This thesis examines whether explainable machine learning can support bid/no-bid decision-making for large Dutch construction projects. The study is conducted as a case study at Count & Cooper, a Dutch project-management and tender advisory consultancy active in complex construction tenders. The bid/no-bid decision is a critical early decision point, because contractors must decide whether to invest substantial time and resources in preparing a tender while important project information is still uncertain. To address this problem, the thesis first analyses the Dutch tendering context and identifies decision factors from literature, desk research, and expert validation. These factors are then operationalised into a structured dataset based on 101 historical tender opportunities. Several supervised learning models are compared, including Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and XGBoost. Because of the limited dataset size and data-quality constraints, model performance is evaluated using repeated 5-fold cross-validation. In addition to predictive accuracy, the thesis emphasises interpretability by analysing model coefficients and SHAP-based feature importance. The results show that bid/no-bid outcomes can be predicted to a moderate extent using characteristics that are available early in the tendering process. Random Forest achieved the strongest overall predictive performance, with Logistic Regression and linear SVM performing similarly well. Across models, tender duration, contract duration, project value, project type, and contract form emerged as influential drivers. At the same time, the analysis shows that important internal decision factors, such as strategic fit, current workload, and client capability, were not consistently documented in the available historical records and therefore remain outside the current modelling scope. The thesis concludes that explainable machine learning can provide useful and transparent screening support for bid/no-bid decisions, but that the current results should be treated as a proof-of-concept rather than a deployable decision tool. The main practical recommendation is therefore to improve the structured capture of tender characteristics, internal decision context, and decision rationale, so that future models can become more robust, realistic, and decision-relevant.

Startup accelerators have become key players in entrepreneurial finance, yet their effectiveness in securing follow-on funding for startups varies considerably. This thesis investigates how specific accelerator characteristics influence the funding outcomes of startups post-acceleration, focusing on three dimensions: likelihood of funding occurrence, total funding amount, and funding speed. The study utilizes a dataset of 647 startups from 18 accelerator programs within South Holland, The Netherlands. These data were collected from the Dealroom database. This research employs quantitative analysis, to test hypotheses derived from resource-based view theory.....

This thesis investigates the impact of Environmental, Social, and Governance (ESG) risk factors on the risk and return dynamics of equity investment portfolios, addressing a critical gap in both academic and industry research. The study utilizes Principal Component Analysis and Fama-MacBeth regression to quantify the material impact of ESG risk factors on financial performance, integrating these factors into an extended Fama-French model for asset pricing. The findings reveal that ESG risk factors can mitigate negative impacts on investment returns, underscoring the importance of incorporating ESG considerations into investment strategies. Despite challenges such as inconsistent data quality and limitations of multi-factor models, the research contributes to the understanding of ESG integration and suggests avenues for future exploration, including the development of more precise models and the assessment of long-term effects across different market conditions.

Path dependence occurs when a company excessively rely on its historical strategies, inhibiting its ability to adapt to new circumstances. Kodak's failure to embrace digital photography is a notable example of this phenomenon. The company's entrenched success in film-based photography led to a reliance on outdated strategies, ultimately contributing to its bankruptcy when digital technology disrupted the analogue photography industry. Similarly, startups that heavily rely on equity crowdfunding as their primary source of financing may encounter challenges due to path dependence. While equity crowdfunding has the advantage of attracting capital from a wide range of investors, overreliance on this method can lead startups to overlook alternative funding sources that may better suit their financing needs, such as venture capital firms. Venture capital firms support startups beyond capital funds. They also provide strategic support, expertise, and valuable networks necessary for a startup's long-term growth. Thus, highly dependent on a single funding source, such as equity crowdfunding, may result in suboptimal outcomes and increase the risk of organizational failure.

This study aims to explore whether startups' initial external financing from equity crowdfunding leads to path dependence in their subsequent financing. The main research question of this study is, "Does startups' initial external financing from equity crowdfunding lead to path dependence in their subsequent financing?". This study is particularly relevant to entrepreneurs and investors, providing valuable insight into the potential path dependence in equity-crowdfunded startup financing.

To achieve the research objective, this study employs an exploratory research approach to investigate path dependence in equity-crowdfunded startup financing within the institutional context of British startups. The research utilizes secondary data from Crowdcube, Crunchbase, and the UK Company House, encompassing equity crowdfunding campaign characteristics, startup financing features, and startup profile data. The choice of the British institutional context is justified by the prevalence of equity crowdfunding among British startups, supported by favorable regulatory and tax environments. This study focuses on 74 British startups that received initial external financing from equity crowdfunding via the Crowdcube platform between 2013 and 2018. By examining the financing paths of these startups across three funding rounds, the research aims to identify patterns of path dependence characterized by a consistent reliance on external funding from equity crowdfunding.

Through the exploratory analysis, this study reveals that the 74 startups that initially received external financing from equity crowdfunding followed 20 different combinations of financing paths across three funding rounds. A total of 27 startups (36.49\%) persisted in obtaining external funding from equity crowdfunding across three funding rounds, and this was the most dominant funding path among these startups. Meanwhile, the other 47 startups followed 19 other funding paths with a wide distribution. These findings suggest that startups that initially received external financing from equity crowdfunding tend to seek external funding from equity crowdfunding in their subsequent financing rounds, implying a potential path dependence on equity-crowdfunded startup financing.

This study contributes to the limited literature on path dependence in startup financing, particularly in the context of equity crowdfunding. It builds on previous research that examined path dependence in Swedish startup financing, where equity financing had a strong path effect but did not focus on equity crowdfunding. By focusing on British startups, where equity crowdfunding is prevalent, this study provides initial insights into potential path dependence in this context, laying the groundwork for future research. Future studies should conduct empirical investigations into path dependence in equity-crowdfunded startup financing and examine the impact of high reliance on equity crowdfunding on startup performance to provide deeper insights into this topic.

This study offers valuable recommendations for entrepreneurs and investors. Entrepreneurs are advised to carefully evaluate the choice of initial external financing source for their startup, as it has long-term implications on their startup's financing path. Entrepreneurs should remain open to diverse external funding sources and not overly rely on one funding source, such as equity crowdfunding. They should comprehensively understand their startup funding needs to sustainably grow the business and make informed decisions regarding external funding sources that best align with their startup's funding needs. Thus, their startup financing activity could lead to optimal outcomes for the startup.

Furthermore, investors should take into account the phenomenon of path dependence in startup financing when making investment decisions in addition to evaluating the business and human capital aspects of startups. This process involves examining the historical financing activities of the startups and determining whether there is a recognizable pattern of path dependence in their funding. Although, to the best of our knowledge, there has been no research on the impact of path dependence in startup financing on startup performance, considering this phenomenon is crucial. According to organizational path dependence theory, path dependence could lead to inefficiencies and an increased risk of organizational failure. Therefore, it is paramount for investors to consider this factor in order to make well-informed investment decisions.

In conclusion, this exploratory study provides valuable initial findings on the potential path dependence in equity-crowdfunded startup financing. It emphasizes the need for entrepreneurs and investors to carefully consider initial financing decisions and calls for further research to better understand path dependence in equity-crowdfunded startup financing.

Poland represents an emergent venture capital (VC) market and it faces several critical challenges that impede its growth and dynamism. Key issues identified include a lack of growth capital, diminishing market activity, dependency on public funds, and a scarcity of foreign investment. To address these challenges, this thesis proposes the internationalisation of Poland's VC market by attracting foreign capital as a viable solution. Given that emergent VC markets similar to Poland are understudied in existing literature, this study provides a qualitative analysis framework to better understand these markets through the perspectives of industry participants. Focal to the research are the determinants of the foreign investor's decision to enter the Polish market with different degrees of commitment. The key results reveal ecosystem dynamics, incorporating complex network of variables and processes, which ultimately have their effect on the perception of risk and return in such ecosystem. This comprehensive analysis aims to offer new insights into the unique dynamics of emergent VC markets and propose actionable strategies to address the ecosystem issues and enhance their development, by integrating into the global venture capital landscape.

In the current environmental conditions, with the rise of sustainable finance concepts like Environmental, Societal and Governance (ESG), firms in the financial sector have found new ways to drive sustainable change. Banks in particular play a key role in promoting sustainable practices both within their organization and also have a significant effect on the global economy. However, banks have had difficulties integrating ESG practices in their sustainable credit distribution products to corporate clients.
Due to the qualitative nature of ESG data, even with the involvement of regulatory bodies, there are no established standardized processes for ESG integration. Literature exhibits a clear knowledge gap on the utilization of ESG data in the credit risk assessment process. Furthermore, the primary barriers faced during this process have been attributed to comparability, materiality, accuracy, and reliability of ESG data quality with the lack of comparability having the most significant impact. Hence, based on the knowledge gap identified, the following main research questions were formed:
“How can banks in the EU effectively utilize corporate ESG data during the sustainable corporate financing process?”
By fusing a thorough literature review and 11 interviews of professionals from the banking industry, consultancies, and asset management companies, a process flow diagram was mapped highlighting the different phases of the sustainable corporate financing process. The main phases were comprised of: Opportunity, Due diligence, Determining need for ESG data, Sourcing ESG data, Corporate Sustainability Assessment, Setting KPI’s and Decision. Furthermore, during this process the primary barriers were classified as Data Quality Barriers (Lack of Materiality, Lack of Accuracy, Lack of Comparability and Lack of Reliability) and Integration Challenges (Lack of Data, Sourcing Data, Quantification of Data). Given the relevance of the comparability barrier, its effects were studied in more detail and was followed by proposing a conceptual framework bolstered by stakeholder theory, legitimacy theory and institutional theory to solve the barrier of Lack of Comparability. The relevant dependent variables in this framework were identified as: Data Harmonization Initiatives, Standardization Efforts, Industry Collaboration, Regulatory Interventions/Compliance and Client Engagements. As directed by the conceptual framework, banks were recommended to adopt the dependent variables Data Harmonization Initiatives, Standardization Efforts and Industry Collaboration and were further advised to help clients adhere to compliance. Furthermore, stakeholders' motivation and regulatory incentives were highlighted as key determiners in addressing the barrier. A processual validity approach was adopted to ensure validity throughout the research process which additionally consisted of validating the generated process flow and conceptual framework by relevant experts.
The outcomes of the explorative research showcased the intricacies in the sustainability credit risk assessment and the stakeholders involved while highlighting the interrelation between the barriers identified. Though the lack of a comparability conceptual framework was proposed to be a barrier with significant effects, during the interview analysis it was revealed that the advent of the Corporate Sustainability Reporting Directive (CSRD) would have a significant effect on this barrier and that challenges like sourcing ESG data and lack of ESG data would be more relevant in a few years. Although the conceptual framework accounted for this, some of the limitations in this research study were the inability to recruit more interviewees and also the inability to gather interview data from an external data provider to retrieve a true holistic approach. For future research, studies are recommended to research the effects of the implementation of CSRD and to study the state of other pressing barriers.

This thesis serves as an attempt to establish the initial empirical linkage between environmental, social and governance (ESG) factors and startup valuation by venture capitalists. While substantial academic work has addressed the ESG topic and how firms’ ESG characteristics impact their financial performance and valuations, relatively little ink has been spilled on the issue in the entrepreneurial finance literature. An important impediment for researchers and for investors in the entrepreneurial finance markets wanting to adopt the practice of responsible investing has been the lack of a unified framework for the assessment and quantification of startups’ ESG characteristics. This thesis proposes a startup ESG framework that is based on the status quo of existing ESG frameworks and related literature. The study then analyses a proprietary dataset of 47 technological startups that seek funding from the Dutch venture capital (VC) firm FORWARD.one, to empirically investigate whether the positive relationship between firms’ ESG characteristics and financial valuation, found in the public market setting and the crowdfunding and token offering setting, also holds in the VC context. Multiple Linear Regression (MLR) analysis and Independent Sample t-Tests are used to examine the impact of the startups’ ESG risk scores on their financial valuations. The results indicate that the amount of ESG risk in a startup is negatively correlated to its financial valuation, meaning that venture capitalists do value startups’ ESG characteristics. As a result also those entrepreneurs that seek funding from venture capitalists have an economic incentive to work on their sustainability performance. However, this study finds that sustainability performance is only valued to the extent that it concerns ESG risk management, i.e. minimizing ESG-related negative externalities. The creation of ESG-related positive externalities is not valued by purely financially driven venture capitalists. The study does not attempt to establish a causal mechanism. The findings contributes to the still emergent literature around the role of ESG in entrepreneurial finance markets and several promising avenues for further research are suggested.

The global emphasis on environmental sustainability has led to the rise of "green finance," a financial paradigm focused on environmentally friendly investments. Central to this paradigm are green bonds, designed to fund climate and environmental projects. Their growth has been significant, but their true impact, especially in the face of concerns like greenwashing, requires critical assessment. Understanding the influence of green bonds on labor markets is crucial, as it provides insights into the broader economic implications of this sustainable financial movement. The United Nations’ Sustainable Development Goals (SDGs) serve as a guiding framework for global sustainability efforts. These goals, ranging from eradicating poverty to ensuring environmental protection, aim for realization by 2030. Green bonds, influenced by these SDGs, address the global sustainable financing gap, estimated between $5 to $7 trillion annually. They resonate with core SDG principles, particularly in areas like economic growth and job creation within green supply chains. The SDGs, therefore, form the backbone of the green bond evolution, with specific alignments like SDG Goal 8, which emphasizes "Decent Work and Economic Growth." However, as the green bond market grows, so do concerns about its authenticity and transparency. One such concern is "greenwashing," where initiatives are misleadingly promoted as environmentally-friendly without substantial backing. For instance, while the European Investment Bank’s (EIB) investments in clean transport projects have positively impacted European economies, some green bonds have been criticized for lacking transparency in their fund deployment.
The primary aim of this study is to delve into the influence of green bond issuance on labor market dynamics, specifically focusing on job creation and destruction. Understanding these parameters is vital as they offer insights into the health and vibrancy of an economy. Acquiring data on green bonds presented challenges. Comprehensive databases, while rich in information, often come with substantial access costs. The primary resource for this research was the Climate Bonds Initiative (CBI). However, the selective nature of the CBI’s database meant that not all green bonds in the market were accounted for. The data extraction process was manual, resulting in a dataset that covered green bond issuance from 23 OECD countries from 2014 to 2022. In addition to green bond data, this study also considers short-term interest rates and Domestic Credit to Private Sectors by Banks. These variables are crucial as they play significant roles in influencing lending and investment behaviors, and they offer alternative financial channels to green bonds. The research is underpinned by two main hypotheses. The central hypothesis posits that green bonds have a direct impact on labor markets, potentially leading to either job creation or destruction. A secondary hypothesis suggests that the impacts of green bonds vary across industries, meaning that certain sectors may benefit more than others from green bond issuance. This research delves into the nuanced relationship between green bond issuance and employment dynamics within OECD countries. Findings indicate a significant correlation: for every 1% increase in green bond issuance, there’s a corresponding 0.05% rise in employment on average. Considering the green bond market has witnessed a staggering 90% annual growth since 2016, understanding this relationship becomes paramount. While the overarching data suggests a positive correlation between green bond issuance and employment, it’s essential to note that the impact is not uniform across all industries. This observation aligns with the hypothesis that while some sectors may see job growth due to green bond issuance, others might experience job losses.
Different industries exhibit varied reactions to green bond issuance. For example, sectors like Agriculture and Manufacturing tend to show a negative correlation, possibly due to the capital-intensive nature of sustainable projects in these areas. On the other hand, sectors such as Human Health and Social Work Activities demonstrate a positive correlation, likely attributed to the labor-intensive nature of green initiatives in these fields. An intriguing observation is that while green bonds generally bolster employment, they have a minimal effect on reducing job vacancies, as evidenced by a slight negative coefficient of -0.009 between the Job Vacancy Rate (JVR) and green bond issuance. This research, while comprehensive, has certain limitations. Relying on the job vacancy rate and employment as indicators for job creation and destruction might not encapsulate the full dynamics of the labor market. Additionally, the granularity of the data used could be enhanced for a more nuanced analysis. The study’s focus on 23 countries, sourced from the ICMA green bond database, might not reflect the complete global implications of the green bond market on labor dynamics. Green bonds are undeniably pivotal in guiding the global transition towards sustainability. However, their influence on employment is complex and multifaceted. This research emphasizes the need for a deeper understanding of the nuanced effects of sustainable finance on the broader economic canvas. As global priorities continue to tilt towards environmental sustainability, the insights from this study can serve as a beacon for policymakers and industry leaders. It’s crucial to harness the potential of green bonds effectively while being aware of their diverse impacts across different sectors.

The broad goal of this thesis is to explore what is currently motivating consumers to adopt BigTech mobile payment services in the Netherlands. The term BigTech refers to a collection of the largest and most dominant companies in the IT industry, including Google, Apple, Meta, and Amazon, among others. The BigTechs have been leveraging their core competencies in order to enter the financial industry by offering contactless mobile payment services, such as Apple Pay and Google Pay. Further involvement of BigTechs in the financial industry could lead to increased systemic risk, as well as power concentration risks due to their already large influential market power. The Dutch central bank (DNB) and the Dutch competitive authority (ACM) have released reports in which they acknowledge these risks. They state that the competitive balance between BigTech and the financial incumbents will moreover depend on the relative distrust the consumer currently has towards the BigTechs as provider of financial services compared to incumbent financial institutions. Both authorities indicate that the direction which this competitive balance is taking remains unclear, yet the adoption of contactless mobile payment services in the Netherlands, the majority of which is provided by BigTechs Apple and Google, has seen increasing growth. Therefore, this thesis aims to evaluate whether this distrust still wields this influential balancing power in the Netherlands, or if there are other motives that are more strongly influencing this trend instead.
Reviewing the relevant past literature found moderating and mediating effects between constructs examined in mobile payment studies to often be excluded from analysis. As a result, this thesis also aims to address this research gap. A suitable starting research framework was selected after reviewing eleven prominent research models and a conceptual model was designed based on these reviews. Data was subsequently collected using an online survey questionnaire. The 217 collected responses were subjected to data analysis of which the results indicate that the Dutch consumer is mainly driven by three functional motives regarding respectively: how well the technology is expected to perform, how well the technology is perceivably supported, and to which extent the consumer has habits that are similar to using mobile payment services.
Perceptions of involved risk and feelings of distrust towards providers of mobile payment services only reduced the incentive to adopt the technology among respondents within the age group of 25-34, and solely weakened the performance-based motive. It was furthermore found that the habit-based motive reduced both risk perception and distrust of the users. No motivational differences were found between users of BigTech services or those offered by financial incumbents, or between users and non-users.
The Dutch relevant authorities may induce from this research that the competitive balance in the Dutch financial sector is likely tipping in favour of BigTech as consumers are driven mainly by utilitarian needs to which BigTech can more easily cater than financial incumbents. Dutch financial incumbents may therefore require additional support to reduce the potential for harmful levels of competitive pressure in the financial sector and limit the sector’s exposure to concentration risk, which the involvement of BigTech can bring about. Dutch financial incumbents may induce from this research that the contemporary Dutch consumer mainly prefers improved functional capabilities. According to the results, performance, wide-spread support, and fit with consumers’ existing habits, should serve as key focus areas for improvement in order to compete efficiently. The theoretical contribution that this research made regards the discovered mediating and moderating effects of the evaluated constructs in mobile payment adoption research. The obtained results thereby implore future research in this field to similarly evaluate such effects in order to increase the explanatory power of the employed research model and potentially derive additional and crucial insights.