Industrialised countries, the Netherlands foremost among them, are staring down a wave of bridge renewals that dwarfs historic maintenance cycles: assets erected in the post-war boom are expiring together, yet public budgets, labour supply and procurement routines remain locked in business-as-usual mode. Heijmans, a tier-one Dutch contractor committed to modular and circular building methods, asked how it might steer the early, “explorative” phase of public bridge projects so that Industrial, Flexible & Demountable (IFD) solutions become the default choice rather than an after-thought. Three questions framed the study: how is that front-end decision spiral organised, which forces help or hinder IFD inside it, and what concrete levers can a contractor pull to tilt outcomes towards modular adoption?
To answer these questions the research combined a literature synthesis on demand-side innovation and modular construction with twelve semi-structured interviews spanning national, provincial and municipal clients, engineering consultancies and sector experts. The analysis followed a three-cycle coding protocol into ten recurring themes and, ultimately, three influence modes: Cultivate, Configure and Convince mapped onto the Desirability-Viability-Feasibility (DVF) framework.

Theoretical insights
This thesis introduces the Cultivate–Configure–Convince (CCC) model and shows that its effective ordering is market-contingent rather than fixed. Derived from coded analysis of thirteen interviews (§5.3), CCC distinguishes three influence modes for suppliers: Cultivate (build awareness, legitimacy, trust), Configure (align technical, organisational, and contractual conditions), and Convince (evidence of viability and risk mitigation). The core contribution is that five procurement-market archetypes exhibit different CCC sequences, meaning CCC should be treated as a repertoire that adapts to procurement structure rather than a universal ladder. This market-sensitive interpretation is consistent with research on demand-side innovation in regulated, high-capital sectors, where public procurement shapes uptake and diffusion (Edler & Georghiou, 2007; Uyarra et al., 2014). Accordingly the figure to the right summarises how sequencing varies across archetypes; detailed rationale is provided in §6.3. Managerially, CCC functions as a market-sensitive sequencing framework: first diagnose the procurement archetype, then time Cultivate/Configure/Convince to focus resources, reduce transaction and political risk, and accelerate innovation adoption. In sum, the thesis reframes influence not as a fixed sequence but as a market-aligned playbook for suppliers and system integrators, with relevance beyond construction wherever procurement mediates innovation.


Practical insights
The evidence indicates that, although technical uncertainties are tolerated and cultural resistance is easing, public clients ultimately prioritise demonstrable life-cycle value. Viability therefore trumps feasibility and desirability. Contractors can break this stalemate only by supplying audited ‘cost-and-carbon’ dashboards, involving engineering consultancies, certified pilots and then hard-wiring IFD metrics into procurement templates. A five-horizon pathway emerges: ignite internally with a small certified span and open data passport, flip external bias by forming a multi-contractor coalition and harvesting tool, prove at scale via ordinary-span interface tests and shared cost benchmarks, lock-in with 3-to-5-span bundles and framework contracts, and, finally, normalise IFD through open data portals and multi-owner agreements. Each horizon is gated by an explicit go/no-go check to limit sunk costs and keep investment tied to verifiable savings...

Subcontractor evaluations are a critical component of post-project reviews in the construction sector, significantly influencing future procurement decisions, subcontractor selection, relationship management, and risk mitigation strategies. Despite their strategic value, existing subcontractor evaluation practices often suffer from several persistent shortcomings: high subjectivity, lack of standardized performance metrics, limited documentation, exclusion of subcontractor perspectives, and minimal use of structured or historical evaluation data. In response to these challenges, this thesis examines whether and how integrating ChatGPT 4.0 with a Multi-Criteria Decision Analysis (MCDA) framework can enhance the consistency, objectivity, and strategic value of subcontractor evaluations within HOCHTIEF Nederland.
Building on a comprehensive literature review and exploratory interviews with key procurement and project staff, the study identifies gaps in traditional evaluation processes, particularly the overreliance on static rating templates and the absence of dual-perspective analysis. To address this, a novel AI-enhanced evaluation framework is developed using a design science methodology. The framework enables structured performance assessments based on both internal HOCHTIEF feedback and subcontractor self-evaluations. ChatGPT 4.0, embedded in HOCHTIEF’s internal AI assistant “NextChat” supports this process by interpreting qualitative data, prompting for clarification when needed, generating justifications for ratings, and summarizing insights into actionable reports.
The framework was implemented in a pilot case study involving a subcontractor working on a real HOCHTIEF data centre project. Evaluation inputs from both parties were processed using the AI assistant and benchmarked against HOCHTIEF’s existing manual evaluation methods.
Validation of the framework was multi-faceted. Process validation demonstrated that AI-generated reports aligned closely with manual evaluations, with a Mean Absolute Percentage Deviation (MAPD) of less than 10%, indicating high accuracy. Stakeholder validation was conducted through structured surveys with HOCHTIEF personnel, assessing insightfulness, transparency, clarity of follow-up queries, added value, and perceived limitations. The results were consistently positive.
While the results indicate strong potential for improving subcontractor evaluations through AI integration, the study also highlights critical limitations and risks. These include the need for high-quality, context-rich input data, the need for human oversight and verification of the results, data availability challenges, and the necessity of embedding the tool within existing procurement databases to ensure organizational consistency. Furthermore, successful implementation depends on training and change management strategies, particularly in organizations with limited digital procurement maturity.
The study contributes theoretically by empirically validating the integration of AI and MCDA in construction procurement and practically by providing a scalable tool that enhances the structure, transparency, and usability of post-project subcontractor evaluations. It is supported by established adoption frameworks, including the Technology–Organization–Environment (TOE) model and the Unified Theory of Acceptance and Use of Technology (UTAUT). Overall, this research offers a data-informed, dual-perspective, and AI-supported approach to subcontractor assessment, positioning it as a robust enhancement to current construction management practices.

The integration of sustainability into water infrastructure projects is no longer optional it is essential for delivering long-term environmental, social, and economic value. However, the implementation of sustainability in green water projects introduces a unique set of complexities that can contribute to significant delays and operational inefficiencies. These challenges include regulatory complexity, innovation adoption barriers, financial limitations, and institutional inertia. Despite the growing emphasis on sustainability in infrastructure, the specific impact of these factors on project timelines remains underexplored in existing literature.

This thesis investigates how sustainability-related complexities affect the timely execution of green water projects and identifies targeted planning strategies to mitigate those impacts. The central research question driving this study is: What planning strategies can help in the successful implementation of Sustainability in Water Projects?

To answer this, the following sub-questions are explored:
1. What are Green Water Projects?
2. How do they differ from traditional projects?
3. What differentiating green factors could result in delays in Green Water Projects?
4. How can these delays be mitigated?

A qualitative multi-phase research approach was adopted to answer these questions, consisting of four key stages: exploratory interviews, literature review, semi-structured expert interviews, and expert feedback workshop with industry stakeholders at Bilfinger Engineering and Consultancy. The exploratory interviews scoped the landscape and helped define "green water projects" in practical terms. The literature review established the conceptual framework, while the semi-structured interviews provided in-depth insights into sustainability-related project delays. The final expert validation tested the practical applicability of the proposed strategies.

The research draws on real-world experiences, including cases involving hydrogen infrastructure, algae-based protein production, and sustainable fuel development, to contextualize the analysis.

The study identifies four core planning solutions tied to the delay drivers:
• Regulatory Uncertainty: Mitigated through early stakeholder alignment and adaptive frameworks like Front-End Loading (FEL) and the Transition Management Framework.
• Technological Novelty: Addressed via iterative testing and feedback using tools such as the Innovation Chasm Strategy and Adaptive Management.
• Financial Feasibility: Enhanced by reducing risk perception through Risk Scoring Matrices, Process Thinking, and Outcome-Based Financing approaches.
• Institutional Capacity: Strengthened through Organizational Learning, Bow Tie Risk Models, and Multilevel Transition Management, which foster resilience and governance alignment.

Building on these findings the study introduces a comprehensive roadmap structured around four interlinked pillars consisting of early stakeholder engagement, bridging the innovation adoption gap, adaptive project management, and institutional alignment with long-term sustainability goals. These pillars are operationalized through a layered approach across strategic, tactical, and operational levels, reflecting the complex, dynamic, and socio-technical nature of sustainability implementation. This multi-level structure enables flexible and adaptive planning that accommodates evolving regulatory, technological, and financial conditions, thereby supporting resilience in project delivery.

A key insight of this research is the redefinition of the traditional Iron Triangle of project management. By incorporating sustainability as a core dimension alongside cost, time, quality, and scope, the study proposes a new paradigm for project planning that aligns with contemporary environmental and social requirements. This reconceptualization allows project teams to evaluate trade-offs more holistically and design solutions that do not sacrifice long-term goals for short-term efficiency. Although the strategies have been tailored to green water projects, they are designed for adaptability and can be applied more broadly to green projects.

Ultimately, the findings serve as a practical guide for project managers and policy stakeholders seeking to overcome sustainability-induced delays. The research contributes to both academic understanding and industry practice by offering an actionable, multi-level planning framework that supports the successful implementation of sustainable infrastructure. By embedding adaptive and transition management principles alongside enhanced governance synchronization, the proposed strategies enable proactive management of uncertainty and institutional alignment, which are essential for scaling sustainable innovations in complex infrastructure projects.

This thesis provides insights and recommendations for the identification and response to creeping crises during the early stages of construction projects, with a special focus on engineering consultancy firms such as Witteveen+Bos. While existing research on crisis management in construction projects focuses on the execution phase, there is still a gap regarding early-stage crises, particularly creeping crises that are crises that develop gradually. These crises are difficult to detect, often going unnoticed until they reach the tipping point, which is the moment the crisis is visible and it has already damaged the outcome of the project. The main research question of this study is: “How can engineering firms identify and implement early warning signals to detect and manage creeping crises in construction projects?" and it is divided into four sub-questions in order to structure the study in a more systematic manner. To answer the research question and to develop an actionable framework, a qualitative mixed-methods research design is chosen. The research includes a literature review spanning general crisis theories, High Reliability Organizations (HRO), sensemaking, mindfulness, and early warning systems. The second phase involves semi-structured interviews with Witteveen+Bos professionals, where the main objective is to get insights of the most common creeping crises within the organization, barriers to detection, and the existing tools and techniques. The final phase consists of a validation workshop with Witteveen+Bos’ professionals to assess the framework and get a final round of feedback. After carrying out an analysis, findings reveal six common creeping crisis types: scope creep under stakeholder pressure, effort compensation due to overcommitment, stakeholder misalignment, legal or regulatory infeasibility and obstacles, and external contextual drift. Based on these crises and the barriers encountered, a four-stage Early Warning System (EWS) framework is developed: signal detection, signal interpretation, coordinated response, and learning and system adaptation. This framework integrates HRO principles, mindfulness, and sensemaking mechanisms but is adapted into the engineering context, emphasizing soft skills, technical tools, and qualitative judgment. Additionally, the proposed framework is designed to be flexible and customizable, allowing adaptation to different crises, and project teams, with the option of choosing different tools and techniques, including qualitative mechanisms. The validation workshop confirmed the relevance and feasability of the framework. The participants reacted positive both verbal and nonverbal, and showed a strong recognition of the findings presented. Although feedback was provided, the four-phase framework was generally well understood as well. Ultimately, this research contributes a practice-oriented model that supports engineering firms in detecting and managing creeping crises proactively, embedding early crisis recognition within professional routines while enabling future integration of tools such as AI or predictive analytics.

Renovation and replacement (R&R) projects in public infrastructure are becoming increasingly complex, due to factors such as scope uncertainty, operational constraints, and the involvement of multiple stakeholder interests. Prior research has shown that for a successful delivery of complex projects it is essential to award contracts based on quality aspects, such as the contractor’s ability to manage complexity, rather than relying solely on price.

However, there is limited empirical evidence on the extent to which public clients translate project complexity into award criteria. This study addresses that gap by examining the case of ProRail, the Dutch railway infrastructure manager, and its use of award criteria in recent R&R tenders. It aims to analyze to what extent project complexity is translated into award criteria for the procurement of these projects. The research combines qualitative insights from interviews on perceived project complexity with a quantitative analysis of the award criteria and their weightings in four recent ProRail R&R tenders.

Findings reveal a partial but positive relationship: in more complex R&R projects, ProRail uses more project-specific quality criteria that are related to project complexity. Projects that were perceived as less complex relied more on ambition-related award criteria and price. Interview participants also mentioned that at ProRail technical complexity was addressed through strict requirements and not through award criteria, while organizational and environmental complexity were more translated into award criteria to create differentiation between bidders.

The research offers a first empirical foundation for understanding how a public client incorporates project complexity into its procurement practices. Although this study focuses only on ProRail, its findings and recommendations are relevant for other public infrastructure clients and can serve as a basis for future research into the alignment between project complexity and procurement strategies.

The scale and complexity of projects in the construction sector have grown significantly in recent years. Larger projects typically result in worse performance, including overspending and delays in the calendar.
This research focuses on identifying and analyzing Early Warning Signals (EWS) to mitigate schedule delays during the design phase of infrastructure projects managed by Sweco, a consultancy company in the Netherlands. The primary aim is to explore how effectively EWS can be used to identify potential issues early and prevent project delays.
The research begins by assessing the current knowledge and application of EWS among project managers, controllers and directors at Sweco. Initial findings indicate that while most participants have a basic understanding of the concept of EWS, they do not actively use or recognize it in their daily workflows. Their awareness of these signals primarily stems from gut feelings and extensive experience rather than systematic identification and application.
To identify the most relevant EWS, the study combines insights from existing literature with practical experiences shared by Sweco experts. This process involves creating a comprehensive list of potential EWS, which is then narrowed down and prioritised based on their perceived impact and likelihood. The prioritisation is similar to a risk assessment method, considering both the probability and potential impact of each signal.
The study examines how to measure data related to the signals and proposes measures on how to handle those EWS better. Some of the suggestions include establishing clear working agreements, balancing formal and informal communication, enhancing collaboration through workshops and visual tools, and leveraging advanced technologies like AI and BIM. The study further emphasises the importance of continuous client communication, internal quality checks, and ensuring appropriate expertise for project tasks.
The research provides a comprehensive framework for identifying, measuring, and managing EWS to improve project outcomes and reduce schedule delays in infrastructure projects. The findings emphasise the need for systematic approaches and technological integration to enhance early warning capabilities and project management practices. By implementing the recommended strategies, Sweco can better anticipate potential issues, make informed decisions, and ultimately deliver projects more efficiently.

Keywords: Early Warning Signals (EWS), schedule delay, design phase, infrastructure projects, project management, measurability, prioritisation

Construction accidents are known to occur often; in 2022, there were 129 accidents in the Netherlands for every 100,000 workers . Beyond the tendency to place the responsibility on employees, this study investigates the impact of client involvement in enhancing safety performance. The majority of safety research focusses on the building phase, indicating that client influence decreases as projects progress. The study highlights 43 crucial client responsibilities with a focus on pre-construction phases, specifically in the Planning, Inception, and Feasibility; Design, and Procurement and Tendering phases. Moreover, Semi-structured interviews reveal differing practices between infrastructure and oil & gas projects, providing the opportunity to learn from these differences and highlighting areas for improvement, such as establishing stricter safety objectives, early contractor involvement, and enhanced knowledge sharing. The findings suggest that optimizing client roles in pre-construction phases can significantly enhance safety performance in construction projects.

As concerns about climate change increase, which can harm the environment, all kinds of businesses face a challenge called sustainability. In the construction sector, one pathway to greater sustainability is designing and constructing buildings with low carbon emissions. Some researchers have explored this challenge by investigating the portion between embodied and operational carbon, as well as the methodologies for calculating each type of carbon emission in buildings. Having an understanding of the design's performance against this challenge will provide more opportunities for design optimization. However, there is limited literature discussing methodologies to optimize whole-life carbon emissions, especially for apartment buildings in the Netherlands. This thesis project aims to fill this research gap by closely examining the practical relationship between embodied and operational carbon and by achieving optimized building designs to minimize whole-life carbon emissions. The scope of this thesis includes analyzing embodied carbon from stages A1 to A5, operational carbon at stage B6, focusing specifically on studio apartments located in the Netherlands. To achieve the aim of this thesis, which is to explore the relationship between embodied and operational carbon in apartment buildings located in the Netherlands, several key steps were undertaken. This study began with a comprehensive literature review and analysis to define factors and methodologies for calculating both embodied and operational carbon emissions. Subsequently, a case study was conducted using a simplified model in Excel and IES software to quantify these emissions. Optimization strategies were then implemented using Rhino 7 and Grasshopper. A detailed framework was developed in Rhino 7 and Grasshopper to guide optimization and analyze the resulting data. Finally, validation and evaluation of the framework and its outcomes were conducted through expert interviews. The findings yielded several critical insights. For instance, certain materials with higher embodied carbon can lead to lower operational carbon, while those with lower embodied carbon may result in higher operational carbon. Moreover, increasing thickness can effectively reduce operational carbon and contribute to overall reductions in whole-life carbon emissions, up to Rc 4; beyond this, the benefits diminish. Furthermore, materials with high embodied carbon above Rc 4 tend to increase whole-life carbon emissions, despite potential reductions in operational carbon. Lastly, each Rc of the façade has its own optimal façade opening, and window frame material only influences a small amount of the embodied carbon and has no influence on operational carbon. However, this result is based on Dutch circumstances and specific MEP inputs. Therefore, these results will differ if different locations and MEP inputs are used. Through this framework, designers are provided with practical guidance to achieve optimal solutions in apartment building design. Additionally, this framework has already been tested by expert respondents in this field, as detailed in Chapter 5. Recommendations for future research include expanding the scope to whole entire apartment (from foundation to roof) and integrating financial considerations into optimization strategies.

The Dutch government aims for a fully circular built environment by 2050, transitioning from a linear to a circular economy. This involves establishing construction hubs, divided into circular hubs (focusing on closed-loop material chains) and non-circular hubs (focusing on efficient transportation). Currently, only a small fraction of construction and demolition waste is reused, making the role of circular construction hubs crucial.

This study investigates how to stimulate the realisation of urban mining hubs in the Netherlands. The primary research question is: How can the realisation of urban mining hubs in the Netherlands be stimulated? Data was collected through a literature review and semi-structured interviews with key stakeholders in the construction sector.

Findings highlight the undefined role of hubs within the urban mining process and the advantages they offer, including resource conservation, financial savings, and employment opportunities within a circular economy. Barriers include insufficient material supply and demand, inventory uncertainties, and inadequate legislation. An actionable framework was developed, consisting of three phases: initiation, optimisation, and expansion, with a focus on innovation, education, and collaboration among stakeholders.

Prompted by the 2023 Turkey earthquake and lessons on deviations, this study examines deviations in Paraguay. It clarifies that changes are formal procedures, whereas deviations are informal alterations to original plans, assessed post hoc. The concept of an “accepted deviation” is defined as an informally allowed variance in project requirements. The question is how to prevent deviation abuse. The study uses a qualitative, exploratory, inductive design, drawing on literature review, interviews, document analysis, and expert evaluation. Eight professionals from public and private sectors in Paraguay participated; three private experts validated findings.
Findings show that literature treats changes as formal and prospective and deviations as informal and retrospective; once deviations occur, they are accepted or rectified, with limited guidance beyond acceptance. In practice, deviations arise through bilateral agreements, unilateral contractor actions, or errors; formal change orders differ by sector, with the public sector imposing strict regulations and finance delays, while private sector relies more on informal agreements. The study identifies six preventive measures: improve final design; include paid, thorough contractor reviews in contracts; reduce change-order bureaucracy; enhance teamwork and communication; anticipate unforeseen events; hire qualified professionals. For managing deviations, four feasible practices are recommended: seek specialist opinions; document informal agreements; embed deviation management into regulations; rely on experience and safety considerations. Conclusions stress understanding the differences, reducing deviations, and applying proposed practices, while noting they are not universal remedies. The study suggests avenues for further research, including sector-specific analyses, agile methodologies, client/financier perspectives, ethics, and a protocol for middle-ground modifications.

This study examines improving the documentation and application of lessons learned in tender processes within the Dutch construction sector, focusing on Royal BAM Group. Despite the need for effective knowledge management, challenges like fragmented knowledge sharing and inconsistent documentation persist, limiting organizational learning. Using Social Network Analysis (SNA) and Root Cause Analysis (RCA), the research identifies key organizational, technological, and cultural barriers impacting knowledge sharing. The study proposes a GIS-based application to enhance access to lessons learned across departments. Recommendations include short-term actions and long-term strategies to formalize documentation and foster a learning culture, aiming to optimize future tender projects.

In the construction of subsoil structures, a common challenge is the presence of a high groundwater level in combination with the absence of a naturally impermeable layer or an environment susceptible to settlements due to lowering the groundwater level. To overcome this issue, a building pit with an underwater concrete floor (UCF) can be constructed. The UCF ensures structural rigidity and allows for the building pit to be drained such that a dry and safe subsoil construction site is obtained.

The objective of this thesis is to investigate how design efficiency of underwater concrete floors can be improved. In an effort to reduce material usage and achieve cost-effective structures, the following research question was stated:

“What is the influence of design parameters and how can parameters be adjusted to improve design efficiency of an underwater concrete floor, and to what extent can the addition of fibre reinforcement contribute to this optimization?”

A parametric model was developed to provide insight to the sensitivity of parameters and their impact on design resistance. Furthermore, the model was utilized to examine under what circumstances potential material savings can be obtained by implementing fibre reinforced concrete in UCF’s. This was accomplished through the evaluation and comparison of the minimum required thickness based on bending moment resistance in various scenarios, for both UCF’s and steel fibre reinforced UCF’s (SFUCF).

Results obtained with the parametric model established that, in order to enhance the bending moment resistance of an uncracked UCF, increasing the nominal thickness becomes relatively more effective compared to increasing the concrete strength class for higher normal forces. When utilizing a compression arch to obtain bending moment resistance, the implementation of ribbed tensile elements or an increase in nominal thickness are found to be the most suitable methods for increasing resistance. For enhanced shear force resistance, increasing the nominal thickness over the concrete class provides relatively more additional resistance for slender UCF’s. The results found that through the application of ribbed piles, most punching shear force resistance can be obtained.

Three use cases for a SFUCF were identified using the parametric model. When centre to centre (c.t.c.) distances larger than 4.4m are applied in combination with a substantial normal force, significant material savings of up to 0.3m thickness are possible, which equates to a reduction of material usage by 30%. For situations where the effective height of the compression arch is small, it was also found that material usage could be reduced by 30%. Perhaps the most significant use case for a SFUCF is when the normal force is close to zero, and additional normal force cannot be obtained through membrane action. In these situations, the application of a SFUCF can make an otherwise near impossible project feasible.

As a new design approach, a cost-based optimization tool was developed using the parametric model. An already executed UCF was evaluated using the tool, it was determined that a more cost-effective design could have been achieved, with potential savings of up to 30% in costs.