Large organisations increasingly establish dedicated innovation hubs to explore emerging technologies, business models, and external partnerships. However, these units remain embedded within parent organisations whose governance structures are primarily designed for reliable, efficient, and highly controlled operations. This creates an organisational ambidexterity challenge: innovation hubs require flexibility, experimentation, and tolerance for uncertainty, while the wider organisation depends on standardisation, accountability, traceability, and risk control.

This thesis investigates how structures designed for exploitative operations influence exploratory innovation activities within an embedded corporate innovation hub. The study adopts a qualitative, phenomenon-centred case-study design, using the Collins Aerospace Innovation Hub as an empirical entry point into the broader organisational phenomenon. A theoretical analysis of ambidexterity, governance, process management, and embedded innovation units was combined with several semi-structured interviews and secondary cases from comparable organisational settings. The findings were analysed across three interconnected levels: industry, firm, and innovation unit.

The results show that industry-level requirements related to safety, certification, and regulation are primarily translated into internal governance procedures at the firm level and subsequently experienced as operational tensions within the innovation unit. The firm-unit interface therefore represents the main practical location of the exploration-exploitation tension. While exploitative structures can constrain experimentation when applied too early or uniformly, they also support accountability, future certifiability, and the transfer of exploratory outcomes into the wider organisation.

The thesis concludes that the central managerial task is not to remove governance, but to tailor it to the maturity and uncertainty of exploratory work. Differentiated governance, phased controls, boundary-spanning roles, internal alignment mechanisms, and a carefully designed balance between autonomy and organisational connection can help innovation hubs remain sufficiently flexible to explore while sufficiently integrated to generate value for the parent organisation. ... Read more

Innovation diffusion research alternates between structured life cycle and evolutionary models and process perspectives that emphasize disruption, reversals, and contextual complexity. This thesis develops the Modular Non Linear Technology and Innovation Diffusion Model as an integrated analytical architecture that reconciles structural regularity with real world complexity.
The model consists of two tightly coupled components. The trajectory model is descriptive and answers how technology and innovation diffuse. It conceptualizes diffusion as an eight phase modular system consisting of Invention or Discovery, Innovation, Pilot, Adaptation, Acceleration, Stabilization, Decline, and Legacy. Phases are defined by functional purpose and empirically interpretable entry and exit conditions. By treating phases as modular states rather than as a fixed chronological sequence, diffusion histories are reconstructed as transition sequences instead of a single canonical path. This enables systematic representation of skipping, looping, regression, compression, overlap, and parallel progression within a bounded transition space. The navigation framework is explanatory and answers why diffusion unfolds along a specific pathway. It identifies and categorizes internal and external drivers and links them to transition sequences through a structured driver transition matrix. This framework clarifies how interacting technological, resource, market, institutional, organizational, and infrastructural conditions shape feasible pathways and constrain alternative trajectories.
To operationalize the model, a methodological framework was developed that integrates criteria driven phase reconstruction, transition space mapping, driver typology construction, and structured case validation. The architecture was subjected to breadth oriented micro validation across more than forty historical innovation and technology cases and depth validation through two longitudinal illustrative cases, namely mRNA COVID 19 vaccines and passenger airplanes. Across cases, diffusion histories mapped coherently onto the modular phase architecture without imposing artificial linearity. The bounded transition grammar proved sufficiently flexible to represent diverse diffusion patterns while preserving analytical comparability. Driver mappings provided systematic explanatory depth for pathway divergence, acceleration, regression, and stabilization.
The thesis contributes an integrated descriptive and explanatory language for analyzing innovation diffusion, enabling cross case comparison, cumulative theory building, and more structured reasoning for managerial and policy decision making. ... Read more

Rotterdam’s petrochemical cluster illustrates how deeply integrated oil-and-gas systems can stall decarbonisation despite mounting policy pressure. Combining the Technology Innovation System framework with Path Theorem, this thesis develops an analytical lens that is both diagnostic and dynamic. A qualitative case study reveals an incumbent Oil & Gas TIS that is technologically mature yet economically eroding, and an emergent low-carbon-hydrogen TIS that remains fragile amid volatile regulations and missing backbone infrastructure. The cluster is caught in a “paradoxical interdependence”: firms are physically interconnected but strategically isolated, reinforcing lock-ins such as the Green Fling, Incrementalism and Solitariness traps. Two path-creation interventions are proposed. Cluster Billboarding to attract like-minded entrants and Industry-Authored Roadmaps to align incumbent visions. Both target the Network Formation & Coordination building block to unlock self-reinforcing, hydrogen-oriented trajectories. Findings emphasize that organisational collaboration and a stable regulatory climate, more than technology itself, dictate the speed of transition. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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?” ... Read more

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.   ... Read more