How technology can advance port operations and address supply chain disruptions

Supply chain disruptions continue to be a significant challenge as the world economy recovers from the pandemic-related shutdowns that have strained global supply chains. Shocks challenge the adaptability and resilience of maritime ports. The reaction of automated container terminals to supply chain disruptions has renewed interest, given the dramatic scenes of ships anchored for weeks. In this dissertation, I provide a vision of how technology can enhance a port’s ability to anticipate and handle shocks by improving coordination, cooperation, and information exchange across port stakeholders. The vision will be helpful for academics and practitioners to perform research that advances theory and practice on the use of advanced technologies to improve port operations. I use complex adaptive systems theory to develop a qualitative cross-case study of the ports of Los Angeles, Vancouver, and Rotterdam. I examine the effect that automation and other technologies have had on the efficiency of these ports, both in daily operations and during the disruption caused by the COVID-19 pandemic. Using critical tenets of complexity and with a rigorous application of the case study method, I develop theoretical propositions and practical insights to ground the vision of the port of the future based on current practices. The findings from the cross-case study suggest that automated terminals were more efficient during the pandemic than non-automated terminals. I propose that transitioning to higher levels of automation, supported by emerging technologies like blockchain and the internet of things, will make ports more resilient to supply chain disruptions when those systems are coordinated through Port Community Systems

Decentralized procurement mechanisms for efficient logistics services mapping - a design science research approach

Companies tend to outsource logistics services for flexibility or platform operating costs reduction. To do so, they typically use centralized platforms to delegate the services procurement process. However, those platforms can be prone to information asymmetries between carriers and shippers which can lead to sub-optimal procurement outcomes. A more transparent and efficient way to manage the procurement of logistics services between carriers and shippers could be a decentralized platform based on blockchain and smart contracts. In this paper, we design, implement, and evaluate the potential for a decentralized logistics services procurement system, following a design science research approach. In so doing, we contribute by (1) developing such a decentralized logistics services procurement system that addresses the allocation problem, and (2) developing a set of nascent design principles guiding the elaboration of decentralized procurement mechanisms on blockchain

Trust in Software Supply Chains: Blockchain-Enabled SBOM and the AIBOM Future

Software Bill of Materials (SBOM) serves as a critical pillar in ensuring software supply chain security by providing a detailed inventory of the components and dependencies integral to software development. However, challenges abound in the sharing of SBOMs, including potential data tampering, hesitation among software vendors to disclose comprehensive information, and bespoke requirements from software procurers or users. These obstacles have stifled widespread adoption and utilization of SBOMs, underscoring the need for a more secure and flexible mechanism for SBOM sharing. This study proposes a novel solution to these challenges by introducing a blockchain-empowered approach for SBOM sharing, leveraging verifiable credentials to allow for selective disclosure. This strategy not only heightens security but also offers flexibility. Furthermore, this paper broadens the remit of SBOM to encompass AI systems, thereby coining the term AI Bill of Materials (AIBOM). This extension is motivated by the rapid progression in AI technology and the escalating necessity to track the lineage and composition of AI software and systems. Particularly in the era of foundational models like large language models (LLMs), understanding their composition and dependencies becomes crucial. These models often serve as a base for further development, creating complex dependencies and paving the way for innovative AI applications. The evaluation of our solution indicates the feasibility and flexibility of the proposed SBOM sharing mechanism, positing a new solution for securing (AI) software supply chains

Blockchain technology to secure data for digital twins throughout smart buildings’ life cycle in the context of the circular economy

Blockchain technology (BCT) can be leveraged for digital twins (DT) to enhance data security, collaboration, efficiency, and sustainability in the construction industry (CI) 4.0. This study aims to develop a novel technological framework and software architecture using BCT for DT throughout the lifecycle of smart building projects in the context of the circular economy (CE). The study identifies key challenges and technological factors affecting BCT adoption. It also identifies which project data types can benefit from BCT and the key factors and non-functional requirements (NFRs) necessary for the adoption of blockchain based digital twins (BCDT) in CI 4.0. The study finally proposes a software architecture and smart contract framework for BCDT decentralized applications (DApps) throughout the lifecycle of smart infrastructure projects. The study offers a technological framework – the decentralized digital twin cycle (DDTC) – with BCT to enhance trust, security, decentralization, efficiency, traceability, and transparency of information. The study found that the key data from the project lifecycle relevant for BCDTs relate to the BIM dimensions (3D, 4D, 5D, 6D, 7D, and 8D) and a novel contractual dimension (cD) is also proposed. Additionally, BCDT maturity Level 4 is proposed, leveraging BCT to enhance collaboration, process automation, and data sharing within a decentralized data value chain. The main NFRs for BCDTs are security, privacy, interoperability, data ownership, data integrity, and the decentralization and scalability of data storage. A five layered software architecture and a smart contracts framework using Non-Fungible Tokens (NFTs) are offered to address key industry use cases and their functional and non-functional requirements. The framework narrows the gaps identified around network governance, scalability, decentralization, interoperability, energy efficiency, computational requirements, and the integration of BCT with IoT, BIM, and DT. A cost analysis permitted developing criteria to evaluate the suitability of blockchain networks for BCDT applications in CI 4.0 based on key blockchain properties (security, decentralization, scalability, and interoperability). The study provides an industry-specific analysis and technological approach for BCDT adoption to address key challenges and improve sustainability for the CI 4.0. The findings provide key building blocks for industry practitioners to adopt and develop BCDT DApps further. The framework enables a paradigm shift towards decentralized ecosystems of united BCDTs where trust, collaboration, data sharing, information security, efficiency, and sustainability are improved throughout the lifecycle of smart infrastructure projects within a decentralized CE (DCE)

Sustainable Development Report: Blockchain, the Web3 & the SDGs

This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

IoT Applications, Platforms, Systems, And Framework based on Blockchain

The Internet of Things (IoT) has lately evolved as a new technology capable of providing real-time and cutting-edge sensing capabilities to numerous industries such as healthcare, agriculture, smart cities, smart homes, and supply chain. Because of this technology's inherent promise, it has already seen exponential growth in a wide range of use-cases across numerous application domains. As academics around the world continue to examine its capabilities, there is widespread consensus that in order to get the most out of this technology and fully realise its potential, IoT must be built on a flexible network architecture with strong support for security, privacy, and trust. Blockchain (BC) technology, on the other hand, has lately emerged as a breakthrough technology with the promise to give several beneficial qualities such as robustness, support for integrity, anonymity, decentralisation, and autonomous control. Several BC systems are offered, which may be appropriate for various use-cases, including IoT applications. As a result, the integration of IoT with BC technology is seen as a potential solution to some critical concerns. To do this, a good grasp of the requirements of various IoT applications and the viability of a BC platform for a specific application satisfying its underlying requirements is required. This project explains many ways such as the gateway process and sensor device. By addressing the present blockchain concerns, IoT may enable a variety of security services, all of which are described in detail. Various authors present some common facts on the use of blockchain in IoT, which aids in a thorough understanding of the concept. Blockchain improves security and privacy in IoT platforms. In this project, an extra immutable ledger is created using all of the resources and information mentioned in the existing procedure. [1]

Sustainable Development Report: Blockchain, the Web3 & the SDGs

This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Secret Smart Contracts in Hierarchical Blockchains

This article presents the results of an implementation of a new platform based on swarm communication and executable choreographies. In our research of executable choreographies, we have come up with a more general model to implement smart contracts and a generic architecture of systems using hierarchical blockchain architecture. The novel concepts of secret smart contract and near-chain are introduced. The near-chain approach presents a new method to extend the hierarchical blockchain architecture and to improve performance, security and privacy characteristics of general blockchain-based systems. As such, we are subsequently defining and explaining why any extension of blockchain architectures should revolve around three essential dimensions: trustlessness, non-repudiation and tamper resistance. The hierarchical blockchain approach provides a novel perspective, as well as establishing off-chain storages (near-chains) as special types of hierarchical blockchains stored in a distributed file system. Furthermore, we are providing solutions to the difficult blockchain concerns regarding scalability, performance and privacy issues

Short-Term Power Demand Forecasting Using Blockchain-Based Neural Networks Models

With the rapid development of blockchain technology, blockchain-based neural network short-term power demand forecasting has become a research hotspot in the power industry. This paper aims to combine neural network algorithms with blockchain technology to establish a trustworthy and efficient short-term demand forecasting model. By leveraging the distributed ledger and immutability features of blockchain, we ensure the security and reliability of power demand data. Meanwhile, short-term power demand forecasting research using neural networks has the potential to increase the stability of the power system and offer opportunities for improved operations. In this paper, the root mean-square-error model evaluation indicator was used to compare the back propagation (BP) neural network algorithm and the traditional forecasting algorithm. The evaluation was performed on the randomly selected five household power datasets. The results show that, by comparing the long short-term memory network (LSTM) model with the BP neural network model, it was determined that the average prediction impact increases by about 25.7% under stable power demand. The short-term power prediction model of the BP neural network has the average error values more than two times lower than the traditional prediction model. It was shown that the use of the BP neural network algorithm and blockchain could increase the accuracy of short-term power demand forecasting, allowing the neural network-based algorithm to be implemented and taken into account in the research on short-term power demand forecasting