This work explores of the status of the Technological Innovation System for vehicle-to-grid technology in the UK and derivates relevant strategies that policymakers and companies can use in order to foster its technological adoption.

The rapid advancement of quantum computing and communication (QCC) technologies promises transformative benefits for companies, yet also poses ethical and societal challenges reminiscent of historical technological introductions. This study addresses the Collingridge Dilemma, which posits that controlling technology becomes increasingly difficult as it matures, while knowledge about the impacts is absent at the beginning. Through a systematic literature review and expert interviews, this research investigates the negative societal impacts of QCC. While existing literature predominantly focuses on cyber security implications, expert insights reveal a broader spectrum of impacts, including environmental considerations. The study identifies interrelations among impacts and acknowledges their inherent ambiguity. A novel general classification framework is proposed to guide policy and management decisions, leveraging insights from both literature and interviews. Recommendations include prioritising security audits, fostering agility in response to emerging threats, enhancing technological literacy within organisations, and establishing regulatory frameworks. Despite limitations, the study underscores the need for further exploration in this nascent field, offering avenues for future research.

In a biomechanical engineering study, a pressure-activated, colour-changing, and flexible material has been developed, stemming from an initial problem application. However, a technical innovation can transcend its original intent, thereby gaining value for engineers or technical managers. The problem is that there is a lack of guidance in retrieving alternative applications, and research into such problem-finding methods is scarce and dispersed across various groups. Through an innovative approach to the literature review, valuable tools and techniques have been identified within relevant articles, categorisable into qualitative, quantitative, and hybrid approaches. These approaches are delineated across four conceived steps: (1) Define the technological characteristics, (2) Generalise the function of the technology, (3) Link the generalised functions to abstract problem applications, and (4) Choose an application. Furthermore, connections have been established among the different approaches, enabling multiple paths for executing these four steps. This research presents the design of a framework that showcases multiple problem-finding processes suited to different situations. The qualitative component of this framework has been validated by implementing these steps for the pressure-activated, colour-changing and flexible material and retrieving its initial purpose and other feasible and innovative applications.

Recent findings by the OECD highlight that a significant proportion of refugees in Europe possess high levels of education, often being overqualified for their roles. However, literature seldom addresses the unique challenges these highly educated refugees face when integrating into the labor market. This research examines the role of entrepreneurship in integrating highly skilled Syrian refugees into the labor markets of Germany and the Netherlands. Using a qualitative research design, including literature review, desk-based research, and semi-structured interviews, the study reveals that both countries currently lack specialized support for such refugees during their asylum and integration processes. They face numerous challenges, including legislative, administrative, financial, socio-cultural, and market-related barriers. Moreover, collaboration between local government actors and business incubators is sparse. In light of these findings, the research advocates for improved policies and specialized business incubator models tailored for these refugees, aiming to leverage their skills and education for the benefit of host countries. The insights provided by this research underscore the untapped potential of educated refugees, emphasizing the necessity for more inclusive policies and support structures. Future directions for research include exploring bespoke business incubator models in Germany and the Netherlands and broadening the study's scope to other nations and demographics. This study contributes scientifically by delving into the niche domain of highly skilled refugee entrepreneurship and societally by emphasizing the invaluable economic and innovative potential of this group. Practical implications suggest refined integration strategies and infrastructures to better harness their capabilities.

Industrial biotechnology is labelled by the European Commission as one of the six key enabling technologies to fight climate change. Industrial biotechnology is a sector where biocatalysts (cells or enzymes) are used to convert renewable feedstocks (e.g. sugars) or even waste into valuable compounds such as renewable chemicals or food (ingredients). Unfortunately, the road from invention to commercial production is long in industrial biotechnology, and most biotechnologies that look promising after laboratory development fail to cross the Valley of Death and reach industrial scale. Industrial biotechnology has a long technology development time before being commercialised, is capital intensive, has economies of scale, and usually produces bulk products with low profit margins requiring large industrial-scale production for economic viability. Scale-up support can facilitate scale-up towards industrial scale. Scale-up support was, for example, offered with the Bioprocess Pilot Facility at the Biotech Campus Delft, before its bankruptcy in November 2022. This bankruptcy occurred while being fully booked. This has left the Planet B.io - Biotech Campus Delft scale-up support ecosystem with a lot of potential. In an attempt to scientifically address this scale-up support problem, a knowledge gap was found on the verge of technical scale-up, industrial biotechnology, and scale-up support ecosystems. This led to the main research question: How can a scale-up support ecosystem for industrial biotechnology be best organised and operated?

To answer this, a multiple case study was conducted on the scale-up support ecosystems of Planet B.io - Biotech Campus Delft, Copenhagen, and Brightlands Chemelot. This case study was performed through desk research and semi-structured expert interviews with 3 different types of experts (ecosystem, technical scale-up and start-up expert) per ecosystem, resulting in 9 interviewees. This case study applies the Technological Innovation System (TIS) framework to a novel context and integrates it with the four identified scale-up support elements (technical facilities \& services, funding \& business services, network formation \& coordination, and knowledge \& talent) offering a framework to study scale-up support ecosystems. This study identified the scale-up support requirements for industrial biotechnology. These scale-up support requirements are, among others, a flexible and fully-serviced shared piloting facility up until TRL 6 ($\approx$ 2000 L bioreactor), a lab- to pilot- and industrial-scale technical support service, investment planning service and help with raising funding. These should be offered within a scale-up support ecosystem using milestone-based billing as a preferred revenue model, whereas a government voucher system should be set up to pay for the lab- to pilot- and industrial-scale technical support service. Also, the most important stakeholders for a scale-up support ecosystem were identified, including multiple large corporations, government institutions, universities (and other types of education), suppliers, and service providers. Based on the findings, a roadmap for the development of the Planet B.io - Biotech Campus Delft scale-up support ecosystem was proposed, focusing on strengthening the network, knowledge, talent, and funding before offering a piloting facility and business services. This study contributes to the field with a framework to study scale-up support ecosystems as well as with practical recommendations for scale-up support ecosystems in industrial biotechnology and similar industries, identifying the scale-up support requirements, its business models and required stakeholders.

New Product Development (NPD) of applications incorporating breakthrough technologies can be beneficial for companies, but can also come with serious drawbacks. Therefore, the NPD process must be approached with great care. Rather than adopting the chaotic trajectory of the NPD process, where applications are introduced, withdrawn, and reintroduced naturally over time, business prosperity could be enhanced if companies can up-front formulate a set of possible future applications for a breakthrough technology. The most promising alternative can hereafter be chosen to be further developed in the NPD process, possibly reducing the chance of having to switch to the development of other applications (and thus circumventing the Collingridge dilemma). In this thesis, I start with defining the terms (breakthrough) technology and application. Then, I suggest a ten-step framework that is suited for formulating applications for a breakthrough technology, based on the comparison and symbiosis of five existent frameworks that are helpful in reaching the aforementioned goal. Factors that are of importance in that process are also investigated. None were discovered in scientific literature, but some suggestions are made based on the current work. The framework is applicable to breakthrough technologies of which it is non-obvious, and even unsure, what the technology can do, how it can be implemented into applications, and whom it might serve. Next to this, the breakthrough technology must still be in the innovation phase. The process itself must make use of qualitative and quantitative approaches in a balanced way, must continuously involve known sets of experts, must look into the future, and must formulate concrete applications for the emerging technology. The framework is then partially applied to the breakthrough technology of quantum dots (QDs). The technology profile and the application profile were gathered, first, based on scientific records. Then, the most frequently used keywords and the most increasingly used keywords were retrieved for both profiles. The most frequently used keywords showed that carbon dots are the most dominant area of research that is being conducted on QDs and that optics and imaging are the two major fields where QDs are being incorporated. The most increasingly used keywords confirmed the observation that QDs are in the adaptation phase, where QDs are still surrounded by substantial uncertainty. Finally, with the aid of text mining software of VantagePoint and programming software of R, two dendrograms were formed. The remaining steps of the framework were not carried out in the current thesis project. It was concluded that the ten-step framework is most likely better suited for breakthrough technologies that are more in their infancy than QDs (so, breakthrough technologies still in the innovation phase). The framework should, next to this notion of novelty, be applicable to any breakthrough technology, regardless of the field that the breakthrough technology is situated in. As long as it is non-obvious, and even unsure, what the breakthrough technology can do, how it can be incorporated into applications, and whom it might be useful for.

This Master Thesis research addresses strategies for deploying sustainable aircraft technologies, with the primary goal to accelerate sustainability transitions within the aviation industry. The focus of the research is on analysing hydrogen and ultra-efficient aircraft technologies in comparison to a conventional aircraft, with 50% SAF drop-in, as the benchmark technology.

The Technological Innovation System (TIS) framework, viewed from a company perspective, serves as the basis for this research. The TIS framework can be defined as "the network of actors interacting within the industry, subject to certain institutions and involved in the generation, diffusion, and utilisation of a novel innovation." Through the examination of seven essential dimensions, referred to as TIS building blocks, the most significant bottlenecks impeding the implementation of hydrogen and ultra-efficient aircraft have been identified.

This knowledge has been utilised to create a three-phased deployment strategy for both sustainable aircraft technologies, considering timing and scale. The research scope has focused on the regional market segment, using a 70-90 passenger Embraer 175 aircraft design as reference aircraft. Key insights from the research have led to proposed recommendations to industry stakeholders, policy-makers and academics.

Solar Electric Vehicles recently emerged in the market to solve dilemmas that have been hindering the EVs mass uptake: limited driving range, long charging time, and limited charging infrastructures. The SEV utilization is especially interesting for those who live in areas with many sun hours annually but have limited EV charging infrastructures. Interestingly, Indonesia is located along the equator, lacks EV charging facilities, and has a big market size for SEV. Even more, Indonesia has the urge to boost its decarbonization to meet its climate goals, especially in its transport sector. The combination of these facts leads to the overarching question if SEV could be easily mass adopted in Indonesia. However, the TIS perspective argues that, as part of a complex system of systems, SEV would need not only good technological features but also other “actors, factors and functions” to help it to reach its mass adoption (Ortt et al., 2013). Therefore, it leads to the main research question:

“From the technical innovation system perspective, how could solar electric vehicles reach mass adoption in Indonesia?”

This research is conducted in collaboration with Lightyear – a SEV producer. As Lightyear is aiming to mass produce its SEV, therefore, this research is conducted to explore and evaluate the Indonesian market, so that the best strategy recommendation could be provided to Lightyear so it could commercialize its SEV in a large scale in Indonesia. The qualitative research approach is implemented in this research by reviewing diverse online literature, including both scientific and grey literature.

The TIS Framework (Ortt & Kamp, 2022) and the Ten Niche Strategies framework (Ortt et al., 2013) are used as the starting point of the research. TIS is defined as innovation systems around a specific technology that consists of four main elements: the technology, a network of actors, the institutions, and the demand. Ortt & Kamp’s TIS framework is a tool to examine the TIS of an innovation that is in its adaptation phase to judge whether the innovation is ready for its mass uptake or whether a small-scale niche introduction strategy is needed prior to the large-scale diffusion. The framework consists of three major elements: TIS building blocks (most important aspects needed for large-scale diffusion), influencing factors, and strategies. When certain influencing factors negatively affect the completeness of the TIS building blocks, they pose as barriers to the mass adoption of the innovation. Certain strategies could be implemented to circumvent these barriers, such as the generic Ten Niche Strategies proposed by Ortt et al.

The research is conducted in four major steps. First, basic information about SEV technology is explored. Second, a new framework called “the Best Strategy Framework” is developed to extend and complete the original TIS Framework and Ten Niche Strategies Framework so that the users/readers could select the best strategy based on the combination of barriers that hinder mass adoption of the innovations. Third, the newly developed framework is used to evaluate the Indonesian market and to identify the barriers that might hamper Lightyear’s SEV mass adoption in Indonesia. Finally, by using the newly developed framework, the best strategy that could circumvent the identified barriers is selected and proposed to Lightyear.

When attempting to enter a market, it is of the utmost importance to make a well-thought decision. Numerous academics have examined the first-mover advantage literature to determine whether entering first, second, or late is more advantageous. After many decades, there is still no consensus, and it appears that we are in a dialogue of the deaf. This thesis gives a list of first-mover advantages and disadvantages and discusses the symmetry between first-mover advantages and first-mover disadvantages, as well as first-mover advantages and second-mover disadvantages, in order to extent the topic. This list alone is not enough to settle the debate, so we introduce the pattern of development and diffusion. The pattern of development and diffusion contextualises the problem and shows the demonstrates the effect of first-mover advantages on the development of a product category. The relationship demonstrates that a setting can be either dynamic (a market entry has a substantial impact on the product category) or static (a market entry has little effect).
This thesis proposes a model to illustrate the factors that influence the decision to enter the market. Aspects that influence the formulation of a market entry strategy are included in the model. For the sake of simplicity, only the strategy to enter a market has been investigated. Next to the model, we created a flowchart that describes the steps required to develop a market entry strategy. Eventually the goal is to make a well-thought decision. The dialogue of the deaf on first, second or late being most favourable has been the cause of this thesis but the conclusion is none of those. The most important part of first-mover advantages and disadvantages is the effect they bring along with the entry into a market. This thesis claims that first-mover advantages are advantages and disadvantages that may be evaluated over the development of a product category, rather than belonging to any particular order. The weights of (dis)advantages differ over the course of the development so at different points in time, different advantages can be utilised. The first-mover (dis)advantages present aspects that can be utilised at a particular situation. The decision maker should foresee whether, given the current (dis)advantages, after its introduction the situation is most favourable or if the situation is most favourable when you wait, and competitors have entered the market. The combination of the pattern of development and first-mover advantages show this principle and show why the dialogue of the deaf on market order is not useful. The decision to enter a market has never been simple, and it likely never will be. This thesis offers direction for the decision-making procedure and explains how to comprehend it. The complexities of market entry decision making are not yet resolved, but a well-thought decision is getting closer.

This thesis explored the contrast between the overarching category of entrepreneurship (from here on, “mainstream entrepreneurship” or ME) and the subset of technology entrepreneurship (TE) through a comparison of The Netherlands (low TE/high ME) and Japan (high TE/low ME), addressing the problem that currently no dedicated frameworks for TE exist. Five influencing variables were explored at the country level of analysis, namely economic development, technological development, institutions, education, and culture. In contrast to ME, TE benefits from better technological development and education. These influencing variables showed high values, whereas for ME they showed low values. With analysis of 44 additional countries, these results were confirmed, and economic development was also deemed important to TE. A culture high on long-term orientation and individualism (Hofstede dimensions) appeared to benefit TE. Institutions showed little difference between ME and TE. The additional analysis firmly showed that ME and TE are different and unrelated. which was confirmed by a low correlation coefficient and corresponding p-value.

This thesis shows that TE and ME are different, should be treated as such, and has identified several influencing variables that affect TE differently than ME. Thus, TE and ME can be independently stimulated by increasing the levels of the influencing variables. For governments seeking to increase their levels of TE through relevant policies, despite a traditionally non-entrepreneurial environment, it means that all is not lost, and that the levels of TE can be raised by focusing on increasing levels of education, economic environment, and technological environment. Managerial recommendations include the geographical placement of technology start-ups and the diversification of the team to improve success.

The chemical industry needs to quickly adapt to deal with climate change's environmental and economic challenges. The chemical industry is a sizable contributor to climate change. On the other hand, their contribution to financial stability and growth is considerable. Adopting sustainable process technologies is the most promising solution for the industry as the current processes are the leading cause of emissions. This thesis aims to formulate a model that describes the adoption decision of a production firm in the chemical industry. It focuses on the adoption criteria at play, the relative importance of these criteria and the influence that actors of the production companies' environment (further referred to as context) have on adoption. Research conducted for this thesis is done through the lens of the sectoral view, focussing on organisational level criteria and interactions. The Netherlands has a sizable presence of industrial activity. As such, this context is used for this study. The organisational level focus of this thesis, together with the specific context of the chemical industry, inspired us to choose the Technology-Organisation-Environment (TOE) framework to describe the adoption of sustainable process technologies (SPT) in the chemical industry. During the creation of this thesis, it seemed no prior work applied TOE to the chemical industry. Therefore, the TOE framework is combined with industry-specific adoption criteria. The study provided three primary insights. The first insight is a new set of adoption criteria specific for the chemical industry. This insight is valuable as general adoption model literature criteria are purposely vague. Vague formulation of the adoption criteria is helpful to help potential customers evaluate radical innovations that they do not fully comprehend. However, managers in the chemical industry seem to know the exact criteria for assessing sustainable process innovations in the chemical industry. The second insight from the interviews concerns the tendency of adoption criteria to change in importance in particular situations. This variation is an essential addition to the existing literature in which adoption criteria are generally applicable and equally important across various adoption situations. The interviews identified four dimensions that demarcate adoption situations: three continuous technological dimensions and one discrete contextual dimension. The third insight of this thesis is the importance of the organizations surrounding the focal production firm. The adoption system refers to the businesses and organisations that influence production companies in their adoption decisions. The adoption system of the chemical industry consists of regulators, clients, competitors, engineering firms, development firms and feedstock suppliers. The collaboration with multiple stakeholders is of utmost importance when considering SPT adoption. In conclusion, the TOE framework with industry-specific adoption criteria seems to fit adoption in the chemical industry. However, due to the varying adoption situations in the chemical industry, it is crucial to consider the adoption dimensions. Future research could focus on finding the weight of these criteria. Whist doing this, it is essential to consider the adoption dimensions. It could be interesting to find out what influence the different dimensions have on adoption.

Maritime Autonomous Surface Ships (MASS) is a breakthrough technology whose development incites excitement and doubts. MASS is still in its pre-diffusion phase, which means it still undergoes adaptations to best suit the market with the ultimate goal of reaching large-scale diffusion, despite the uncertainty about the timing in which large-scale diffusion will happen. Many breakthrough technologies, however, do not reach diffusion and that is related to actors and factors affecting its Technology Innovation System (TIS). Therefore, this research aims at answering “How can MASS reach diffusion within the maritime industry?”

Knowing the time point of large-scale diffusion of a radically new high-tech innovation is a highly relevant topic. Companies, researchers, and government institutions can plan their research and development efforts, production, as well as marketing plans according to the predicted time point of large-scale diffusion. The research is based upon the assumption that specific indicators can predict the start of large-scale diffusion. The scientific field of forecasting the start of large-scale diffusion is relatively new. Therefore, an explorative methodology was required for this research. During the explorative process, it was ensured that indicators reflect on the holistic environment of an innovation by minding the so-called data collection cube.  A data selection funnel was created, narrowing scientific branches down to a list of indicators in three steps. Each of these steps has its own criteria designed to: • Select scientific branches with the highest potential to find results in the literature reviews • Derive indicators that can observe the diffusion • Select indicators that can predict the start of large-scale diffusion   The last step of the data selection funnel, selecting the indicators which can actually predict, was carried out with the support of three researchers. Eight criteria were used to select the most potential indicators: (i) Prediction, (ii) Timeliness of prediction, (iii) Availability of data, (iv) Cost of data, (v) Quantifiable& Objectivity, (vi) Empirical proof, (vii) Generalizability, (viii)Simplicity. The researchers were asked to evaluate the indicators according to the criteria (i) and (vi) as part of the scientific quality gate selecting the most potential indicators. After the indicators have been evaluated, a sensitivity analysis has been performed to improve the robustness of the selection mechanisms and to rule out an arbitrary selection of the indicators. Out of 50 indicators found in the literature or derived from the literature, 38 indicators were selected according to the selection mechanism. These 38 indicators have been split into two sets of judgemental and non-judgemental indicators to prepare the design of the forecasting approach.   The forecasting approach aims to guide a user towards the correct forecasting technique given an innovation and situation. Five forecasting techniques were found to befitting the: (i) assumptions-based modelling, (ii) Delphi method, (iii)analogous forecasting, (iv) time series & regression models, and (v)artificial neural networks. However, each of the five forecasting techniques have disadvantages that can be overcome by one of the other methods. Hence, the forecasting approach has two stages. First, the user is guided towards the primary method and subsequently towards an additional method overcoming the disadvantages of the first method and improving the overall reliability of the forecast. For each method, a set of indicators is recommended.   Once the forecasting approach has been developed, the completeness of indicators has been checked by using Ortt & Kamp’s 14 factors influencing the pre-diffusion phase. Additionally, four validation interviews applying the research on green hydrogen have been performed to let external actors reflect. These validation interviews formed the practical quality gate forging a bridge to the earlier mentioned scientific quality gate.   

Knowing the time point of large-scale diffusion of a radically new high-tech innovation is a highly relevant topic. Companies, researchers, and government institutions can plan their research and development efforts, production, as well as marketing plans according to the predicted time point of large-scale diffusion.
The research is based upon the assumption that specific indicators can predict the start of large-scale diffusion. The scientific field of forecasting the start of large-scale diffusion is relatively new. Therefore, an explorative methodology was required for this research. During the explorative process, it was ensured that indicators reflect on the holistic environment of an innovation by minding the so-called data collection cube.

A data selection funnel was created, narrowing scientific branches down to a list of indicators in three steps. Each of these steps has its own criteria designed to:
• Select scientific branches with the highest potential to find results in the literature reviews
• Derive indicators that can observe the diffusion
• Select indicators that can predict the start of large-scale diffusion   The last step of the data selection funnel, selecting the indicators which can actually predict, was carried out with the support of three researchers. Eight criteria were used to select the most potential indicators: (i) Prediction, (ii) Timeliness of prediction, (iii) Availability of data, (iv) Cost of data, (v) Quantifiable& Objectivity, (vi) Empirical proof, (vii) Generalizability, (viii)Simplicity. The researchers were asked to evaluate the indicators according to the criteria (i) and (vi) as part of the scientific quality gate selecting the most potential indicators. After the indicators have been evaluated, a sensitivity analysis has been performed to improve the robustness of the selection mechanisms and to rule out an arbitrary selection of the indicators. Out of 50 indicators found in the literature or derived from the literature, 38 indicators were selected according to the selection mechanism. These 38 indicators have been split into two sets of judgemental and non-judgemental indicators to prepare the design of the forecasting approach.   The forecasting approach aims to guide a user towards the correct forecasting technique given an innovation and situation. Five forecasting techniques were found to befitting the: (i) assumptions-based modelling, (ii) Delphi method, (iii)analogous forecasting, (iv) time series & regression models, and (v)artificial neural networks. However, each of the five forecasting techniques have disadvantages that can be overcome by one of the other methods. Hence, the forecasting approach has two stages. First, the user is guided towards the primary method and subsequently towards an additional method overcoming the disadvantages of the first method and improving the overall reliability of the forecast. For each method, a set of indicators is recommended.   Once the forecasting approach has been developed, the completeness of indicators has been checked by using Ortt & Kamp’s 14 factors influencing the pre-diffusion phase. Additionally, four validation interviews applying the research on green hydrogen have been performed to let external actors reflect. These validation interviews formed the practical quality gate forging a bridge to the earlier mentioned scientific quality gate.  

Since the introduction of the shipping container as early as 1968, the shipping industry experienced great increase in trade and efficiency. The shipping container revolutionised the way goods are handled within the ports and enabled the growth of international supply chains. However, as this growth of trade continued into the late 1900s and early 2000s, both customs and the organisations within this chain experienced an increased administrative burden. This administrative burden was experienced within the different information streams to get the goods smoothly from the selling actor to the buying actor. Additionally, many actors within the supply chain perceive opportunities to greatly increase trade efficiency. Improving their business model through the addition of information based new services, expanding business through integrating other actors, and lowering costs through the development of cost-effective in-house capabilities. Early digitisation efforts have only produced limited results, as these mainly focused on automating internal business processes. These internal processes were often not able to automate communication with other actors. Processes still relied on a significant amount of paper communication.
The introduction of digital platforms has greatly affected different industries, for example enabling direct booking within the air travel business. Replacing paper documentation with an electronic equivalent can enable an increase in efficiency, through reduced administration costs and improved planning and operational capabilities. Efforts in introducing a digital platform within the shipping industry have been taking place using different governmental research efforts. However, as a possible additional effect, the digital platform may put reconfiguration of the network in motion. This reconfiguration enables certain actors to partake a bigger role, whereas other actors might lose control of the supply chain process.

The TradeLens platform launched in 2018, is such a digital platform. This platform allows sharing both documentation (e.g. the commercial invoice, packing list, bill-of-lading) and supply chain events (e.g. lodging ENS, the actual time of arrival) with the other actors. The platform uses a blockchain infrastructure. This structure is used to increase the trustworthiness of the data. Firstly, the auditability hinders documentation fraud as the actors within the network can trace the exact moment and actor that placed uploaded a document. The immutability of the blockchain infrastructure allows the automation of information processes. When the information is uploaded it cannot be changed. It was developed by a co-operation between a shipping carrier and a technology developer. The platform was tasked with alleviating the pressure on the administrative systems of the different actors within the supply chain. This research investigated possible scenarios due to the introduction of a digital platform using the TradeLens platform as the main research case.

Research Question and Objectives
This research aims to address the different possible future configurations of the network and roles within the container supply chain. To address this, the following main research question was developed: What is the possible supply chain configurations that come with a digital information infrastructure?.
In addressing this research question a number of research steps and clarifications have to be answered. Firstly, the research has to determine what is considered an actor within the supply chain ecosystem and what are the key activities performed in that ecosystem. Secondly, the research aims to perform an analysis of each actor and thus explain the different roles to be able to perform this analysis a theoretical model has to be developed. Thirdly, the research will evaluate the ecosystem using this model. Fourthly, the different scenarios will be developed using the developed model.
Research Method
The research employed three main methods of data collection. Firstly, a literature review is performed to identify the important information and innovation concepts to be used throughout the research. Secondly, through analysing many different public sources, the research gains company insights and information for constructing different roles, activities, and resources. Thirdly, through interviews with experts on the TradeLens platform where careful attention is given to the shifting activities, resources and control within the configuration of the network.

The used approach can be defined in four steps. First, the researchers developed an initial meta-framework using the findings from the literature review. Secondly, the different concepts within the meta-framework were combined into constructing a model for the assessment of the ecosystem. Thirdly, a generic container shipping case is construed from the information gained from the different public and academic sources. Lastly, a comparison is performed between the construed case and a test case of a Dutch tyre importer. The main findings within these steps will be discussed in the following paragraph.
Main Findings
The research identified five key theories to be of importance within the model. These are 1. Ecosystem theory, 2. Stakeholder theory, 3. Diffusion theory, 4. Control Point theory and lastly, 5. Barriers and Stimulating Factors. Firstly, the concept of the business ecosystem. An ecosystem describes how different actors within a business domain influence and interact with the other actors outside and within the direct business network. This research investigates the effect of digital platforms on ecosystem reconfiguration. The chosen system of analysis for this ecosystem reconfiguration is the blockchain-enabled platform, TradeLens. This platform enables information sharing between the different actors using a trusted blockchain structure. The TradeLens ecosystem can be considered a service ecosystem, as the main value creation is intangible and the many different actors within the ecosystem co-produce the final value within the system. Secondly, stakeholder theory describes when someone can be considered a stakeholder and how to evaluate motivations and incentives. Thirdly, diffusion theory described how an innovation such as TradeLens goes through different phases before mass-market adoption. Fourth, the control points theory explain how different actors within a business process are able to exercise control on that process. Control points were used to describe how different actors are able to perform certain roles within the ecosystem. Lastly, barriers and stimulating factors describe how certain factors can enable or disable a certain development to progress further. In the case of TradeLens this was used to investigate further growth barriers and stimulating factors.
This meta-framework was converted into a six-point assessment model. This model uses a comparison between different states of an ecosystem, to evaluate possible scenarios. The first case is that of the generic constructed benchmark. This benchmark has been developed from cross-referencing a selection of public and academic sources. The main task of the constructed case was to show a generic and common supply chain structure. To assess the enhanced version of the supply chain, a case study of a Dutch tyre importer was selected. This case was selected due to the extensive documentation around this case. Additionally, this case has ships of non-hazardous and non-perishable goods that do not require additional certificates and documentation that might be applicable for other goods. The constructed benchmark case and the tyre importer case were both evaluated using the six-point assessment. With regards to key activities, the main difference found was that the tyre importer self-organises its land transport as the organisation owns its own transportation vehicles. Secondly, the tyre importer case performed the import declaration itself. This in contrast with the benchmark case, where this task was delegated to a freight forwarder who organises both the land transport and the lodging of the import declaration. This main difference becomes more visible when assessing the second point, the key actors. Here it was observed that the freight forwarder was missing on the importing side within the tyre case. This was possible as the buyer/tyre importer performed the activities of the freight forwarder. Within the value exchanges and the key information, it was observed that the buyer was able to directly lodge the required data for the import declaration. This automated the customs lodging process and increased cost-effectiveness. Secondly, within the TI case, the buyer had its own land transport capabilities and did not rely on an intermodal operator to collect the goods from the port. This allowed the buyer to redevelop its strategy with regard to the supply chain. The effects of the digital platform allowed the process of lodging the customs declaration to be more efficient as the commercial invoice and HS codes could be directly gathered from this platform. This was made possible due to the API and blockchain data pipeline architecture of the digital platform. The API-structure allowed the data to be automatically collected, whereas the blockchain structure enhanced the trustworthiness of the submitted data. Regarding, intermodal transport. The digital platform allowed the buyer to have an accurate and actual time of release and arrival of the container. This allowed the buyer to improve the planning of the collection of the container. When observing the control points it was identified that the main control points of the freight forwarder are two-fold. First, it has the expertise and capabilities to be able to perform the customs lodging. Secondly, it has the capability of gathering and forwarding logistics data within the network. Within the tyre case, both of these control points were absorbed by the buyer.

Using the control point evaluation a set of four different scenarios were identified. These developed scenarios are not comprehensive, but a combination of these scenarios are likely to be observed in the near future. For every scenario, it is evaluated how the actor could use its current control points and the digital infrastructure to increase its control on the process and thus enable reconfiguration. Firstly, the status-quo scenario. In this scenario, there is not a clear actor who absorbs the activities of other actors. The main benefits of the digital infrastructure are experienced throughout the chain as the different actors increase their efficiency using automation and digitisation of the communication processes. In this case, no reconfiguration is thus observed. The second scenario is the development of capabilities to perform more logistical tasks within the supply chain by either the buyer, the seller or both. As observed within the tyre case, the buyer is able to more efficiently perform the customs lodging and the arrangement of land transport due to having access to the commercial invoice and the actual time of arrival and release of the container. An identified stimulating factor within the capability development of the buyer/seller is the standardisation of the data and the development of a market solution to booking and tracking logistical transport. The third scenario is where the carrier becomes a one-stop shop for logistics. Using their central position within the supply chain, they are able to redevelop their value offering. This offering is expanded with the logistical support of lodging customs data and providing intermodal transport. The fourth scenario is that of the freight forwarder expanding its value offering. Here the freight forwarder expands into managing the customer’s warehouse and perform a larger set of logistic services towards the customers.

While innovation has always been viewed as a way to create sustained competitive advantage, the need to innovate has never been more for the financial sector. The financial industry, especially the financial service industry has been dominated by traditional institutions: Banks, in the past. However, with the advent of the digital transformation era, the distinction between different industries hardly stands. Tech companies are challenging established financial firms through high tech financial products and services. This creates a highly competitive innovation environment for Banks to compete in. Innovation was not a high priority for banks previously, however now they see themselves fighting against technology companies on unfamiliar battlegrounds. To compete with technology companies, the financial industry is shifting its focus to products and services based on emerging breakthrough innovations. Innovations centers are being set up in organizations that experiment with several technologies simultaneously. This study is aimed to help innovation centers at financial organizations in their innovation efforts, more specifically in understanding when the innovations are ready. When several innovations are being developed in parallel, it is easy to lose sight of what qualifies as mature. Past literature, in the field of innovation management, has suggested Innovation readiness assessment as a method to understand the maturity/readiness of innovations. However, most of these studies have been fragmented, with no application in the financial sector. Based on these gaps this study is used to answer the research question “How can innovation centers at financial institutions evaluate the readiness of emerging technologies in the pre-diffusion phase?” Through an intensive literature review, four dimensions are identified as crucial to innovation readiness: Technology, Organization, Market, and Regulation. The Regulation dimension is later combined with the Market dimension to keep this study more generalizable. Based on these dimensions, an initial framework is developed combining factors from each of the four dimensions. The initial framework consists of 28 factors: Six technology factors, ten organization factors, and twelve market factors including factors for the regulatory aspect. The initial framework is later tested in a financial organization using three case studies. Each case study is considerably different from the other. These cases are investigated from a dyadic viewpoint, considering opinions from both technology and business actors in the organization. The data is collected via semi-structured interviews and is predominantly qualitative. Furthermore, Data is codified and analyzed using a Computer Assisted Qualitative Analysis Software (CAQDAS). The results from the analysis are presented in the form of individual case reports followed by a cross-case study of all distinguishing factors. The framework is readapted into a tool, based on the insights generated. Known as the Financial innovation readiness tool (Financial IRT), it delineates readiness factors into Pivotal, Indeterminate, and Differential. While Pivotal factors are highly relevant to innovation readiness, the Differential category accounts for factors with fluctuating relevance across cases. This tool is supplemented with a process for its application. The process allows innovation centers at financial centers to surface relevant readiness factors associated with an innovation and compare different innovations. As an addition to the existing decision-making process, the tool allows exploration and identification of potentially successful innovations. Prioritizing ideas allows time, effort, and investment to be directed towards projects with more chances of being a final product. Hence, with the use of the Financial IRT, the innovation process at financial organizations could be made more efficient. Although the results are quite encouraging, the generalizability of the tool is weak. The tool needs to be tested for its applicability across industries. Moreover, the tool is in no way definite in its application. The study was explorative in nature. There may exist other concepts that were not covered in this study. This opens the possibility for further investigation.

Floating wind seems to be on the cusp of achieving large-scale diffusion with the commissioning of floating wind farms of commercial-scale. From a single full-scale prototype off the Norwegian coast in 2009, now to double digit rated capacity floating wind turbines to be commissioned by the end of 2022 and tens of gigawatts of installed capacity expected to be switched-on globally over the next decades. This can lead to fundamental changes in related industries and society, and the floating wind turbine is therefore considered a breakthrough technology. However, several designs of floating wind turbines have been invented, introduced and to some extent diffused in the floating wind market, while a dominant design has yet to emerge. The pattern of development and diffusion by Ortt & Schoormans (2004) is a widely adopted procedure that reveals how such a breakthrough technology may surpass consecutive phases that are characterized by distinct milestones prior to large-sale diffusion. This development and diffusion process may take on a lengthy and chaotic character in which large-scale diffusion of the breakthrough technology is blocked by barriers. Therefore, Ortt & Kamp (2019) developed a theoretical framework of core and influencing factors that serve as a prerequisite for large-scale diffusion of breakthrough technologies. To overcome or circumvent these barriers, the innovating company may adopt a niche strategy during the innovation phase to commercialize the technology, or to reintroduce the technology to the market after changing the physical aspects or the business model in order to better align the technology to the market during the market adaptation phase (Ortt, Langley, & Nico, 2013). Furthermore, niche strategies may be adopted to increase the knowledge and resources within the company, or to influence the broader technological innovation system by changing the behavior, opinion or perception of Suppliers, Customers or Institutions to gradually create or shape the niche market (Schulz, 2019). Thereby, the companies that developed the alternative designs of a floating wind turbine are well-guided in assessing the market and selecting a niche strategy accordingly. IHC IQIP is a supplier of equipment for the installation of reliable foundations and moorings in the offshore wind market and hence offers a unique set of knowledge, skills and competences to developed Complementary Products and Services – one of the core factors for large-scale diffusion - for the emerging floating wind market. Nevertheless, the perspective of a supplier of Complementary Products and Services and its strategic impact on the development and diffusion process has been largely neglected in the management and innovation literature. The theoretical objective of this thesis was therefore to create a better understanding about the mechanisms that drive market formation in a niche market where alternative designs of a breakthrough technology compete to achieve large-scale diffusion from the perspective of a so-called Complementor. In turn, the managerial objective was to develop a theoretical framework that aids managers in selecting a niche strategy to develop and diffuse Complementary Products and Services that are tailored to one or more designs in such a niche market.