Global supply chains currently are inefficient and unsustainable, due to their overlap and lack of interconnection. The Physical Internet (PI) proposes a paradigm shift in the way we move, store, supply, realize and use goods. The goal of the PI is to interconnect global supply chains, amongst others, on a digital level. For this, information systems are needed. Seaports, being drivers of global supply chains, therefore also need information systems on an integral level. In certain ports, Port Community Systems (PCS) serve as port’s information systems. They facilitate information exchange between stakeholders to better connect port processes. This research explores the potential role of PCS in PI ports. It does so by performing a Design Science Research (DSR). The artefact that is designed, is a conceptual information system that addresses key (PI) port functions. A case study analysis at Portbase, the Dutch PCS, has revealed what information is exchanged between which stakeholders. PI literature provides grip for PI information system requirements. The integration of the PCS analysis and the PI requirements has led to a design of an information system that shows the potential of a PCS in a PI port. The design shows that, according to the current offer of PCS services, PCS’ potential role focuses mainly on compliance related processes in PI ports. It also shows that the offer of logistics related services that are needed in PI ports, is limited. It is therefore recommended that PCS focus on an extension of logistics related services that are needed in PI ports. Future research may address the potential of PCS in a federated network of platforms.

Increasingly specialised logistic services are triggering the disaggregation of supply chain functions and fostering the generation of information silos. This is perceived by European customs as a threat, since it affects the reliability of the import risk assessments and cargo inspections. In parallel, the rise of data sharing platforms based on blockchain technology (BCT) are fostering collaboration and accelerating the verification of trade finance documents in the logistics industry. The cross-organisational trust achieved in these platforms has driven the digitisation the documents from which import declaration data is extracted and shared with European customs. The latter see combining data from multiple platforms an opportunity to automate the cross-validation of declaration data, which is still performed manually to a large extent. This would improve supply chain visibility, turn declarations more agile and risk assessments more effective. However, it remains unclear how to integrate declaration procedures in these data ecosystems. There are two major barriers to overcome. Firstly, the lack of interoperability solutions to make data exchanges with multiple platforms compatible for the aggregation of declaration data. Secondly, the need to adapt available identity management solutions to the distributed architecture of these platforms to promote trust between declarants and their partners. To tackle this, a peer-to-peer data collection architecture is presented as a novel solution to migrate from import declarations based on data duplication towards information sharing based on links to the original and trusted shipping data stored in BCT platforms.

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

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

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

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

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

Consumption of environmentally friendly products has grown more widespread than it was a few years ago. As a result, consumers are becoming more conscious of the environmental effect aspect while making purchases of goods and services. The consequence is that FMCG firms are attempting to develop creative solutions, such as altering the production process, the kind of packaging materials used, modifications to the supply chain, and logistical techniques.
Because of the complex structure of the company and the low-profit margins per product, pricing FMCG goods may be a difficult task to master.

Specifically, the thesis study investigates the sustainable efforts implemented by a particular brand. Through the case study, in-depth information about the brand is collected, including pricing practices and sustainability methods. In addition, the critical ICT tools are identified, and their impact on the product's pricing is analyzed through interviews and desk research.

The research output focuses on leveraging the data and information to maximize the profit margins based on the investment made. Furthermore, based on the ICT architecture observed throughout the study, suggestions are given that will assist organizations in achieving a better return on their investments.

Role of digital infrastructures to improve data exchange on trade lanes becomes more critical as complex border procedures contribute to inefficiency of the international supply chain. However, digital infrastructures innovation in international trade (DTI) has not reached the implementation phase. We are interested to analyse digital trade infrastructures innovation process based on its innovation system. The dynamic of innovation system influences the speed of innovation process. We argue that the blockages and unblocking strategy of DTI innovation process can be clearly identified if the innovation system is examined by looking at two levels of analysis, which are structural, related to changes in system’s structure (e.g., actors, networks, governance) and functional, related to the ability of such system to perform certain functions towards achieving its objectives. To the knowledge of the author, there is no theoretical lens which discusses activities and events happened in DTI innovation system to a detailed breakdown of its structural or functional changes. Mainly the existing studies only focus on using the innovation system analysis as the analytical tool for directing innovation policy and neglect the collective action process that is very relevant with characteristics of DI development. Therefore, the research objective is to create and apply a conceptual framework, to identify the unblocking strategy for digital trade infrastructures innovation process by looking at structural and functional analysis of the innovation system. We develop conceptual framework namely Structural-Functional Analysis Framework, based on the desk research. We evaluate the framework through a longitudinal IT innovation case study on EU funded project. Documents analysis and interviews are employed as data collection methods. From the framework evaluation, this study reports that the combination of analyses concerning structural changes and functional performance of an innovation system is capable to provide richer explanation on issues that limit an innovation system to further develop the DI innovation, a strategy that can be done to mobilise the innovation process, and the DI innovation process itself.

The last decade saw the rise of e-commerce trade and the shift of the manufacturing industry to the emerging economies, China first of all. In this context, the European Customs Authorities experienced an explosion of small parcels coming from e-commerce websites, often from China, and faced difficulties to detect fiscal frauds and security threats using their conventional risk management systems. To address this problem, the European project PROFILE brings together the customs administrations of Netherlands, Belgium, Sweden, Norway, and Estonia, aiming to provide the EU with a shared platform for: (1) accurately assessing customs risks; (2) optimizing operation and logistics by integrating multiple sources of information; (3) developing a shared data platform to share customs risk management (CRM) practices.

As part of this project, the Dutch Customs Administration (DCA) and International Business Machines (IBM) Corporation are collaborating to deploy the cutting-edge technologies of artificial intelligence to automatically cross-check the customs declarations coming from Chinese e- commerce against online information. Through a Design Science approach, I carried out this research for the Delft University of Technology, written in collaboration with IBM Netherlands, aiming to deliver a preparatory study for the developing team before the PROFILE project begins. This includes knowledge brokering between the Dutch Customs Administration and IBM Netherlands so that a more precise problem scope can be defined, and the requirements elicited. In particular, this research focuses on the first part of the project: the development of an adaptive web-crawler for e-commerce, able to compare the declarations documents against online information.

According to the Dutch Customs Administration, the web-crawling system should gather the description of the goods from declarations, search the product on the web, find its price of sale on the e-commerce platforms, compare it with the value declared in the declaration, and return a risk indicator of green/red flag to the targeting officer. The design process of this system follows approaches coming from the systems engineering discipline, starting with the requirement analysis, addressing them with the state-of-the-art big data analytics, and finally deriving the logical components of the system, whose design is presented through a logical architecture.

First, the application domain is investigated. When goods entry the Netherlands need an entry declaration. These goods arrive at the harbor of Rotterdam or airport of Schiphol, where some of these are imported into the country and become import/export, and others stop temporarily as transit waiting to be shipped somewhere else. The Dutch Customs Administration monitors these processes through risk management systems aiming to stop non-compliant goods. This research describes these practices, with a higher focus on the e-commerce risk targeting. About the e- commerce world, a study of the e-commerce processes behind an online purchase is also carried out through a real purchase on Chinese e-commerce. This was used to observe how the Chinese sender described the item, and how the Dutch Customs assessed the risk and decided on the duties to be paid. This led to reflect on the possible frauds scenarios and how to address them. Finally, the Dutch Customs also reported that the products descriptions are often vague and ambiguous, and a more accurate formulation of the problem is described.

Secondly, an in-depth literature on the fields of web-crawling and big data analytics techniques is carried out. The possible technologies that could be useful to address the requirements and the problem formulation are investigated. Starting with an analysis of the existing literature on the field of big data analytics, this research also covers the recent trends of machine learning and artificial intelligence. To avoid reporting a too big literature, the topics reported have been accurately chosen, for instance describing only the techniques for web analytics and text analytics.

This literature on big data analytics is further broken in two sub-topics, one more theoretical, which classifies the types of analytics methods and defines the technology of machine learning and natural language processing, including the last paradigms of deep learning and reinforcement learning, and one more practical, where guidelines for the design, development, and implementation of machine learning techniques are proposed. It is here that a theoretical framework to systematically reflect on the challenges of the field of big data analytics has been identified. This framework is then used to systematically collect the main technological challenges of the use case under analysis and translate them into non-functional requirements.

Finally, the last part of the literature describes what a web-crawler is and what web- crawling/web-craping means. This later extends to the concepts of focused web-crawling and smart, intelligent, adaptive web-crawling, where machine learning techniques are deployed to improve performance. The literature concludes by providing related works of machine learning techniques implemented in smart web-crawling of the e-commerce websites and stating the knowledge gap that needs to be bridged to address the use case under analysis.

After the application domain and the literature review, the knowledge from these previous phases combines in a continuous iterative process according to the design science methodology (Hevner, 2014). Through unstructured interviews with the DCA and IBM experts, the requirements elicitation is carried out. The approach by Armstrong and Sage (2000) deriving from the field of systems engineering is used. The main objective of the system to be developed is broken down into a series of sub-activities that must be carefully structured to formulate the requirements. About the non-functional requirements, instead of reflecting on the different domains – technological, environment, law compliance, etc. – as it is proposed by the same systems engineering approach mentioned earlier, this research uses the framework identified in the literature review about the main challenges of big data project (Sivarajah, 2016).

To derive the components of the architecture from the requirements and customer needs, the methodology proposed by Suh (1998) called Axiomatic Design has been used, mapping the requirements into architectural components in a rigorous manner. In this way, the design domains proposed by this methodology – customer, functional, physical and process domains – are taken as the reference point for the design process: first, the business needs are identified, then these are translated into requirements, which are mapped into design features. The process domain is left out of this research and will be addressed by the IBM development team in Ireland.
The design cycle leads to the design of a web-crawling system represented through a service- oriented architecture (SOA). Its block diagram and black-box description of each application service are provided. Furthermore, the architecture functionality is described with an architecture walk-through and a sequence diagram in the unified modeling language (UML). The result is an innovative real-time web-crawling system to identify the value of a given product on the e-commerce websites. It deploys natural language process models to filter the non-relevant search results, and other machine learning models to best matching the remaining relevant results with a given item description.

The design and architecture description of this innovative web-crawling system is the main artifact of this research, while the mixed methodology of systems engineering methodologies and big data frameworks is another important scientific contribution.

Today, shipping industry is a complex system involving multiple actors, multiple interests and intricate interactions occurring at different levels.With any disruption to interaction occurring there would be multiple impacts and accumulation of costs on individual actors operating in the system.Unless these risks are well understood and prioritized based on the situational demands, the businesses will find it difficult operate in such complex actor-intensive system.In energy industry, Risk Based optimization (RBO) approach has been in use to manage the large infrastructures and multiple assets. RBO approach has been effective in identifying and prioritising the risks affecting the performance of the assets.Research was thus taken up to investigate this idea and thereby to develop a risk based decision making (RBDM) approach for international shipping domain. Further, to improve visibility in supply chain, development of a large scale Digital Trade Infrastructure (DTI) called Data Pipeline is in progress under the project called CORE. This research also tried to evaluate the extent to which both the concepts could reinforce each other and improve the supply chain quality.In the process, a prototype of RBDM Tool was developed and used to analyze the trade lane of JamboFresh, a fruit importing company in the Netherlands. By coping with the challenges posed by RBO approach of energy industry, by narrowing down the limitations offered by current risk management practices, and by incorporating the relevant multi-actor theories a RBDM Appraoch was developed. Based on the findings and discussions several reccomendations were laid down.

Container vessels arriving in a port before or after their scheduled time can cause problems in the container terminal planning and planning of hinterland transportation. This in turn leads to an increase of the costs in the supply chain. Vessels communicate their Estimated Time of Arrival via Automatic Idetification System(AIS) data to the port. This arrival time is estimated by the crew of the vessel and manually inputted into the AIS. In this research a proof of concept is shown that the Estimated Time of Arrival (ETA) prediction of container vessels can be improved. Vessels en route to the Port of Rotterdam are used as a case study. Different frameworks and algorithms are introduced to improve the data quality of AIS messages, to identify a set of possible routes and to do predictions based on the set of possible routes. It is possible to do predictions based on pre-processed AIS messages and a set of possible routes that perform at the same level as the best guess of a vessel’s crew.

Trade costs for the international supply chain are enormous, even in the absence of formal border barriers. In fact, the costs involved in moving a container physically are less than half the costs of managing the information about the transport activity. Thus, the physical infrastructure in international trade is fairly efficient, but that is not the case for the information infrastructure.
In addressing the complexity of the border activities, both public and private organizations are interested in making the compliance process more manageable and less costly, while still achieving the same level of security and safety. For the government, a well-managed border activity not only improves the revenue but also promotes the ports and increases their competitiveness. Based on the empirical finding, a 1% reduction in the transactional cost in relation to the border compliance process is worth $43 billion. Therefore, it is necessary for all stakeholders, both private and public organizations, to support an effective and efficient border-related compliance process, which can be done through the IT innovation of the compliance process.

Product master data (PMD) can be defined as a set of data that represents a selection of characteristics and aspects of its accompanying physical product. For several reasons, these data sets are increasingly exchanged between organizations within supply chains. Although this process is traditionally often supported by non-automated technologies such as Excel spreadsheet, telephone, email, and fax, the adoption of data pools is on the rise. These inter-organizational systems allow the data supplying party to publish a product’s master data set in one centralized system after which it can be accessed by all subscribed data recipients.

Companies that establish relationships with other organizations, submerge in a process of decision making in terms of the agreements related to information sharing that should be held between them and their allies, customers or providers. The involved organizations, in the information sharing arrangements, have to make a determination toward the type of system to be used to exchange information, and the governance of the systems to structure its management mechanisms. There is a comprehensive literature regarding the adoption of inter-organizational organization systems (IOS) including areas like factors that affect their implementation, benefits for the organizations that use them and the different existing types of IOS. There is also broad literature about information technology (IT) governance. Nevertheless, there is a lack of research debate concerning the factors that affect both, the implementation of information exchange systems and the IT governance of such systems.
This study aims to close the aforementioned gap by bringing an explanation about which factors influence the implementation of either a dyadic or a multilateral typology of information exchange system, used among companies, and the IT governance design whether it is centralized, federal or decentralized of such information system IS. Specifically, this research is addressed as an empirical study on how internal and external factors motivate companies to follow an information sharing arrangement which is formed by the typology and the IT governance of the information exchange system. The scope of this research is narrowed to the information sharing arrangements between private companies and their banking allies in Colombia, since the private companies in the South American country are the selected population; the central research question of this research is: Which factors influence the information sharing arrangements between private organizations and their banking allies?...