In today’s climate of the increasing use of fake news for which deepfakes may be used, and their widespread distribution through social media, the challenge of distinguishing reality from manipulation is growing. The development of deepfake detection technologies (DFDTs) is therefore crucial. The number of deepfake detection companies (DFDCs) is growing rapidly, changing the competitive landscape. Literature review shows that little is known about strategic opportunities for DFDCs. Therefore, the aim of this research is to provide business strategies, for DFDCs in the emerging DFDT market, in order to maintain or gain a competitive advantage. The knowledge gap lies in the fact that research is done into business strategies for emerging technologies, however, not specifically for DFDTs. To generate concrete and valuable results, the focus is on the Netherlands...

The 21st century has seen a significant rise in clean technologies driven by urgent environmental challenges alongside transformative digital innovations shaping global interactions. Despite these significant events, cleantech startups face substantial challenges and missed opportunities in effectively integrating digital technologies into their sustainable business strategies. To fully harness the potential of digital innovations, addressing the trade-offs and synergies cleantech startups encountered between digital and sustainable strategic practices is crucial, as is understanding the underlying causes of their strategic choices. Despite the rising interest of academia in sustainable and digital entrepreneurship, academic research fails to identify these trade-offs and synergies within cleantech startups. As a result, the main objective of this research is to explore and identify trade-offs and synergies that arise when entrepreneurs follow a sustainable and digital strategy simultaneously within cleantech startups and how they are influenced by their stakeholders, resources, and external environment. By examining the influences of resources, stakeholders, and external pressures, the research seeks to understand entrepreneurs' strategic decision-making process and the implementation of digital technologies within a complex environment. The main research question is defined as follows: “How do Dutch cleantech startups navigate the synergies and trade-offs between digital and sustainable practices, and what are the underlying dynamics shaping these interactions?” A systematic literature review mapped the existing academic perspectives on the strategic practices of Dutch cleantech startups, revealing the research gaps. The study employs the resource-based view theory and is complemented by the institutional theory as the foundation of the research. The research uses the concepts of digital and sustainability strategic orientation to explain how their practices are influenced and define the resources and external incentives as moderators. Semi-structured interviews were conducted with nine Dutch cleantech startups in various industries, such as agriculture, shipping and renewable energies. A qualitative content analysis was conducted to explore the trade-offs and ynergies, resources and incentives, followed by a stakeholders analysis, interview comparison and relational analysis to research the underlying dynamics. The findings show that the startups navigate complex trade-offs between sustainable and digital practices, balancing investment in digital tools for profitability and scalability with commitments to sustainable R&D. Pressures from financial investors prioritise digital scaling and profitability over sustainable impact. Startups prioritise external sustainability impacts over internal sustainable practices and technical talent acquisition over workforce equality. Synergies emerge from leveraging technologies like AI, machine learning, dashboards, and blockchain to enhance product quality, validation, credibility, operational efficiency, and regulatory compliance, supported by collaborations with universities and incubators. Stricter sustainable regulations secure funding and stimulate market demand, facilitating the integration of digital and sustainable strategies. Moderating dynamics are financial resources, influencing the balance between profit-driven practices and sustainable investments. Technical team knowledge enhances digital capabilities, and social networks with incubators and R&D institutions foster collaboration synergies despite challenges in data exchange due to limited digital infrastructure. Normative pressures from customers' expectations and coercive pressures from investors and regulators further shape strategic priorities, emphasising compliance with technical standards. Further research is recommended to evaluate the impact of various digital technologies in enhancing synergies and trade-offs. Furthermore, the direct relationship between resources and external incentives warrants further exploration to understand their influence on strategic practices. Additionally, addressing investor influence, including distinctions between impact investors and traditional venture capitalists, could be helpful. Broader studies with diverse samples from different regions and countries and longitudinal studies are recommended to explore the long-term effects of digital and sustainable orientations and practices.

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.

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.