Open Source Software security depends on a small, largely volunteer workforce of maintainers who triage incoming vulnerability reports. Since 2024, AI-generated reports have disrupted the assumption that surface quality signals underlying substance, something that recognition-based triage depended on.

This study investigates how AI-assisted security reports affect OSS maintainers and triage practices through twenty semi-structured interviews analyzed using Reflexive Thematic Analysis. Five themes emerged: a temporal shift in report quality, an evaluation crisis and adaptive response, asymmetric cost distribution, strain on the expertise pipeline and ecosystem viability concerns.

Maintainers independently converged on reproducibility as the signal AI cannot fake, began scrutinizing reporter identity alongside report content and deployed AI-assisted pre-triage while preserving human final judgment. Five practical recommendations are offered which are grounded in practices maintainers had already developed independently. ... Read more

Organizations put data quality governance in place to keep their data fit for use, yet when a concrete data quality problem arises, the response inside the organization often runs differently from what the designed arrangements prescribe. This research examines how client organizations across the public and private sectors enact the response to data quality issues and where that enactment diverges from what governance frameworks prescribe. It traces the full lifecycle of a data quality issue across six stages: detection, ownership assignment, escalation, prioritization, remediation, and learning and feedback. The study is exploratory and qualitative, grounded in Practice Theory, which distinguishes the formal practices meant to govern each stage, the praxis through which the work is actually done, and the practitioners who do it. Evidence comes from eleven interviews with data consultants describing client engagements, collected with the Critical Incident Technique and analyzed using Template Analysis, covering nineteen issue-response episodes across sectors including banking, healthcare, manufacturing, and the public sector. The central finding is that formal governance designs and the enacted response operated as two distinct layers rather than as one system, held together by practitioners who translate the frameworks into action rather than implement them as written. Issues moved through the lifecycle when an actor with real authority engaged, through internal mandate or external regulation, instead of because a process moved them. Known imperfections were routinely tolerated where the provable cost of fixing outweighed benefits that were hard to show in advance, so the cost-of-poor-quality argument could run in reverse. The findings describe consultant-mediated settings and are meant to transfer rather than generalize. The study contributes an empirical account of the end-to-end issue-response process, which no prior study in the reviewed literature had centered on, and gives governance designers a grounded view of where formal mechanisms hold and where informal practice does the work. ... Read more

Managers of established technology firms hear the same advice from many directions: a broad and varied knowledge stock drives innovation, and widening the portfolio opens new room to grow. At the same time, a firm must keep refining what already works to stay efficient. Underneath these two demands sits a simple question that turns out to be hard to answer: Does spanning more technical fields help a firm break into genuinely new ground, or does it mainly help the firm do more of what it already does well? Innovation research distinguishes between exploration, the search for knowledge new to the firm, and exploitation, the refinement and reuse of existing knowledge. The answer shapes how firms should invest in the structure of their knowledge base.

This thesis studies two features of a firm's accumulated knowledge base. The first is breadth, defined as the number of distinct technical fields in which a firm operates. The second is coherence, which describes how closely related those fields are. The thesis tests the proposed coherence paradox: that the relatedness supporting efficient refinement may simultaneously limit exploration because genuinely novel knowledge often emerges from combining distant fields. Under this view, breadth and coherence would push firms toward different innovation strategies.

The argument is tested using a large sample of medical technology (MedTech) firms and their patents between 2007 and 2022. This setting allows both breadth and coherence to be measured directly and followed over time. Knowledge depreciation is incorporated through rolling time windows, and additional analyses using longer lags confirm that the findings are robust to this choice. Exploration is measured using three complementary indicators because no single measure captures the concept completely.

The results do not support the coherence paradox. Firms with broader knowledge bases perform more exploitation while also showing higher levels of exploration on the measures that capture movement toward distant or external knowledge. Only one exploration measure, the number of entirely new technology classes entered, declines slightly for firms already active in many classes, reflecting the simple fact that fewer unexplored classes remain available. The two measures capturing movement toward distant or external knowledge both indicate that broader knowledge bases stimulate exploration, and this relationship is strongest among the largest firms.

For managers, the findings suggest that a broad and coherent technological knowledge base supports both exploitation and exploration simultaneously. Firms can therefore strengthen existing capabilities while expanding into new technological areas. The results suggest that firms should broaden their knowledge bases by adding related technical fields rather than deliberately diversifying into unrelated ones. Because knowledge accumulation through patenting takes place over several years, such expansion should be viewed as a long-term investment. Firms can also assess their growth potential by comparing their technological footprint with that of close competitors.

For research, this study shifts part of the explanation for how firms balance exploitation and exploration from organizational design toward the structure of their accumulated knowledge. The findings indicate that knowledge structure shapes a firm's overall innovation capacity without forcing a trade-off between refinement and search. The study also demonstrates that conclusions about exploration depend on how exploration is measured, since available indicators capture different aspects of novelty. Finally, the reported relationships describe associations over time rather than causal effects, and the findings should be interpreted accordingly. ... Read more

The global maritime and inland shipping sectors face intense regulatory and market pressure to decarbonize, driven by the European Union’s mandate to slash maritime greenhouse gas intensity by 80% by 2050. As a result, alternative marine fuels, such as methanol and ammonia, are seen as emerging alternatives to replace traditional fossil-heavy bunker fuels. However, establishing the supporting infrastructure to enable the bunkering of these fuels presents a fundamental coordination challenge. These large-scale investments are interdependent; they must be committed before technologies are proven, markets are formed, or regulations are finalized. Therefore, they are subject to hesitation on the part of possible risk-averse actors, resulting in a delay in the deployment of such key projects. This thesis aims to investigate how variations in technological, market, and regulatory uncertainty influence the governance of alternative marine fuel bunkering infrastructure. It explores how coordination configurations respond to the specific uncertainty profile associated with a particular fuel pathway. A comparative qualitative case study design approach was considered. Two pilot demonstration projects located in the same Amsterdam–Rotterdam–Antwerp (ARA) port area were examined as cases. These include methanol bunkering at the Port of Antwerp-Bruges under the FASTWATER project, and ammonia bunkering at the Port of Rotterdam under the MAGPIE Demonstrator 4 initiative. In contrast to many studies examining cases across multiple institutions, regions, or geographic settings, this research focused on two cases sharing the same institutional and regional context but differing in terms of fuel type. This allows the effect of a particular fuel’s uncertainty profile on its respective coordination arrangement to be isolated. Data collection comprised semi-structured interviews with project participants and domain experts, supplemented by project consortium deliverables. The material was analyzed abductively in ATLAS.ti, utilizing a framework-derived codebook iteratively refined by emergent data. The findings reveal that because both methanol and ammonia are mature industrial molecules, the critical uncertainty lay not in chemical viability but in the composition of technological, market, and regulatory risks: Methanol (regulation-led): The dominant constraint was the time-consuming process of obtaining an exemption for methanol under an inland navigation standard that did not contain any references to methanol, which caused a sequential cascade of regulatory obstacles to arise with each subsequent engineering modification. Market risk was significantly reduced due to ownership of the vessel by the port authority. Ammonia (standards-and-liability-led): There existed neither a ship-to-ship bunkering standard nor a liability framework for allocation at the time of the project. Moreover, there existed an unresolvable chicken-and-egg situation between producers, charterers, and off-takers regarding the timing of commitments due to each party waiting for one or more of the other parties to make a move first. As a consequence of these two distinct uncertainty profiles, contrasting structures of governance were created. Methanol (lead organisation): The port established internal coordination by combining operational, regulatory, and coordinative functions into one entity facing outward toward external regulators. Ammonia (NAO): The port served as a neutral facilitator within a Network Administrative Organization (NAO), facilitating communication among independent organisations through personal trust. Nevertheless, this model proved limited when a receiving vessel refused participation due to the absence of a defined instrument to assume open-ended liability. The findings suggest that it is the composition of uncertainty, rather than its magnitude, that influences how infrastructure coordination is established. While regulatory risks may be centralized, procedural in nature, and thus able to be addressed by a single capable public actor, decentralized market and liability risks necessitate network brokerage, a form of governance structure that is inherently fragile until standardized frameworks for liability and standards mature. ... Read more

As cybersecurity threats continue to evolve, organizations face increasing pressure to proactively identify and manage vulnerabilities. Coordinated Vulnerability Disclosure (CVD) programs offer a structured approach to receiving and responding to vulnerability reports. While prior research has largely focused on the operational aspects of CVD implementation, this thesis investigates the upstream decision-making factors influencing vendors' adoption of such programs.

Using a multiple case study approach and guided by the Technology-Organization-Environment (TOE) framework and Stakeholder Theory, this study examines how technological readiness, organizational culture, and environmental pressures affect the adoption of CVD programs. The analysis is based on 15 semi-structured interviews with security professionals from vendors with and without CVD programs.

The findings reveal that successful CVD adoption is often driven by strong internal capabilities, openness to transparency, support from leadership, and external regulatory pressure. In contrast, barriers include resource limitations, reputational concerns, and unclear internal processes. The study highlights the importance of third-party platforms, legal guidance, and a tailored approach that aligns with the organization's risk profile and industry context.

This research contributes to the academic literature by shifting attention from post-adoption practices to the decision-making processes leading to adoption. It provides actionable recommendations for vendors and stakeholders to improve vulnerability management and increase preparedness in an increasingly complex digital environment. ... Read more

Engine test runs are among the most resource-intensive steps in the aircraft maintenance cycle. On average, each run consumes around 13,000 liters of fuel, sometimes peaking at nearly 64,000 liters, equivalent to more than 200 tonnes of CO2 emissions per test. Beyond the environmental cost, a failed test can delay engine delivery by up to three months, as the engine often has to re-enter the full maintenance cycle. These failures not only drive up costs and resource consumption, but also disrupt planning and reduce the availability of engines for airline operations. In this context, the ability to predict rejection risk before a test is performed could unlock substantial savings, improve reliability, and reduce the environmental footprint of engine maintenance.

This thesis explores the development and possible implementation of a predictive model that assesses the risk of engine rejection during test cell acceptance runs at an aviation Maintenance, Repair, and Overhaul (MRO) facility. Engine test runs are costly, resource-intensive, and critical for quality assurance, but occasional failures lead to significant delays, rework, and planning disruptions. Early identification of engines at high risk of rejection could enable proactive planning and improve operational efficiency.

The study focuses on the challenges of predictive modeling under real-world constraints: a small, imbalanced dataset and limited failure labels. To overcome these limitations, the research integrates domain expert knowledge at multiple stages of the modeling pipeline, including feature selection, data curation, and the specification of Bayesian priors. A hybrid methodology combining CRISP-DM and the Design Science Research Methodology (DSRM) guides the iterative model development, evaluation, and implementation process.

Various modeling techniques were explored, including logistic regression, random forests, and Bayesian logistic regression with informative priors. The study compares conventional ML models with an expert-informed alternative under different performance objectives. These different performance objectives are prioritizing recall to support early intervention, and later precision to support robust planning. Model evaluation was performed through 5-fold cross-validation.

Results show that expert knowledge significantly improves both the quality of input data and the relevance of engineered features. While Bayesian priors didn’t really contribute to performance, the most impactful improvements stemmed from expert-driven data cleaning and categorical encoding. However, model interpretability remained limited: although rejections could be predicted, the model could not reliably indicate why they occurred.

Consequently, the model’s use case was reframed from an initial ’proactive technical intervention’ to ’planning support’. Under a precision-tuned configuration, the model achieved 50% precision in flagging high-risk engines. Because 87% of rejections were associated with long turnaround delays, each high-precision flag became a useful proxy for high-impact disruptions. This insight provides valuable input for planners seeking to reduce schedule volatility.

The study contributes to literature on expert-informed learning by highlighting how domain expertise can improve data quality, and not just simple model design, in low-data environments. It also offers an empirical evaluation of how different types of expert input affect predictive performance. Practically, the study provides a roadmap for applying expert-informed modeling in safety-critical, data-constrained MRO settings.

Recommendations for future research include validating the approach on other engine types, improving expert elicitation methods by reducing the subjective nature, exploring scalable data curation (e.g., via automation or LLMs), and developing interpretable models that can suggest targeted maintenance actions. ... Read more

Urban noise management often suffers from a gap between broad, city-level policies and the street-level conditions actually experienced by residents. This thesis develops and validates an \emph{interpretable} machine-learning framework that combines street-view imagery (SVI) with on-site acoustic measurements to predict both a standard physical metric (A-weighted equivalent sound level, LAeq) and a psychoacoustic metric (Zwicker Loudness), which reflects how loud sounds are perceived by people. The approach integrates advanced computer-vision feature extraction with ensemble learning, and uses interpretable AI tools (e.g., SHAP) to show how specific visual characteristics of the streetscape—such as vegetation cover, road proportion, building facades, and scene perception scores—are linked to predicted noise outcomes.

Tested across several Dutch cities, the models produce consistent, street-level predictions, enabling high-resolution \emph{diagnostic noise maps} for both LAeq and Loudness. Building on these maps, the thesis introduces a policy translation framework aligned with the Dutch \emph{Omgevingswet} and the EU Environmental Noise Directive (END). This framework includes: (i) identifying noise “hotspots” using both absolute thresholds (from WHO guidelines) and relative, within-city rankings; (ii) diagnosing the main visual features driving noise levels, using local model explanations; (iii) selecting targeted interventions—such as traffic flow adjustments, façade and surface treatments, and nature-based solutions—supported by documented mechanisms and measurable indicators; and (iv) establishing an update loop for periodic review as new imagery and measurements become available. An illustrative micro-case demonstrates how this process turns model outputs into actionable planning decisions and performance metrics.

The study's contributions are threefold: (1) an end-to-end, interpretable pipeline linking SVI and acoustics; (2) a dual-metric evaluation (LAeq and Zwicker Loudness) that combines legal compliance with a perception-based perspective; and (3) a concrete, regulator-aligned pathway from predictions and explanations to policy action. Limitations include the sample size relative to feature dimensionality, the absence of direct GIS or morphological data integration, and the geographic focus on Dutch cities. These factors point to future work involving larger and longitudinal datasets, multi-sensor/GIS integration, and transfer learning for broader applicability, while encouraging cautious, phased adoption in real-world planning. ... Read more

The healthcare sector is facing serious challenges. On the one hand, the population is ageing, resulting in a higher pressure on healthcare resources. On the other hand, less than half of the world’s global population is covered by essential healthcare services due to limiting resources. Frugal health innovations are developed to be affordable, accessible, and make effective use of limited resources. As such, frugal health innovations can help to decrease the resource-dependency in the healthcare sector, contributing to healthcare access to all. Yet, the adoption of frugal health innovations remains limited. Adding to this issue, the adoption is not studied from a theoretical perspective and empirical evidence on the reasons for (non-)adoption remains scarce. Understanding what affects the adoption from a theoretical perspective helps to identify underlying principles at hand, allowing to build a conceptual framework. Such a conceptual framework can guide frugal health innovation development for increased adoption probability and promote future theoretical studies on frugal health innovations. This research aims to understand what factors affect the adoption of frugal health innovations from a theoretical perspective, by asking the research question “What factors affect the adoption of frugal health innovations?”.

To guide the research, the first sub-research question “What theoretical framework is most appropriate to describe adoption of frugal health innovations?” was asked. Answering this question ensured a departing point for the theoretical understanding of frugal health innovation adoption. Secondary data from the literature was retrieved through a literature review, from which it followed that nine theoretical perspectives have been used to study the adoption of non-health-related frugal innovations. By comparing the theoretical perspectives against the context of frugal health innovations, it followed that the Unified Theory of Acceptance and Use of Technology 2 is the most appropriate theoretical perspective to study the adoption of frugal health innovations.

To further guide the research, the second sub-research question “What empirical evidence exists, that can give information on factors affecting the adoption of frugal health innovations?” was asked. Answering this sub-research question allowed to synthesize empirical evidence in the Unified Theory of Acceptance and Use of Technology 2 framework to arrive at a conceptual framework for the adoption of frugal health innovations. Secondary data from the literature was retrieved through a literature study, and the empirical evidence was put in the context of frugal health innovations. From this, it followed that the possibility to experiment with the innovation (Trialability), the innovation- fit with the customers’ lifestyle (Lifestyle Compatibility), the availability of required knowledge to use the innovation (Consumer Literacy), the trust toward the provider of the innovation (Trust), the technical performance of the innovation (Performance Expectancy), the ease-of-use of the innovation (Effort Expectancy), the degree of social pressure to use the innovation (Social Influence), the price of the innovation (Price Value), and the degree of resource- and infrastructural constraints impeding the use of the innovation (Facilitating Conditions) facilitate the intention to adopt frugal health innovations (Behavioural Intention). Interestingly, the synthesis revealed that Price Value, Facilitating Conditions, and Trust also act as a barrier in case they are not properly addressed by the frugal health innovation.

Ultimately, the conceptual framework was empirically validated in the context of frugal health innovations through semi-structured interviews with four frugal health innovation developers. Because developers were surveyed, in contrast to consumers by the studies from the literature review, the adoption, and not consumer-central behavioural intention to adopt, was studied. To increase the possibility of adoption, results suggest that trust between the developer and consumer should be established (Trust), the innovation should align with the preferences of the consumer (Lifestyle Compatibility), the innovation should be designed so that it is easy to use and install (Effort Expectancy), and the innovation should be priced appropriately to ensure affordability whilst maintaining a positive perceived price- quality relationship (Price Value). Further, results suggest that it is imperative to understand the context of the addressed health-related issues, as the performance of the frugal innovation must be superior to traditional health innovations if the latter shows poor performance or side effects, or can be inferior if they are used indicatively where the traditional innovation is used confirmatively (Performance Expectancy). Understanding the context is also of importance to determine whether the use of the frugal health innovation is not impeded by the lack of resources and/or infrastructure, or, appropriately addresses their absence, thereby providing a market opportunity (Facilitating Conditions). Additionally, results suggest that the severity of the health problem (Problem Severity) also affect the adoption, whilst only relevant in case frugal health innovations are sold to governmental organizations. All in all, this exploratory research provides a first conceptual framework to study the adoption of frugal health innovations and opens up the debate on what is required for their adoption. Developers are advised to tailor frugal health innovations according to the principles observed in this research study, as doing so likely enhances the probability of adoption. However, considering the lack of a consumer-perspective in this research study, a logical next step is to further gather empirical findings on frugal health innovation adoption using the developed conceptual framework, to ensure a more robust image of the factors affecting the adoption of frugal health innovations. ... Read more

This thesis explores how risk assurance consultants in a Big Four professional services firm adopt and experience large language models (LLMs) in their daily work. Using a qualitative approach with semi-structured interviews, this study identifies the technological, organizational, and environmental factors that drive or hinder adoption. Additionally, this study investigates the consequences of GenAI on work practices and experiences of consultants. Findings predominantly reveal that consultants embrace LLMs mainly for efficiency, ideation, and drafting tasks, but remain quite cautious with client-facing or high-stakes work due to concerns about data security, quality, and accountability. Adoption is shaped by peer influence, leadership advocacy, and ease of use of the technology but constrained by transparency gaps and unclear governance. Governance ambiguity often leads to rejection of GenAI tools, which was particularly found to be the case in high stakes work where mistakes carry significant consequences both for the professional and the firm.
The research shows that LLMs are transforming consulting workflows from “creator to curator” ways of working; consultants increasingly start with AI-generated drafts and focus on refinement and contextualization. While productivity and output quality improve, workload remains high as cognitive effort of consultants and managers appear to shift to reviewing and verifying outputs. This redefines professional identity and expertise, emphasizing judgment, prompting skill, and ethical evaluation. Ultimately, the study concludes that generative AI is not replacing consultants but augmenting their capabilities. Successful integration requires trust, training, and responsible governance, marking the beginning of a new phase in knowledge- intensive work where human insight and AI collaboration coexist. ... Read more

While many researchers have researched the factors affecting standard consortium success, the size and diversity of a consortium were given the most importance. However, investigating the combined effect of these two factors on standard consortium success using specific indicators of success was limited. Past research required action on applying a new approach to determine the extent to which these variables work together toward the success of standard consortia. It was also important to investigate the network configurations of consortia given the multiple factors that come into play in the process of standardization over the years. This required a configurational approach with huge consortium-level data to test. The objective of this research is to find the configurations of size and diversity that lead to standard consortium success, in the ICT and telecommunications industry, success being represented by specific indicators. The data was collected from the websites ‘consortiuminfo.org’ and LinkedIn using Python packages and was analyzed using Crisp-set Qualitative Comparative Analysis (csQCA). This analysis was done considering two indicators of success individually and combined as a single variable, summing up to three analyses. The analysis revealed that the size and diversity of consortia are necessary conditions, but only diversity is found to be a sufficient condition for standard consortium success in this sample dataset of ICT consortia. The findings suggest that researchers should continue to explore the involvement of other factors along with the size and diversity as combinations instead of only analyzing the variables’ effects individually. Furthermore, by doing this the scope of the research broadens by breadth and depth as more data and more insights about factors of standard consortium success can be gathered.

... Read more

In today's fast-paced global environment, the primary challenge for high-tech companies is maintaining a consistent supply of raw materials in the form of specialized parts from their suppliers. This is essential to sustain manufacturing operations and meet performance targets, ultimately ensuring customer satisfaction. The specialized parts used as raw materials are often technically intricate and costly, which contributes to lengthy lead times for manufacturing and sourcing. Consequently, these parts are generally maintained at low inventory levels. If received incorrectly or found defective during use and if the nature of the defect is such that they are unserviceable, they require immediate intervention such as repair, reconditioning, remanufacturing, or quality analysis to ensure operational continuity. Direct replacement of these parts with new, fault-free parts is often not feasible within the required timelines due to their lengthy sourcing durations. In this context, the emerging field of Reverse Logistics becomes critical, facilitating the efficient handling of these defective parts by shipping them to their respective suppliers to take the appropriate action and ensure that they are swiftly returned to operational status, thereby minimizing downtime and maintaining the supply chain's integrity. These are termed as high-impact issues in Reverse Logistics.
Any delay in shipping defective parts or products to their suppliers extends the time required to perform necessary actions such as repairs or quality checks. These delays result in downtime and can halt the manufacturing operations of high-tech companies until the corrected parts are received back and reintegrated into the production process.
To achieve these objectives, it is essential to have a robust standardized information-sharing and communication process flow throughout the organization. This will ensure timely and accurate management of these defective parts as requested by various stakeholders within high-tech companies. The unavailability of such a process flow leads to significant delays and operational inefficiencies, undermining the company's ability to respond quickly to critical situations and maintain consistent manufacturing outputs.
Stakeholders throughout the organization, responsible for the supply and demand planning of critical and low-inventory parts, initiate requests to the Reverse Logistics Team for shipping defective parts to the supplier when they are deemed as unserviceable or incorrectly received and there is no new inventory to replace them. For the Reverse Logistics Team to achieve timely shipments, they require access to relevant information that is timely, accurate, and centralized through a platform or interface that offers transparency, traceability, and accountability. This system must also be scalable to accommodate an increasing volume of requests in the foreseeable future.
Due to the lack of a standardized process flow, stakeholders currently employ fragmented and inconsistent methods for communicating and sharing information about defective parts with the Reverse Logistics team. These methods are highly unreliable and risky, lacking traceability and visibility in a centralized interface where all incoming and processed requests can be monitored. The existing methods need continuous monitoring by the RL team to ensure they do not miss any requests. Furthermore,
when these existing communication practices are deployed, necessary preliminary steps required before sending requests to the Reverse Logistics team get bypassed, creating bottlenecks and hindering their ability to efficiently manage and expedite the shipment of defective parts. Therefore, the necessity of developing and integrating a standardized process with an advanced Information System like ERP, and adopting it organization-wide, will significantly streamline the defect-handling process. This strategic integration enhances transparency, traceability, and accountability, ensuring that requests from various stakeholders to ship defective parts from high-tech companies to suppliers are managed efficiently and effectively. The Reverse Logistics Team is pivotal in ensuring that these defective parts are promptly shipped to suppliers upon notification.
The literature underscores the necessity for a process flow that expedites the shipment of unserviceable and incorrectly received parts to suppliers for necessary corrective actions. It highlights a notable deficiency in the standardization and formalization of process flows within Reverse Logistics.
This leads to the research question of the thesis which is How can high-tech companies standardize their information-sharing and communication processes to effectively manage high-impact issues in reverse logistics? To address this research question, the research methodology used in this research draws on the Information Systems Research Framework, integrating aspects of people, organization, and technology, both current and prospective. A comprehensive qualitative analysis was conducted, involving 22 semi-structured interviews for thematic analysis complemented by document analysis to delve into the challenges and impacts arising from the absence of standardized information-sharing and communication processes. Utilizing the Technology-Organization-Environment (TOE) framework, this research explores the technological, organizational, and external environmental contexts that influence technology adoption, specifically Information Systems in an organization. Additionally, it incorporates business process management and standardization theories to elucidate the standardization of business processes and the role of information systems therein. This provides foundational insights for developing an Information Systems based process flow, while also emphasizing the importance of change management theories and models for ensuring its successful adoption. This comprehensive approach facilitates a deep understanding of the factors necessary for successfully developing and adopting information systems as a standard process flow within high-tech companies to manage high-impact issues.

This rigorous qualitative analysis based on the literature framework and theories reveals that high-tech companies seeking to develop and standardize their information-sharing and communication processes to manage issues related to the shipment of unserviceable and incorrect parts in Reverse Logistics require a comprehensive approach. This approach incorporates technological, organizational, and environmental factors that significantly influence the development and successful adoption of such standardized process flows.

This research, therefore, by studying the challenges and impacts resulting from the lack of a standardized information sharing and communication process flow identifies key technological, organizational, and external environmental factors, along with their inter-dependencies, that influence the development and successful adoption of such an Information System-based standardized process flow. A framework called IS-PSF is developed which consists of these factors and inter-dependencies identified which are further spread across the phase of change management (transition from an existing state which in this case is the unavailability to the future state which is post-adoption of the to be Information System based process flow). The research methodology employed to develop the IS-PSF framework is distinctive, integrating the TOE framework with theories of business process standardization and change management models.

There are many relevant academic and practical insights derived from this research. The research demonstrated that while documentation of agreed procedures, rules, and guidelines can contribute to standardization, true standardization is unachievable without the integration of information systems alongside these formalization efforts based on the nature of the business processes used. The research highlighted that high-tech companies should deploy a proactive strategy for understanding the need for standardization by monitoring the performance of the business processes using performance indicators or metrics. The research showcased that having a robust and matured IT infrastructure alone is not sufficient but the role of human factors and how the stakeholders make sense of a technology (information systems in this case) are crucial for selecting an appropriate IS on which the standardized process can be developed and successfully adopted.

The research highlights the role of effective change management communication and strategy is vital to ensure a successful transition from the existing non-standardized fragmented information-sharing and communication practices to the standardized Information System process flow. An effective change management strategy decides whether the change management will be successful or a failure. The research also points out the importance of periodic reviews of the process flow by the process owners for continuous improvements. The research highlights that at times, owing to customer requirements, market volatility, environmental regulations, and the aim to set industry standards, high-tech companies standardize their processes in Reverse logistics.

From a practical perspective, the framework developed in the research helps managers make informed decisions on technology investments and change management strategies, allowing for seamless adoption of new systems across organizational boundaries. The study's practical application of the conceptual framework bridges the gap between theory and practice, providing actionable insights for improving process performance and stakeholder satisfaction in high-tech industries.

Overall, this study contributes to the development and successful adoption of an Information Systems Standard Process Flow. This framework is designed to efficiently and effectively manage issues related to unserviceable and incorrectly received parts, aiming to expedite their shipment to suppliers for necessary actions. The goal is to minimize delays in the process flow through the development and successful implementation of a standardized information system-based process flow. ... Read more

This study explores the decisive aspects during an evaluation for the viability of an existing innovative interorganisational partnership. This research focuses on six interorganisational partnerships within the maritime sector, using semi-structured interviews conducted with eleven participants from two perspectives, the strategic and the operational. The analysis found three aspects to be decisive during an evaluation, which are the task-related, the partner-related and the environment-related aspect. Among these three aspects, ten categories are found. This research provides academic contributions and practical recommendations for organisations and individuals involved in an innovative interorganisational partnership. Among these practical recommendations, the trigger for an evaluation, the criteria for an evaluation, and the involved individuals who should execute the evaluation are provided. ... Read more

The energy transition requires the adoption of various hazardous chemicals to generate, transport and utilize energy. In this adoption process, value conflicts between stakeholders need to be considered to foster the social acceptance of these chemical molecules. To be able to anticipate on these value conflicts, this study aimed to develop and evaluate a methodological framework for analyzing and addressing value conflicts in the adoption of hazardous chemicals in the energy transition. By integrating principles from systems engineering and value-driven design methods, as well as input from experts in both fields, a framework was developed. The developed methodological framework consisted of three steps being: 1) Applying Systems Thinking to define the socio-technical system the chemical is adopted in and conceptualize stakeholder values (conceptual investigation), 2) Identifying values and value conflicts (empirical investigation) and 3) Classifying and addressing value conflicts (technical investigation). This approach innovates upon the default tripartite value-sensitive design approach by incorporating Systems Thinking in the conceptual investigation phase to suit the broader context of socio-technical systems design rather than just the design of physical technological artifacts like wind turbines and nuclear reactors. Furthermore, it combines parts of existing VSD frameworks in the empirical and technical investigation phase in a novel way.

The methodological framework was evaluated by conducting a case study on the adoption process of ammonia in the Dutch energy transition. To inform the empirical investigation, 11 expert interviews with policy advisors, industry players and research experts provided in-depth information about the values and value conflicts at play. However, it was noted that the broad nature of the interview questions limited the ability to derive specific technical design requirements, suggesting that future studies should adapt the interview questions to focus on particular parts of the socio-technical system if desired. In the empirical investigation phase, value hierarchies were constructed from the value level to the norm level, which provided useful for identifying value conflicts. The results of the empirical investigation revealed seven major values which play a role in the adoption process of ammonia in the Dutch energy transition being: efficiency (of both spatial planning and the energy transition in general), competitiveness, cooperation, safety and health, environmental sustainability, transparency, and (procedural and distributive) justice. The values identified in this study were found to be comparable with those found in related works on the adoption of technologies like nuclear
energy and wind turbines. Seven value conflicts were identified by comparing the norms related to each value and the framework was used to address and classify them. This allowed to derive policy implications.

There is a need for more transparent communication with the public about the energy transition, available technology alternatives to reach net-zero, the associated risks of those alternatives, and the ethical dilemmas that the government is facing. It was established that local communities are willing to bear risks if the government clearly states what the ethical dilemmas are in the energy transition and the choices made in these dilemmas. This vision can build social acceptance from the industry and local communities and address the identified value conflicts between safety and health, justice, and efficiency. In this vision, the government should also address their standpoint on the ethical desirability of adopting certain chemicals in the energy transition. Therefore, it is necessary that the government
has specified the intended use-cases for chemicals like green ammonia. This clarity can help address value conflicts related to competitiveness and environmental sustainability. Furthermore, it is important that the government keeps fostering a strong collaboration between industry and government. This is especially important when adopting chemicals that are new and where the government possesses limited expertise on. As the industry could possess the necessary technical expertise, the government could set regulatory boundaries upon collaboration with industry, enhancing regulatory preparedness. Moreover, to ensure that imported ammonia is produced green, certification standards should be put in place. These interventions could address the identified value conflict between environmental sustainability and competitiveness, fostering the social acceptance of ammonia adoption. ... Read more

90% out of all startups fail, which is the cause of several reasons like lack of funds, lack of market need and bad management among other things. Digitalization can help startups to solve these problems, by performing processes more efficient than when they are performed manually.

The objective of this research is to build a model to estimate the average influence of digitalization on the success of a startup in all phases during their lifecycle among other established factors, according to their own input. Moreover, this research will investigate the current use of digitalization at industrial startups and how digitalization can help industrial startups to accelerate their innovations. Additionally, this will result in a few examples of how digitalization is used today at startups and a number of recommendations for further research.

This research focuses on industrial startups that are located in the Netherlands, because the Netherlands is a leading high tech country with a world class technical university and science hub and for the reason that similar research has been done in several other countries, only no research has been found on the impact of digitalization (on industrial startups) in the Netherlands. This research will answer the following main research question and sub-questions:

Main RQ: How can digitalization help industrial startups to accelerate their innovations?

SQ1. What are the obstacles that industrial startups in the Netherlands run into during the startup and transition phase?

SQ2. How do startups evaluate their digitalization strategy?

Employees from eight startups have been interviewed during qualitative exploratory expert interviews. These eight startups are divided in two groups. The first group will entail five startups that are currently in the early stage startup phase and the second group will entail three startups that are currently in the scale up phase. During the analysis of the data, the startups (and their data) in the first group are compared with each other. After this, the startups (and their data) in the second group are compared with each other and at last, (the startups in) both groups are compared with each other.

The different obstacles from startups resulted from different research methods. The obstacles that were found during a literature review are: a lack of funds, lack of market need, lack of experience, bad management, premature scaling and a strong competition. From the interview with the investment director of YES!Delft the following obstacles resulted: lack of long term vision, producing everything in-house, going to the market too late, not separating main and side issues & not clearing obstacles in the near future before they run into them. The startups came up with some similar obstacles, but also different ones, like finding (new) people, sales and/or customer acquisition, cybersecurity, lack of funds, big geographical distances, strict/heavy legislation, finding suitable (scalable) software programs, maintaining high quality standards, long negotiation times with customers and decisions of widening/narrowing the product portfolio.

All startups stated that digitalization is very important (one even called it a key success factor), however only three startups could give some kind of definition of what it is exactly and only two startups have a digital roadmap. Even though several startups stated that they would recommend to other startups to start as early as possible with digitalization, they all stated that digitalization is the least important in the first two phases of a startup compared to the last two phases.

The examples of applications that startups mentioned, range from the more simple examples like online meetings and 3D modelling software, to the more advance examples like an ERP system, MES system, machine learning models and newly created API’s. With the help of these applications of digitalization, startups can save time and money in the long run.

During this research it became clear that digitalization can accelerate the innovations of industrial startups, but it is not the most important factor and cannot carry a startup on its own. Digitalization is a tool to get somewhere and not a goal on itself.

The contribution of this research to the literature is a conceptual model that has been used during this research to measure the influence of digitalization (among other variables) on the success of industrial startups in the Netherlands. The practical contribution of this research for startups is to create awareness among startups about the influence of digitalization, the fact that startups can read about the obstacles that they could encounter and some possible solutions for these obstacles as well. Companies that offer applications of digitalization can use this research as orientation for the creation of tailormade digitalization solutions for startups.

Recommendations for further research are: to dive deeper into the phenomenon digitalization, to investigate why some startups say that digitalization needs to be used early, but then contradict themselves with filling in the conceptual model, the influence of digitalization at startups in other sectors and the influence of digitalization among larger corporations.
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Much research has been conducted regarding which steps to take to enhance the likelihood of entrepreneurial success. However, entrepreneurs often turn to practical books for insights on what steps to take, resulting in a research-practitioner gap. This thesis aimed at combining different models and methods into one integral yet simple framework that is practically applicable for startup founders in the early phase: customer discovery. The scientific literature for these models and methods was included. The framework included the Customer Development Model, Diffusion of Innovations Model, Technology Acceptance Model, the Mom Test method and the Lean method. This framework was then tested on a practical use case to test the applicability of the different aspects in a real-life scenario. This use case was the company Plense Technologies, a startup I recently co-founded and still in the customer discovery phase. The metric of learnings and insights was used to assess the framework during this phase. Although the initial framework proved to be insightful, some additions were made. These four additions were (1) the distinction between directive- and non-directive interviews at the different phases of the customer development insight cycle, (2) interviewing suppliers, (3) the benefit of startup coaches and (4) doing an internship to get a better understanding of the customer. With these additions, the resulting framework proved to be integral and simple to apply in a practical context. Entrepreneurs can use the models and methods in the framework to rapidly iterate and improve the business model, ultimately increasing the chances of entrepreneurial success. Factors mentioned that may influence how the framework can best be applied are the financial climate, regulatory environment, culture, market segment, market type, product type, the role of the customer and the relevance of deep tech. These should be further assessed in future research to validate their applicability in different contexts. ... Read more

Maritime sectors have been notorious for their slow paced innovation efforts and although it is an efficient sector, it has big impact on the environment just because of the size of the industry (M. Rahim, et al. 2016). There is a lot of activity on the seas, changes in this sector could make a big difference when making our world become more sustainable. However, the sustainable field is a field that is faced with wicked problems. There are always many stakeholders involved and their interests and expectations on these matters can vary wildly. Conversations are important to bring alignment and understanding across stakeholders (Whitemore, 2013). These conversations involve the political and social sciences to investigate. A list of stakeholders was drafted and they were assessed on the grounds of their discourses. A discourse is “a way of shared, structured ways of speaking, thinking, interpreting and representing things in the world.” (Guardado, 2018, p 72) The following RQ was formulated: How can different stakeholders regarding the sustainable transition of the maritime industry be assessed using the discourses of Dryzek?

With a basis of Q-methodology, a list of statements was created that, based on Dryzek’s discourse theory, is then used to judge the respondents on their environmental beliefs. Also the sustainability reports of selected companies where investigated. It was possible to identify the main themes that could count on agreement/disagreement and controversy. Nature and the existence of limits to our activities where rated highly, while the way to solve it remained controversial. People are more imaginative than their company’s current policies indicate. People see the limitations to the systems that surround them. The willingness of the employees is there, or there is a lack between the strategy of the board and the values of the employees. Further action is required to bridge the gap.

It is indeed possible to asses different stakeholders and firms on their discourses and the research shows two methods to do it. The set up of the interview and the statements proved to be able to provide information about the environmentalism of the stakeholder. This information gives an insight into the social context of environmentalism and brought forward interesting observations about the willingness of the employees and the stance of the companies. The reports indicate a gap between what is needed (and wanted) and what is currently being done. The companies should be more radical and imaginative in both their vision and their solutions, instead of focussing on the solutions alone. Vision is often omitted from the reports, an important oversight.

Overarching vision and motivation can be uncovered but the specific points of departure for technological advancement remain hidden. The thesis brings a contribution to investigations on stakeholder alignment in the clean shipping sector and uncovers some important issues. The firms specific operating context remains to be investigated with more detail, as to properly find the barriers that hold back solving wicked problems. However a good effort is made to indicate the grounds for disputes from the actors.
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