This research lays forward a framework where supplier segmentation, supplier collaboration models, and supplier development strategies are integrated, specifically for remanufacturing. As remanufacturing is gaining popularity this pioneering research may serve as a first step towards more research for companies that are willing to drive remanufacturing across the whole supply chain. This research compares two proven supplier segmentation methods and links it with supplier new collaboration and existing supplier development strategies. As a result of this study, an integrated framework is proposed. For future research, the framework can be applied to other cases or the framework could be extended.

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.

Increased competitiveness with other transport systems and declining operation margins have motivated freight forwarders in the air cargo transport industry to look into horizontal collaboration. This thesis focuses on developing a fully integrated five phase auction based coopetition model, a form of horizontal collaboration where competition is preserved. A combinatorial auction is used to exchange transportation requests without having to reveal critical company information. Freight forwarders submit requests into an auction pool, where they are grouped into attractive bundles by a central planner and offered for auction. The request selection and bundling procedures, developed in this thesis, are based on the time windows of the request deliveries. A freight forwarder’s bid on each bundle is equal to the marginal profit of that bundle, which is obtained by solving two NP-hard routing problems with a simulated annealing and large neighbourhood search metaheuristic. A unique aspect of the auction, is that the dock capacity of the ground handlers is taken into account, which helps to alleviate truck congestion at the ground handlers. The potential of the auction based coopetition model is shown for an air cargo supply chain scenario. There is a clear increase in profitability for the collaborating freight forwarders, because the auction model decreases the transportation costs for the entire coalition. This cost reduction is achieved by an increase in transport efficiency, while the collaboration disadvantages as seen in literature are limited.

The Internet-of-Things has grown much in popularity over the past years, leading to the gathering of large amounts of pervasive and detailed data. This same trend is seen in the agriculture industry, where a lot of data can be collected on the cultivation methods. The agriculture industry is considered to be a strategically interesting industry for the Internet-of-Things by KPN, the company that commissioned this research. Despite the rapid data collection, businesses rarely exploit the full potential value of their IoT data. One of the methods of value creation with IoT data is to share the data with other parties. Data platform ecosystems make the sharing of data possible, but require the participation from all sides of the platform, especially the data providers, to be successful. Platform sustainability is an important research topic within Information Systems research. However, it remains unsure how the participation of data providers can be ensured. Furthermore, Information Systems researchers have often stressed data governance to have an important role in the success or effectiveness of data platforms. This research aimed to explore how important ecosystem data governance is relative to other relevant factors for the participation willingness of IoT data providers. This knowledge can consequently be used to develop data platforms which IoT data providers are more prone to participate in. Due to the limited time to complete this research, it was decided to focus on the Dutch horticulture sub-sector within agriculture. This sub-sector is considered to be the most advanced Dutch agricultural sub-sector in terms of digitalisation and Internet-of-Things adoption. Relevant factors to data platform participation were identified by means of a literature review. The Best-Worst Method was used in a survey amongst 30 Dutch horticulturists to determine the relative importance of each of the relevant factors. Additionally, six face-to-face semi-structured interviews were conducted to identify concerns related to the relevant factors. The survey results show a low spread of the factors in terms of weight, indicating that Dutch horticulturists do not base their participation decision on just a few decisive factors. Ecosystem data governance is considered around half as important as the most important factor, the benefits of participation, and around three times as important as the least important factor, the external pressure. Although the benefits, human readiness and technological readiness are weighted higher, KPN is recommended to focus on the factors that can be directly influenced by them to direct development time and resources more efficiently. It is therefore recommended to focus on developing a data platform with a high level of security and a low level of complexity. Furthermore, the ecosystem data governance should be another focal factor as appropriate ecosystem data governance can likely eliminate concerns related to several other factors, such as the benefits of participation, safety of data, and the trust in and readiness of other participants. The concerns regarding the misuse of data, unfair distribution of generated value, and the loss of ownership and control over own data, can all be addressed in the ecosystem data governance.

A distribution network design is of importance to systematically organize the flow of products from supply points to demand points. A distribution network is not only crucial before sales but also after sales because regardless of the initial quality of product, malfunctions occur. These malfunctions need to be repaired by replacing defective parts, which are delivered through after sales distribution network and all activities, carried out from the report of the malfunction until the product is up and running, are called after sales services. The replacement parts are called service parts or spare parts and this thesis project focuses on the distribution network design for delivery of these items. Customer surveys point out that high quality after sales services has become a criterion for selecting supplier companies. A shorter response time to failures and availability of service parts in the storage are given importance. Because after sales services became a field that companies can differentiate themselves from the competitors, practitioners have an increasing interest on establishing the optimal distribution network design to meet customer expectations while being cost-competitive. The researchers have addressed service parts distribution with a strong focus on inventory management. However, distribution network design involves more decisions such as number of facilities, facility locations, allocation of customer demand to these facilities, and storage capacities. In addition, the managerial aspects and strategies for service parts logistics in business case studies are derived from electronic, automotive and aviation industries. Considering these, there is a knowledge gap about distribution network design for service parts in healthcare industry. This thesis project aims at filling this gap by introducing a general mathematical model for distribution network optimization based on an empirical study, conducted in General Electric Healthcare service parts delivery network.

With the rising global pollution and rising concern over sustainable operations, manufacturing companies are under tremendous pressure from its stakeholders to adopt Sustainable Supply Chain Management (SSCM). However, companies in addressing SSCM, largely focus on the economic aspects neglecting the other two crucial pillars of sustainability. To tackle this issue and further promote the TBL approach in SCM, this study empirically analyzes the factors influencing the successful implementation of environmental and social sustainability practices in manufacturing SCM. This study takes into account 8 different sustainability practices corresponding to environmental and social pillars and set of 10 contextual factors that are suggested to influence the successful implementation of sustainability practices in the existing literature. The data collected from 112 product manufacturing companies and logistic regression analysis reveal that 9 out of 10 factors significantly influence the implementation of at least one of the sustainability practices. Sustainability Policies and Objectives (SPO) being the major contributor shows significant influence towards 4 of the practices and relatively low significant influence on 3 other practices. However, Downstream Supply Chain Factor (DSCF) do not significantly influence the implementation of any of the practices. Based on data analysis results, a detailed discussion is conducted and answer to the main research question is provided. Next, the limitations of the research study, recommendations for future studies are provided. Finally, a personal reflection and managerial implications are provided.

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.

The increasing awareness towards environmental protection demands industries to enact viable solutions in their operations, one such example is the introduction of the concept of “Green Supply chain management” in supply chain operations. The supply chain process operates as a link connecting firms and industries to deliver a product or service to the end customer. The procurement activity in the supply chain process plays a vital role in providing the materials for production and consequently to business sales of the firm. Over the years, the technological development and integration of information technology in procurement process have transformed manual information sharing to a more automatized system of Enterprise Resource Systems (ERP) in the business to the business operational platform. The growing importance of green practices in manufacturing firms and the research gap reviewed in the literature addressing the relation between ERP systems on green supply chain motivates to carry out this research. In this report, I attempt to answer the research question formulated addressing the relation between ERP and Green supply chain operational performance through a Case study. The research is carried out structurally adhering to the research framework developed in the initial stages of background study. I follow the case study methodology to collect the relevant data to reflect on the conceptual model developed through literature review and to answer the research question. Finally, I conclude the research by providing recommendations based on the analysis and reflect on the limitations and future research prospects.

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 the contemporary global environment, supply chains are increasingly vulnerable to disruptions, with environmental and supplier disturbances posing frequent challenges. This research aimed to understand the influence of a systematic supplier selection approach, combined with an effective risk mitigation strategy, on supply chain performance amidst supply-side disruption risks. We identified a significant gap in current supply chain management: the lack of a structured supplier selection methodology, which can lead to inefficiencies and performance declines. To address this, our study employed the best worst method (BWM) for systematic supplier assessment and ranking. Simultaneously, a discrete-event simulation model on the Simio platform was utilized to emulate supply chain dynamics, factoring in various suppliers and potential disruptions. Our findings, contextualized within the polymer industry, highlighted Material Quality, Supply Reliability, Price, and Lead Time as the most critical criteria for supplier selection. The BWM rankings correlated strongly with actual supply chain outcomes, emphasizing its effectiveness. In terms of risk mitigation, flexibility-oriented sourcing strategies were superior to redundancy-oriented ones, demonstrating better management of supply-side disruptions and reduced safety stock levels. These results have both societal and scientific implications. Societally, a methodical supplier selection process ensures resilient supply chains, essential for sectors like healthcare and food, and promotes global collaboration and innovation through diversified supplier sourcing. Scientifically, our research validates the BWM's utility for supplier selection, challenging conventional beliefs linking higher costs to superior risk mitigation. A key insight was the growing importance of flexibility in modern supply chain risk management. For the polymer sector, we recommend a BWM-based structured supplier selection process. By partnering with top-ranked suppliers and diversifying geographically, businesses can reduce safety stock levels. Our simulation model provides a practical tool for decision-makers, facilitating scenario testing to identify optimal strategies. However, our study's limitations must be acknowledged. Tailored primarily for the polymer industry, the specific assumptions underpinning our simulation may not be universally relevant. Thus, while our insights are valuable, their applicability might be limited by data constraints and the polymer sector's distinct attributes. In conclusion, a methodical supplier selection, paired with a flexibility-oriented sourcing approach, optimizes supply chain performance in the face of supply-side disruptions. Enhancing these elements can guide businesses in developing agile supply chains, ensuring cost-effectiveness and improved performance.

When competing standards are introduced into the market, the firms that introduce the standards often put considerable effort into becoming dominant. Such a face-off is called a standards battle. This level of competition can slow market adoption and increases costs for all those involved. It is therefore important to better understand standards battles and analyze possibilities to better approach them in the future. Scholars have worked to create frameworks of factors for dominance and some have even combined these with a view of the dominance process to reach a progress-based overview of battles in general. Such an overview can help standard supporters, those firms that introduce and promote a standard, to identify and leverage factors in their battles at the correct time. This research is a continuation of this approach, working towards a general template for future battles and attempting to validate previous results. A literature review was conducted to select a framework of factors for dominance, to find a selection of phases to divide the progression of a standards battle, and to review previous research’s statements regarding the importance of factors during specific phases. The framework constructed by v.d. Kaa (Van de Kaa et al., 2011) was selected as the framework of factors and the division of phases as described by Suarez (Suarez, 2004) was chosen. An overview of the existing literature on the combination of both factors and phases was then constructed. This provided a reference against which the results of this research were later compared. A selection of factors was then made for each phase using previous literature and an expert interview. Ten experts from the consumer electronics, information technology and telecommunications industries were selected using convenience sampling. The experts were asked to weigh the selected factors against each other in each phase using the Best-Worst Method. This is a Multi Criteria Decision Making method that provides a set of weights from two different comparisons made for each phase. From the responses, the weights of the separate factors were calculated. From this calculation a consistency indicator was also derived. All results met the required consistency. The sets of weights were combined to reach average weights for each phase. These results were analyzed and interpreted to provide further understanding. The highest rated factors are: technological superiority for the first and second phase, timing of entry for the third phase, complementary goods for the fourth phase and installed base for the fifth phase. A comparison with existing literature was performed. This showed an indication for dynamics observed by den Uijl (Den Uijl, 2015) and a general match with statements made by Suarez (Suarez, 2004). The novel approach of this research to consider factors for dominance in combination with the phases of a battle using expert interviews to reach a view on battles in general has not been used before. It therefore also has interesting implications. The results of this research provide a partial validation of claims from other scholars regarding the importance of factors for dominance during phases of a standards battle. They also provide additional information on the progression of the contribution of factors and are the first step towards a progress-based template for battles in general. It was shown that there are similarities and differences between different industries in which standards battles take place. The findings of this thesis can be used by industry actors to better adjust their standard and standard supporter characteristics to what is required at each stage of a battle. It will also help them identify factors that competition may be lacking, opening up new possibilities for targeted competition. Future research is this field is required. A fully quantitative approach using a complete set of factors can give a more definitive answer to the posed research questions. This research provides the starting point towards a cross-industry applicable selection of highly contributive and lowly contributive factors depending on the stage of the technology. More research could be done on the differences and similarities between industries using a historical approach.

One of the ways that Transmission System Operators (TSOs) can become more sustainable is by integrating sustainable goals in their projects using the associated procurement and tender processes. However, there are several limitations related to this integration. This research aims to identify these challenges by looking at the Dutch TSO, TenneT and its specific context. Furthermore, the research aims to provide a decision-support framework through which these limitations can be countered and the integration of sustainable goals in projects can be achieved. First, a literature study was conducted to define sustainability and the concepts associated with it. To properly understand the context of TenneT and identify the limitations associated with sustainability, company professionals were interviewed. This pointed to the need for prioritisation and gradual integration of sustainability measures. A desktop study was also conducted to identify the company’s sustainable goals, their associated measures, and their real-life applications. A decision-support framework for integrating sustainable goals in projects, based on Multi-Criteria Decision-Analysis (MCDA) was proposed. Using the Best-Worst Method (BWM), as the selected MCDA method, developed by Rezaei (2015), a sustainability workshop was organised where decision-makers from TenneT were asked to select relevant sustainability goals for TenneT, and the ones selected by three or more decision-makers were then used for performing the BWM. To avoid focusing on already well-performing sustainability goals, the performance of their associated measures was studied, using a Maturity Model based on the work of Silvius and Schipper (2015). Finally, an Importance-Performance Analysis (Martilla and James 1977) was performed, to assess future actions for each sustainable goal. The BWM showed that the Planet aspect was selected as the most important one for stimulating sustainability in projects. Additionally, Reducing Emissions was selected as the most important sub-aspect while in the People aspect, Health and Safety ranked first. The Maturity Model showed that the least integrated goals in projects are Human Rights, Labour Conditions and Decent Work, Energy Consumption, Materials and Natural Resources and Circularity and Waste. The BWM and Maturity Model also produced interesting results regarding the awareness of decision-makers and how they perceive sustainable goals and the performance of their associated measures in projects. Based on the Importance-Performance analysis, the research suggests integrating the sustainable goal of Circularity and Waste in the company’s following projects. This can be achieved by using existing sustainable measures, such as the Raw Material Passport (RMP), in the tender process. Using measures such as the RMP in the pre-qualification phases or selection phase, as entry requirements with specific targets to be met, or as an award criterion, aiming to create added value for the project, can stimulate the contractors and suppliers to act more sustainably. This will in turn increase TenneT’s sustainable performance and will help the company meet its own sustainable targets.

This thesis proposes a truck arrival shift (TAS) policy to control truck arrivals at seaport terminals. The aim is to reduce congestion at terminal gates which is caused by a lack of port-hinterland alignment. We proposed, developed, and applied a modeling framework to assesses the impact of the TAS policy for the use case of the Port of Rotterdam. This policy is designed for the implementation of a Time Slot Management System (TSMS) and takes the behavioural aspect of Truck Operating Companies (TOC) into account. The time of day preferences of TOC for container pick-ups are inferred from the exchange of information between port and hinterland stakeholders using discrete choice modelling (DCM). These preferences are used to shift truck arrivals and consequently reduce the high waiting time of trucks at terminals gates. To evaluate the effectiveness of the designed TAS policy, we developed a simulation platform that resembles terminal operations using discrete-event simulation (DES). For the allocation of trucks to a certain time period, a choice-based heuristic is designed to approximate the optimum configuration of the TAS policy. The optimum TAS policy design shows that significant gain can be obtained at a low shift rate. Moreover, a measurable amount of waiting time gain can be achieved by the application of the designed TAS policy.

To decrease Europe’s harmful emissions, the European Union aims to substantially increase its offshore wind energy capacity. To further develop offshore wind energy, investment in ever-larger construction vessels is necessary. Designing these vessels is difficult however, as this market is characterised by a large but seemingly unpredictable growth of market demand, turbine size and distance from shore. Currently no way of dealing with such market uncertainty within the ship design process was found to exist. This research aims to develop a method that is able to deal with market uncertainty in early ship design by increasing knowledge when design freedom is still high. The method uses uncertainty modelling prior to the requirement definition stage by performing global market research, and during the concept design stage by iteratively co-evolving the vessel design and business case in parallel. The method consists of three parts; simulating an expected market from data, modelling multiple vessel designs, and an uncertainty model that evaluates the performance of the vessels in the market. The case study into offshore wind foundation installation vessels showed that the method can provide valuable insight in the effect of ship design parameters like main dimensions, crane size and ship speed on the performance in an uncertain market. These results were used to create an initial design that is expected to perform well in the uncertain market. The developed method thus provides a way to deal with market uncertainty in the early ship design process.

Offshore wind plays a major role in the transition of conventional energy towards sustainable energy sources. To keep up with the increasing installation demand in this sector new offshore wind installation vessels are needed. There is a need for more certainty and predictability regarding the requirements of the future offshore wind installation vessels. To translate the market developments towards input variables for future vessel concept designs, the methods ’needs analysis’ and ’concept exploration’ from the systems engineering framework are applied. Epoch-era analysis is selected as scenario modelling method to capture the uncertain and the fast changing market by generating various future possibilities each posing different vessel requirements. A parametric model is created to determine the performance of a set of vessels defined by their length, beam, depth, crane capacity, speed, and transport strategy. The case study shows that the application of Epoch-era analysis and parametric modelling is capable of generating insights in important aspects for designing future offshore wind installation vessels. The strength of this method is that it has the flexibility to select different key performance indicators but also provides the opportunity to incorporate the importance of short term against long term goals. It can therefore be tailor-made to a stakeholders strategy. Applying their wishes while analysing many different options results in robust input variables for the concept vessel design.

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.

Ports are the most important nodes in the supply chain of cargo and improving their sustainability will positively affect the sector as a whole. This improvement can be achieved by incorporating stakeholders in the process of port development. Social, environmental and economic development achieved together are defined as sustainable development. In the prospect of sustainable port development, Ethiopia is an interesting country to study because of its rapid and relatively stable economic growth since 2005 and its low logistics performance. This study is built around a dry port expansion project in Ethiopia, for which a 150 million USD loan from the World Bank recently became available. Modjo Dry Port (MDP) is located close to the capital of Ethiopia and its largest production and consumption areas. Before acting directly, the sustainability of the alternatives according to different stakeholders, should be considered. Incorporating sustainable development in the project in general is a significant challenge. This leads to the formulation of a research question. How to evaluate strategic alternatives for sustainable expansion of Modjo Dry Port? This study describes a method on how to develop a number of distinct alternatives, and proposes a framework for the evaluation of sustainable dry port expansion. Such an evaluation tool for the dry port site specifically, does not yet exist. The framework is tested for MDP in Ethiopia. For the development of the alternatives of MDP, two overarching themes at the dry port were identified: operations are inefficient with dwell time of 50 to 60 days on average, and no diversification of cargo. Based on these themes three alternatives for MDP are defined. For the sustainable evaluation of Modjo Dry Port the Multi-Criteria-Multi-Actor analysis (MAMCA) is used because it explicitly incorporates stakeholder incentives in a more traditional multi-decision criteria analysis (MCDA). The MAMCA consists of seven steps. Step 1 and 2: Four stakeholder groups for MDP are defined: internal, community, public policy makers and private companies. For the 3rd and 4th step, a framework for evaluation is constructed, based on literature and stakeholders’ input. The criteria are categorised based on the three pillars of sustainability: social, environmental and economic development. In step 5 the weights for the criteria of the evaluation framework are determined by stakeholders. In the last steps of the MAMCA the proposed alternatives were scored against the current layout of MDP for all criteria in the evaluation framework. The final output is a multi-actor view on scoring the alternatives. Dry ports closer to Addis Ababa are a suitable alternative for MDP. Stakeholder participation is an important part of the study, however, it proved difficult to integrate a sufficient number of stakeholder responses in the analysis. For MDP specifically, stakeholder groups showed similar interest, and the preference for different alternatives is equal amongst the groups. Analysis shows that the alternatives improving operation efficiency score markedly higher on sustainability.

Recently, pressure on port authorities to improve port efficiency is increasing due to port competitiveness. Multiple activities within a port influence the efficiency of a port. In this research, the processes of the 'nautical chain' are considered. The nautical chain consists of piloting by a pilot, positioning by tugboats and (un)mooring by boatmen. The provided services are dependent on each other, which makes information sharing between the actors of the nautical chain essential. Enhancing information sharing in the nautical chain could provide opportunities for efficiency improvements. However, current literature does not provide any details on information sharing in the nautical chain. Consequently, it is unknown what parts of the information sharing might be crucial to focus on for improving its efficiency. This research aims to fill this gap, by researching the information that is shared in the nautical chain of the Port of Rotterdam in the delays that frequently occur through expert interviews and observations. The information that is shared in the frequent delay situations is considered critical for efficiency improvements, because the shared information contributes to decisions that reduce the cascade effect of a delay trigger. Following from the identified information sharing in the frequent delays, the areas of critical information sharing are distinguished.

Logistics plays an import role in e-commerce and so in the online grocery market. This research analysed different transport packaging solutions for the home delivery of dry groceries. Insights into the effects of several transport packaging have been gained. A case study has been applied to PostNL, to find the best alternative for the delivery of dry groceries in their supply chain. Sustainability plays an important role in this research. The Triple Bottom Line of social, economic and environmental sustainability are the fundamentals for the criteria on which the alternatives have been evaluated. Also, constraints of the systems in which the transport packaging must function in have been established. The criteria are important aspects like environmental impact, costs, food safety, ergonomics and logistics performance. Weights have been identified to show the relative importance of the criteria. The identification of the importance of the weights has been done by conducting a questionnaire to actors in the food delivery supply chain of PostNL. The method which has been used for the determination of the weights is called the Best-Worst Method (BWM). The alternatives have been assessed on the criteria and compared to each other. This has been done conducting a Multi-Criteria Analysis (MCA). The scoring of the alternatives on the criteria has been done using interviews, questionnaires, calculations models and experiments. One of the calculations models is a Life Cycle Assessment (LCA) in which the environmental impact of the alternatives has been determined. A useful methodology, combining MCA, LCA and BWM, has been developed for the assessment of sustainable transport packaging solutions.

The online grocery retail industry is rapidly growing and has to improve order picking activities which is one of the most costly and labor-intensive activities of their supply chain. Gamification has been promised to increase the motivation and productivity of order pickers, but empirical findings in real world work environments are still missing. In this case study, a gamified design was tested during an intervention with professional order pickers. The design contained the following game elements: points, badges, leaderboards, performance graphs and avatars. The results show that the motivation of the order pickers are positively influenced by the intervention and that this led to a higher productivity. Besides, it was found that different game elements were differently appreciated depending on the level of experience of the order picker.