Collaborative Innovation can serve to elevate the production potential of firms and organisations as well as preparing them for the future. This process of two organisations collaborating together is very complex and becomes even more difficult when organisations are large and very different in their organisational culture or function. This research describes the design of a tool to aid Collaborative Innovative Capacity in public - private organisational partnerships. The research is based on a case study within the Dutch national rail infrastructure management organisation and focuses on the relationship between this organisation and its maintenance contractors. Through literature research and semi-structured interviews the studied situation is found to consist of two parties trying to innovate together using an imperfect collaborative system. Their separate, struggling relationships with this system are not shared or understood by the other party. This gives rise to a wall of misunderstanding. The designed tool is based on the assumption that through better understanding of the barriers which are present in the other party’s struggling relationship with the collaborative system, the wall of misunderstanding can be lowered which in turn increases Collaborative Innovative Capacity in the public - private organisational partnership. This tool takes the form of a serious game which presents players with scenarios which (potentially) hinder them in their game objective. These scenarios are representations of real-world barriers to innovation. Through confronting players with scenarios which are related to another organisational role than the one they occupy in their professional life, they should gain new perspectives about the struggling relationship of the other party with the collaborative system. Thereby lowering the wall of misunderstanding and increasing Collaborative Innovative Capacity. The results of the design and preliminary testing show that the developed serious game does have an effect in the form of gained attitudes towards the importance of sharing different experienced barriers towards innovations with one another. However measurements show no actual newly gained insights into practical barriers which were not already known to the players. While further research, more extensive testing and measurements, and further specification and expansion of scenarios can be undertaken to increase the value of this tool, after reconsideration a revised design objective is formulated which focuses on the interaction between the participants and relaxes its rigid view on the wall between them. This could yield a tool which is more in tune with the essence of the problem which would also cause it to be much simpler in nature.

Maritime logistics is important for the international volume of trade. Ports are critical in cargo transhipment and provide services to vessels like traffic management, piloting, towage and mooring, which together are called the Nautical Chain since these services are dependent on each other. Due to the importance of maritime logistics, it is important that the supply chain functions resiliently and thus ports function resiliently. For ports to function resiliently, the Nautical Chain should function resiliently. Currently there is no knowledge on the resilience of the Nautical Chain, which is the gap this research addresses. The aim of this research is to gain insight in the current state of resilience of the Nautical Chain, and gain insight in the effect different mitigation strategies have on improving this resilience. A literature review is performed and a discrete event simulation model is built to gain insight in the resilience of the Nautical Chain. The results show that the largest improvement to the resilience of the Nautical Chain can be achieved by a simultaneous increase in pilots and tugs.

Emission-free zones are being instituted in cities in the Netherlands to combat the emissions caused by transportation activity causing operators of large commercial vehicle fleets to electrify their vehicle fleet. E-truck fleets need sufficient charging infrastructure and power capacity at the distribution centres they operate from. However, due to the prevalence of grid congestion causes, the capacity of actors’ connection to the power grid is be constrained and solutions behind the electricity meter are necessary to either increase local supply or reduce momentary demand. The main research question is: “What is the most cost-effective electric infrastructural composition and operation to facilitate the electrification of heavy truck fleets of large-scale distribution centres in grid congested areas in various scenarios to ensure that the route schedules can be driven?” This thesis proposes a mathematical mixed-integer linear programming (MILP) model which simultaneously optimizes the composition and operation of the electric infrastructure of a distribution centre, while considering the periodic energy balance, for various scenarios in the electrification process. This has not been done earlier in the literature for distribution centre-like systems, while no similar use case has been studied in the Netherlands or its general region. Before the model was applied to the real-world case, it was verified using a recalculable numerical test and validated using linear regression analysis. In the model validation the K-means method was used to determine a typical day per month, to comprise the simulation period to 288 time periods of an hour. The proposed mathematical model was tested by means of a case study and various scenarios for the distribution centre of a supermarket company to analyse the models’ behaviour in a practical setting. The results show that from a greedy charging subscenario to a variable electricity prices subscenario, the model is able to decrease the yearly total costs and the number of infrastructure components required. The model is able to reduce the yearly total cost by up to 19.4% in the final scenario. The infrastructure investment steps in the electrification process to take, would be to install consecutively or collectively 1, 3 and 7 charging stations and 994, 1623 and 4340 PV panels in 2022, 2025 and 2030, leading to a PV installation with a total rated power of 1.562 MW, which proved to be the more cost-effective than wind turbines and battery storage. The results of the scenarios, the graphs and the sensitivity analysis show that the model is effectively able to optimize the infrastructural composition and operation to minimize the cost in all cases, giving managerial insights into the decisions that need to be made in all steps of a fleet electrification process.

Adapting the size of upending cradles according to the ever-increasing dimensions of offshore wind turbine monopiles is costly and requires structural modifications to the associated Heavy Lift Vessels (HLVs). This study therefore investigates the potential of the Monopile Upending Smart Tool (MUST), which is a platform suspended in the HLV crane, on which a winch is installed. Two grommets of constant length connect the platform with two trunnions attached to the monopile, and the winch cable suspends the bottom of this structure. Unwinding the winch cable allows for in-crane upending of the monopile. This way, the dependency on the size of the available cradle is circumvented. The focus is laid on determining the workability of the application of the MUST in the crane of the Seaway Strashnov and identifying limitations in its design. Moreover, the potential of systems that increase the workability or reduce the limitations is investigated.

The installation of monopiles using the MUST comprises three phases: the barge mooring / lift-off, upending / slewing and lowering / driving phase. Based on the results from a qualitative critical event analysis, the lift-off phase is expected to be limiting. Hence, a hydrodynamic model is developed to quantitatively analyse this phase. Experimental simulations, which are performed in parallel with the model development, result in the preliminary conclusions that multiple pendulum effects influence the results to a limited extent, while viscous roll damping and hydrodynamic interaction effects can be strong determinants of the resulting responses.

The relative z-motion between the lifted monopile and the barge and the barge roll response are identified as governing parameters. To reduce the first limiting factor, a system that allows for instantaneously increasing the vertical clearance between the monopile and the barge is proposed. The effectiveness of this system is tested for two barge loadcases. For the first case, the average workability increase for the optimal heading at a typical location is calculated as 8.3%. For the second, the increase is marginal, as the barge responses are more limiting. Furthermore, is it found that a Passive Motion Compensator (PMC) can reduce the probability of the introduction of snap loads in the winch cable, and therefore allows for system optimisations. A PMC with 10% of critical damping can reduce the required winch capacity with a factor of 2.3 w.r.t. the uncompensated case.

It is recommended to perform follow-up studies into the system performance during upending / slewing and lowering / driving. Also, it is advised to evaluate the effect of a larger barge and a PMC on the workability. To balance the associated investments and workability increases, the logistical models developed in a parallel study can be used. Finally, for iterative calculations, it was found to be beneficial to make an estimate based on a fast simplified model and to subsequently feed the results back into a more detailed, but slower model.

This thesis focuses on the transition from multichannel to omnichannel retailing. To provide insight into this, the current challenges and related indicators are identified by means of a multiple case study. In addition, a theoretical framework for the omnichannel retailing concept is designed. On the one hand, this will help to increase the understanding of omnichannel retailing and, on the other hand, it will provide insight into where retailers currently find themselves in this transition and what challenges this involves.

At the UN conference of 2015, the promotion of inland waterway transport (IWT) was named as a Sustainable Development Goal by the United Nations. While IWT has been identified to make goods transport more CO2- efficient, the long-term viability of the Dutch IWT sector is at risk.

Currently, Dutch IWT businesses benefit from increased demand for transport capacity during climate change induced periods of low river depth by being able to charge higher prices to shippers, thereby increasing short term profits. This thesis research project concludes that this behaviour is unsustainable due to the disregard for providing price competitive and reliable services to shippers, which will ultimately damage the reputation of the Dutch IWT sector. This can lead to shippers choosing other modes of transport, which will damage the long-term viability of IWT demand.

A lack of evident optimal climate adaptation measures that would better guarantee the long-term viability of an IWT business under any climate scenario is one of the reasons why IWT businesses have thus far been hesitant towards implementing climate adaptation measures. This thesis research project studies the potential of using a robust decision analysis in supporting IWT businesses’ decision-making on climate adaptation measures that could safeguard the long- term viability of the Dutch IWT sector. It conducts a robust decision analysis and then evaluates its potential using feedback from stakeholders of the Dutch IWT sector.

This thesis research project present the results from the robust decision analysis to IWT stakeholders to evaluate how these could impact their decision-making. Stakeholders noted that they believe that the produced influence diagram could be used as a standard communication object to produce a better consensus of how measures influence the long-term viability of IWT demand. Furthermore, stakeholders expressed that the robust decision analysis provided them a better understanding of which measures were able to better guarantee the long-term viability of IWT demand. Results from evaluation interviews with stakeholders therefore provide grounds to believe that robust decision analyses have potential to support IWT businesses’ decision- making on climate adaptation measures that could safeguard the long-term viability of the Dutch IWT sector.

To better govern inventory control of spare parts in tandem with scheduling of maintenance operations in a railway setting, a Railway Spare Inventory & Maintenance Scheduling (R-SIMS) model is developed. To suit the railway industry setting the model includes an inventory control strategy which envokes continuous monitoring and a reorder level as well as an order up-to level. Moreover a condition based maintenance (CBM) strategy is used with periodical inspections. These strategies are combined in a simulation model which assumes stochastic step-wise deterioration of parts as well as stochastic lifetime lengths to predict the expected cost per part per period. The three maintenance scheduling and spare inventory decisions to be minimised in terms of their resulting costs are 1) when to replace parts based on their condition, 2) when to buy new spare parts and 3) how many spare parts to procure at each order. These decisions are represented by values of the three decision variables: the CBM threshold L_p, the reorder level s and the order up-to level S. The minimisation of these decision variables is performed through surrogate modelling, a branch of machine learning optimisation techniques which deals with complex black-box functions. It does so by running experiments and estimating a surrogate function which in turn is optimised mathematically. Multiple surrogate modelling methods are compared in experiments to test their performance, speed and stability. These experiments showed that the Tree-structured Parzen Estimator algorithm as used in the HyperOpt Python library was one of the best performing methods (only rivaled by the MVRSM algorithm), moreover it was shown to be the fastest as well as the most stable of the tested algorithms for this particular problem application. This research contributes to the existing theory by creating a modelling framework for the joint optimisation of spare inventory and maintenance scheduling decisions which is specifically tailored to the railway context and includes possibilities for minimal maintenance. In practice this model can be used by maintenance providers to increase the financial success of their maintenance operations and by infrastructure managers to increase insight into their maintenance providers' operations.

The growth in the e-commerce platforms and online shopping has been increasing exponentially in the last decade. Businesses and logistics companies are finding new ways to ensure fast, sustainable, and safe deliveries to customers through existing means. However, to meet the ever increasing demand of deliveries, innovative shipping or delivery alternatives have been on the rise across the world. Crowd-Shipping is one such concept which aims at taking advantage of regular travellers with unused space and additional time who can pick up packages, in order to deliver packages to customers who lie along or near the same route for a small compensation. Since the Netherlands has witnesses massive e-commerce growth and demand for efficient and fast deliveries, this study aimed at how Crowd-Shipping can potentially be implemented in the Netherlands through considering a set of drivers, barriers and a business model innovation perspective. The study first investigates the existing research on the concept, focusing on the drivers, barriers and business model aspects. In order to explore these findings and potentially more or findings, we conducted the methodology which consisted of interviews and surveys. Post the interviews and surveys, a thorough analysis of the findings was conducted through content analysis, descriptive statistics and correlations. The results from the research indicate the importance of the findings from the literature with respect to existing drivers, barriers and business model perspectives while also providing insight into more drivers, barriers and business model perspectives that need to be considered for Crowd-Shipping deployment. These results are discussed in detail providing in-depth insight on the Crowd-Shipping aspects mentioned. We conclude the research by suggesting how Crowd-Shipping can be implemented in the Netherlands considering these drivers, barriers and business model aspects, following which, further research recommendations are provided.

As the complexity of global supply chains increases, so does the turbulence and disruption they are suffering from. The medical equipment after-sales service supply chain is closely related to the healthcare industry. Therefore, the ability to provide high levels of customer satisfaction with after-sales services affects not only the performance of the medical equipment companies but also the lives and health of patients. This motivated us to study supply chain resilience in order to help managers in the medical equipment industry improve the resilience of after-sales service supply chains. Through literature research, we found that there is no research specifically on the resilience of the after-sales service supply chain of medical equipment. To fill this gap, we formulated the main research question for this thesis as: “How to assess the resilience of the after-sales service supply chain in the medical equipment industry?”. To answer this research question, we design a supply chain resilience framework by using a mixed-method approach to help managers assess the resilience of medical equipment after-sales service supply chains. And we opted for a mixed-method approach in two phases: (1) Framework development: We identified and synthesize the elements of existing supply chain resilience frameworks found through literature research into a single resilience framework applicable to the after-sales services supply chain for medical equipment. This framework identifies the enablers that need to be maximized and the vulnerabilities that need to be minimized to enhance supply chain resilience and operationalizes these elements as observable indicators. (2) Framework validation: Considering the strong growth of the medical equipment market in China, and the Chinese government ambition to provide safe, effective, convenient, and affordable healthcare services to both rural and urban residents by 2020, we have validated the proposed framework by interviewing professionals working in medical equipment companies located in China. We used questionnaires and semi-structured interviews to determine how participants perceived the importance of the identified elements and indicators. We expect that the resilience framework will help managers to better deal with turbulence and disruptions. The resulting framework identifies 11 enablers and 5 vulnerabilities, operationalized by 43 indicators. As the proposed supply chain resilience framework has not been tested empirically by applying it within a medical equipment company, a first recommendation is to perform such tests. By analysing and summarizing the results of the actual application, the framework can be improved further. Moreover, the expert validation was limited due to research time constraints. The reasons why participants considered some enablers and vulnerabilities to be unimportant could be investigated further, and the indicators can still be operationalized further. Finally, the relative importance of enablers and vulnerabilities could be investigated by using a multi-criteria decision-making method, so as to help managers select only the more important elements to improve the resilience of their supply chain.

Digital transformation in procurement is important for Purchasing and Supply Management (PSM) organisations to develop global organisational competitiveness. Generally, procurement performance can be determined and improved through the use of a maturity model. Existing models do not cover the latest (e-)procurement processes (E-Sourcing, Procure-to-Pay, and Supplier Relationship Management) resulting from digitalisation. Therefore, an extension to existing maturity models was required to assess company performance. A literature study was conducted to describe and explain meaningful concepts and several maturity models were selected to review and compare the frameworks most suitable for an extension. Experiences of a major PSM organisation called the Corporate Group strengthened the research study by determining key topics and industry best practices, providing a foundation for the extension. A company analysis resulted in an understanding of (digital) procurement and the selection of Schiele (2007) due to its comprehensiveness. Semi-structured interviews were conducted with procurement experts to review Schiele's model and develop an extension. The extended model contains an additional spend management domain and a new dimension covering e-procurement. Multiple purchasing functions and stage descriptions were developed, whereby the model consists of 56 original and 22 new assessment questions. The new dimension includes Spend & Data Management, Contract Management, Market Intelligence, E-Sourcing, Transactional Procurement, and Supplier Relationship Management. Entity A is part of The Corporate Group and provided the ideal opportunity to test the extended model through a multiple-case study. Maturity assessments were conducted of several operating companies (OpCos) to determine maturity levels and whether the extended model actually measured purchasing maturity. The extended model was able to quickly provide a performance overview and guide the OpCos towards improvement. Self-assessments as an alternative for third-party audits were provided, including a digitalised approach to process data easily. However, comparing results among OpCos outside of their sub-unit delivered an unexpected outcome. It was questionable whether the model measured purchasing maturity or rather the perception of it. Although the results were unexpected, the extension appeared to be more accurate. This was most likely due to the elaborate stage descriptions, enabling assessors to identify stage levels more easily. This research study provided a foundation for assessing e-procurement using an extended maturity model but limited itself to the Corporate Group. Thereby, it confirmed the criticism regarding the four stages being too rigid. Potential future research is recommended to improve both the extended model and the assessment approach. First, it must be shown to what extent e-procurement is covered in the new dimension and whether the extended model can be sufficiently generalised. Interviews should be conducted with procurement experts from different companies or industries to validate the extension through statistical analysis. Secondly, the assessment approach could be improved by including a control person and more experienced people, ensuring critical thinking and more realistic maturity levels. Self-assessments are not necessarily less reliable compared to external audits, but they rather need support to guide the process through a standard protocol. The subsequent step should be to formalise a proper action plan to initiate improvement.

Climate change is triggering among others a larger demand for offshore wind energy. This leads to new developments of which larger next-generation Wind Turbine Generators is the most relevant. These next-generation WTGs create problems for the carrying capacity of current-day installation jack-up vessels that work according to the conventional installation method (shuttling). These installation vessels can carry less or even nil of these WTGs per trip compared to the current-day WTGs. Fewer turbines per trip would allow the larger current-day installation vessels to maintain their work. However, they have more sailing time since more trips are required. This could also be more inefficient since the Offshore Wind Farms are moving further offshore. The other option within the conventional method is to build larger installation vessels that would carry more WTGs per trip.

Another installation method in the literature called feedering is a potential substitute for the conventional method. Very limited research has been done for feedering as well the practical implementation whereas the conventional method has extensive research and is mostly used in practice. The models in the literature compared two different feeder methods, called, the base port feeder and feeder-ship method, to the conventional method. The models are generic and lack different strategies to find the best feeder solution. The feeder-ship method has the most potential to solve the aforementioned problems and is therefore further investigated to find the best installation strategy, being either the conventional or feeder method.

First of all, the feeder-ship method is evaluated based on practical knowledge and adapted so a base port is used to temporarily store all components that come from the production port. The feeder sails back and forth between the base port and the installation site to supply the installation vessel with WTG components. The installation vessel will stay at the installation site to be as efficient as possible (the least amount of sailing time). This research only looks at the feeder and installation side and leaves the port elements out of the problem. Feeder strategies (within this method) differ in the number of feeder vessels/types and transfer options using either barges or Platform Support Vessels and being indirect (transfer components onto the installation vessel) or direct (install components from the feeder). The installation vessel for feedering is also looked into as being either a current-day or a special feeder purpose installation vessel. Different carrying capacities of the installation vessels are used to create different strategies for the conventional method.

A stochastic Discrete Event Simulation model is created and used in this research to evaluate the strategies. The output of the DES simulation is the project duration per sailing distance and strategy. The costs for this duration is calculated in a costs model from the perspective of the contractor as well as the developer. Besides duration and costs (based on the European market), the strategies are also evaluated on emissions (fuel consumption) since this is an increasingly important element in the industry. A sensitivity analysis has been performed to get a better understanding of which critical parameters the feeder strategies are most sensitive to. The analysis is also used to find the best next-generation WTG installation strategy in Europe which is the main focus of this thesis.

In this thesis, the optimization of inventory management within RTI pooler networks is considered. The inventory management by RTI poolers consists of the network configurations on which the network relies, as well as the relocation schedule of RTI poolers that determines the functionality of the system.