Blockchain Service Research Articles

Development of a service blueprint for blockchain services.

As blockchain has been actively applied in various services, a tool for visualizing the complex service processes reflecting the characteristics of blockchain has been required. A service blueprint is a tool to visualize all key systems and encounters in service delivery. Although several blueprints already exist, they have limitations to systematically visualize and analyze blockchain service processes. This study develops a Blockchain Service Blueprint (BSB) specialized in visualizing and analyzing blockchain service processes. A comprehensive literature review and an analysis of blockchain services were conducted to identify characteristics of blockchain services and limitations of existing blueprints. The BSB was developed based on the derived key components of blockchain service processes, so that it has the optimal structure with key elements to visualize complex processes of blockchain services. The usefulness of the BSB was verified by both comparisons with traditional blueprints and expert interviews. The proposed BSB can intuitively and clearly visualize a service process between customers and service providers in blockchain services. Using the Blockchain Service Blueprint (BSB), providers can identify and improve service processes to enhance sustainability, and this study offers researchers cases and a development process that demonstrate the BSB's effectiveness across various blockchain services.

Blockchain for Mass Customization: The Value of Information Sharing Through Data Accuracy by Contract Coordination

This study provides the game-theoretical framework to investigate the relationship between the blockchain service and mass customization in the environment of information sharing and contract coordination. Specifically, we construct the game-theoretical models of the manufacturer and the retailer to discuss the optimal strategy of information sharing by the retailer in the case of mass customization. The result explores the conditions of information sharing for the retailer because she understands the end market information of nearby consumers. This discussion helps us to understand that the motivation of the manufacturer pays for the retailer’s construction of a blockchain system in the case of two types of products, such as a standard product and a customization product. Finally, we use the method of contract coordination to obtain the optimal strategy. Results reveal that information costs significantly impact sharing decisions, and cost-sharing contracts can incentivize retailers to share market data. This study has two main contributions. On the one hand, this study adopts the blockchain service for mass customization by supporting contract coordination, showing the technical value of avoiding false information and tampering-proof. On the other hand, although big data has the same information sharing function, this technology can’t play the role of secure data transmission. In order to increase the accuracy of information sharing, we analyze the fusion results of two technologies in the aspect of increasing the accuracy of data sharing, which better reveals the technical value.

Open BIM exchange on Blockchain 3.0 virtual disk: A traceable semantic differential transaction approach

Abstract Building information modeling (BIM) has become prevalent in construction engineering management. However, the efficiency of traditional file-based BIM exchange between multidisciplinary teams remains low due to the transmission of redundant data from mostly unchanged BIM objects. Additionally, the traceability of changes between BIM files is limited. This paper proposes a traceable semantic differential transaction (tSDT) approach for open BIM exchange, which minimizes data redundancy and enables semantic-level traceability of BIM changes. Furthermore, openBIMdisk implements the tSDT and provides a Blockchain 3.0 virtual disk to support efficient, traceable, and secure BIM exchanges across multiple blockchain services. A pilot study of a modular construction project demonstrated the effectiveness of tSDT and open-BIMdisk. Experimental results indicated that tSDT achieved minimal BIM redundancy for storing and restoring all BIM changes, using a sheer 0.007% of disk space on average. openBIMdisk facilitated BIM version management and object-level semantic traceability with a response time of 5.3 ms. The contributions of this paper are twofold. First, tSDT offers a novel and efficient approach for semantic BIM change traceability. Second, openBIMdisk provides BIM practitioners with a Blockchain 3.0 application featuring intuitive and user-friendly interfaces for BIM exchange.

Platform's blockchain introduction strategy with considering competition between new and refurbished products

As the second-hand market continues to grow, many retail platforms initially specializing in selling new products (e.g., Amazon, JD, and Walmart.com) have begun allowing refurbishers to directly sell refurbished goods on their platforms and gain additional profits. The platform can provide blockchain certification services for refurbishers to eliminate consumers' concerns about quality. In contrast to the existing literature, which primarily examines the introduction of blockchain technology from the perspective of cost factors, this paper investigates the platform's blockchain introduction in the context of competition between the new and refurbished products and its impacts on the manufacturer's and the refurbisher's profitability. Motivated by practices, two prevalent selling modes for the new product are considered: reselling mode (R) and agency selling mode (A). Even without considering the cost of blockchain, we find that the platform may have no incentive to introduce blockchain under both modes because it could trigger a severe cannibalization problem or an excessively high price for the refurbished product. The refurbisher (manufacturer) benefits with (without) blockchain under mode R, but this result occurs under mode A only when the blockchain service fee is low. We also discuss the welfare and environmental implications of blockchain. We find that the selling modes may modify the environmental implications of blockchain, but not the welfare implications of blockchain.

A Blockchain‐Based Proxy Re‐Encryption Scheme With Cryptographic Reverse Firewall for IoV

ABSTRACTAs the internet of vehicles (IoV) technology develops, it promotes the intelligent interaction among vehicles, roadside units, and the environment. Nevertheless, it also brings vehicle information security challenges. In recent years, vehicle data sharing is suffering to algorithm substitution attacks (ASA), which means backdoor adversaries can carry out filtering attacks through data sharing. Therefore, this paper designs a blockchain‐based proxy re‐encryption (PRE) scheme with cryptographic reverse firewall (BIBPR‐CRF) for IoV. In our proposal, CRF can promise the internal safety of vehicle units. More specifically, it can prevent ASA attacks while ensuring chosen plaintext attack (CPA)‐security. Meanwhile, the PRE algorithm can provide the confidential sharing and secure operation of data. Moreover, we use a consortium blockchain service center (CBSC) to store the first ciphertext and re‐encrypt it with smart contracts on the blockchain, which can avoid single point of failure and achieve higher efficiency compared to proxy servers. Finally, we evaluate the performance of BIBPR‐CRF with regard to communication cost, computational cost, and energy consumption. Our proposal is the most fitting for IoV application, in contrast with the other three schemes.

Implementation mode selection for blockchain technology in green product traceability

Implementing blockchain technology to improve traceability can enhance consumer trust in green supply chains. However, the associated high fixed costs can pose challenges for companies when choosing the implementation mode. In this study, we investigate the value of blockchain adoption and explore a manufacturer’s choice between third-party or self-implementation. Specifically, we consider the traceability level and the greenness degree in a supply chain comprising a manufacturer, a retailer, and a third-party platform providing blockchain services. Our findings indicate that self-implementation by the manufacturer increases the degree of greenness, and the retailer’s involvement in decisions about traceability levels improves the manufacturer’s traceability level. The highest profits for supply chain members are achieved when both parties opt for self-implementation. Additionally, self-implementation outperforms third-party platform implantation when incentivizing the manufacturer to invest more in green and blockchain technologies. Consequently, blockchain technology’s value exceeds its costs, encouraging supply chain members to select self-implementation whenever possible. However, when the fixed costs or the cost coefficient of green investment or traceability are excessively high, the manufacturer may need to outsource blockchain services to a third-party platform. Furthermore, through comprehensive system dynamics analysis, we find that blockchain’s adoption or non-adoption and imposing an investment cap on the product’s green degree have a little effect on profitability for suppliers, manufacturers, logistics providers, and third-party platforms.

A sequential multiple attribute three-way group decision-making method to heterogeneous MAGDM problems with unknown weight information

As a decision model to depict the human cognitive process, three-way decision (3WD) provides a reasonable semantic interpretation for solving practical multi-attribute group decision-making (MAGDM) problems. At the same time, there often exist different types of information due to the subjective and objective criteria in practical decision-making problems, thus it is necessary to develop some efficient frameworks to deal with the MAGDM problems with heterogeneous information. In this paper, based on 3WD theory and sequential strategy, we propose a sequential multiple attribute three-way group decision-making (SMA3WGD) method for the heterogeneous MAGDM problem with unknown weight information to achieve this goal. At first, we compute the weights of decision-makers by using the consensus degree between each of the decision-makers in a group. Then, we calculate the collective evaluation result of multiple decision-makers by utilizing the mathematical planning method with two objectives of minimum difference and high similarity between group evaluation values and individual evaluation values. Meanwhile, a nested sequence of the set of attributes is constructed according to the attribute values offered by decision-makers that have different degrees of consensus on different attributes. On this basis, a multilevel granular structure for the heterogeneous MAGDM problems is constructed, and then the compute of the cost functions and conditional probability is explored in a single level of granular structure, and the thresholds and three-way decision rules of alternatives are further determined depending on the principle of cost minimization. Furthermore, by using a sequential strategy, we obtain a sequential three-way decision result of the heterogeneous MAGDM problems under the multilevel granular structure. At last, the practicality and advantages of the suggested method are demonstrated via a blockchain service provider selection case study, a parameter sensitivity analysis along with a comparison analysis.

Pricing and blockchain adoption for competitive sellers on an e-commerce platform with different contracts

We examine the impact of a blockchain technology (BCT) adoption strategy on the decisions and profits of branded companies and counterfeiters, and then discuss how BCT helps counterfeiters transform on a platform offering blockchain services and commission contracts. Our results show that BCT can make the branded seller better off when a platform has more brand-conscious consumers, despite the high adoption fee. Due to the free-riding effect, the counterfeiter’s best choice is often not to adopt BCT. As the fraction of brand-unconscious consumers increases, even with low adoption fee, the branded seller will not use BCT, but the counterfeiter will adopt BCT to transform her business and become a legitimate seller by offering innovative products, which increases consumer surplus. As the counterfeit probability and blockchain added value increase, both sellers proactively adopt BCT to disclose product authenticity, which may worsen the platform and social welfare. Importantly, there is a win–win–win outcome for sellers, platforms and consumers when at least one seller adopts BCT, depending on the interaction among the abovementioned factors. Compared with the proportional-fee contract, the fixed-fee contract improves the cost affordability of both sellers. In the context of different consumer types on platforms, our findings offer guidelines for branded companies to solve the authenticity problem of products and for counterfeiters to transform their businesses.

Antecedents and outcomes of innovative blockchain usage in accounting and auditing profession: an extended UTAUT model

PurposeThis article aims to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) model to understand the factors affecting the usage behavior of Blockchain from accountants' and auditors’ perspectives and its impact on their performance.Design/methodology/approachA quantitative research approach employing a web-based questionnaire was applied, and the empirical data were gathered from 329 potential and current users of Blockchain in the accounting and auditing profession in Jordan. The analytical model was based on structural equation modeling (SEM) using AMOS 25.0.FindingsThe experimental findings of the structural path confirmed that performance expectancy (PE), social influence (SI), Blockchain transparency (BT) and Blockchain efficiency (BE) were significantly affecting individuals’ behavioral intention (BI) toward the use of Blockchain-based systems and helped to explain (0.67) of its variance. Also, BE has a positive significant impact on PE. Whereas, in contrast to what is anticipated, the influence of effort expectancy (EE) on BI was not supported. Additionally, users’ intentions were found to affect the actual usage (AU) behavior and helped to explain (0.69) of its variance. The outcome variables proposed in this study: knowledge acquisition (KACQ) and user satisfaction (USAT) were significantly influenced by the AU of Blockchain technology.Practical implicationsThis study outlines practical implications for government, policymakers, business leaders and Blockchain service providers aiming to exploit the advantages of Blockchain technology (BCT) in the accounting and auditing context.Originality/valueTo the best of the authors’ knowledge, this article is one of the few studies that offer an evidence-based perspective to the discussions on the effect of disruptive and automated information and communication technologies (ICTs), on the accounting and auditing profession. It applies an innovative approach to analysis through the integration of UTAUT, contextual factors: BT and BE, besides two outcome factors: KACQ and USAT within its theoretical model. This study extends and complements the academic literature on information technology/information systems acceptance and use by providing novel insights into accountants' and auditors’ views.

Enabling intrinsic intelligence, ubiquitous learning and blockchain empowerment for trust and reliability in 6G network evolution

This study investigates the 6th Generation (6G) wireless communication network as a vital component of Ubiquitous Learning, which makes it possible to build trustworthy relationships and accurate intelligence in a variety of contexts. The important significance of blockchain technology is recognized, and its potential to improve the performance of the 6G network is investigated. Blockchain technology powers Ubiquitous Learning as a decentralized tool. But in Ubiquitous Learning contexts, problems arise when varied communication settings, information asymmetry, and resource limits confront wireless-connected devices functioning as blockchain consensus nodes. To solve these difficulties, which are critical for Ubiquitous Learning, a blockchain sharding and incentive system is presented. The purpose of this technique is to improve the learning process in the 6G network by cultivating reliable intelligence. A sharding architecture that integrates a contract theory-based incentive mechanism and a realistic Byzantine fault tolerance mechanism, particularly tailored for Ubiquitous Learning settings, is described. This model analyses the useful Byzantine consensus mechanism and block broadcast characteristics in wireless networks. This study finds the best contract combination for both completely symmetric and asymmetric information scenarios, optimizing block rewards for customers that seek blockchain services.

Blockchain service platform evaluation with probabilistic linguistic preference information based on Choquet integral and ExpTODIM

The application of Internet of Medical Things (IoMT) can improve the treatment efficiency of medical institutions, but it still has hidden dangers in security and privacy. The introduction of blockchain technology into IoMT is expected to prevent these hidden dangers. This study proposes a multiple criteria decision aiding model to select a suitable blockchain service platform for IoMT to enhance its safety and reliability. The proposed model combines the probabilistic linguistic term set (PLTS), multiple criteria hierarchy process (MCHP), 2-additive Choquet integral and ExpTODIM method to assist decision-makers (DMs) to obtain a reliable and low-risk decision result. The MCHP is employed to analyze decision-making problems by hierarchical criteria. The 2-additive Choquet integral is adopted to reflect interactions between criteria, and parameter values in the 2-additive Choquet integral are indirectly determined based on the preference information of DMs. PLTSs are used to represent the evaluation information of experts and the preference information of DMs. The ExpTODIM (Exponential TODIM) method is adopted to rank alternatives considering the psychological characteristics of DMs. An illustrative example demonstrates the applicability and merits of the proposed model with comparative analysis.

Collaboration of Vague Theory and Mathematical Techniques for Optimizing Healthcare by Recommending Optimal Blockchain Supplier

The Internet of Medical Things (IoMTs) has the potential to revolutionize healthcare delivery by connecting medical devices and applications to healthcare IT systems via the internet. This connectivity enables the collection, transmission, and analysis of patient data, facilitating remote healthcare delivery and enhancing patient outcomes. However, the security and privacy of the data transmitted and stored within IoMT systems remain critical concerns. Blockchain technology offers a promising solution to address these challenges in IoMTs applications. Blockchain provides a decentralized and immutable ledger where transactions, in this case, patient data, are securely recorded and cannot be altered retroactively. This ensures the integrity and confidentiality of sensitive medical information while eliminating the need for a central authority to manage data exchange. This study proposes a comprehensive fuzzy decision-making framework for selecting the best blockchain provider in the IoMT field. The framework comprises two main steps: Determining the relative importance weights of the criteria utilizing the Stepwise Weight Assessment Ratio Analysis (SWARA) method. Determining the most suitable supplier for blockchain services providers employing the Ranking Alternatives with the Fuzzy ROOT Assessment Method (RAM) technique. A comparison between Fuzzy Multi-Criteria Decision-Making (MCDM) methods is employed to ensure the robustness and validity of the proposed framework.

Analysing factors influencing the adoption of blockchain technology in maritime freight enterprises

ABSTRACT Maritime freight companies are beneficial in carrying the majority of commodities globally. The large number of parties involved makes data exchange hard. Blockchain technology’s potential benefits are becoming more apparent to maritime freight firms. This report examines the important factors influencing blockchain technology adoption in the maritime freight sector. To calculate their weights, the study applies the Grey-DEMATEL based Analytic Network Process. According to the analysis, the most important determinants are government policies, firm size, and perceived cost of investment. These insights can assist government agencies, freight companies, and blockchain service providers in planning successful implementations and increasing competitiveness.

Vendor capabilities development in blockchain sourcing: A parallel play approach

Vendor capabilities development has been an important research stream in the information systems (IS) sourcing literature. The existing research, which was based on the context of implementing centralized enterprise systems, focused on the adoption of deliberate learning and implicit learning, with the assumption that effective selection between these two learning approaches is sufficient for service providers to acquire vendor capabilities. However, this assumption may not hold in implementing a decentralized system based on enterprise blockchain. Because an enterprise blockchain system affords a new way of governing transactions and demands a new governance mode, it creates an uncertain and complex landscape in which the mere selection between deliberate learning and implicit learning becomes insufficient. Addressing this gap is crucial because many enterprise blockchain projects fail due to the incompetence of service providers. By conducting an in-depth case study of a successful blockchain service provider, our study reveals a new mechanism for developing vendor capabilities: parallel play. As with parallel play by preschoolers, the service provider combines a set of learning approaches featuring borrowing from peers and learning through experimentation. Our study extends the IS sourcing literature on vendor capabilities development from the context of implementing centralized enterprise systems to the context of implementing decentralized enterprise blockchain systems. Our findings also provide guidelines for blockchain service providers to follow when acquiring vendor capabilities and for clients to use when selecting service providers.

Data-Tracking in Blockchain Utilizing Hash Chain: A Study of Structured and Adaptive Process

This study presents a series of structured and adaptive processes aimed at tracking and verifying transactions recorded on the blockchain. Permissioned blockchains are employed across diverse enterprises for various purposes, including data recording, management, the utilization of blockchain services, and authentication. However, the processes of data tracking and transactions incur substantial resource and time expenditure. Furthermore, there is potential for information asymmetry within the blockchain ledger due to data breach attacks. Consequently, we propose a contract structured as a hash chain to mitigate resource and time consumption in the tracking and verification processes by organizing transaction hash values and content in a hash chain format based on cryptography. We generate a hash chain for the recorded transactions along the process line and expedite the tracking and verification process by navigating the relevant hash chain. This approach achieves faster and more accurate tracking procedures compared to conventional transaction tracking processes, simultaneously maintaining data symmetry within the blockchain ledger. We conduct a comparative analysis of a contract-based hash-chain-employing structure and two contracts related to tracking in terms of tracking time, CPU usage, and network traffic, among other metrics. The findings suggest that structuring transaction data in the form of a hash chain significantly enhances the efficiency and integrity of the data-tracking and verification processes. Consequently, in this study, we advocate for the adoption of contracts based on the hash chain format when leveraging the blockchain for tracking and verification purposes across various institutions.

VC-Vault: A User-Friendly, Secure, Privacy-Enhancing Verifiable Credentials Wallet

The shift from centralized identity systems to decentralized alternatives is becoming more imminent. Users are increasingly encouraged to embrace the principles of Self-Sovereign Identity (SSI), relying on two key components, Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), to regain total ownership and control over their identity and data, as well as how and to whom they are shared. This emphasizes a pressing need for VC wallet solutions that are not only user-friendly, but also uncompromisingly secure. In this paper, we introduce VC-Vault, an innovative wallet application that incorporates the principles of SSI and conforms to the European Blockchain Services Infrastructure (EBSI) standards. VC-Vault operates across both desktop and mobile platforms, delivering a coherent and effortless user experience. By establishing seamless integration with EBSI services, SSI principles, and VCs, VC-Vault places the control of digital identity and credentials firmly in the discretion of users.

The use of blockchain technology in law enforcement

This article explores the possibilities of using blockchain technology in police work. Examples of the use of blockchain in various areas of police activity, such as personal data management, control of drug trafficking and other prohibited substances, traffic monitoring and the fight against cybercrime, are considered. The authors note that thanks to the storage of data in the blockchain, it becomes possible to increase the protection of the confidentiality of personal information, ensure transparency and efficiency of police work, as well as prevent fraud and corruption. The conclusion of the article emphasizes that the use of blockchain can improve the work of the police and ensure greater security of citizens. Distributed ledger technology, or blockchain as a service (BaaS) is indeed a relatively new product on the market that allows you to provide blockchain services for corporate clients. This solution allows you to use more reliable and secure methods of data processing and transaction management within the organization. All these economic effects can lead to a reduction in costs and an increase in the efficiency of the police. In general, the use of blockchain technology in the police can have a number of advantages, such as increasing transparency and accountability, reducing data processing time and combating data falsification. However, it is necessary to take into account some risks, such as the possibility of data privacy violations, as well as difficulties in integrating with existing systems and training personnel. In general, the introduction of blockchain technology into the police requires careful analysis and an approach that takes into account all aspects of the use of technology and its impact on the organization.

Multi Container on Docker as a Support for IoT-Based Blockchain Electronic Transaction Systems

The use of blockchain as a supporting element in securing transactions is growing, as the presence of the blockchain system ensures enhanced security in the data transaction process. However, it should be noted that blockchain requires a more complex system for data verification. This complexity is not a concern when using paid blockchain services. However, when users aim to implement it privately, multiple nodes are needed for transaction verification. We present a proposed scheme for the use of multiple nodes utilizing Docker for transaction verification. This approach makes the costs more affordable and the maintenance easier.

A New Smart Contract Anomaly Detection Method by Fusing Opcode and Source Code Features for Blockchain Services

Digital assets involved in smart contracts are on the rise. Security vulnerabilities in smart contracts have resulted in significant losses for the blockchain community. Existing smart contract vulnerability detection techniques have been typically single-purposed and focused only on the source code or opcode of contracts. This paper presents a new smart contract vulnerability detection method, which extracts features from different levels of smart contracts to train machine learning models for effective detection of vulnerabilities. Specifically, we propose to extract 2-gram features from the opcodes of smart contracts and token features from the source code using a pre-trained CodeBERT model, thereby capturing the semantic information of smart contracts at different levels. The 2-gram and token features are separately aggregated and then fused and input into machine-learning models to mine the vulnerability features of contracts. Over 10,266 smart contracts are used to verify the proposed method. Widespread reentrancy, timestamp dependence, and transaction-ordering dependence vulnerabilities are considered. Experiments show the fused features can help significantly improve smart contract vulnerability detection compared to the single-level features. The detection accuracy is as high as 98%, 98% and 94% for the three vulnerabilities, respectively. The average detection time is 0.99 second per contract, indicating the proposed method is suitable for automatic batch detection of vulnerabilities in smart contracts.

Selection of a viable blockchain service provider for data management within the internet of medical things: An MCDM approach to Indian healthcare

Health 4.0 is gaining significant attention globally to support better treatment and care for people. Digital technologies such as the IoMT “(”Internet of Medical Things“”) and blockchain substantially promote quality health services. Literature shows that embedding blockchain in IoMT is an effective way to attain secure and quality healthcare. Selecting a viable blockchain service provider (BSP) becomes a complex task and can be considered an MCDM “(”Multi-Criteria Decision-Making“”) problem. Earlier studies on BSP selection indicate that complex expressions cannot be well-modelled and methodical estimation of decision parameters by capturing hesitation and interaction of entities is not adequately explored. Driven by the issues, authors put forward a novel MCDM framework with (i) a double hierarchy linguistic structure for data collection in natural expressions; (ii) regret measure for experts' reliability calculation; (iii) a weighted CRITIC approach for criteria weight determination, and (iv) CRADIS-Copeland algorithm for ranking BSPs. Finally, a case example from Recent Indian healthcare is exemplified to demonstrate the framework's applicability. Recently, the Indian healthcare sector launched initiatives/plans as part of Health 4.0 to promote data management for a better quality of treatment by seeking support from digital technologies such as IoMT and blockchains to ensure data privacy and improved customer experience. Sensitivity analysis and comparison with extant methods infer that (i) BC1, BC5, and BC3 are the top three BSPs for the considered problem; (ii) criteria such as privacy aspects, intercommunication capability, global accessibility, and total cost constitute 58% importance in the supposed decision problem; (iii) developed model reduces human intervention/biases; (iv) developed model is robust to weight alteration and yields unique rank orders with both personalised and cumulative ordering of BSPs; and (v) proposed model produces broader rank values that aid in effective backup planning.