Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
9.5
5.1
Journals
JTAER
Special Issues
Blockchain Business Applications and the Metaverse
share announcement

Blockchain Business Applications and the Metaverse

A special issue of Journal of Theoretical and Applied Electronic Commerce Research (ISSN 0718-1876).

Deadline for manuscript submissions: 20 May 2025 | Viewed by 3621

Special Issue Editor

Dr. Rand Low

E-Mail Website
Guest Editor
1. Bond Business School, Bond University, Gold Coast 4226, Australia
2. UQ Business School, University of Queensland, Brisbane 4072, Australia
Interests: portfolio optimization; market risk; dependence modelling; copulas; pairs trading
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, “Blockchain Business Applications and the Metaverse”, delves into the transformative potential of blockchain technology and its synergy with the burgeoning metaverse. This collection of articles offers a comprehensive exploration of how blockchain is revolutionizing various business sectors by enhancing transparency, security, and efficiency. The integration of blockchain with the metaverse—a fully immersive digital universe—presents unprecedented opportunities for innovation across industries such as finance, real estate, healthcare, non-for-profit, entertainment, and supply chain management.

Contributors to this issue provide insightful analyses and case studies demonstrating how decentralized ledgers are being employed to create trustworthy virtual environments, facilitate seamless digital asset transactions, and establish decentralized governance models. The fusion of these technologies promises to redefine user interactions, digital ownership, and the overall economic landscape.

Furthermore, this issue examines the challenges and regulatory considerations that accompany these advancements, providing a balanced perspective on the potential pitfalls and strategies for mitigation. By presenting cutting-edge research and expert opinions, “Blockchain Business Applications and the Metaverse” aims to inform and inspire stakeholders, paving the way for innovative applications that could reshape the future of digital business and virtual experiences.

Dr. Rand Low
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Theoretical and Applied Electronic Commerce Research is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • blockchain
  • metaverse
  • cryptocurrency
  • Ethereum

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 3678 KiB  
Article
Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology
by Jikuan Xu, Jiamin Zhang and Junhan Wang
J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 76; https://doi.org/10.3390/jtaer20020076 - 18 Apr 2025
Viewed by 309
Abstract
The issue of image copyright infringement is prevalent in current e-commerce activities. Users employ methods such as image cropping, compression, and noise addition, making it difficult for traditional copyright detection technologies to identify and track infringements. This study proposes an image copyright registration, [...] Read more.
The issue of image copyright infringement is prevalent in current e-commerce activities. Users employ methods such as image cropping, compression, and noise addition, making it difficult for traditional copyright detection technologies to identify and track infringements. This study proposes an image copyright registration, protection, and management method based on artificial intelligence and blockchain technology, aiming to address the current challenges of low accuracy in digital copyright infringement judgment, the vulnerability of image fingerprints stored on the chain to tampering, the complexity of encryption algorithms and key acquisition methods through contract calls, and the secure storage of image information during data circulation. The research combines artificial intelligence technology with traditional blockchain technology to overcome the inherent technical barriers of blockchain. It introduces an originality detection model based on deep learning technology after conducting both off-chain and on-chain detection of unidentified images, providing triple protection for digital image copyright infringement detection and enabling efficient active defense and passive evidence storage. Additionally, the study improves upon the traditional image perceptual hashing in blockchain, which has poor robustness, by adding chaotic encryption sequences to protect the image data on the chain, and its effectiveness has been verified through experiments. Ultimately, the research hopes to provide e-commerce entities with an effective and feasible digital copyright protection and management solution, safeguarding their intellectual property rights and fostering a legal and reasonable competitive environment in e-commerce. Full article
(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)
►▼ Show Figures

Figure 1

25 pages, 7161 KiB  
Article
Automated Runtime Verification of Security for E-Commerce Smart Contracts
by Yang Liu, Shengjie Zhang and Yan Ma
J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 73; https://doi.org/10.3390/jtaer20020073 - 13 Apr 2025
Viewed by 314
Abstract
As a novel decentralized computing paradigm, blockchain is expected to disrupt the existing e-commerce architecture and process. Secure smart contracts are the crucial foundation for e-commerce based on blockchain. However, vulnerabilities in smart contracts occur from time to time and cause significant financial [...] Read more.
As a novel decentralized computing paradigm, blockchain is expected to disrupt the existing e-commerce architecture and process. Secure smart contracts are the crucial foundation for e-commerce based on blockchain. However, vulnerabilities in smart contracts occur from time to time and cause significant financial losses in e-commerce. Some static verification methods have been developed to guarantee security for e-commerce smart contracts at design time, but they cannot support complex scenarios at runtime. As a lightweight verification method, runtime verification is a potential method for secure e-commerce smart contracts. The existing runtime verification methods are based on the manual instrument, which leads to additional overheads and gas consumption. To deal with this, we propose a passive learning-based runtime verification framework for e-commerce smart contracts. Firstly, by exploring the Genetic algorithm to evolve state merging and automaton reorganizing in order to simultaneously split time and gas behaviors, we propose a passive learning method to model runtime information for e-commerce smart contracts (PL4ESC). It directly learns P2TA (priced probabilistic timed automaton) from runtime traces without any prior knowledge. Then, we integrate PL4ESC with the open-source PAT (Process Analysis Toolkit) to automatically verify the security of runtime e-commerce smart contracts. The experiments show that PL4ESC is better at accuracy and precision than state-of-the-art passive learning methods. It improves accuracy by 1 to 4 percent compared to TAG and RTI+. As far as we know, it is not only the first learning method that can learn a P2TA from traces, but it is also the first automated runtime verification framework for e-commerce smart contracts. This will provide security guarantees for blockchain-based e-commerce. Full article
(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)
►▼ Show Figures

Figure 1

25 pages, 659 KiB  
Article
Market Phases and Price Discovery in NFTs: A Deep Learning Approach to Digital Asset Valuation
by Ho-Jun Kang and Sang-Gun Lee
J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 64; https://doi.org/10.3390/jtaer20020064 - 3 Apr 2025
Viewed by 404
Abstract
This study introduces the Channel-wise Attention with Relative Distance (CARD) model for NFT market prediction, addressing the unique challenges of NFT valuation through a novel deep learning architecture. Analyzing 26,287 h of transaction data across major marketplaces, the model demonstrates superior predictive accuracy [...] Read more.
This study introduces the Channel-wise Attention with Relative Distance (CARD) model for NFT market prediction, addressing the unique challenges of NFT valuation through a novel deep learning architecture. Analyzing 26,287 h of transaction data across major marketplaces, the model demonstrates superior predictive accuracy compared to conventional approaches, achieving a 33.5% reduction in Mean Absolute Error versus LSTM models, a 29.7% improvement over Transformer architectures, and a 30.1% enhancement compared to LightGBM implementations. For long-term forecasting (720-h horizon), CARD maintains a 35.5% performance advantage over the next best model. Through SHAP-based regime analysis, we identify distinct feature importance patterns across market phases, revealing how liquidity metrics, top trader activity, and royalty dynamics drive valuations in bear, bull, and neutral markets respectively. The findings provide actionable insights for investors while advancing our theoretical understanding of NFT market microstructure and price discovery mechanisms. Full article
(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)
►▼ Show Figures

Figure 1

17 pages, 1861 KiB  
Article
Inspection as a Service Business Model for Deploying Non-Destructive Inspection Solutions Within a Blockchain Framework
by Joan Lario, Marcos Terol, Begoña Mendizabal and Noel Tomas
J. Theor. Appl. Electron. Commer. Res. 2025, 20(1), 52; https://doi.org/10.3390/jtaer20010052 - 18 Mar 2025
Viewed by 371
Abstract
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 [...] Read more.
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
(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)
►▼ Show Figures

Figure 1

30 pages, 975 KiB  
Article
Using Blockchain Technology to Combat Counterfeits: The Optimal Pricing Scheme of Two Competitive Platforms
by Jizi Li, Xiaodie Wang, Longyu Li and Dangru Zhao
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 3253-3282; https://doi.org/10.3390/jtaer19040158 - 23 Nov 2024
Cited by 1 | Viewed by 1298
Abstract
This paper investigates using blockchain technology to fight deceptive counterfeits in an electronic commerce environment. Thereby, a two-period pricing model is built under two competitive platforms: a blockchain-based platform which ensures product authentication and provides a higher value to customers but increases customers’ [...] Read more.
This paper investigates using blockchain technology to fight deceptive counterfeits in an electronic commerce environment. Thereby, a two-period pricing model is built under two competitive platforms: a blockchain-based platform which ensures product authentication and provides a higher value to customers but increases customers’ privacy concerns, and its rival (i.e., the traditional platform) in the absence of blockchain implementation which is perceived as having a lower value due to the existence of deceptive counterfeits and thus faces more government enforcement. Customers on both platforms are influenced by the electronic word-of-mouth (eWOM) effect, and customers value a platform more if the platform has more online sales. The two platforms either adopt the fixed pricing scheme or the modifiable pricing scheme and so four possible cases may occur. By deriving the equilibrium of each possible case, we analytically find that the attenuation of consumer privacy concerns, increases in government enforcement efforts, and eWOM can benefit the platform’s adoption of blockchain technology to combat counterfeits, and a strong eWOM effect is conducive to consumers but deteriorates price competition and thus harms both platforms. Whether the pricing schemes enhance the competitiveness of the blockchain-based platform over its rivals depends on the eWOM effect and the advantage gained from adopting blockchain technology. Full article
(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop