Strategic behavior is inherent to multi-actor decision-making, allowing actors to see their goals reflected in the process and outcome, which is needed for achieving satisfaction. Traditional decision-making often favors those with the loudest voices, which can lead to decisions that reflect only the preferences of a few rather than a balanced consideration of all stakeholders' interests. While strategic behavior is necessary, its associated risks such as stagnation, perceived unfair distribution of benefits, and suboptimal solutions are well-documented. These can negatively impact the decision quality. These risks are tied to the strategic approach employed, whether competitive or collaborative, and are influenced by how the decision environment is structured. The literature indicates that a dominant reliance on competitive strategies within such environments often leads to the issues mentioned earlier.
While Decision Support System literature acknowledges the risks of strategic behavior, a lack of behavioral insight has been identified as a limitation. Understanding how decision support systems influence behaviors is crucial for improving their effectiveness. Emphasizing the importance of learning from real-life manifestations of decision-makers' behavior. It is assumed that the limited understanding how strategic behavior unfolds in practice within decision support system (DSS) supported decision-making environments, supports the understanding how these environments influence such behavior. This limited understanding hinders the development of effective decision support systems as well as current decision making practices. This research addressed this gap by employed a behavioral informed approach, used qualitative research methods such as interviewing and directly observing participants behavior with the use of a Decision Support Systems (DSS). Providing an understanding of how decision environments, shape strategic behaviors.
Through a qualitative analysis using the Preference-Based Accommodation Strategy (PAS) approach as a research instrument, this study explored how this design and decision support system facilitates a decision-making environment and influences the use of strategic behavior. Through analyzing the occurrence of these different approaches, collaborative or competitive, within specific decision environments, patterns were identified. These patterns revealed which environmental factors encourage or diminish certain strategies employed. For instance, collaborative patterns increase under conditions of transparency and inclusivity, while competitive patterns decrease as these address the underlying causes that facilitate such behaviors. These were found consistent in both literature, current decision making and the design and decision making process supported and facilitated by the PAS approach. This research provided insight into how the structure of a decision environment, such as the one created by the PAS approach, influences the nature and prevalence of strategic behaviors.
The PAS approach integrates features such as transparent information, transparent modeling and analysis, interdependency of goals, the overall preference score, and open dialogue. These elements create a transparent and inclusive environment where collaborative strategic behavior is naturally incentivized and is both effective and rewarding, reducing the reliance and effectiveness of competitive strategies. The research shows that PAS addresses limitations in current decision-making environments by fostering a transition from competitive to collaborative strategic behavior, through a transparent and inclusive environment.
By moving beyond assumptions, this research provides a clear understanding of how the PAS approach shapes and influences strategic behavior, offering insights into the design of decision support systems and current decision making practices that promote collaborative strategic behaviors over competitive strategic behavior, enhancing the potential to mitigate the risks mentioned earlier.

In the field of urban development few challenges are as tough as the housing problem. The cause for this is the rapid expansion of urban populations combined with slow construction processes. The Open Design Systems (Odesys) methodology is a preference-based design methodology for creating and evaluating designs. For this it uses a-priori method of optimization, where the preferences of stakeholders for each project objective are determined in the beginning of the process. Designs are thereafter created based on these preferences. Central to the success of preference-based design is the attitude of stakeholders towards using the methodology, which in other words is acceptance for this methodology. How can acceptance be evaluated? To do this the Technology Acceptance Model (TAM) was used. The system design features in the TAM were categorized in the “Use”, “Functionality” and the “Presentation”. Modifications to the Odesys methodology were made in these categories to see the effect on the stakeholder acceptability using the TAM. This research attempted to raise the acceptability for the Odesys methodology with the use of 2 case studies. The conclusion was that for the “Use” category the acceptability was dependent on the project design phase and the involvement of stakeholders. For the “Functionality”, the result reliability and the running time were important factors. The “Presentation” category consisted of the interface and the distinction between group and individual sessions. Modifications to these were developed and tested. This resulted in an increased perceived usefulness and a perceived ease-of-use , which according to the TAM results in an increased acceptance.

This thesis aims to design an interactive tool that facilitates collaboration between Microsoft’s teams in the datacenter development design process. Current datacenter development strategies of Microsoft do not sufficiently take into account socio-technical aspects which is causing project delays. Such socio-technical aspects are internally represented by different teams at Microsoft, such as the Community Affairs team and the Environmental team. Incorporating the preferences of all the relevant teams during the design, results in enhanced collaboration through increased mutual insights, which can be used to develop new design solutions. Such new design solutions inherently incorporate more socio-technical aspects...

In response to the European Commission's initiative to shift freight transport from road to inland waterways, there is a need to expand the capacity of inland ports to accommodate larger cargo ships. This expansion requires lowering the water bottom, which will increase the forces exerted on the quay walls. The quay walls should therefore be reinforced by applying structural adjustments, for minimal costs and environmental impact. The goal of this thesis is therefore to develop a decision support tool, which is able to directly determine the preferred configuration of structural adjustments. To maximise the aggregated preference of all stakeholders involved while satisfying the systems constraints, the a-priori design optimisation method of the Preferendus is applied.

The tool, developed using computational science, uses Python because of its capability to automate repetitive calculations. It integrates with the program D-Sheet Piling that is used for specific sheet pile calculations. The tool is designed to be used during the preliminary design phase, enabling quick assessment of potential reinforcement adjustments and facilitating insight into the preferred solution. It evaluates three main strategies for quay wall reinforcement: lowering active soil stress, increasing passive soil stress, and enhancing pile stability. The tool uniquely focuses on maximising the aggregated preference of involved stakeholders and is capable of evaluating failure mechanisms of sheet piles.

It is tested on three case studies, all located in the industrial harbour Loven in Tilburg. The results show that the tool effectively proposes which structural adjustments are applicable to create a sheet pile design that satisfies. The thesis concludes by drawing specific conclusions for each structural adjustment considered in the project. Moreover, it concludes that the development of a decision support tool has been successful. In particular, the tool enhances efficiency in sheet pile calculations, offers detailed insights into the environmental and financial impact of adjustments and enables the direct determination of the preferred configuration of structural adjustments. This eliminates the need to choose the preferred configuration from a number of designed variants, which is the current approach.

Additionally, the thesis recommends to conduct a follow-up research on the applicability of underwater anchors, which have shown significant structural potential. Furthermore, it recommends to conduct laboratory tests to potentially improve the cohesion and angle of internal friction of soil layers. If those soil parameters can be improved, no structural adjustment may be necessary to reinforce quay walls at all.

Negotiations in urban development projects can take a long time, going back and forward to the designer many times, even leading to stalemate situations. Requirements can be set intuitively, without knowing what the side effects of the constraints will be for the urban development. On top of that, approval of all stakeholders is needed to be able to implement the design. An integral process of decision-making, with cooperation, open communication and considering everyone’s opinion, seems to be challenging when it comes to urban development projects.

Current decision-making methods, such as Linear Programming, are lacking in terms of cooperation between parties, only finding a feasible design for a group of stakeholders and satisfying one party. Considering preferences helps overcome this problem. In this thesis, an a priori design optimization approach (PDOA) has been developed as decision support system, applied and tested on a real-life urban planning case, Waelpolder.

The PDOA returns a quantitative design (Program of Requirements) for the to be developed area which is considering preferences and wishes of stakeholders a priori, before a design is generated. By basing the design on preferences of stakeholders, intuitively determined requirements are avoided and designs will be more compliant to stakeholders’ needs. The PDOA generates a design by optimizing on overall preference. So, finding a feasible solution is guaranteed, on top of that the approach is able to find a most desired group solution.

The Preferendus (based on Tetra) method, where stakeholders do not make the same amount of compromises in a design, is preferred to use in the PDOA rather than the goal attainment method, where stakeholders do the same amount of compromises. This is mainly because the Preferendus returns more extreme designs and can better show the impact of adjustments in requirements in comparison to the more moderate designs generated with goal attainment. In addition, the stakeholders of Waelpolder indicate that it is realistic that one party should do more compromises than another party. Therefore, the Preferendus is better able to support decision-making and open up discussions.

The PDOA allows a new direction in decision-making, where negotiations become an open glass box rather than a black box. Openness & transparency, which is one of the fundamentals of the PDOA, takes away strategic play between stakeholders. Stakeholders are forced to express what they want upfront, before any design is created.

The approach supports negotiations in decision-making as it provides insights in a rapid and simple manner. The tool allows requirement modification, thereby showing the impact of certain requirements and presenting alternative possibilities. In addition, long negotiation processes where stakeholders need to get aligned are avoided because of the required openness and adaptability of the tool.One of the stakeholders within Waelpolder is willing to implement the PDOA within its organization as slip school model in urban development projects, to investigate the effects of adjusting requirements. Due to the iterative value of the approach, the stakeholders are positive about using the approach in other area developments, in an early stage.

The purpose of this graduation thesis entitled "Probabilistic restructuring of complex construction project activity linking using GERT: an alternate network distribution in mitigation controller" is to analyse the effect of project network structures when the duration of the project activities is distributed stochastically and its following effect on the existing Mitigation Controller©. The researchers at TU Delft have developed a state-of-art tool called Mitigation Controller© (MitC) for automating the search for finding the most cost-effective set of mitigation measures to ensure the probability of the project's completion at a required level. However, there is a modelling error in the project network diagram of this tool. The risks and uncertainties are modelled using a Program Evaluation and Review Technique (PERT) distribution. The current Mitigation Controller has managed
to recreate the human-oriented selection of mitigation measures, but it has not considered all possible scenarios within a complex construction project.

PERT is the most straightforward distribution used for explanatory purposes. This does not reflect reallife conditions. There are instances where certain activities are repeated when the result does not meet the required quality. To overcome the limitations of PERT, it is suggested to implement the Graphical Evaluation and Review Technique (GERT) for scheduling construction projects. A new code
is integrated into the existing Mitigation Controller to generate new network paths based on the probabilistic nature of the project activity. The novel network structure is used to compute the optimal set of mitigation measures using Monte Carlo analysis and linear optimisation. It is also observed that the optimisation solver takes a substantial amount of time to compute depending on the number of activities on the project. An efficient Monte Carlo analysis is implemented to reduce optimisation time within the tool.

Environmental sustainability has become an urgent matter on the Dutch political agenda, which will affect the built environment in the near future. Consequently, organizations have to adapt their real estate to new regulations for building performance and their own sustainability goals. The Preference-based Accommodation Strategy (PAS) is a decision-making strategy that aids organizations in finding a Corporate Real Estate Portfolio (CREP) that aligns with the organization’s values. This research aimed to stimulate organizations to improve the environmental sustainability of their CREP by changing the decision-making process. Therefore a sustainability reference model (SuRMo) was developed for PAS and tested on the CREP of Colliers, an international real estate consultancy firm with multiple offices in the Netherlands. In the pilot study, PAS and the SuRMo were used to evaluate three alternatives for a new office space in Utrecht. In an iterative process using the operation research methodology four tests were conducted which compared the outcome of the different decision-making processes. The four tests analysed 1) the current decision-making process, 2) the decision-making process and outcome using PAS, 3) the decision-making process and outcome using PAS with the SuRMo 2.0 and 4) the sustainability performance of Test 1-3 compared to Dutch sustainability goals for 2050. In the three tests the decision outcome resulted in the same office building that performed best in terms of environmental sustainability and matches the governmental goals for 2050. However, between Test 1 and Test 2 the total number of criteria increased from 7 to 37 and from two implicit environmental sustainability criteria to five explicit criteria. The outcome of this research shows that PAS increased the number of environmental sustainability criteria and changed the decision-making process of Colliers from implicit to explicit. The stakeholders expressed the need for the SuRMo because they lack knowledge about environmental sustainability in CREP but concluded that it requires further development for user-friendliness and suitability with PAS. The three actionable conclusions for practise are that PAS should be used in decision-making about CRE with a further developed SuRMo, Green Building Rating Systems should be used for sustainability in CRE decision-making instead of greenhouse gas emissions and project developers and investors can use the explicit outcome of PAS to adapt the supply to the demand on the real estate market.

Marine contractors as Heerema Marine Contractors (HMC) have made decommissioning part of their core business. Being the owner of two of the largest semi-submersible crane vessels (SSCVs), the choice for single lift jacket removal is straightforward. However, jackets in the Northern North Sea have a weight and height exceeding the crane capacity of these vessels. Moreover, not all jackets have the structural integrity to be single lifted. Piece small jacket removal can be a solution but is often overlooked by the expectance of being labour-intensive and therefore too expensive. This thesis has the objective to develop a methodology for advising a jacket removal strategy based on a decision support model while comparing piece small versus single lift decommissioning. Comparing the two removal methods is done for a single case study of the Kinsale Bravo jacket, provided by HMC.

The budgets of both removal methods, resulting from the case study, are used as input for the decision support model (DSM). Based on the jacket characteristics, the model uses constrains, rules of thumb and calculations to determine several possible outcomes. These outcomes can then be further optimised based on costs, duration and Co2 emissions. Based on either one of these optimisations a removal scenario can be established by the model.

With an increase of data documentation and standardization in the construction field in The Netherlands, by norms such as the NEN, there is a possibility to introduce data-driven approaches to certain areas within the construction industry. One of these is the area of budget estimation which is currently fully dependent on a cost estimating professional. Due to the need for estimations that are effective and time-efficient, especially in the primary phase of a project, the potential of introducing a data-driven approach is explored through this thesis. The main objective of this research is the development of a data-driven model, in the form of a Virtual Assistant (VA), to increase the objectivity of the estimation of maintenance budgets of civil engineering structures. From a literature study it is apparent that a fitting data-driven approach for the development of this model is the machine learning technique Decision Tree Classification (DTC). The VA model is developed using historical data, in the form of past input and past output, to train the model and therefore make predictions. Data that is used as past output for this model is a budget range which is documented as a budget class and data that is used as past input is data that is ensured to be objective and gives a description of each bridge. In this case the past input data are the characteristics of the bridge which refer mostly to the dimension of the bridge, the NEN2767, which captures the decomposition and condition of the bridge and to a lesser extent the duration of the maintenance. Through exploring past cases the machine learns rules and predicts the outcome for a new case and therefore predicts the budget range. This shows in which range the budget guess of the estimator should fall. Generally in order to develop a VA model and make it applicable for industry use it is important that an organization that uses such model aligns their data storage with the DTC methodology. This means the introduction of standardizing data in classes and the introduction of standard procedures to document the data. Only when these elements are present within the organization, the data that is used for past input and output can be regarded as objective and the VA can fulfill its function which is to verify the budget estimators guess in an objective manner.

Projects in the Complex Engineer-to-order (ETO) sector are subjected to frequent schedule delays caused by engineering changes, supply chain delays and fabrication delays. Project organizations are faced with the challenge of realigning the project duration within the pre-determined time. Schedule delays often lead to 3-5% rise in project cost. This requires an efficient on-the-go reactive approach. At present, the development of strategy to realign the project is extensively manual in nature. This makes the exploration of alternative realigning strategies cumbersome. Lean Project Planning (LPP) and advances in Building Information Modelling (BIM) has enriched on-the-go planning. However, no existing tool equips the project organization to generate, visualize and evaluate possible set of alternative strategies in the event of a triggered change. No attention has been provided to integrate strategy generation algorithms like Evolutionary Algorithm with the LPP and BIM approaches. In this research, a tool was developed to enable the project organizations to generate and visualize strategies integrating Modified Evolutionary Algorithm (MEA) with LPP and BIM from a metaheuristic approach. Furthermore, by undertaking a case study on strategies adopted in real-life change events in a representative Complex ETO project, the reliability of the generated strategies was investigated. The application of the proposed tool in the real-life test case showed the advantages of having multiple alternative realignment strategies.

In most of the current starting construction projects, most stakeholders use virgin materials for building elements. Considering climate change, building materials are getting scarce, it is necessary to reduce the number of virgin building materials and improve circularity in the construction industry. The problem is the absence of a middle man that could research the data of existing usable materials and connect this information to stakeholders of starting dwelling projects. This raises the research question: How can an operational model link the supply of existing building materials with the demand for new construction projects in order to reduce the use of virgin materials and thereby improve circularity in the construction industry? The goal of this research is to provide a useful tool for the construction industry to join the transition towards a circular economy. Based on three levels of scale, an operational model is developed that gives a comparison between the materials costs of existing building elements and virgin building elements for a starting dwelling project. This comparison results in insight and an overview for clients, such as municipalities or housing corporations into the costs of potential dwellings built with existing building materials. The operational tool also gives insight in whether or not reusable building materials provide a feasible business case, considering a framework based on the clients input.

Deciding on where to locate the company’s assets is one of the main issues of the corporate real estate management field. It should support aligning the organization’s real estate strategy to its organizational objectives. Understanding which information is needed by the decision-makers is crucial to make a proper judgement. However, the awareness of criteria range and their relative importance is lacking in the majority of cases. Although literature recognises a number of structures based on which the criteria should be determined, this knowledge is disperse. It is not fully exploited to enrich the process, due to the scarcity of proper expert tools. As the high level of expertise and the vast amount of knowledge is required, the companies have to rely solely on available human resources.

This thesis provides the development of an expert tool, gathering state-of-art knowledge of location criteria. It strives to improve the (re)location decision making in large companies. It is done by using a hybrid research method, combining the operational research with an empirical one. The determinants for use of certain location criteria and the criteria itself are identified in the literature and linked to each other in a computer program. Through gathering the input from stakeholders, the tool suggests a prioritised list of criteria that should be used in the process.

The expert tool is tested in a pilot study at a company in order to evaluate the effectiveness and attractiveness of the model. It is done with a series of tests and interviews in connection with a pilot case. In addition, the acceptance and trust in the system are challenged.

Overall the tool is evaluated positively. It improves the location decision-making process by increasing the stakeholders understanding of the problem, transparency level, as well as empowering the decision-makers to express their needs that could have been omitted when using a traditional approach. This leads to better assessment of location alternatives. Although the tool itself requires a number of improvements before being able to be used in practice, the idea behind it was highly valued by the users.

Infrastructure projects in the construction industry are complex. This complexity leads to unavoidable changes in scope. When scope changes are not formalized and managed correctly, it is a risk contributing to project failure. A scope change that is not formalized is scope creep. This research looks at the causes and effects of scope creep in both literature and practice. Furthermore, a case study is conducted to recommend a course of action to anticipate scope creep and its effects.

Because of increased secularization and decreased parish revenues, obsolete churches are being sold. Adaptive re-use could preserve the cultural heritage these buildings represent, while having many further benefits. Decision modelling helps view these problems with every actor and their viewpoints in context and in relation with one another and the goal function. The case of the [church name] in [village name] was modelled in the original situation as well as an extended case, where more choice options were added and the new position of the Diocese was considered. Then more situations and aspects from various cases were modelled. In this way the fitness for use of a decision model for choices to be made in adaptive re-use of obsolete churches was proven. The use of decision modelling in adaptive re-use of obsolete churches might in the future lead to more successful outcomes.

The Dutch construction industry is rising again. The economical crisis has had a major impact on the infrastructure sector, as the sector has experienced many cutbacks. Even though the economy is recovering, the consequences of these cutbacks are still present. According to the Economisch Instituut voor de Bouw (2016), the Dutch infrastructure task for the period of 2015- 2030 amounts to almost €245 billion. In response to the major infrastructure task, the Ministers of Economic Affairs, Housing & Public Services, and Infrastructure & Mobility initiated 'De Bouwagenda' late 2016. The aim of De Bouwagenda is to strengthen the construction sector and to offer solutions to the encountered challenges, as it is not feasible to realise the urgent task within the current system. One of the three concrete objectives that result from the initiative is a productivity increase of at least 10% in the construction industry by 2025. This exploratory research project focuses on improving the design productivity, which can be defined as "the efficiency of the production of a design solution, that is effective to the overall requirements and customer needs". The aim of this research is to discover which (combination of) design method(s) contributes to the enhancement of the design productivity of Dutch infrastructure projects, in order to contribute to the productivity objective of De Bouwagenda at a meta-level. In order to do so, this research identifies the factors that affect the current design process of infrastructure projects, also referred to as waste, and explores design methods that address these wastes...

Research on the influence of political and economic uncertainty on the decision-factors for accommodation decision-making in corporate real estate management. Research showed that economic uncertainty, and not political uncertainty, did influence the decision criteria during the last decade. A shift can be seen from practical, costs and efficiency related criteria to accommodation criteria that are focused on branding of the building and the attraction the best employees in these times of war-for-talent. The aftermath of the financial crisis caused this change, since the current upcoming economy creates an upcoming market with more and new business opportunities. Companies use their real estate to differentiate from other companies and to attract and retain the best employees.

Context – The stricter regulations on energy-efficient developments to prevent climate change and resource depletion, the expected rising energy prices and hence the rising monthly living costs for households, the changing process in urban area development, the demand for housing in the western part of the Netherlands and the increasing possibilities of technology.

Objective – To identify effective possibilities for optimisation of the business case of a real estate developer in the realization of energy neutral residential neighbourhoods with all-electric, single-family, owner-occupied dwellings. The definition of energy neutral in this research is about net zero building-related energy demand.

Methods – Literature review, expert meetings, case study research with semi-structured interviews, linear programming, expert focus group meeting and unstructured expert interviews

Results – 1) Identification of various solutions within current practise to optimise the business case from a viewpoint of the real estate developer to realize energy neutral residential neighbourhoods. Aspects of the business case are split in: organizational aspects (e.g. parties involved, public-private collaboration, type of contracts), the financial aspects (e.g. method of financing, amount of investment and total costs of ownership) and the physical aspects (e.g. dwelling program, spatial and/or building technical interventions) 2) Creation of the decision support tool (DST) for modelling the optimal business case with output in the form of the optimal dwelling program and energy installations 3) Identify the optimal business case to get an energy neutral neighbourhood by applying the DST.

Conclusions - All outcomes of the different research methods show that it is possible to create a feasible business case for a real estate developer in the development of the highest energy ambition of present-day, zero-on-the-meter, within current available methods and means. The business case of energy neutral residential neighbourhood development can be optimised within all its aspects. First, by integrated contracts and involvement of (energy) advisors early in the project. Second, by the involvement of third financing (e.g. Energy Service Companies) and a higher selling price, which is made possible by the additional borrowing capacity for the mortgage. Third, it is recommendable to apply a conceptual approach within the dwelling design and to the installation technology on the scale level of a single-building. In the case study and most of the modelled outcomes these concepts are based on ground source heat pumps and PV-panels. Last, the modelled output showed that BENG-legislation could lead to bigger dwellings. In addition, the designed DST has added value for the multi-actor decision-making processes in residential energy neutral neighbourhood development. The DST could help as guidance to provide insight in the various possibilities by exploring the solution/ design space during multiple decision moments and the DST could also be useful in education of laymen.

Keywords - Energy neutral residential developments, BENG, zero-on-the-meter (‘nul-op-de-meter’), financing energy efficiency, Energy Service Company (ESCO), green mortgage, additional borrowing capacity, decision support tool, case study research, linear programming

The question of where to locate your business is at the core of the field of corporate real estate management. This thesis provides a framework for answering this question in an uncertain world. Building on the Preference-based Accommodation Strategy design approach developed by Arkesteijn et al., risk management and mitigation is incorporated in this approach which results in the Location Decision-Making Framework.

The framework consists out of a procedure, activities and a mathematical model, which is piloted at a company as to test the effectiveness and attractiveness of the model. Overall the model is evaluated positively and helps stakeholders in making a substantiated decision on where to locate their real estate.