As Dutch infrastructure continues to age and complexity increases, conventional document-based approaches are reaching their limits. This thesis develops a structured, knowledge-based Model-Based Systems Engineering (MBSE) framework that addresses key socio-technical dimensions by integrating Semantic Linked Data within a Common Data Environment (CDE) to support the governance and execution of infrastructure renovation and replacement programmes. The framework primarily explores technological solutions with the right capabilities, while systematically considering the socio-technical conditions required for successful adoption. Unlike existing MBSE practices, it introduces a semantic and knowledge-driven foundation that does not yet exist in the current infrastructure sector. It focuses on practical applicability and aims to enhance interdisciplinary coordination, lifecycle traceability, and long-term information reuse and knowledge sharing across organisational boundaries. A case study involving a movable bridge illustrates how semantic modelling can be applied in practice.

A key contribution of this research is the demonstration that Semantic Linked Data enables stronger connections between Systems Engineering, asset management, and programme-level governance. It facilitates integrated decision-making, participatory system approaches, and open communication through shared semantics across disciplines and stakeholders. While the technical foundations are maturing, the study highlights a lack of structured understanding among Systems Engineers regarding the diversity of available tools and their effective application. Moreover, organisational aspects and the practical embedding of MBSE in real work processes are often overlooked.

The thesis concludes with strategic recommendations for gradual implementation and collaborative learning, including the formation of a Semantic Linked Data consortium led by asset owners. Such a consortium is critical for the consistent development and maintenance of ontologies and interoperability standards across the programme. Further exploration is needed into how small, incremental and iterative efforts can deliver visible value to diverse stakeholders, how the desired organisational change can be guided, and how the transition to new digital technologies can be made feasible within complex, multi-actor environments. To ensure coherence, socio-technical interdependencies must be developed in alignment with the MBSE system model (language, method, and tools). The proposed approach, based on structured semantic modelling, provides a scalable pathway towards a more adaptive, efficient, and data-driven infrastructure sector.

Changes in weather patterns due to climate change, such as increased precipitation intensity and hotter and dryer summers, are already occurring despite efforts to reduce emissions. Climate adaptation (CA) is a crucial method to deal with these effects of climate change. An example of an endorsed CA measure is in increasing and improving urban green space (UGS). The Dutch government aims to promote participation and stimulate citizen action, but municipalities have not adopted this outlook on citizen action yet. An example of such actions are Green Citizen Initiatives (GCIs), which are valued by municipalities because of the creation of public value in non-state and non-market ways, contributing to CA by creating and improving UGS. Municipalities can facilitate these initiatives by maintaining ownership of the initiative and UGS with the initiators, whilst steering and supporting the process and providing resources. Recent literature has identified barriers that affect the process of realising GCIs. It showed that there is no clear, common or singular approach employed by municipalities to facilitate GCIs. Therefore, this thesis aims to provide insights into the process of realising GCIs and the barriers municipalities and initiators face to improve facilitation of GCIs. This is achieved by answering the following main research question: How can Dutch municipalities facilitate green citizen initiatives to contribute to local climate adaptation?

The process of facilitating GCIs was defined from the perspective of GCI initiators based on literature, including the following five phases; Gathering Support, Gathering Resources, Design, Execution and Maintenance. After each phase a moment of evaluation should take place to decide if returning to an earlier phase is needed. Semi-structured interviews and a card-sort were used to gather practical data on this process. Thematic analysis of this data revealed eight key barriers. Recommendations to mitigate these barriers were identified, with which the Citizen Empowerment for Climate Adaptation (CEfCA) framework was developed. Municipalities can apply this framework to reduce the negative effects of the barriers and increase the number of successful GCIs for CA. This framework was validated by an expert discussion with a participant from front running municipality Arnhem, that currently already actively facilitates GCIs.

This thesis attempts to fill the gap in scientific literature on how GCIs are facilitated and how to improve this in practice. The CEfCA-framework provides recommendations to improve the process of realising GCIs, but a change in attitude towards CA with instead of for citizens may be needed to effectively implement the proposed framework. Further research is recommended on how this systemic change in outlook can be achieved.

With the pressing need to address climate change and reduce greenhouse gas emissions, governments around the world have set ambitious climate goals, necessitating a transi- tion to renewable energy sources. In the Netherlands specifically, the government has recognized the potential of district heating networks as a vital strategy for decarboniza- tion, given that 81.5% of domestic energy consumption is dedicated to thermal loads. The development of new energy assets, the integration of storage solutions, the use of in- termittent renewable energy sources, and the inclusion of multiple energy carriers such as fuels, power, and heat, collectively referred to as hybrid renewable energy systems, have made the energy infrastructure more complex than ever before. The challenge lies in understanding the implications of integrating diverse renewable assets and optimiz- ing the system for both reliability and economic feasibility, as optimal sizing in hybrid renewable energy systems remains insufficiently understood. This study aims to answer the following research question: What is an effective approach to capacity optimisation in renewable energy systems that integrate thermal and power sources with hybrid energy storage? This study adopts both qualitative and quantitative research approaches, employing multi-actor analysis, system design, optimization techniques, and data analysis to de- termine the optimal sizing of the identified system components. The study integrates real-world data from Eneco’s district heating network in Utrecht, employing optimisa- tion models to minimise costs while ensuring a reliable supply of heat for the connected households. The research addresses sub-questions related to optimisation techniques, hybrid system design, and operational performance. The study results show that a systems engineering approach to capacity optimization in hybrid renewable energy systems can provide robust solutions to the challenges of balancing reliability, economic feasibility, and sustainability in energy infrastructure. By taking an integrated approach that spans multi-actor analysis, system design, opti- mization design, model development, and result analysis, relevant system components can not only be identified but also capacity-optimized. Throughout the study we have shown that single-layer optimisation using mixed integer linear programming provides the most accurate results in diverse hybrid systems with complex asset dispatch. Fur- thermore, we identified masked time resolution adjustment as the highest-performing simplification technique, achieving a 91.58% reduction in solution time while showing minimal differences in results compared to full optimization. For Utrecht’s district heat- ing network specifically, we showed that a renewable hybrid system, relying on thermal energy storage, power-to-heat, and CO2 compensated fuel-to-heat, is economically and technically feasible up until an operational power-to-heat fraction of 85%.

Purpose of the Study
This thesis addresses the growing challenge of urban heatwaves by developing a decision-support system (DSS) called NBScenarios, which helps policymakers implement Nature-Based Solutions (NBS) to mitigate urban heat island effects. This study focuses on Paris as a study case, with the overarching goal to propose different options that optimize the configuration of green roofs and trees along streets (replacing parking spaces) to effectively reduce urban heat islands. These configurations balance differently goals that are challenging to reconcile: maximizing the cooling effect, respecting budgetary constraints, prioritising adaptation benefits to the most vulnerable population, while guaranteeing access for all urban citizens to cool spaces.

Problem Statement
Despite the potential of Nature-Based Solutions for urban climate adaptation, their implementation is blocking at the decision-making stage. Existing decision-support systems (DSS) often lack social considerations, limiting their real-world effectiveness. Many DSS are not adaptable across diverse urban contexts and do not integrate multi-objective optimization, which is essential for balancing conflicting priorities like costs and environmental benefits. Moreover, DSS are often complex, limiting stakeholder engagement. This highlights the need for modular, expandable tools that support informed, inclusive decision-making.

Research Approach
This thesis employs a multi-objective optimization (MOO) approach, utilizing the ε-NSGA-II algorithm and integrating spatiality. The selection and definition of case-relevant nature-based solutions, objectives, and constraints, is structured by the XLRM framework, in particular. A spatial grid (100m x 100m cells) covering Paris allows for detailed urban data to be processed and integrated into the DSS. The DSS generates a range of contrasted Pareto-optimal solutions, balancing trade-offs among objectives and corresponding NBS mapping, providing policymakers with a diverse range of options.

Key Findings
The DSS produced a range of optimal and diverse options for NBS implementation in Paris, with green roofs and on-street parking transformed into street trees. Results showed typical values for cooling effects ranging from 0°C to 7.5°C, initial costs spanning from €500 million to €3.5 billion, and clear trade-offs between maximizing cooling and minimizing costs. Solutions effectively revealed the spatial distribution of cooling impacts and highlighted disparities between areas with vulnerable populations and high cooling potential.

Conclusion
NBScenarios provides a flexible and adaptable framework for policymakers to balance environmental, economic, and social objectives in urban climate adaptation. While the study focuses on Paris, the DSS is designed to be applied to other cities facing similar climate challenges, allowing for scalability and adaptability. The findings highlight the system's ability to inform critical policy decisions related to heatwave mitigation, including cost considerations and social justice factors, facilitating trade-offs between competing priorities.

Recommendations
For future work, the DSS could incorporate uncertainties and include other NBS types or objectives. Continued testing in different urban contexts is also recommended to refine the system and ensure its broader applicability. The creation of an interactive dashboard, based on the DSS current output, could further improve stakeholder engagement and decision-making.

Significance of the Study
This research advances urban climate adaptation by integrating multi-objective spatial optimization into decision-support systems for nature-based solutions. Academically, it addresses social factors and NBS mainstreaming while offering a modular, interdisciplinary DSS adaptable to other cities. Societally, the study enhances policy-making and stakeholder engagement, emphasizing social justice in climate strategies. The DSS enables cities globally to scale NBS effectively, bridging gaps between technical design and actionable, socially responsible urban resilience policies.

Math Anxiety (MA) is some of the most notable mental health issues. The causes and development of MA are complex and inconclusive. This study highlighted that language patterns differ between people with high and low MA. Especially, the word categories positive emotion, insight, articles and linguistic dimensions. This study included two personality differences (self-esteem and curiosity) to better explore the inner world of people with high and low MA through their language patterns. Self-esteem and curiosity moderate the relationship between MA and people’s language patterns.

Maintaining a healthy eating behavior can be challenging, especially under stressful situations. Self-control plays a pivotal role in this struggle, since it allows one to resist immediate desires in pursuit of higher-level goals. The level of self-control can differ among individuals, with varying degrees of “strength”. This strength can be likened to a “muscle”, which has specific power and endurance and enables the exertion of self-control at a certain time. Power is linked to the individual situation-invariant levels of trait self-control, which enables the initial exercise of self-control at a particular moment. However, the maintenance of self-control over time is attributed to “muscle endurance”, which is represented by individual depletion sensitivity. Like a muscle that can become depleted after exertion, the exercise of self-control can deplete available cognitive resources, leading to ego depletion, decreased self-control capacity, and thus unhealthy food choices. Food recommender systems are considered effective tools for promoting healthier choices and may be seen as nudges that make healthier options more salient. Many studies have demonstrated the effectiveness of recommender systems and digital nudging in influencing users’ food choices in the direction of healthier ones. Attribute frames, including positive and negative types, are popular information nudges in the health field. Nonetheless, their impact on eating behaviors remains a controversial issue. Evidence has shown that dispositional factors, such as self-control levels, may moderate the effectiveness of attribute frames.

This study aimed to examine to what extent attribute frames steer human food choices toward healthy ones, and in what way self-control levels influence that relationship. An online experiment was conducted, utilizing attribute frames as the independent variable, food choices as the dependent variable, and depletion sensitivity and trait self-control as moderating variables. Participants were randomly provided seven different food options, each of which came with an attribute framing message, to evaluate the effects of positive and negative attribute frames on healthy food choices. The Depletion Sensitivity Scale (DSS), and Brief Self-Control Scale (BSCC) were used to assess the individuals’ levels of depletion sensitivity and trait self-control, in respect. The findings revealed that positive attribute frames effectively encouraged healthy food choices, while negative frames had a relatively lower impact. Depletion sensitivity moderated the relationship between attribute frames and healthy food choices, suggesting that individuals with low depletion sensitivity were more likely to select healthy options under positive framing conditions. However, no significant moderating effect of trait self-control was observed. Lastly, the relationship between attribute frames and food preference was found to be significantly moderated by gender differences. In conclusion, this study provided evidence supporting the influence of attribute frames on healthy food choices and the moderating role of depletion sensitivity on this relationship. The significance of considering gender differences in the analysis of the effect of attribute frames on food preferences was also illustrated.

Reducing meat consumption is considered a crucial and urgent element in terms of reaching climate targets, public health and the protection of animal welfare. Especially in industrialised countries, it is considered the most important recommendation in the field of sustainable food consumption. The transition is difficult to realise, as meat consumption is a complex area involving numerous institutions and stakeholders with conflicting interests and consumers with very different opinions and behaviour. Meat consumption is the result of diverse individual factors, while being rooted in culture and social norms. It is thus considered challenging for policymakers to set this transition in motion, as intervening in the system comes with uncertainties, a lack of understanding, and possibly resistance on both the stakeholder and consumer side. Simulation models can be supportive in such a case, as they can support an increased understanding of the system, while being able to deal with the transition and all its complexity. Specifically agent-based models can be a suitable tool to support policymakers in making sense of this transition, as this type of modelling can deal with heterogeneity of consumers and is able to provide insight on how various policy interventions affect the individual and overall system behaviour.

The process of developing a simulation model for policy support using a technique that is not widely understood and accepted yet, can be challenging. Participatory modelling is a method in which stakeholders are involved throughout the modelling process to promote social learning and achieve model improvement. In this thesis, a participatory modelling process was designed to identify the potential use of agent-based modelling in reducing meat consumption in the Netherlands. The study focused on including elements of behaviour in the ex-ante evaluation of policy with the use of an agent-based model.

An agent-based model representing meat consumption behaviour of Dutch young adults was evaluated and improved together with a group of participants. Knowledge elicitation with the stakeholders working in the field of policymaking, research, and academia occurred through interviews, workshops, and mind mapping. The key findings of these sessions were that the participants desire to gain understanding on the socio-cultural factors influencing meat consumption and how these can be targeted with interventions. To respond to this lack of knowledge, the agent-based model was adjusted to capture meat consumption behaviour according to the COM-B wheel. This is a theoretical framework in which behaviour is categorised into physical and psychological capability, reflective and automatic motivation, and physical and social opportunity. In the agent-based model, consumers select and consume meals from a supermarket, take-away, or restaurant. Dietary preferences are based on knowledge and skills, environmental and animal welfare concerns, income, desired meat consumption, and social norms. The consumers are able to adapt their dietary preferences through reflection processes. The individual profiles were empirically grounded with input data from a cross-sectional questionnaire.

The agent-based model was used to study the effectiveness of various policy pathways that were formulated in consultation with involved participants. The policy pathways included in this study were various meat price increases, an increase of the vegetarian representation in the food environment, a social marketing campaign targeted at social norms, and combinations of the three. Of these interventions, meat price increases showed to be most effective in reducing the overall meat consumption. Increasing the vegetarian representation in the choice was effective, but to a lesser extent. The social marketing campaign on social norms showed no direct effect on the amount of meat consumed. When interventions were combined, even higher reductions were observed.

This study sheds a light on how the field of policy and science can together work on a gained understanding of this complex transition, with the use of agent-based modelling.

Open research data sharing and reuse can bring more transparency to the research, save researcher time by preventing repetitive data collection processes, and lead to more collaborations. However, open research data sharing has not become common practice in some research fields such as Epidemiology due to a variety of issues. We propose that the negative impact of issues in front of open research data adoption can be tackled by the right institutional and infrastructural instruments. The objective of this study is to understand the roles that infrastructural and institutional instruments (or their combinations) can play in promoting open research data sharing and (re)use behavior in Epidemiology. To achieve this objective, first, we conducted a systematic review investigating what instruments could be used to lead researchers to open data practices. Then, to examine the availability and importance of the proposed instruments in Epidemiology, we conducted a case study that includes interviews with Epidemiology researchers and a research data management consultant who work at various University Medical Centers (UMCs) in the Netherlands. We also evaluated the transferability of our case study findings in a workshop with data stewards and research data officers that work in different research fields at a Dutch research university. To our best knowledge, this study is the first study that focuses on the field of Epidemiology while examining the roles of instruments in open research data adoption based on field-dependent characteristics. Our study shows that researchers in Epidemiology do not openly share or reuse research data due to many different reasons relating to the legal, cultural, technical, and organizational issues. Many of the potentially effective instruments are not fully within the reach of Epidemiology researchers. Researchers do not have sufficient access to research data managers, search engines with satisfactory functionality, overarching registries, and reward systems for data sharing contributions. Institutional instruments can support open research data adoption by reversing the lack of an open data sharing culture with the right incentivization approaches, by the provision of financing, and by actively supporting researchers via data stewards, research data managers, libraries, and data privacy officers. Infrastructural instruments have the potential for supporting open research data adoption by increasing the findability and interoperability of the research data, and making researchers’ interactions with data infrastructures easier. Our study shows that institutional instruments (especially those that target enhancing the open data sharing culture and creating data sharing incentives) are in a more vital position to open research data adoption. Nevertheless, considering that many instruments complement one another, to increase the effectiveness of the instruments, they should be combined. We recommend conducting case studies in other contexts (e.g. involving policymakers, infrastructure providers, etc.), considering that the issue that we examined in this research is a multi-actor issue and that in this single case study, we only focused on researchers.

Over recent decades there have been advances in the research behind adaptive policy approaches. More recently, emerging qualitative approaches for managing deep uncertainty has drawn the attention of planners in the water industry, particularly in water utilities. Despite interest from both the water industry and the research community to see these novel approaches applied, there have been limited applications and no published guidance to support the operationalisation of these approaches in water utilities. This thesis seeks to bridge this gap by answering the question: “What are the factors influencing the adoption of adaptive policy approaches by water utilities?” To answer this question, a design science approach was used to understand current barriers and enablers to the adoption of such methods in water utilities, and to design a framework to support adoption of adaptive approaches. This work was conducted through a grounded theory analysis of interviews of relevant water utility practitioners in Australia and the Netherlands and members of the decision making under deep uncertainty and adaptive planning research community internationally. The outcome of this study is a maturity framework of barriers and enablers to the uptake of adaptive approaches in water utilities, designed to support utilities and researchers in evaluating their level of adoption and to identify strategies for increasing the implementation of adaptive approaches where appropriate.

In the last decade many development projects focused on agricultural development, wherein smallholder farmers are challenged to change their traditional practices and make use of new technologies and techniques. However, it is seen that smallholder farmers are not able or willing to apply learned practices or increase production. One reason for this is that interventions focus on capacity building in a way that they include training in knowledge and skills, but they do not take into account the values, attitudes and beliefs of farmers and their surroundings. Therefore, this research answers the following research question: Can capacity building be included in agricultural projects focused on smallholder farmers in developing countries, and if so, how? A case study about women smallholder farmers in Kerala, India, is conducted. Findings show that not only the knowledge and skills are hindering a woman smallholder farmer’s capacity to grow, but also her internal motivation, level of empowerment, ability to take risks, the perception towards farming and informal institutions are important for her capacity. Hence, this study proposes a framework with components to consider when developing a strategy for capacity building of women smallholder farmers. This study provides a better understanding of the importance of certain components for capacity building and can help project initiators when they are to include capacity building in agricultural development projects to develop sustainable projects.

Risk management, a process aiming to decrease or eliminate the likelihood and impact of unwanted effects on a project during its lifecycle, has become highly significant due to complexity, uncertainties and high competition. Numerous tools and techniques have been developed for successfully implementing risk management. However, risk is frequently inadequately addressed and existing tools and knowledge are not used and exploited at a high degree. This research examines current practices of the risk management process and identifies barriers and opportunities pointing to improve its implementation through the exploitation of information and knowledge of past projects. The investigated knowledge and information focus on project drivers, characteristics and other KPI’s. The empirical study of the research incorporates the analysis of seven risk registers/projects of Witteveen+Bos and development of interviews of W+B risk and project managers involved in the analyzed projects. Subsequently, validation of the results is achieved through extra interviews of risk management experts external to Witteveen+Bos and a conceptual framework is developed. The last step of this qualitative research entails the validation of the conceptual framework which is tested with a case study implemented through an online workshop and a questionnaire.
By analyzing the literature findings and empirical data, it is concluded that information and knowledge management during the implementation of risk management are not adequately developed while simultaneously constitute a major barrier to its success. Therefore, a conceptual framework that incorporates a way of structuring risk related information is developed while targeting to also tackle certain identified barriers of the current procedures such as the understanding of risk structure to the whole project and the adequate exchange of information during the process.
The framework suggests a higher quality use of risk registers while structuring information and afterwards exploiting the information for capturing lessons that can be reused in future projects. It provides a way of clustering information during the development of projects and at the same time incorporates the development and use of risk networks. The development of risk networks is initiated by grouping risks based on their source. The aforementioned sources are selected based on the results of the research and named ‘Key Sources’. The aim of using risk networks is to increase risk insights while displaying risk exposure visually. In this way barriers such as lower understanding of risks, incomplete communication of risks as well as short term view of risks may be addressed or eliminated. Another part of the framework concerns the development of evaluation concerning the process as well as the description of risk related information. It is concluded that even though, there is a wide array of identified barriers to the effectiveness of risk management implementation, overcoming information and knowledge management barriers can constitute a higher level way of overcoming other barriers as well.

Dietary habits refer to the set of choices or decisions one makes regarding the foods consumed. They include choices and decisions on what to eat when to eat, how much to eat, and where to eat. Taste preferences, food diversity, frequency of meal consumption, portion sizes, snacking behavior, and meal skipping all have an impact on this. According to research, not only physiological but also psychological elements such as emotions, stress, and personality differences influence our dietary choices. Many studies have been conducted to determine how to alter problematic eating choices by regulating emotions. Understanding one’s personality type, on the other hand, can help someone to become more aware of the foods liked and disliked. This is the first study to look at the combined effect of emotion regulation strategies and, in particular, Type-D personality type on eating choices. This thesis focused on women from various ethnic origins. The study looked at which emotion control strategies, such as cognitive reappraisal and expressive suppression, were employed. Individuals were also assessed on the extent to which they were in the possession of a Type-D personality type by scoring on the two variables in this model, which are negative affectivity and social inhibition. This study hypothesized that people with Type-D personality, or those who score high in Negative Affectivity and Social Inhibition, employ less emotion regulation strategies and make poor dietary choices. The main findings confirm the hypothesis. As per the findings, reappraisal strategies outperform suppression methods. It was discovered that when reappraisal methods were used, women preferred more healthy food items like vegetables. However, when suppression strategies were used, unhealthy food items such as snacks were favored. Furthermore, the study looked at how age, a control variable, affected the use of emotion regulation strategies in food choices. Younger women were found to apply more reappraisal strategies for healthier foods, whereas older women used suppressing methods. In conclusion, this study confirmed previous research on the independent influence of emotion regulation and personality type on diet, and it also added new insights to the research by examining the combined effect of these factors on diet choices.

Accidents in buildings happen frequently and if people are not evacuated in time, this can have major consequences. The behaviour of building occupants is one of the most critical determinants herein.
Evacuation behaviour consists of two phases: the response phase and the evacuation movement phase. During the response phase, a building occupant is notified of an incident and performs a series of information and action tasks. When the response phase is finished, a building occupant will initiate movement towards an exit or safe place during the evacuation movement phase.
In this thesis, the focus is on response-phase behaviour. There are many factors influencing response-phase behaviour, four of these are: culture, cues, affiliation and setting.
Culture is defined as "the collective programming of the mind distinguishing the members of one group or category of people from others". For this research, national cultures have been considered.
Cues are any kind of changes in the environment, which indicate that something is not normal. Affiliation encompasses the tendency for people to seek friends or colleagues. Lastly, setting limits the knowledge obtained and the type of actions which can be performed based on the location of the building occupant.

The following research question has been answered: " How does culture, in combination with cues, settings and affiliation, influence response-phase behaviour and time and total evacuation time ? ”. To answer the research question, a case study was introduced. In this case study library evacuations have been considered in Czech Republic, Poland, Turkey and the UK. Within the context of this case study a questionnaire and an agent-based model have been developed.

The results show that that there are significant differences in the number of response tasks being performed. Turkey performs the highest number of response tasks, followed in a decreasing order by Poland, Czech Republic and the UK. Furthermore, it has been found that response behaviour in all countries is influenced by cues, setting and affiliation, which results in significant differences between the countries for their response and evacuation time. It has been found that, as with the number of response tasks, Turkey has the highest evacuation and response times, followed in a decreasing order by Poland, Czech Republic and the UK. Lastly, it has been found that affiliation and being informed by a staff member highly affect response and evacuation times, while the setting and seeing fire do not. The degrees to which these factors influence response and evacuation times differ per country.

Overall, this research acknowledges the importance of performing cross-cultural research for evacuation behaviour. It has shown the need for policy makers and emergency planners to discuss effects of culture on evacuations. Additionally, it provides a new approach to study the effect of cultures, in combination with cues, setting and affiliation, on response-phase behaviour and response and evacuation times.

Anxiety is one of the most widespread and dangerous mental health disorders in developed and underdeveoped countries, affecting a wide number of college students all over the world. If not correctly treated in time, it might procure irreparable damages in people’s life, leading to drastic consequenses such as depression and suicidal intentions. However, although some students seek for medical consultation, only one quarter of them is able to have access to clinical treatments. At the same time, chatting apps gradually became a new communication trend during the last few years, resulting in the development of a new cutting-edge technology named conversational agents. After several studies, this technology has been found to be a possible solution for the healthcare imparity between demand and supply. With this invention, students might have the possibility to chat with a sort of “online therapist” anywhere and anytime they feel the need, without stigma or judgement barriers. In order to successfully implement these conversational agents, the therapeutic alliance between the doctor and the patient should be recreated as accurately as possible. Personality seems to be an important factor for the success and eventual satisfaction in the whole treatment. The present research – through LIWC software – explores the extent to which students use different linguistic patterns in an expressive writing task depending on their personality and mental health status. This study hypothesized that students sufffering from Generalized Anxiety Disorder (GAD) use different words than mentally stable students, and that their linguistic patterns are further influenced by their behavioral activation or inhibition systems. The main findings were in line with these two hypotheses. Based on the results, both students affected and not by GAD use different words specifically depending on their BAS levels. In conclusion, as predicted by previous researchers, personality is well-reflected through language styles: each student with a specific behavior, mental health characteristic, and even nationality expresses him/her self with different linguistic patterns.

Chatbots have been considered as one of the leading technologies in the e-commerce domain as virtual shopping assistants able to guide customers throughout the entire shopping experience automatically. However, this technology is currently registering a high failure rate, and several users are still skeptical of its effectiveness. One of the reasons for this low performance lies in the fact that chatbots have a poor human-likeness that negatively influences customer perception of the technology. Secondly, the low level of personalization does not allow for tailored services based on customers’ needs and requirements. Previous studies discovered that it is possible to attach specific personality traits to chatbots in order to increase their human-likeness. Besides, other researchers have discovered the importance of service personalization as a distinctive requirement for successful e-commerce businesses. Depending on consumers’ decision-making behaviour, scientists have found that different services lead to different levels of customer satisfaction. The present study explored the two sides of Human-Computer Interaction with the final aim of understanding how to better align chatbot personality with human decision-making personality. Two different chatbot personalities (neutral and extravert) were created and randomly assigned to different users. During the experiment, participants had to complete a real chatbot conversation focused on dress shoes and were asked to conduct a post-interaction questionnaire to assess their satisfaction. Results showed that it is possible to effectively attach an extravert personality into a chatbot conversation through the use of language, emoticons and GIFs. Moreover, participants with different personal decision-making behaviour and gender registered different levels of customer satisfaction. Finally, the chatbot neutral personality registered different level of customer satisfaction depending on gender and personal decision-making behaviour. These findings support the literature by analyzing the complementary relationship between chatbot and human personalities. Future studies could use these findings to develop chatbot experiences that better fit with customer needs and requirements.

Digital technologies have enabled uninterrupted mass persuasive communications everywhere and anytime, aiming at convincing people to change their beliefs, thoughts, and behaviors. Research has shown that persuasive technologies are most effective when the messages and means are tailored to people’s recipients’ unique characteristics, particularly personality. Previous studies have thus investigated the one-to-one relationship between the Big Five personality traits and influence styles—the engines behind any personalized persuasive technologies. Prior investigations yielded partially inconsistent results, potentially because the Big Five at the trait level is too broad an instrument in characterizing individual differences. This thesis drills down from personality trait to personality aspect – the next level of analysis in the personality hierarchy. The present study examines which personality aspect is most sensitive to which influence styles, generating a matrix of connections between personality and influence. Notably, aspects of Agreeableness and Conscientiousness were found to be most strongly related to influence styles. The findings refine existing theoretical knowledge of the relationships between personality and influence style. Future designers could utilize these nuanced associations between personality aspects to create more personalized, and powerful persuasive technologies. Ethical implications of the findings are discussed.

Today’s increasing complexity, rising interconnectivity and larger systems in engineering require new approaches and methods for effective engineering. This is also the case for the technological installation in infrastructure sector (TII), which designs technical systems for infrastructural civil structures. To assist in engineering, Model Based System Engineering (MBSE) can be implemented that provides more control and linkage by means of modelling. The implementation process for MBSE is limited described in literature, especially for the TII sector. Desk research helped to understand and characterize the challenges of the TII sector. By means of in-depth interviews with Siemens Mobility engineers next, requirements were developed. Based on those requirements a framework for implementation of MBSE was constructed that consists of eight building blocks. An implementation process was constructed that puts the framework blocks in order and adds more information for implementing MBSE. The main component, the actual modelling, is split up into technical and process modelling. The technical modelling is fed by the choices and interactions of the process modelling. In the implementation process described which framework blocks are important at what moment, as well as update characteristics of the eventually MBSE environment. In the end, the MBSE methodology and the designed process with framework blocks seem promising for maintaining control of future engineering projects. It provides structure to for setting up the new engineering methodology for the TII in special.

The oil and gas industry is seeking to improve safety on its current operations procedures (Choudarki, 2012). From all oil and gas operations, Topside Installation Processes (TIP) are the only offshore activity that counters one of the golden safety rules, “do not stand or walk under suspended loads” (Peuscher & Groeneweg, 2012). As a consequence, marine companies are seeking to improve these processes through different technological solutions (Heerema Marine Contractors, 2014). TIP generally consist on the lifting of a heavy module, topside, and its placement on a fixed structure on the sea, jacket (Hee et al., 2007). Traditional positioning tools such as bumpers and guides are not suitable for these type of processes given the heaviness and big dimensions of topsides (Heerema Marine Contractors, 2017). As a consequence, part of the vessel crew is located on the jacket, under the suspended topside, to guide the positioning processes (Breidablikk, 2010). TIP imply the presence of crew members under a suspended load, which is contrary to oil and gas companies’ safety policy. The offshore industry is currently investigating ways to circumvent having personnel on the jacket during topside installations (Heerema Marine Contractors, 2014). The implementation of a camera-based augmented reality positioning tracking system could fulfil the current safety requirements. The use of augmented reality as a positioning tool is a completely new technology that has never been used before in this domain. This research explores the potential expected benefits of the use of an Augmented Reality Positioning System (ARPS) during Offshore Topside Installation Processes (OTIP). This research also investigates the system’s usefulness and the users’ system perception on its usability in OTIP. Moreover, it explores the implications and factors that should be considered in order to successfully implement the ARPS in this type of processes. The research is based on a case that relates to the first augmented reality positioning system for topside installation processes, that is being developed by TWNKLS and Heerema Marine Contractors. The research methodology is based on data collected from different experiments and interview processes. The conclusions include discussion about the benefits, usability and implications of ARPS in OTIP, and recommendations for the ARPS developing companies and for future research. Key words: Augmented Reality, Innovation, Topside Installation, Safety, Offshore, Positioning Processes.