In the Netherlands there is currently a high demand for affordable housing (Volkshuisvesting en Ruimtelijke Ordening, 2022). Earlier research indicated modular integrated housing can serve as a repercussion against this problem (Khan et al, 2022). The Dutch government wants to promote innovation in the construction industry to help solve the housing shortage, but this industry has been described as traditional instead of being innovative (Abbot et al., 2006). Startups, though, are often linked with innovation (Colombo & Piva, 2008, De Groote & Backmann, 2020; Spender et al, 2017). However, when analyzing the Dutch housing construction industry and it’s challenges through the scope of Porter’s five forces (2008), which are the threat of new entrants, power of buyers, power of suppliers, threat of substitute products and rivalry between firms in the industry, it becomes clear that it is a difficult industry for startups to enter and become competitive. This is due to the barriers of entry (e.g. high fixed costs, volatility and access to clients), powerful buyers, and possible retaliation from competitors. Furthermore, innovation and partnerships play a significant role for startups to become competitive in this industry, as partnering with incumbent firms can help the startups overcoming the previously stated challenges linked with the house building industry. These type of partnerships between startups and incumbent firms are initiated because of a startup’s innovative capabilities and are a way for the larger firm to gain access to new business models, which is beneficial for the continuity of their own firm. However, due to their asymmetric nature, these partnerships could cause different types of challenges for managers of involved companies. In this research, the innovation strategies employed by the concept housing startups and their partners are analyzed to see how they plan to become competitive. This research is meant to help (future) startups of this industry, and to provide them with guiding principles on collaborating with incumbent firms. These principals are developed after an exploratory literature review and interviews with managers of concept housing startups and their partners already operating in the Dutch house building industry.

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.

Op de huidige Nederlandse woningmarkt heerst een krapte, waardoor de doorstroming van de woningmarkt is vastgelopen. Er is sprake van een kwantitatieve en een kwalitatieve mismatch op de woningmarkt; zowel in aantallen als in type woningen sluiten vraag en aanbod niet op elkaar aan. Hierdoor zijn de instroomkansen of doorstroomkansen voor starters en jonge gezinnen verkleind (Van der Heijden & Boelhouwer, 2018). Om de doorstroming weer op gang te brengen, is het noodzakelijk om een oplossing te vinden, waarmee de mismatch in de toekomst kan worden verkleind. In dit onderzoek wordt de rol van de empty-nester als belangrijk onderdeel van de oplossing gezien. Empty-nesters bezitten veel eengezinswoningen, wonen ruim en kunnen in de toekomst meer zorgbehoefte verwachten (Crutzen & Hagen, 2020; Daalhuizen et al., 2009). Wanneer de empty-nesters verhuizen en daarmee woningen voor starters of jonge gezinnen beschikbaar komen, kunnen verhuisbewegingen en daardoor de doorstroming op de woningmarkt weer beter op gang komen (Buys & Hu, 2018). De empty-nesters verhuizen in de meeste gevallen echter niet, omdat zij in hun huidige situatie nog geen goede alternatieven zien (Rli, 2020). Omdat veel empty-nesters deze stap zelf niet zullen nemen, zullen zij uitgenodigd moeten worden om deze verhuisbeweging wel te gaan maken. Het doel van het huidige onderzoek is om inzichtelijk te maken wat de effecten zijn van sturingsmaatregelen, gericht op empty-nesters, op de doorstroming op de Nederlandse woningmarkt. Hiervoor is de volgende onderzoeksvraag opgesteld: ‘Hoe kan de impact van sturingsmaatregelen gericht op de Nederlandse woningmarkt en het uitnodigen van empty-nesters om te verhuizen inzichtelijk gemaakt worden, met als doel de doorstroming op de woningmarkt te vergroten?’ De Raad voor de leefomgeving en infrastructuur (hierna: Rli) (2020) en de Raad voor Volksgezondheid & Samenleving (hierna: RVS) (2020) onderschrijven het belang en de noodzaak van het maken van beleid om verhuisbewegingen, en daarmee de doorstroming op de woningmarkt, op gang te brengen. Zo wordt door de Rli (2020) een toetsingssysteem aanbevolen die de impact van sturingsmaatregelen kan testen. Om een antwoord te kunnen geven op de onderzoeksvraag, is de woningmarkt in zowel de huidige als toekomstige situatie geanalyseerd aan de hand van het DAS-raamwerk van De Jonge et al. (2009) & Van der Zwart et al. (2009). De gegevens voor de analyse komen van het reeds beschikbare databestand van het WOoN2018. Er is een operationeel onderzoek gedaan met als uitkomst een product dat inzichtelijk maakt wat de effecten op de doorstroming van de woningmarkt zijn van sturingsmaatregelen, zoals verhuisvergoedingen, grondprijssubsidiëring, collectieve woonvormen en sociale woningbouw, welke zijn gericht op het uitnodigen van empty-nesters om te verhuizen. De ontwerpcyclussen van Hevner (2007) zijn als basis gebruikt bij het creëren van dit product. Om het product vorm te geven, is een lineair programmeringsmodel gecreëerd, dat kan doorrekenen wat de effecten zijn van sturingsmaatregelen op de doorstroming van de woningmarkt. De resultaten uit het ontwikkelde model in het huidige onderzoek laten zien dat door het toevoegen van duurdere woningen aan de woningmarkt er meer verhuisbewegingen plaatsvinden. Deze verhuisbewegingen worden vergroot wanneer er bij de nieuwbouwproductie rekening wordt gehouden met de voorkeuren van empty-nesters. Bovendien wordt door deze verhuisbeweging van empty-nesters een reeks verhuizingen teweeggebracht, waardoor er aan het einde van de verhuisketen woningen vrijkomen voor starters. De resultaten wijzen tevens uit dat er een nieuwbouwproductie van 1,5 miljoen woningen nodig is om tot het jaar 2040 aan de groeiende vraag te kunnen voldoen. Tot slot laten de resultaten zien dat het uitnodigen van empty-nesters om te verhuizen bijdraagt aan het verkleinen van zowel de kwantitatieve als de kwalitatieve mismatch. Concluderend laat het huidige onderzoek zien dat beleid, specifiek gericht op het uitnodigen van empty-nesters om te verhuizen, getest kan worden op de gevolgen voor de doorstroming van de woningmarkt door de impact van sturingsmaatregelen inzichtelijk te maken aan de hand van een lineair programmeringsmodel.

Ageing is a demographic development in the Netherlands that leads to an increasing amount of older households. Most people aged 55 years and older do not want to move or cannot find a house that meets their demand. This
is expected to block the housing flow and increase the already existing mismatch on the housing market, which will lead to difficulties on the housing market for other household types. To give the other household types more
opportunities on the housing market, houses for people aged 55 years and older need to be built. However, policy makers and housing developers often do not exactly know how to attract these households. In this thesis, the qualitative housing demand of people aged 55 years and older is researched. The main research question was What kind of new housing is needed to best accommodate the different 55 years or older groups in the Netherlands?. With a combination of literature research, traditional surveys and a conjoint analysis an answer is given to this question. The focus lay not only on the independent housing preferences, but also on the relative importance of the different preferences. A distinction between households based on age, mobility, future household composition and preferred owner-occupied housing type is made. The research showed that most household groups have equal preferences but the importance of certain housing qualities in their housing choice differs. The price and suitability for elderly people
were important in the housing choice of most groups. But for groups that want to move to apartments (older people, less mobile people) for example, the housing type is more important and the tenure is less important compared to groups that want to move to one-family houses. This becomes especially clear when comparing the trade-offs different age groups make. To accomodate the different 55 years and older groups, it is best to focus on the housing preferenes of people aged 65 years and older, as these people are pickier than people aged 55-64 and housing preferences less often change after this age.

The Dutch population is ageing. The impact of the housing situation of the elderly on society is therefore increasing. The current housing situation of the elderly may be inappropriate regarding the use of space and the wellbeing of the residents. Especially the housing situation of owner-occupiers aged between 55 and 75 is not suitable. Relocation can improve the housing situation of these older adults. However, in the Netherlands, the willingness to move is low for older adults, which is one of the reasons for their low residential mobility. It is, however, unsure what will work in enhancing this willingness to move, as there are currently no well-developed instruments regarding this issue. There is also not much research on possible interventions regarding the willingness to move of owner-occupiers aged between 55 and 75. Therefore, this research aims to examine how instruments can increase the willingness to move of owner-occupiers aged between 55 and 75. The main research question of this study is: How can the willingness to move of owner-occupiers aged between 55 and 75 be increased by instruments on a municipal level?

To answer the research question qualitative research has been conducted. This qualitative research consists of two parts: literature research and case study research. The selected case is the municipality of Rotterdam, one of the four big cities in the Netherlands. Based on this research it can be concluded that instruments can influence the willingness to move by making residents aware of push and/or pull factors, creating pull factors, influencing the evaluation of the current situation, reducing transaction costs of relocating and influencing the evaluation of the new situation. Instruments that influence the triggering mechanism, e.g. push factors and pull factors or awareness of these factors, have priority over instruments that influence the evaluation mechanism, e.g. evaluation of the current situation, transaction costs of relocating, and evaluation of a new situation.

The shortage of housing stock in The Netherlands is one of the major societal issues at present. It is predominantly the people who want to enter the housing market for the first time, the so-called ‘starters’, who face severe problems due to a lack of stock and suitable dwellings. This problem is manifest in the rental as well as in the owner-occupied housing sector. The sole focus of government policies is on housing for the lower social class and the rest of the housing market is dominated by the private sector. Objective – This research aims to define the position of starters on the Dutch housing market in comparison with the position of starters in the context of 1993. The research question that is answered is: ‘To what extent do the factors societal context, housing policy and housing stock influence the opportunities for starters on the housing market in 2018 compared to 1993?’. This question is answered on the basis of the housing choice model. This model is based on the career / life cycle theory of Priemus (1984). In the housing choice model, an extension has been made based on the theory of Dieleman (2001) which takes the external factors that determine the choice of a home into account. Methods – The research is conducted by a literature study and a quantitative analysis. The quantitative analysis has been done on data generated from an extensive quasi longitudinal study. Specifically, the data of 1993 and 2018 were compared to each other. Results – The literature study and the quantitative analysis show that the starter on the Dutch housing market has a good social position in terms of income, education and employment. However, as housing policies failed to respond to the changed social context ultimately resulting in too few houses being built, the position of the starter has deteriorated. This deteriation position is confirmed by the data analysis, which indicates that starters conform to the market situation. Firstly, it is apparent that significantly fewer starters than in the past are entering the housing market. Secondly, starters are entering the market at a much older age than their predecessors. Finally, it is clear that starters in every age category are more likely to choose to live in multi-person households to increase their payment capacity. Conclusions – The final conclusion of this study is that the opportunities for the starter on the housing market in 2018 are mainly determined by the housing stock. However, the relative scarcity of housing stock for the starter is chiefly the result of housing policies which have not responded to societal changes. This implies that housing policy is ultimately the decisive factor in the disadvantageous position of the starter. The average starter has a good starting position from a social perspective due to low unemployment, very low interest rates and good prospects for social growth. However, the starter has minimal chances of entering the housing market due to, in particular, insufficient suitable housing stock. This applies to both the free rental sector and the owner-occupied sector and homes are hardly financially accessible for starters. This good starting position has mainly been confined to the lower rental and owner-occupied sector on the housing market in 2018. This means that starters are more likely to opt for a home in a relatively expensive segment or postpone the choice for a home.

Policy reforms in response to the crisis were initially expected to dampen future house price increases. Instead, the Dutch owner-occupied housing market has overheated not even five years after its recovery. As this could indicate a structural change in the housing demand of households, models were estimated using logistic regression analysis to examine how household mobility has changed following the crisis and position these changes in the context of macroeconomic and institutional developments. Based on the macroeconomic developments, the demand for owner-occupancy was expected to increase after the crisis. For one, the economy was gaining momentum rather than losing it, offering much better prospects for the near future. In addition, house prices were still relatively low and credit cheaper than ever, which greatly increased the accessibility of the owner-occupied sector for lower income households and offered interesting investment opportunities. Regarding institutional developments, the various reforms following the crisis are believed to cause an increase in the demand for affordable owner-occupied housing as a result of the tightened lending criteria in combination with the restricted accessibility of the social rental sector. In addition, the reforms are also expected to polarise households by widening the gap between the rental and owner-occupied sector through equity requirements. The results of the empirical analyses reveal a significant quantitative increase in demand with the intention to move nearly doubling from 21% in 2002 to 39% in 2015. The preference for homeownership itself, on the other hand, remained relatively stable. The most surprising development over time is the convergence of households from different income categories with respect to the intention to move, the preferred tenure, and desired purchase price. It is therefore believed that favourable macroeconomic conditions shortly after the crisis temporarily ameliorated the negative effects of the institutional changes. Further research is necessary to confirm whether the surge in the intention to move is merely a temporary effect of the crisis or an indication of a growing mismatch between housing demand and supply.

During the last decade, two developments on the Dutch housing market have received a lot of attention. One of these developments concerns the recovering house prices and specifically the strong price rises in cities. The other development is related to the growth of the private rental sector and particularly the buy-to-let market. This market consists of the private rental dwellings owned by reasonably small private landlords. These landlords predominantly buy owner-occupied dwellings to rent them out, hence the name buy-to-let. The growing buy-to-let market and the recent price rises have often been linked to each other. Some people claim that the buy-to-let landlords are driving up the house prices. Nevertheless, the relation between these two developments has not been properly studied yet for the Netherlands. Consequently, the objective of this study is to gain more insight in the Dutch buy-to-let market in general and specifically the relation between this market and the regional house price development. Mostly quantitative research methods are applied to answer this research question since especially quantitative information on the Dutch buy-to-let market is missing. House price models have for instance been made for Groningen, Breda and Zoetermeer. The research shows that the Dutch buy-to-let market is still quite small as the buy-to-let dwellings only comprise 5% of the total Dutch housing stock. By comparing the house price development of different municipalities with a varying share of buy-to-let, it can be seen that the recent house price increases are on average stronger for the municipalities with a high share of buy-to-let dwellings. It is however possible that these stronger increases are caused by other factors than buy-to-let. When comparing the results of the three regional house price models no big differences in the drivers are found. The results show that the determinants for the house price development are, despite the varying share of buy-to-let dwellings, in general the same for the three municipalities. Furthermore, a buy-to-let indicator could not explain some of the remaining unexplained variance. Based on these results, it can be concluded that none of the results actually point at an inflationary effect of buy-to-let investments. However, because only three municipalities were studied, no general conclusions can be drawn and the possible inflationary effect of buy-to-let landlords cannot be completely excluded.