This thesis addresses the increasing vulnerabilities in modern supply chains, particularly within the maritime industry. Emphasizing the crucial role of procurement in risk mitigation, the study challenges conventional lean management, advocating for agile supply chain strategies. It introduces the Integrated Supplier Matrix (ISM) to enhance supplier segmentation, combining aspects of the Purchasing Portfolio Matrix (PPM) and Supplier Potential Matrix (SPM).

Conducted as a case study at Allseas, the research employs the Best Worst Method (BWM) to rank risks, identifying the uniqueness of the product, rules and regulations, and external factors as significant concerns. Through graphical representations and ISM-based supplier segmentation, relationships between supplier willingness, capabilities, risks and profit impact are established. The findings stress the importance of communication and trust in supplier relationship management (SRM) trade-offs, including inventory reliance, contract durations, sourcing strategies, and addressing non-performing suppliers.

The research provides insights for maritime managers, recommending the integration of theoretical SRM approaches with multi-criteria decision-making methods for resilient supply chains. The suggested shift from lean to agile management and the ISM implementation offers practical strategies to optimize relationships, navigate complexities, and establish adaptive procurement approaches, effectively mitigating supply chain risks.

The financial industry has been significantly transformed by innovations, but traditional banks have managed to maintain their dominant position without implementing many innovations. However, new technologies have caused a shift and should no longer be ignored. Financial institutions are now facing competition from high-tech newcomers, also known as Fin- or BigTechs, that threaten their dominance. A recent study shows that financial institutions have a growing interest in (cloud) platform business models (Fintechs) without being handled in a responsible way. Firms are under pressure to transform, but guidance on how to design and control this transformation is hard to find. EU regulators are concerned about the speed and scale at which financial institutions are moving critical functions and market operations to a few cloud platforms and will soon have to demonstrate their ability to recover from a cyber-attack. Choosing a secure cloud platform is essential, but the complexity, risks and regulation make this decision-making process challenging. This study aims to identify the key factors influencing the adoption of cloud platforms within the Dutch financial sector and determine the most suitable Cloud platform for this sector.

Based on the knowledge gap and the aim of this research, the following main research question was formulated: What are the key influencing factors that determine the adoption of a cloud platform within the cloud platform battle within the Dutch financial sector? The study uses a qualitative approach and the Best-Worst Method to determine the key factors and the most suitable cloud platform. As the focus is on standard selection, a modified version of van der Kaa's 2011 framework was eventually chosen to identify the most important factors in this battle. From the 29 factors in the framework, the 24 most relevant were selected and five additional specific Cloud platform factors were added. This resulted in a new set of 29 factors relevant to Cloud platform adoption. Data is collected through literature review and expert interviews. Interviews were conducted with 13 IT/Cloud experts from various Dutch financial institutions, varying from the consulting, banking, insurance, government and academic sectors.

Ultimately, this research showed that the factors: 1) Security & privacy, 2) Brand reputation and credibility, 3) Pricing strategy, 4) Commitment and 5) Compatibility, are the key influencing factors determining the adoption of a cloud platform within the cloud platform battle within the Dutch financial sector. Based on these key factors and the platform comparison, it was found that among the three most dominant cloud platforms (Amazon Web Services (AWS), Microsoft Azure, and Google Cloud), Microsoft Azure is currently the most suitable cloud platform for the Dutch financial sector.

Policy making and the decision-making process has developed over the past decades to include more (scientific) evidence to support policy construction, such as the Cost-benefit Analysis or Environmental Impact Analysis. However, depending on the perspective of the policymaker as well as the evaluator, successful policies outcomes may be different for varying stakeholders. This can then potentially lead to conflict during the decision-making process for future policies, on which metrics were deemed successful. Through case studies, in which the advocacy coalition framework will be applied, the role of CBAs and EIAs is explored on the decision-making process for public policy. How the procedural policy tools affected advocacy coalitions’ beliefs and strategies for/against policies is analysed. The ex-ante evaluations without legislative support for incorporation for policymaking seemed to have little effect on policy- or core belief-changes of stakeholders, even when confronted with negative outcomes. With enough opportunities created by coalitions to discredit outcomes not in line with their beliefs. Furthermore, the multi-level decision-making seems to be dominated by the national level government, who hold and maintain formal authority while preventing opportunities for intervention without legislative support. Instead, procedural policy tools that have more legislative support, have more influence on the policy implementation and decision-making process. Procedural policy tools seem to be more informative and symbolic, with outcomes more used for debates without nuances rather than to explore and improve new policy options. Hence, limiting the formal role of the policy tools to explore policy alternatives. The late timing of tools’ use in the decision-making process and exclusion of regional stakeholders in the appraisals exacerbated negative experiences for regional stakeholders. Leading to increased distrust between advocacy coalitions, preventing compromises from being found while creating more conflict among stakeholders. Furthermore, procedural policy tools were very resource dependent, limiting regional actors’ ability to perform analyses due to limited resources. Making them highly dependent national governments, fuelling the distrust and conflict based on the earlier mentioned exclusion and lacking transparency. Creating information (and resource) inequalities which can be exploited during the decision-making process. Suggestions for improvement and conflict reduction are the introduction of formal third-party supervisory committees for procedural policy tools and mandatory (regional) stakeholder-inclusion and methodology’ transparency measures.

The Iron and Steel (I&S) industry is the largest contributor to man-made greenhouse gas emissions. The products of the I&S industry are a constant necessity, e.g. for civil infrastructure. In addition, their processes are interwoven with coal and natural gas properties, which classifies this industry as a ’hard-to-abate’ sector. Furthermore, fundamental technology changes in process and energy utilisation practices are required to fully decarbonise the I&S industry before 2050. Steel processes are divided into two major production routes, the blast furnace and the direct reducing plant. Focusing on the carbon avoidance route, the hydrogen-based direct reduction process is the most promising to decarbonise the I&S industry in Europe due to its ability to use natural gas as an intermediate energy source. Several techno-economic assessments have explored the energy, emissions, and economic potential of such conceptual systems, concluding that carbon emissions are highly sensitive to the CO2 intensity of consumed electricity. However, none have used the electricity mix to estimate the electricity price and associated CO2 missions on an hourly basis to investigate the performance of such systems. Therefore, a case study is proposed of Tata Steel Netherland (TSN), which has recently announced its intention to switch towards hydrogen-based steel through the DRI-REF route. The modelling and simulation research method is used to assess this case-specific process’s technical, environmental, and economic performance in 2030. A conceptual model is developed employing the findings of the literature review. Hourly data from the national electricity mix are acquired from the EMF v7.0 model from the company Blueterra, and TSN provides specific process characteristics. From this approach, several simulations could be made for different hydrogen volumes to evaluate the performance of the DRI-REF system in the Dutch context. The simulations showed a significant shift in energy sources for increasing hydrogen volumes, which leads to a reduction of 70.1% in direct CO2 emissions under the 2030 energy market conditions. However, if the indirect electrical emissions are considered, this reduction potential is only 2.2% CO2 reduction. Although this demonstrates that in 2030 the CO2 intensity of the electricity mix is approximately the breakeven point between NG and H2 production, this development also shows a major shift from CO2 emissions towards the electricity producers. Additionally, the electricity price breakeven point is a factor 3 lower than is currently estimated by using the IPKA0 electricity generation capacity scenario of Tennet. As a result, the levelised cost of production increases by 34.9% for the maximum Htextsubscript2 volume compared to NG-based production, with electricity and capital investments as the largest increasers. Furthermore, the hourly electricity price and associated CO2 emissions data enabled to determine the variability over time. A significant increase in the interquartile spread in emissions and cost calculations is observed for increasing hydrogen volumes. This implies that in the future when electricity is predominantly produced by volatile renewable energy sources such as wind or solar energy, the production uncertainty will increase significantly if this industry shifts towards hydrogen. However, this also increases the potential of flexibility technologies. Industries with flexible production processes can thrive in the Dutch environment as they could provide load-balancing services.

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

E-commerce is rising in demand and sales are forecasted to reach 7.4 trillion dollars by 2025. Many products are shipped to consumers from warehouses directly rather than being displayed in a physical retail store. Smooth and effective warehousing operations are more crucial with the increased dependency on warehouses nowadays. More than 130 key performance indicators (KPIs) exist for warehouses. Often a summarized and meaningful metric is desired to give an accurate evaluation of the overall warehouse performance (OWP). The most common method of measuring OWP used in the literature is done using data envelopment analysis (DEA). However, it is difficult to find empirical evidence that DEA has significantly improved performance evaluation and benchmarking in actual non-production conditions. A new method for measuring OWP is explored using a widely accepted overall metric in the manufacturing industry, namely overall equipment effectiveness (OEE). The use of OEE as a performance measure for warehouses or in logistics generally has not been researched extensively yet. The research problem lies in evaluating the overall performance of warehouses using a modified OEE framework. Therefore, a challenge to identify the components of a modified OEE for warehousing was present. Additionally, a modified OEE formula for the automated warehouse was made based on the major losses that occur in such warehouse. The nature of the items processed at a warehouse and the warehouse utilization stage impacts the KPIs to be considered by a modified OEE model. A framework for a modified OEE for warehouses was developed using these inputs. It was agreed that one of the main uses of an OWP measure lies in reporting performance to different stakeholders, mainly the warehouse contractor. Additionally, using OEE can give insight to areas of improvement which gives a science-based ground for continuous improvement. The research was done using a single case study in the inbound part of an automated warehouse for online clothing retail with an industry leader. Expanding this research into other warehouse areas is suggested, and a final OWP using a modified OEE model may be achieved after numerous iterations and case studies. Further quantitative analysis of the performance of OEE as an OWP can validate the results more. It is argued that a universal indicator of some sort using OEE can be achieved in the future, this can then be used for benchmarking alike warehouses.

In this research, the creation, use and spread of knowledge acquired in Building with Nature pilot projects is researched, with the goal of providing recommendations to improve this use and spread in future Building with Nature pilot projects. To achieve this, a case study with the Sand Engine as the subject is performed. In addition to this, a literature review and interviews were undertaken, and two System Dynamics models were created which were applied to the Sand Engine case. As a results, seven recommendations for future pilots were found: First, ensuring the internal success of the pilot is crucial. 2. Including knowledge creation and spread as design factors in the pilot project design, 3. Designing the pilot project to be multi-functional, 4. Ensuring the pilot project fits the long-term policy plans and strategy of important stakeholders, 5. Involving champions of knowledge, who are able to turn over the project at the right time, 6. Implementing knowledge programs within the pilot project and 7. Ensuring the free sharing of knowledge between stakeholders and interested parties. Recommendations for further research and policy include performing complementary case studies on other Building with Nature pilot projects, expanding the number and variety of interviewees, and implementing a new format of data collection, management and storage in Building with Nature pilot projects.

Public-private partnerships (PPP) is defined as a form of structured collaboration framework in the procurement strategy where risks, costs, benefits and resources are shared between public and private sector through the life-cycle of the project (Koppenjan, 2005). Previous research revealed the use of PPP is still being in question, whether the benefits outweigh the costs of PPP. It is also found the utilisation of Cost-Benefit Analysis (CBA) in transport PPP project appraisal remains a niche. Therefore, this study aims to research what PPP brings societally, as well as to contribute to the existing literature of transport infrastructure by exploring the social potential of PPP project compared to traditional public procurement through the use of societal CBA.

A theoretical conceptualisation is performed by means of modelling the social potential of a PPP project. The result from the conceptual model development is then investigated in an empirical setting (case study). Based on the analysis, an inventory of the potential costs and benefits of a PPP project is presented into two models: PPP project with actual tolls and shadow tolls. The similarities between the two models include the potential social impacts resulting from cost-saving investment, quality-enhancing effect, better risks management, and higher up-front transaction costs in a PPP project. Conversely, implications of PPP with both tolls also have different societal impacts due to distinct payment arrangement between them. Actual tolls provide users with incentives to decide whether or not using the road, since they have to pay the tolls independently. It is thus understandable if there will be a reduction in traffic volume on the road (mobility loss). Road users who decide to avoid such costs will experience a loss of consumer surplus. However, those who keep using the road will experience travel time gains due to less congestion. It is also important to note that mobility loss in PPP project with actual tolls will result in more societal gains, such as environmental gains in which less CO2 emissions would be generated on the road (less pollution). In contrast, the demand for the road use will not be influenced in PPP project with shadow tolls, thus neither environmental nor travel time gains can be obtained. Nevertheless, the private party would receive higher revenue. It has to be acknowledged this study is conducted on a positive case, where all potential impacts in the theoretical conceptualisation were confirmed in the empirical analysis of the Indonesian context.

To conclude, the key takeaway of the research is that in doing the CBA, outcomes of a PPP project compared to traditional public procurement is dependent on the way the tolls are implemented. The research shows the importance of distinguishing between PPP with actual tolls and shadow tolls. Reflecting on the theoretical conceptualisation and empirical analysis, there have been huge implications for the CBA outcomes since there are different potential societal costs and benefits to be expected in the two models. The significant implications have been outlined for the public party, the private party and the road user.

Sales are the backbone for a company, sales forecasting plays an important role in organizational decision-making, and improving the sales forecasting performance has been an intention for managers. Sales forecasting is a management function that is affected by various organizational factors. The aim of this research is to validate a Sales Forecasting Management (SFM) framework to improve the sales forecasting performance in a high-tech industry and study the impact of forecasting on the organization’s business performance. The organizational factors such as sales compensation structure, product life-cycle stage of the company, information logistics, and cross-functional communication of the SFM framework are validated in the context of the high-tech industry. Further, the framework is quantified by developing an appropriate sales forecasting model. Both quantitative and qualitative forecasting methods are studied and the most appropriate technique with high accuracy is chosen. Finally, the effect of sales forecasting performance on a specific business outcome – End of Service Benefits (EOSB) is quantitatively measured. The EOSB is the gratuity payment received by the employees of the company when they are terminated or resigning from the job. It is a crucial operational expenditure that is proportional to the salaries earned by the sales employees and the accuracy in EOSB forecasts has an impact on the company’s stock price and investment decisions. The results of the research show that the accuracy in sales forecasts has a significant impact on the End of Service Benefits forecast. The research also finds that the SFM framework has to be adjusted to include the sales pipeline stages as an important organizational factor that influences sales forecasting management. Thus, the thesis provides an interesting insight to include the sales pipeline stages in the framework to improve the sales forecasting credibility. Finally, the SFM framework is evaluated, the impact of sales forecasting performance on a business outcome (EOSB) is quantitatively measured using a sales forecasting simulation model and the conclusions are derived.

The rise of the so called Insurtechs, leveraging digital technologies to offer superior and personalized offerings, has shaken the insurance industry leading to a new age of innovation and business models. In addition, the importance of a digital customer experience is increasing as the number of sales completed online are rising. Customers expect wide availability of personalized options and offerings tailored to their specific risk scenarios. Traditional insurers should react fast to face the threat of new players and remain competitive in this fast-paced market environment. A customer-centric approach to digitalization is required to meet demanding requests from customers while targeting benefits including financial flexibility, lower Total Cost of Ownership (TCO), speed to market, and availability of information anywhere and at any time. Concurrently, the rise of cloud computing technologies spark interests in traditional players that have an opportunity to tackle these challenges by transforming their IT infrastructure to generate value for clients while substantially improving the enterprise’s operations. The aim of this document is to inspire the management to perceive the need for innovation and structural change and provide them with the tools and key recommendations to tackle the challenge. Besides, the literature is lacking contents weighting the cloud computing advantages in the insurance industry and exploring the business model’s innovations necessary to welcome the use of the cloud. Hence, the additional goal of this research, is to address this gap and explore the barriers hindering cloud adoption in the financial services industry together with the mitigation strategies expected to reduce such risk factors.

The globalizing economy with its new goods and services, knowledge spread, and competition for talent is an increasing complexity for organizations, which requires organizations to adapt more quickly. Organizations are essential to society, as people are more productive in groups. For their continuity, it is important that organizations continuously keep adapting to their environment. The new economy requires agile organizations that can quickly (co-)produce customized responses to the demands of the market. At the present moment, the hierarchical organizational structures face limits of their usefulness and are being replaced by a lean form of organization. In their place, these decentralized organizations are growing to overcome the limitations of these hierarchical structures. The coronavirus pandemic enforced a working from home policy that strongly decreased the access to work. This development stimulated organizations to move to decentralized organizing with a marketplace for team formation. The introduction of self-managing teams enables this desired dynamic and leads to an agile organization. Virtualization has further enriched and diversified these teams. These self-managing teams are useful for constructive conflict, diversity, innovation, performance gains, and synergy. The coordination of work changes with the introduction of self-managing teams. These teams in here in a strong individual choice of people, which is both a benefit and a risk for people and organizations. A digital marketplace is a supporting institution that can provide overview, insights, and access to several opportunities by combining supply and demand of teams and talents across organizational borders. Connecting workers to relevant teams is also the main performance criterion. Still, bounded rationality can result in non-optimal individual choices on the marketplace and a one-size-fits-all approach does not match the preferences of the heterogeneous workers. A filter within the marketplace is needed to decrease the obstacles of decentral coordination of activities, however, there is limited research available on this subject. This research follows the theory of design science research with the three cycles. The design objective is to support users in self-managing team formation with a recommender system and custom filtering algorithms. This is achieved with twelve design artifacts: personalization, criteria and objectives, recommender system, data engineering, ETL script, logical data model, custom filtering algorithms, data science, validation queries, hybrid filtering algorithm, DevOps, and advice on UX design and usage. The designed system was built with the requirements of the program of business demands. The constraints for the recommender system with custom algorithms are personalized recommendations for each worker and the incorporation of platform rules. The objectives are regular updates, scalable, open-source, and easy to set up.

In a world where companies rely increasingly on machines and automated production lines to deliver customer value, asset availability is a becoming a larger driver of companies’ productivity and thus performance. In effect, where maintenance was historically perceived as a cost-centre, it is generally treated as a value-adding business element that must be effectively managed today. However, the increased use of machines and automation has also resulted in an increasing portfolio of assets, often with a highly complex nature. Coupling the growing portfolio of complex assets with factors such as maintenance being a cross-functional activity, stricter HSE requirements, a stochastic maintenance demand, maintenance management complexity has also increased drastically. The result is a reality where maintenance is, on the one hand, becoming more critical to companies’ performance. Simultaneously, it is also a large and growing source of operational issues and costs that is highly challenging to improve.

This thesis project is conducted for a consulting firm specialised in helping customers realise benefits. Prior to this thesis, they had access to a highly successful way of managing maintenance developed and applied in the industry by a second company. This maintenance management approach is called The Maintenance Wheel. It has realised benefits in the magnitude of roughly 10 M EUR per year in combined savings from two large-scale facilities. Moreover, it contributed to a significant increase in maintenance quality. In effect, this maintenance management approach provides a way to cope with the increased maintenance complexity, with massive empirical benefits.

Seeing this, the consulting firm has attempted to help customers with ineffective and inefficient maintenance operations realise benefits through The Maintenance Wheel. However, they have struggled to convince their customers to implement it, seeing that the customers struggle to understand the management approach. As senior managers considering The Maintenance Wheel will perceive it as an innovation, Karabin is struggling with an innovation diffusion barrier, caused by a failure to transfer knowledge on how The Maintenance Wheel works effectively.

The management approach was developed internally by the second company, without considering diffusion. Consequently, there existed no conceptual description of the management approach prior to this thesis. Seeing this, the thesis project research objective was to design an MMF aimed communicating how The Maintenance Wheel works to help cope with the knowledge-based diffusion barrier. Note that an MMF is a theoretical framework explaining an approach to managing maintenance. This MMF effectively provides knowledge on how The Maintenance Wheel work, and was constructed with a design science research methodology.

The evaluation indicated that the constructed MMF sufficiently communicates how The Maintenance Wheel works. After a brief presentation for senior managers with no prior knowledge of how The Maintenance Wheel worked, it was possible to have in-depth discussions. Thus, the knowledge-based diffusion barrier caused by customers’ senior managers not understanding the management approach should be solved.

Nevertheless, the evaluation also showed that one particular area of future development is required. The senior managers interviewed requested examples of how the framework work in practice. In effect, to help more effectively transfer knowledge on how The Maintenance Wheel works, the consulting firm should provide practical examples of the different elements of the framework.

This project has researched the consequences of blockchain technology on the
expected future role of banks. And furthermore, how banks can respond to these effects to improve the innovation strategy and remain their future relevance.

As the insurance industry engages in numerous processes which are characterized by the exchange of data which is updated by multiple parties; a blockchain, as a single source of truth, has the potential to increase efficiency and reduce the complexity of these processes. However, the complexity, uncertainty, transforming potential and barriers to adoption associated with blockchain technology make it hard to assess its impact on insurers. Therefore, this research aims to help insurance industry business decision makers to anticipate the impact of blockchain technology on their business models, by finding the most important parts of the business model that need to be addressed. It does so by means of expert interviews and a business model stress test workshop. In this workshop, experts assess the impact of uncertain future developments on an insurance reference business model which is described using the STOF business model ontology.
It has been found that currently, enterprise-grade blockchain solutions that meet the requirements of the insurance industry regarding governance, privacy, scalability, identity and access management, security and reliability are not available. Besides no concrete insurance use cases that will actually realize benefits have been found. Therefore, it is hard to justify investments that are specifically targeted at blockchain technology. However, there are two investments insurers should make that are not specifically targeted at blockchain technology, but will prepare insurers for technological innovation, whether blockchain will reach maturity in the near future or not. The first and most important investment is related to standardization. The workshops led to the insight that the most crucial uncertainty outcome is the strength of cooperation. The standardization of data formats and field descriptions is a prerequisite for this cooperation. Insurers just started this standardization in order to facilitate data exchange with other insurers. Insurers should continue their standardization efforts, as it will facilitate data exchange in the insurance value chain and being compliant with GDPR, regardless whether blockchain will be implemented. The second investment is related to rationalization, it will enable insurers to respond more quickly to changes in IT and be compliant with regulation. Blockchain can be a driver for thinking about how systems can be developed to support decentralization, a division of roles and agility, however, the rationalization process should not be targeted to a specific blockchain platform, as it is hard to choose from the scattered field of blockchain platforms.

Blockchain technology can be transformational to a lot of business sectors. Businesses have attempted to extract value from blockchain technology but failed to do so. An unexplored blockchain business initiative is Tokenized Ecosystems. Startups using Tokenized Ecosystems have the potential to disrubt incumbent businesses. Yet, it is unclear how they should react. A structured approach to assess whether a business should apply Tokenized Ecosystems to their business processes is lacking. This thesis proposes such a structured approach: a Tokenized Ecosystems assessment tool for business processes. A design science approach is used and gathered insights from academic literature are confronted with empirical evidence. Eight of the most outstanding and globally renowned blockchain and tokenization industry experts and thought leaders were interviewed.

The rise of ICT and the ever increasing competitiveness in industries have pushed firms to increase their propensity in changing and innovating their activities. As this need for firms to change constantly increases, the study of business model innovation have taken the spotlight. There exist a need for the knowledge stream to grow and understand the mechanisms surrounding the process, as firms in business strive to do better business model innovation and gain a sustainable competitive advantage.
The constant strive for innovativeness in doing business model innovation seems to be limitless, yet according to various research on institutional theory, there is a limit in how innovative or distinctive a firm can be to not be shunned by its environment (suppliers, competitors, customers, policy-makers).
More specifically, past research have proposed that innovativeness correlates positively with performance. Yet, neo-institutionalism postulates that there is a limit where innovativeness impacts positively to firms and its processes, before being penalized for being too different.
This research empirically observes how the tensions between innovativeness from business model innovation and conformity from institutionalism impacts the business model innovation process in firms. Furthermore, how does insitutionalism ultimately affect firm performance?
The results of this research shows a U-shaped relationship between institutionalism and business model innovation. The observed results also show that institutionalism's effect towards firm performance is mediated partially by business model innovation. The results of this research also support past observation that business model innovation does correlate positively with firm performance.

Today’s market environment is characterized by increasing competition. This competition forces incumbents to innovate if they want to sustain their competitive advantage. Large enterprises start to adopt methodologies pioneered within the startup world, like the lean startup methodology, the innovate. The adoption of this methodology has proven to be difficult, and incumbents face a lack of control with regards to these ventures.

The practical objective of this thesis is to enable large enterprises to control and steer internal lean ventures (ventures following the lean startup methodology) effectively. The theoretical objective is to bridge the knowledge gap concerning the understanding of internal venturing and the application of the lean startup methodology in large enterprises.

To reach the objective, a case study within a large enterprise was conducted to answer the research question and reach the research objective. 16 in-depth interviews with relevant stakeholders were conducted to collect data. Finally, the results were validated through relevant literature and by comparison to the results of six additional interviews, conducted with two other large enterprises.

The study found that two elements influence the success of the venturing process: First, the implementation of the venturing process itself (Section 5.1). Especially the alignment and coordination of different stakeholders as well as the quality of the employed metrics. Secondly, a set of additional factors arising from the context in which the process is embedded (Section 5.2). This context is made up of the mindset and culture of the company, the organizational environment as well as the quality of its adoption of the lean startup methodology. The analysis of resulted in the identification of the five recommendations to improve internal lean venturing within large enterprises. Details can be found in Section 5.4.

In conclusion, implementing the lean startup methodology can help navigate this uncertainty surrounding innovation. This implementation requires reliable metrics, company-wide alignment, and the commitment to the methodology. Additional to the implementation, company and industry specific factors mediate the success of a venturing initiative. Large enterprises are advised to take an honest self-assessment and follow a searching and learning approach to iteratively and successfully optimize their process for maximal venturing success.

This research evaluates the Pollution Haven Hypothesis for the chemical sector across the globe. It does so by creating a regression model which incorporates five constructs (market potential, infrastructure, factor cost, governance factors and a measure of environmental stringency) to explain the variance of foreign direct investment (FDI) across countries specified for the chemical sector. The results are by no means unequivocally for or against a confirmation of the pollution haven hypothesis, but the evidence suggests a negative effect of the measure of environmental stringency when FDI is specified further to only the manufacture of chemical products and sampled by averaging as much annual FDI data as the dataset includes.

Traditionally, research in supply management has focused on the linear relationship between buyer and supplier (e.g. Chan & Chan, 2004; Hokey, 1994; Rezaei & Ortt, 2012; Sheth & Sharma, 1997) and on the technical issues faced in Supply Chain Management (SCM) (Fisher, 1997). However, as (Kim et al., 2011) and (Bellamy & Basole, 2013) recognized, both perspectives fail to capture the complex and dynamic nature of supply networks. Therefore, it provides managers tools that are based on nonrealistic assumptions. Despite the attention given in the literature to the activity to optimize the supply base the acknowledgement of its strategic importance in the supply management practices, frameworks for carrying out the process to optimize the supply base are rare (Talluri & Narasimhan, 2005). Moreover, the existing frameworks fail to illustrate the complex and dynamic nature of the Supply Networks that encloses the process of supply base optimization (e.g Kraljic, 1983; Luo, Wu, Rosenberg, & Barnes, 2009; Ogden & Carter, 2008; Sarkar & Mohapatra, 2006). Therefore, the academia has not provided managers a representative mental model of the complexities implicated in the process to optimize the supply base nor how to manage them. For this reason, this thesis attempts to fill this gap by exploring what the system level perspective offers to the literature in the field of supply base optimization. In order to fill this gap, three case studies were conducted with three initiatives to optimize the supply base in Royal Philips. This thesis proposes a theoretical framework to visualize and evaluate the landscape of the supply base optimization. This framework characterizes three different networks involved in the optimization of the supply base and proposed to evaluate the landscape based the three fundamental themes: Network structure, dynamics and strategy. The outcome of the research is the creation of propositions to clarify the process that a firm undergoes when optimizing the supply base. The first contribution of this research is to provide a new definition of supply base opti-mization from a network perspective. Based on the input from the experts and the analysis of documentation of the conventions, the definition of supply base optimization is as follows: “Supply base optimization is an ongoing process that aims to have the right number of suppliers with the right capabilities and right performance in order to meet current and future business needs” The second contribution of this thesis is a theoretical framework that serves one main purpose: To provide guidance to analyze the process to optimize the supply base from a network-level perspective, providing researchers a more realistic mental map of the supply network to analyze its processes. On the other hand, the analysis of the data collected in the firm, namely the interviews and the documentation of each convention, lead us to the third contribution of this research, which is the creation of a process to optimize the supply base. This process takes a network level perspective and acknowledges the interactions of the different actors at each network.

The electrification ratio of Sumba Island has been increased in the past five years from about 24.5% in 2010 to about 43% 2015 in which 55% of the share supplied by renewable energy resources (Hivos, 2015). Despite the progress on electrification ratio, there are still about 238 out of 433 villages which do not have electricity access (PLN, 2017). It is because some of these villages are located in remote areas which have limited access to infrastructures, such as roads and grid access. Currently, the rural households in Sumba Island use fossil fuel to provide their electricity needs. However, the use of fossil fuel is considered polluting, noisy, and expensive. Thus, renewable energy-based power generation needs to be introduced. While wind and hydropower could be very attractive for grid-connected options, off-grid solar Photovoltaic (PV) Systems stand out as the best solution for off-grid electrification because of Sumba’s dispersed population and limited infrastructure. Several off-grid PV projects have been carried out by the government as well as private institutions. However, the adoption of off-grid PV technologies for Sumba’s rural areas remains very slow. From the literature, it is known that the role of business model to overcome challenges of the adoption of off-grid PV electrification in rural areas is considered important. However, there is still no literature which explains how a sustainable business model helps to overcome the barriers faced by PV projects in the rural energy market. An exploratory study using desk research and cases study from seven different PV companies are used to understand how PV companies choose types of business models to address the challenges in the rural energy market. Then, this insight will be used to develop advices on business models for PV companies who want to operate their business in the rural energy market in Sumba Island, Indonesia. In this study, We developed a framework which explains the linkage between the barriers faced by PV companies in rural areas in developing countries and how the business model could help the companies to overcome these barriers. By using this framework, we discovered suitable business models which could be implemented by PV companies in rural areas in Sumba Island. Firstly, it is the distributor model which offers various PV products. Secondly, it is the distributor model which offers electricity services delivered by a microgrid. Finally, study limitations and recommended future studies were offered to improve the framework developed from this study.