that the growing housing demand will be met by the housing supply. It is advised to use a combination of these policies to address the issues with the social housing system because no single of these policies can effectively address both the housing scarcity and the poor housing quality of both housing markets. Based on the results, it can be concluded that the combination of the following policies should be used in Dutch social housing: (1) More Planning Capacity for Social Housing, (2) More Subsidy for Social Housing, and (3) Eliminate Landlord Levy. However, it is advised to ascertain the value of the most influential uncertain parameters prior to the selection of the policy strategy because the majority of the KPIs, with the exception of the housing shortage for middle-low income households, are behaviorally sensitive to the uncertain parameters investigated in this study. Moreover, it is challenging to assess the robustness of the investigated policies because of the significant overlap between the findings of the several policies reviewed by the robustness study. The efficiency and robustness of the various policies mentioned in this study and their combination should therefore be thoroughly examined using the data that have been gathered of the most influential uncertain parameters. This information allows for the most precise mapping of the researched system’s behaviour during the application of the policy interventions. Policymakers are then able to decide on a course of action that is supported by empirical facts as a result. Ultimately, it is recommended that the other actors also be included in the policymaker’s selection procedure, as they may have differing opinions about the different policy candidates. The many perspectives that the actors involved have regarding the social housing system must therefore be thoroughly researched.