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.

Digital technologies have increasingly shaped the global construction industry with the fourth industrial revolution (Industry 4.0) emerging as a widely discussed concept. In this context, Construction 4.0 represents the sector’s response to Industry 4.0 principles, particularly through innovative technologies such as Building Information Modeling (BIM). Accurately defining and verifying requirements is essential for project quality and safety, but complex projects often involve thousands of requirements that must be manually checked. As projects grow more complex, there is a clear need for automated verification. This research explores the process of semi-automated requirement verification. The main research question is: “How can a (semi-)automated process be developed to validate and verify requirements within a 3D model?”. This is supported by four sub-questions exploring current limitations, existing tools and methods, and key development stages of automated requirement verification.

A literature review highlights that project requirements are typically derived from the client’s vision and form the basis of contractual obligations. Successfully extracting these requirements is important for defining the project scope and achieving client satisfaction. The literature study also explores various international and national BIM standards, which are adopted to different extents across countries worldwide. Several verification tools were evaluated such as Solibri, Navisworks, BIM Assure, SMARTreview and Verifi3D. From the comparison, Solibri and Navisworks emerged as the tools that provide the most comprehensive functionalities. In terms of requirement structuring methods, the RASE language was identified as the most promising approach due to its clarity and expressiveness.

The research used the Oosterweel project as a case study that is being developed in Antwerp (Belgium) with the aim of completing the city’s highway ring road. The verification process of requirements is broken down in five key steps. The first step focused on the classification of
requirements into geometric and non-geometric requirements using a machine learning model in Python. The second step involved manual rule interpretation using the RASE mark-up language. The third step focused on preparing the model data by filtering the model and performing semantic enrichment. Step four looked at the actual execution of the verifications where different types of requirements were distinguished in classes based on their computational complexity. The last step focused on reporting of the verification results in a Common Data Environment.

Implementation challenges during this process included ambiguous requirement texts, inconsistencies in model data and a fragmented workflow. The insights from the literature review, findings and interviews were combined into guidelines which are divided into three levels: strategic, operational and BIM level. The strategic level focuses on guidelines from the organizational point of view. The operational level looks at how strategic intentions can be translated into practical actions. The BIM level addresses guidelines that relate to the practical
use of BIM. The guidelines are validated through interviews with professionals.

The results of this research show that a semi-automated approach to requirement verification within the BIM environment is feasible and significantly more efficient than current manual methods. Research limitations include the limited scope of one case study and the internal
validation of the guidelines. Based on the research, multiple recommendations were given for future research and practice. Practical recommendations include using a structured approach and the use of open standards. Recommendations for future research include the further
investigation of AI beyond the current machine learning model for requirement verification and the investigation of the impact of the automated verification process.

The design phase of Dutch infrastructure projects is often delayed due to fragmented data systems and a lack of real-time insight. Many companies use multiple, non-integrated platforms, making it difficult to maintain a clear overview of design progress, responsibilities, and deadlines. This research addresses the problem by developing the Design Phase Monitoring Tool (DPMT)—a practical, data-driven solution based on the Design Science Research Methodology (DSRM).
The DPMT goes beyond a standard dashboard. It offers a structured approach to monitoring design activities, using clearly defined indicators and organized data flows to create a comprehensive overview. Developed in collaboration with Heijmans, the tool brings together dispersed information—such as document status, milestone alignment, and verification progress—into a single visual environment. This improves situational awareness, allowing project teams to detect issues earlier and act more proactively.
Validation through a focus group confirmed the tool’s value: users appreciated the improved visibility, the ability to make better-informed decisions, and the shift from reactive to proactive management. Experts suggested the DPMT should become a standard part of the design process. However, the prototype currently relies on manual data entry and static planning dates. Automating these elements and adding predictive features could significantly enhance its impact.
In conclusion, this research shows that a structured, digital approach to design monitoring is both feasible and beneficial. The DPMT helps project teams gain control, improve coordination, and reduce delays. It also lays the foundation for future innovations, such as real-time integration and predictive analytics, and raises the standard for design phase performance in infrastructure projects

The construction industry is transitioning from traditional methods to an industrialized approach, aligning more closely with manufacturing systems where operational efficiency is key to project success. This shift is notably challenging within the prefabricated construction supply chain due to the complexity inherent in combining construction and manufacturing systems, each with its unique characteristics that differ from simpler systems. To effectively manage these complexities, digital twin-enabled simulations offer valuable insights into system behavior, enabling more effective management strategies. However, implementing these advanced simulations requires sophisticated techniques, as current methods often focus on single aspects, neglecting other crucial elements of supply chain management. This paper addresses these challenges by proposing a novel digital simulation approach that enhances supply chain coordination through a mixed-method framework. This framework integrates both micro-level constraints and macro-level tactical decisions, creating feedback loops between different layers of the system. A case study is conducted using supply chain tactics involving inventory and capacity buffers based on the developed model. The study contributes to both theoretical knowledge and practical applications by providing a comprehensive framework for understanding the operational functions of digital twins and offering insights for future academic model development in the prefabricated construction supply chain. It enhances the understanding of operational efficiency and supply chain coordination in this evolving field for both researchers and practitioners.

Infrastructural construction projects in the Netherlands, such as roads, bridges, and tunnels, have become increasingly complex. This complexity introduces various risks, which are further compounded by human biases during risk management processes. This thesis investigates the influence of heuristics and biases on risk assessment in infrastructure projects, with a particular focus on Dura Vermeer, a major Dutch construction firm. The primary research question addressed is: "How do heuristics and biases influence project risk assessment, and what role can serious gaming play in enhancing awareness and management of these cognitive factors?"

The study employs a mixed-methods approach, combining literature review, semi-structured interviews with risk and project managers at Dura Vermeer, and a serious game designed to simulate decision-making processes.

The study identifies several common biases, such as the representativeness heuristic, affect heuristic, and optimism bias, which significantly impact risk assessments. The literature review provides a theoretical framework on the impact of heuristics and biases on risk management. Interviews reveal that while risk assessment at Dura Vermeer follows structured methodologies, biases still influence the decision-making processes. The serious game, incorporating real-life scenarios from Dura Vermeer's projects, demonstrates its effectiveness in engaging participants and fostering a collaborative environment where biases can be identified and addressed. The serious game also highlights discrepancies between perceived and actual use of biases, indicating a lack of self-awareness among professionals.

Findings suggest that although biases are acknowledged, there is a preference for objective risk assessment methods. Serious gaming emerges as an effective tool for increasing awareness of biases, thereby improving risk management practices. The study concludes with recommendations for integrating serious gaming into risk management training at Dura Vermeer, emphasizing its potential to enhance team dynamics and decision-making processes. This research contributes to both theoretical and practical understanding of risk management in construction, offering insights into how biases can be managed to improve project performance. The insights gained provide a foundation for further research and practical applications in the construction sector.

This thesis explores the potential of utilizing Generative AI to enhance knowledge contextualization among stakeholders to promote circularity in the construction industry. Circularity, essential for sustainable development, demands a shift from the linear “take- make-dispose” model to a regenerative approach that minimizes resource consumption and waste. The construction industry, a significant contributor to global material use and waste, faces unique challenges in implementing circularity due to its technical complexity and the wide range of stakeholders involved. Consultants, who play a crucial role in bridging the gap between technical knowledge and practical application, are central to overcoming these challenges. This study focuses on consultants and their ability to disseminate and contextualize knowledge, a process hindered by technical language, the varying expertise of stakeholders, and the multi-disciplinary nature of construction projects.
The research investigates the current applications of Generative AI, with a particular focus on ChatGPT, as a tool for knowledge contextualization in circular construction projects. Through a comprehensive literature review and qualitative data collection from semi-structured interviews with industry professionals, this thesis identifies both the barriers to effective knowledge-sharing stakeholders encounter in circular projects and the potential affordances of ChatGPT in overcoming these challenges. The state-of-the-art capabilities of ChatGPT include features such as contextual comprehension, few-shot learning, and coherent content generation, which allow it to process and present complex information in a user-friendly format tailored to the specific needs of stakeholders. Its affordances, such as knowledge retrieval, organization, and tailoring, enable ChatGPT as a powerful tool to create customized knowledge outputs, making it particularly suited for addressing the diverse and technical demands of the construction industry. The analysis of the interviews highlights that the limited understanding of circularity principles among stakeholders stems from the complexity of technical documentation, the information overload of the documents regarding circularity, and the lack of tailored information that adapts to the specific needs of different actors and projects in the construction process.
The thesis investigates the possibility of ChatGPT as a solution to these issues by dynamically tailoring technical information to match the expertise and tasks of diverse stakeholders. The research studies how ChatGPT's features and affordances in knowledge management can enhance the contextualization of circularity knowledge, improving the accessibility and usability of complex information for non-experts. This approach fosters better collaboration among stakeholders and accelerates the adoption of circularity practices, often slowed by misunderstandings and technical jargon.
The findings suggest that while the potential of ChatGPT in knowledge management is vast, its implementation is still in the early stages. The study proposes a framework for integrating Generative AI into the knowledge-sharing processes of the circular construction industry, aiming to optimize knowledge dissemination and improve stakeholder comprehension. The framework is based on tailoring the capabilities of AI to support consultants in their pivotal role of contextualizing knowledge. By addressing the identified barriers to the adoption of this tool, this thesis contributes to the ongoing discourse on sustainable construction practices and highlights the importance of technology in advancing the industry towards circularity.
This thesis concludes by offering practical guidelines for the integration of Generative AI in circular construction projects, underscoring the need for further research into its long-term implications. The proposed guidelines for integrating ChatGPT into the construction industry focus on three key phases: preparation, where stakeholders are trained to understand the AI’s capabilities; pilot testing, where AI-assisted knowledge contextualization is trialed in a controlled setting; and deployment, where the AI is fully integrated into project workflows with ongoing monitoring to ensure its effectiveness in enhancing communication and knowledge sharing. The research lays the groundwork for future studies aimed at refining AI applications in this context and ensuring that the construction industry can meet its sustainability goals through improved knowledge management practices.

One of the crucial aspects of BIM is the data rich environment connecting project information from different sub-sectors. (Mesároš et al., 2020). Therefore, developing models with consistent and trustworthy building data has gained significant importance in the industry. In contrast, incorrect or incomplete building data in a model could result in chained mistakes across disciplines, rework, or inadequate models for other stages of the building lifecycle.
Most of the improvements in BIM data in organisations take place in data quality reviews by BIM specialists. The lack of integration and complexity of existing data checking tools raised the expertise leading to assessment tools used mostly by BIM specialists. After a specialist reviews a project, corrections are communicated to the designers to solve the data issues in their models. This process is repeated until the desired quality is reached by the design team. Furthermore, missing, or wrong basic data structure can often lead to incomplete or inaccurate data checking processes.
The higher goal of this research is to produce perceivable benefits in the organisational data checking process. This is approached by facilitating the implementation of BIM standards and increasing the compliance of objects during design periods before entering the organisational review. Previous research showed that professionals would prefer to use simple dedicated quality checkers that can minimise manual tasks precisely and reliably instead of advanced software solutions. Thus, the goal is not to replace current workflows and practices, but instead to enhance basic data structures in models before entering the data reviews, by developing and implementing a new design-integrated checking and reporting tool.
The new checking process was verified and validated with specialists and modelers in three ongoing projects. This research showed that the developed design-integrated tool can produce the perceivable benefits in the organisational data checking process explained below:
•Enhancements in data quality before and after regular organisational checking reviews.
•Decrease in the duration and iterations in the organisational reviews.
•Increase of effectiveness and efficiency in detection and correction of data quality issues.
•Decrease of personnel frustration in the organisational process.
Thus, the research fulfilled the main objective to produce perceivable benefits in the organisational data checking process by developing and implementing a dedicated solution that engages designers in the process. The role-specific approach was essential to achieve a solution that meets the specific needs and system requirements of the target group, the designers. The purpose was to add a new prechecking layer to support and enhance existing data quality practices and processes. The result was a steering instrument for modelers working on the detailed design phase to involve them in identifying and correcting data quality issues.
Although the perceived benefits may vary in different contexts and organisations, the new data checking and reporting solution would raise awareness and promote designers’ engagement in the organisational data checking process, who are in a dominant position to identify and correct data quality issues.

People are the main asset of a consultancy firm, and a Project Manager is a key figure in the delivery of projects. Change Management theories suggest that the success of change efforts relies on three components: Leadership, Project Management and Change Management. Therefore, successful sustainability implementation depends significantly on the performance of a Project Manager, how well they are equipped with the knowledge about sustainability and supported with tools and internal processes. But first of all, how well they are aware of the importance of sustainability for the organisation and how strong their intention to implement the changes is.
The project manager, as an enabler of sustainability in a construction project, can contribute to the construction industry to meet sustainable development goals. To facilitate the process of sustainability implementation and create opportunities for action, more knowledge is required about current drivers and barriers for the project managers. This research investigated these drivers and barriers utilising behavioural theories.
Main results
The research design used a mix of qualitative and quantitative methodologies. The literature and organisational documents were used to study the current state of sustainability implementation in theory and practice, and at the same time, several exploratory interviews were conducted. DINAMO survey identified which barriers PM specialists encounter during project delivery. Four main barriers resulted from the survey:
• Complexity of the change
• Lack of Information
• Lack of Involvement
• Manageability of the change
Main conclusions
The study has indicated three points that can help to translate sustainability into project execution.
First, the research has shown the importance of the strategic context. Explanation of the strategic goals and their alignment with other organisational goals plays an essential role in strategy implementation.
Second, it has been concluded from the study that project management practices require significant revisions. Being a key figure in the project, PM must enable opportunities for sustainable goals. Sustainable goals should be inseparable from the project’s success, and the integration of these goals must be facilitated by sustainability leadership.
Third, the study has disclosed that the behavioural control and intention of project managers to change play a significant role in the implementation of sustainability in projects. Behaviour is directly dependent on the working environment created by strategic settings. It is, therefore, a closed loop in which strategic settings influence the behaviour, and behaviour can provide valuable information to re-adjust the strategic settings.

The increasing generation of municipal solid waste (MSW) due to urbanization and population growth has highlighted the importance of effective Municipal solid waste management. Waste sorting plays a critical role in enhancing waste quality and boosting recycling rates, aligning with the circular economy goals of the European Union. However, despite significant waste production in cities, limited separation and recycling occur, primarily due to insufficient citizen involvement. When it comes to involving citizens in sorting household waste, there has been limited research and exploration of the waste sorting behavior of college students. Given that the majority of college students reside in student housing, the research aims to understand college students’ waste sorting behavior in student housing and recommend interventions that motivate students to engage in waste sorting.

To attain the objective, the research utilized a mixed research approach, initially employing semi-structured interviews as the qualitative method and subsequently conducting an online survey as the quantitative method. Qualitative results were derived through the application of thematic analysis and subsequently served as a basis for constructing the questionnaire survey in the subsequent quantitative phase. The factors that impact waste sorting behavior in student housing were identified and quantified in the quantitative phase by employing the partial least square structural equation modeling (PLS-SEM) method.

The results revealed that the subjective norm and perceived behavioral control directly impact students’ intentions to engage in waste sorting, which in turn, indirectly affects their waste sorting behavior. In addition, the waste sorting facilities and information publicity holds a significant influence on the students’ household waste sorting behavior.

Based on the findings, it is suggested that the intervention aimed at encouraging waste sorting among students could involve enhancing the publicity of waste sorting information by providing information prompts in the communal space within student housing and distributing information through social media. Furthermore, interventions like improving the waste sorting facilities could engage students in waste sorting. Additionally, promoting communication within the student housing community and incorporating waste sorting education into the college curriculum were also suggested as interventions to incentivize students to sort their household waste.

The construction industry is shifting towards a more collaborative environment through relational contracts following the early contractor involvement approach. In the Netherlands, one of them is the bouwteam process. The peak of collaboration in bouwteam projects and the construction industry is during the pre-construction phases since there is a higher complexity due to the uncertainty and interdependence of elements. On the other hand, technology innovations opened the way to work across boundaries in a remote way, which is known as virtual teams. Taking both aspects into account, the importance of collaboration through relational contracts and the technological innovations, this research seeks to seize the opportunity to expand the traditional working scope into a virtual or hybrid one in a way that doesn’t jeopardize the performance of projects but rather improves it. Based on the problem definition and objective of the present research, a main research question is defined: How focusing on collaboration improves virtual teams in the bouwteam phase?

Due to the dynamic and complex nature of the construction industry, it is evident that the integration of processes and groups is more challenging to attain in comparison to other industries (Demirkesen & Ozorhon,2017). Therefore, there is a call for better integration of project participants and processes in construction projects (Franz et al., 2017). Consequently, organisational collaboration and integration are often considered inefficient and dependent on individuals. This inefficiency can be caused by individuals not making the right connections to gain access or obtain relevant data for the decision making process. This can be explained by the fact that the industry is renowned for its fragmentation and temporary project teams Whitley, 2006). Due to this fragmentation, it is not uncommon for parties to have their own internal silos. These internal silos contain different sorts of data and have limited connections within their own or with other project teams, resulting in bad data sharing and communication. The presence of data silos and limited data sharing affects risk awareness as this can cause unavailability of data or subjective biases in the decision-making process. As a result, the employees that make the decisions are not (completely) aware of the involved risks, which can give the impression of soundly under-supported choices (van der Meer, 2021). By utilising data sharing and ensuring the proper coordination and communication, one could take on the silo’s created by this fragmentation between and in project teams, and by doing so, one could expect to reduce the detrimental effects on risk awareness. Especially when firms are active in a multinational environment, research has shown that connections between people that cross physical boundaries can enhance opportunities to improve performance and improve entry to information (DeSanctis & Monge, 1999). That is why, one could argue that data sharing could contribute significantly to risk awareness among team members. To investigate this, the following research question has been formulated: How does data sharing in intra-organisational project networks contribute to risk awareness in the tender phase?

Due to the stricter sustainability requirements and associated governmental regulations, the real estate development process in the Netherlands is becoming increasingly complex, narrowing the real estate developer’s opportunity space and increasing the uncertainty regarding the feasibility of the real estate development project. Recently developed AI powered generative design tooling could potentially be used to decrease this uncertainty during the concept design process. However, there is currently no scientific method that helps the (concept) developer evaluate the concept design with the use of this AI powered generative design tooling and make decisions based on more objective design criteria instead of estimated guesses. The goal of this research is to develop an evaluation framework for the concept design process that can be used by real estate development professionals in the Netherlands, during the concept design stage of inner-city apartment buildings, to make more informed choices (based on additional objective information) earlier on in the design process to decrease the uncertainty with regards to the feasibility of the real estate development project. The framework will be developed considering the current visualisation and simulation abilities of AI powered generative design tooling.

Using the concept design evaluation matrix, the real estate developer and other relevant stakeholders are encouraged to 1) carefully determine what they consider important for the specific real estate development project, taking into account the site-specific characteristics, prior to the evaluation and decision-making process. 2) By subsequently focusing on these priorities during the location/market investigation and concept design process (for example by focusing on identifying any uncertainties and/or risks related to environmental factors such as noise pollution), the expert panel expects that the developer 3) can better steer the process because the different interests are clear and the developer can better evaluate the results with stakeholders by using the analysis results and ranking scores of the different parameters in negotiations/discussions. The expectation is that the evaluation matrix combined with the use of AI powered generative design tooling will decrease the uncertainty regarding the feasibility of the real estate development project, and will provide the developer with a handle to ultimately achieve an even better real estate development result.

The Architecture, Engineering, Construction and Operations (AECO) industry can be descripted as a fragmented industry, with relatively low productivity and efficiency. Digital solutions like Building Information Modeling (BIM) can increase an organization's productivity. However, the Built Environment has been slow to adopt digital transformation, due to insufficient information management. Existing literature concentrates on addressing this challenge, by focusing on a single aspect of information management rather than providing a comprehensive picture of all the procedures, parties engaged, information, formats and platforms used as well as their interdependencies. Therefore, the objective of this graduation research is to determine the workflows for information management to allow digitization across the whole lifecycle, by examining multiple aspects. The case study findings lead to the creation of a process map, demonstrating more efficient workflows to be followed, by linking the distributed information between the different parties involved throughout the several project stages, while also considering each party’s digital ambitions. The main processes identified during each project stage concern the production of information deliverables by the respective party, using the suitable format. As both geometrical and non-geometrical information is generated during the different project stages, different formats are used, i.e. information models and documentation. Subsequently and at the end of each stage, the respective information is shared to other parties during specific information exchange moments. A collaborative environment is used by the different parties, both during the production and information sharing. Concluding, as digital transformation becomes even more widespread, a growing number of organizations strive for effective information management. To acquire a more reliable view on the subject, it is necessary to look at several aspects at once, hence the development of the proposed process map. To increase the validity of the outcome, more research and elaboration of the process map's elements is advised. Recommendations for the construction industry, with regard to the incorporation of digital ambitions, are also provided together with suggestions for a further enhancement of the company’s information management.