Search Results (50)

Lack of digitization in data sharing between enterprises and inspection solutions suppliers negatively affects cash flows between parties, which results in late payments that negatively affect the adoption of automatic inspection equipment. This paper contributes to improving the implementation of a new Inspection as a Service Business Model for deploying automatic inspection solutions using non-destructive inspection solutions, and to enhance workflows by integrating Blockchain and Smart Contracts. The Inspection as a Service offers flexible, cloud-based, or on-premise inspection solutions through the Marketplace, reducing upfront costs with a recurring service fee and automated payments. The marketplace platform supports automatic payment processes and facilitates industry adoption of IaaS solutions. The digital ecosystem offers improved capital expenditure and payback periods. It enhances communication, collaboration, data sharing, and payment processes through a subscription model. The case study demonstrates that the IaaS Business Model (on-premise or cloud) improves the economic feasibility of automatic non-destructive inspection solutions by lowering initial investments and enhancing return on investment and payback periods, even with higher operating costs. The analysis confirms the profitability and sustainability of IaaS Business Model over traditional one-fee selling by emphasizing its potential to improve operational performance and sustainability in manufacturing. The current proposal of automatic non-destructive solutions implements a new revenue model based on pay-per-use or volume, which makes it more financially viable to adopt this technology in industry. Full article

Hotel certifications have become increasingly vital in promoting sustainability within the hospitality industry, providing frameworks that guide hotels toward reducing their environmental footprint, enhancing operational efficiency, and gaining a competitive edge in the marketplace. This review explores the development, types, and impact of hotel certifications, with a focus on prominent schemes, such as LEED, Green Key, and EarthCheck. Through an analysis of case studies from globally recognized hotels, we highlight how certifications contribute to significant reductions in energy and water use, improved waste management, and enhanced biodiversity protection, while also delivering economic benefits through cost savings and increased guest loyalty. Our paper also examines consumer perceptions of certifications and their willingness to pay (WTP) for certified hotels. The findings suggest that eco-conscious travelers, particularly younger generations, are willing to pay a premium for hotels that demonstrate a commitment to sustainability; however, consumer awareness of certification schemes remains limited. The barriers to adopting certifications, such as high initial costs, resource limitations, and management resistance, are also discussed, along with the challenges posed by greenwashing and the proliferation of certification schemes. Looking to the future, this review identifies key trends that will shape the evolution of hotel certifications, including increased transparency, the integration of smart technologies, the expanding role of social responsibility, and their alignment with global sustainability goals, such as the United Nations Sustainable Development Goals (SDGs). Hotel certifications are not only crucial for environmental sustainability, but also serve as a powerful tool for enhancing the economic viability of hotels in an increasingly competitive and sustainability-driven market. Full article

This research aims to determine the position and the breakthrough trajectory of sustainable energy technologies. Fine-grained insights into these breakthrough positions and trajectories are limited. This research seeks to fill this gap by analyzing sustainable energy technologies’ breakthrough positions and trajectories in terms of development, application, and upscaling. To this end, the breakthrough positions and trajectories of seven sustainable energy technologies, i.e., hydrogen from seawater electrolysis, hydrogen airplanes, inland floating photovoltaics, redox flow batteries, hydrogen energy for grid balancing, hydrogen fuel cell electric vehicles, and smart sustainable energy houses, are analyzed. This is guided by an extensively researched and literature-based model that visualizes and describes these technologies’ experimentation and demonstration stages. This research identifies where these technologies are located in their breakthrough trajectory in terms of the development phase (prototyping, production process and organization, and niche market creation and sales), experiment and demonstration stage (technical, organizational, and market), the form of collaboration (public–private, private–public, and private), physical location (university and company laboratories, production sites, and marketplaces), and scale-up type (demonstrative, and first-order and second-order transformative). For scientists, this research offers the opportunity to further refine the features of sustainable energy technologies’ developmental positions and trajectories at a detailed level. For practitioners, it provides insights that help to determine investments in various sustainable energy technologies. Full article

In response to the widespread issue of fake comments on e-commerce platforms, this study aims to analyze and propose a blockchain-based solution to incentivize authentic user feedback and reduce the prevalence of fraudulent reviews. Specifically, this paper constructs a tripartite evolutionary game model between sellers, buyers, and e-commerce platforms to study the real comment mechanism of blockchain. The strategy evolution under different incentive factors is simulated using replication dynamic equation analysis and Matlab software simulation. The study found that introducing smart contracts and “tokens” for incentives not only increased incentives for real comments but also reduced the negative experiences caused by “speculative” sellers, thereby influencing buyers to opt for authentic reviews. By structuring interactions through blockchain, the mechanism helped lower informational entropy thus reducing disorder and unpredictability in buyer and seller behavior and contributing to system stability. Further, by increasing penalties for dishonest behavior under the “credit on the chain” system, the platform lowered entropy in the system by promoting trust and reducing fraudulent activities. The real comment mechanism based on blockchain proposed in this paper can effectively enhance the order and transparency within the comment ecosystem. These findings contribute to theory and practice by providing strategic insights for e-commerce platforms to encourage genuine feedback, reduce informational entropy, and mitigate fake comments, ultimately fostering a more reliable online marketplace. Full article

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government which seeks to create a sustainable human-centric society by putting to work recent advances in technology. One of the key challenges in implementing Society 5.0 is providing trusted and secure services for everyone to use. Motivated by this challenge, this paper makes three contributions that we summarize as follows: Our first main contribution is to propose a novel blockchain and smart contract-based trust and reputation service design to reduce the uncertainty associated with buyer feedback in marketplaces that we expect to see in Society 5.0. Our second contribution is to extend Laplace’s Law of Succession in a way that provides a trust measure in a seller’s future performance in terms of their past reputation scores. Our third main contribution is to illustrate three applications of the proposed trust and reputation service. Here, we begin by discussing an application to a multi-segment marketplace, where a malicious seller may establish a stellar reputation by selling cheap items, only to use their excellent reputation score to defraud buyers in a different market segment. Next, we demonstrate how our trust and reputation service works in the context of sellers with time-varying performance due, say, to overcoming an initial learning curve. We provide a discounting scheme where older reputation scores are given less weight than more recent ones. Finally, we show how to predict trust and reputation far in the future, based on incomplete information. Extensive simulations have confirmed the accuracy of our analytical predictions. Full article

The aim of this research has been to enable the management of trustworthy relationships between stakeholders, service providers, and physical assets, which are required in critical energy and mobility cyber–physical systems (CPS) applications. The achieved novel contribution is the concept of trustworthy communities with respective experimental solutions, which are developed by relying on verifiable credentials, smart contracts, trust over IP, and an Ethereum-based distributed ledger. The provided trustworthy community solutions are validated by executing them in two practical use cases, which are called energy flexibility and hunting safety. The energy flexibility case validation considered the execution of the solutions with one simulated and two real buildings with the energy flexibility aggregation platform, which was able to trade the flexibilities in an energy flexibility marketplace. The provided solutions were executed with a hunting safety smartphone application for a hunter and the smartwatch of a person moving around in the forest. The evaluations indicate that conceptual solutions for trustworthy communities fulfill the purpose and contribute toward making energy flexibility trading and hunting safety possible and trustworthy enough for participants. A trustworthy community solution is required to make value sharing and usage of critical energy resources and their flexibilities feasible and secure enough for their owners as part of the energy flexibility community. Sharing the presence and location in mobile conditions requires a trustworthy community solution because of security and privacy reasons, but it can also save lives in real-life elk hunting cases. During the evaluations, the need for further studies related to performance, scalability, community applications, verifiable credentials with wallets, sharing of values and incentives, authorized trust networks, dynamic trust situations, time-sensitive behavior, autonomous operations with smart contracts through security assessment, and applicability have been detected. Full article

Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly. Full article

In today’s dynamic and global landscape, innovation and globalization are intricately linked drivers that propel modern businesses forward, serving as indispensable pillars upon which organizations heavily rely to maintain their competitive edge. Leveraging innovation within the context of global product development (GPD) practices is imperative for organizations seeking to survive and effectively compete in the rapidly evolving marketplace. While preceding studies have primarily focused on the importance of individual and organizational capabilities, policies, and cultural factors in driving product development (PD) performance, they often overlook their interconnectedness within a global context. To address this gap, this study delves into the relationship between organizational factors and global product development performance (GPDP) while examining the moderating influence of global innovation culture (GIC). These organizational factors encompass technological innovation capabilities (TICs), team creativity (TC), dynamic capabilities (DCA), and competitive advantage (CA). Our hypothesis suggests a positive impact of these factors on GPD performance. Employing a structural equation modeling (SEM) approach through SMART-PLS 3, we analyzed data collected from 480 questionnaire forms distributed among registered global product development (GPD) organizations operating in China. The empirical findings underscore the significant influence of organizational factors on GPD performance, highlighting the critical role of global innovation culture in shaping these relationships. These insights shed light on the importance of establishing a harmonious balance between organizational culture and various factors to enhance interaction among organizational elements and optimize global product development performance. Ultimately, these efforts can lead to improvements in the overall effectiveness and sustained global product development. Full article

In contemporary data-driven economies, data has become a valuable digital asset that is eligible for trading and monetization. Peer-to-peer (P2P) marketplaces play a crucial role in establishing direct connections between data providers and consumers. However, traditional data marketplaces exhibit inadequacies. Functioning as centralized platforms, they suffer from issues such as insufficient trust, transparency, fairness, accountability, and security. Moreover, users lack consent and ownership control over their data. To address these issues, we propose DataMesh+, an innovative blockchain-powered, decentralized P2P data exchange model for self-sovereign data marketplaces. This user-centric decentralized approach leverages blockchain-based smart contracts to enable fair, transparent, reliable, and secure data trading marketplaces, empowering users to retain full sovereignty and control over their data. In this article, we describe the design and implementation of our approach, which was developed to demonstrate its feasibility. We evaluated the model’s acceptability and reliability through experimental testing and validation. Furthermore, we assessed the security and performance in terms of smart contract deployment and transaction execution costs, as well as the blockchain and storage network performance. Full article

Over the last few years, the European Union (EU) has placed significant emphasis on the interoperability of critical infrastructures (CIs). One of the main CI transportation infrastructures are ports. The control systems managing such infrastructures are constantly evolving and handle diverse sets of people, data, and processes. Additionally, interdependencies among different infrastructures can lead to discrepancies in data models that propagate and intensify across interconnected systems. This article introduces “BigDaM”, a Big Data Management framework for critical infrastructures. It is a cutting-edge data model that adheres to the latest technological standards and aims to consolidate APIs and services within highly complex CI infrastructures. Our approach takes a bottom-up perspective, treating each service interconnection as an autonomous entity that must align with the proposed common vocabulary and data model. By injecting strict guidelines into the service/component development’s lifecycle, we explicitly promote interoperability among the services within critical infrastructure ecosystems. This approach facilitates the exchange and reuse of data from a shared repository among developers, small and medium-sized enterprises (SMEs), and large vendors. Business challenges have also been taken into account, in order to link the generated data assets of CIs with the business world. The complete framework has been tested in the main EU ports, part of the transportation sector of CIs. Performance evaluation and the aforementioned testing is also being analyzed, highlighting the capabilities of the proposed approach. Full article

Manufacturing as a Service (MaaS) enables a paradigm shift in the current manufacturing landscape, from integrated production and inflexible, fragile supply chains to open production and flexible, robust supply chains. As part of this evolution, new scaling effects for production capacities and customer segments are possible. This article describes how to accomplish this paradigm shift for the automotive industry by building a digital MaaS ecosystem for the large-scale automotive innovation project Catena-X, which aims at a standardized global data exchange based on European values. A digital MaaS ecosystem can not only achieve scaling effects, but also realize new business models and overcome current and future challenges in the areas of legislation, sustainability, and standardization. This article analyzes the state-of-the-art of MaaS ecosystems and describes the development of a digital MaaS ecosystem based on an updated and advanced version of the reference architecture for smart connected factories, called the Smart Factory Web. Furthermore, this article describes a demonstrator for a federated MaaS marketplace for Catena-X which leverages the full technological potential of this digital ecosystem. In conclusion, the evaluation of the implemented digital ecosystem enables the advancement of the reference architecture Smart Factory Web, which can now be used as a blueprint for open, sustainable, and resilient digital manufacturing ecosystems. Full article

As smart transportation systems evolve, secure and efficient V2X communication between vehicles and infrastructure becomes crucial. This paper introduces a Vehicle-to-Blockchain (V2B) communication architecture, leveraging blockchain technology for transparent and decentralized interactions. Our work contributes to the integration of blockchain into V2X and IoT for next-generation transportation systems. We propose several novel blockchain use cases, including a blockchain-based vehicle ownership system based on the multi-token standard, a vehicle scoring system, blockchain–IoT integration, and a decentralized ticket management system for transportation services. The architecture addresses key aspects, such as data integration, validity, and secure messaging, and introduces a decentralized payment system and marketplace for transportation in smart cities. We specifically emphasize the technical implementation of smart contracts for these use cases, underscoring their role in ensuring robust and reliable interactions. Through our decentralized approach, we pave the way for a transformative transportation ecosystem that is adaptable, resilient, and capable of meeting the evolving needs of smart cities. Full article

To ensure the success of energy transition and achieve the target of reducing the carbon footprint of energy systems, the management of energy systems needs to be decentralized. Public blockchains offer favorable features to support energy sector democratization and reinforce citizens’ trust, such as tamper-proof energy data registration and sharing, decentralization, transparency, and support for peer-to-peer (P2P) energy trading. However, in blockchain-based P2P energy markets, transactional data are public and accessible, which raises privacy concerns related to prosumers’ energy profiles while lacking scalability and featuring high transactional costs. In this paper, we employ secure multi-party computation (MPC) to assure privacy on a P2P energy flexibility market implementation in Ethereum by combining the prosumers’ flexibility orders data and storing it safely on the chain. We provide an encoding mechanism for orders on the energy market to obfuscate the amount of energy traded by creating groups of prosumers, by splitting the amount of energy from bids and offers, and by creating group-level orders. The solution wraps around the smart contracts-based implementation of an energy flexibility marketplace, assuring privacy features on all market operations such as order submission, matching bids and offers, and commitment in trading and settlement. The experimental results show that the proposed solution is effective in supporting P2P energy flexibility trading, reducing the number of transactions, and gas consumption with a limited computational time overhead. Full article

Buildings can become a significant contributor to an energy system’s resilience if they are operated in a coordinated manner to exploit their flexibility in multi-carrier energy networks. However, research and innovation activities are focused on single-carrier optimization (i.e., electricity), aiming to achieve Zero Energy Buildings, and miss the significant flexibility that buildings may offer through multi-energy coupling. In this paper, we propose to use blockchain technology and ERC-1155 tokens to digitize the heat and electrical energy flexibility of buildings, transforming them into active flexibility assets within integrated multi-energy grids, allowing them to trade both heat and electricity within community-level marketplaces. The solution increases the level of interoperability and integration of the buildings with community multi-energy grids and brings advantages from a transactive perspective. It permits digitizing multi-carrier energy using the same token and a single transaction to transfer both types of energy, processing transaction batches between the sender and receiver addresses, and holding both fungible and non-fungible tokens in smart contracts to support energy markets’ financial payments and energy transactions’ settlement. The results show the potential of our solution to support buildings in trading heat and electricity flexibility in the same market session, increasing their interoperability with energy markets while decreasing the transactional overhead and gas consumption. Full article

Blockchain technology is used to support digital assets such as cryptocurrencies and tokens. Commonly, smart contracts are used to generate tokens on top of the blockchain network. There are two fundamental types of tokens: fungible and non-fungible (NFTs). This paper focuses on NFTs and offers a technique to spot plagiarism in NFT images. NFTs are information that is appended to files to produce distinctive signatures. It can be found in image files, real artifacts, literature published online, and various other digital media. Plagiarism and fraudulent NFT images are becoming a big concern for artists and customers. This paper proposes an efficient deep learning-based approach for NFT image plagiarism detection using the EfficientNet-B0 architecture and the Triplet Semi-Hard Loss function. We trained our model using a dataset of NFT images and evaluated its performance using several metrics, including loss and accuracy. The results showed that the EfficientNet-B0-based deep neural network with triplet semi-hard loss outperformed other models such as Resnet50, DenseNet, and MobileNetV2 in detecting plagiarized NFTs. The experimental results demonstrate sufficient to be implemented in various NFT marketplaces. Full article