In this paper, we aimed to build a quantitative investment trading model based on a combination of a multivariate cycle ARMA model and Apriori. We first note that in order to have a sound investment strategy, a forecast for the next trading day needs to be made. To do this, a basic time series forecasting model was first built to predict the value of gold and bitcoin for the next day based on the market volatility of the previous 40 days. The next step is developing a trading strategy model with a stable rate of return and some risk tolerance. At the same time, we developed a fixed stop-loss strategy to protect the strategy's stability and improve the risk resistance performance. Ultimately, using this model, we calculated that on 10 September 2021, we will have a return of $4816941 in Bitcoin and $1129.0503 in gold.
Abstract The Gaia-X project was initiated in 2019 by the German and French Ministers of Economy to ensure that companies would not lose control of their industrial data when it is hosted by non-EU cloud service providers. Since then, Gaia-X holds an international association presence in Belgium with more than 334 members, representing both users and providers across 20 countries and 16 national hubs and 5 candidate countries. The Association aims to increase the adoption of cloud services and accelerate data exchanges by European businesses through the facilitation of business data sovereignty with jointly approved (user and provider) policy rules on data portability and interoperability. Although for many enterprises, data sovereignty is seen as a prerequisite for using the cloud, a significant driver to boost the digital economy in business is incentivizing business data sharing. Two decades of cost optimization have constrained business value creation, driving many companies to neglect the opportunity to create shared value within a wider industry ecosystem. Now, thanks to the participation of large numbers of cloud users in the domains of Finance, Health, Energy, Automotive, Travel Aeronautics, Manufacturing, Agriculture, and Mobility, among others, Gaia-X is ideally positioned to help industries define appropriate data spaces and identify/develop compelling use cases, which can then be jointly deployed to a compliant-by-design platform architecture under the Gaia-X specifications, trust, and labeling frameworks. The creation of national Gaia-X hubs that act as independent think tanks, ambassadors, or influencers of the Association further facilitates the emergence of new data spaces and use/enabler cases at a country level, before these are subsequently extended to a European scope and beyond. Gaia-X partners share the view that data spaces will play a similar role in digital business as the web played 40 years ago to help the Internet take off. The Gaia-X Working Groups are at the core of the Gaia-X discussions and deliverables. There are three committees : the Technical, the Policies and Rules, and the Data Spaces and Business. The Technical Committee focus on key architectural elements and their evolution, such as and not limited to: Identity and Access Management: bridge the traditional X509 realm and new SSI realm, creating a decentralized network of identity federations Service Composition: how to assemble services in order to create new services with higher added value Self-Description : how to build digital trust at scale with measurable and comparable criteria The Policy and Rules Committee creates the deliverables required to develop the Gaia-X framework (compliance requirements, labels and qualification processes, credentials matrix, contractual agreements, etc.): The Labels and Qualification working group defines the E2E process for labels and qualification, from defining and evolving the levels of label, the process for defining new labels, and identifying and certifying existing CABS. The Credentials and Trust Anchors working group will develop and maintain a matrix of credentials and their verification methods to enable the implementation of compliance through automation, contractual clauses, certifications, or other methods. The Compliance working group collects compliance requirements from all sources to build a unique compliance requirements pool. The Data Spaces Business Committee helps the Association expanding and accelerating the creation of new Gaia-X service in the market: The Finance working group focuses on business modeling and supports the project office of the Association. The Technical working group analyzes the technical requirements from a business perspective. The Operational Requirements working group is the business requirements unit. The Hub working groups hold close contact with all Gaia-X Hubs and support the collection and creation of the Gaia-X use and business cases. These working groups maintain the international list of all use cases and data spaces and coordinate the Hubs.
Δαμιανός Π. Σακάς, Nikolaos T. Giannakopoulos, Νίκος Κανέλλος, Stavros P. Migkos
Nowadays, the cryptocurrency market is thriving, through the rise in cryptocurrency trading, opening the way for cryptocurrency trading websites’ optimization. Optimization of customer satisfaction is a vital part of cryptocurrency trade organizations’ digital marketing problems. It is vital to keep digital advertisement costs low while driving more traffic to a website. This study aims to define a digital marketing strategy for cryptocurrency trading websites by utilizing digital behavior metrics. Web analytics data were gathered from 10 world-leading cryptocurrency trade websites over 80 days. Statistical analysis of cryptocurrency trade web analytics, Fuzzy Cognitive Mapping modeling, and Agent-Based Model development have been deployed. Enhancement of cryptocurrency trade digital engagement levels can boost organizations’ SEO and SEM strategy campaigns. Outputs of the study provide a handful of insights regarding cryptocurrency trading websites’ digital promotion strategy optimization and the parameters of digital behavior mostly connected with websites’ digital marketing costs and traffic. Cryptocurrency trade organizations should utilize both organic and paid campaigns, observe regularly their website KPIs connected with visitors’ behavior and enhance their website users’ experience, by increasing their engagement.
Non-fungible tokens (“NFTs”) are an emerging digital asset that has captured global attention with multi-million-dollar price tags for seemingly basic pixelated JPEG files. In March 2021, British auction house Christie’s sold a digital artwork, ‘Everydays: The First 5,000 Days’, by artist Mike Winkelmann (“Beeple”) for the Ether equivalent of $69.3 million, making it the third-most expensive artwork by a living artist.1 Beeple’s sale was by no means alone—Sotheby's sold an NFT collection of 101 ‘Bored Apes’ for $24.4 million;2 CryptoPunk #7804, one of 10,000 unique ‘CryptoPunk’ NFTs sold for $7.56 million,3 and Twitter founder Jack Dorsey’s first-ever tweet sold for $2.9 million as an NFT.4 NFT sales in the first-half of 2021 have already exceeded $2.5 billion,5 and, as of October 2021, the total value of NFTs on the Ethereum blockchain is estimated to be at least $14.3 billion.6 On one hand, NFTs may be poised to revolutionize creative industries and drastically alter consumer interaction with digital media.7 On the other hand, the NFT market is simultaneously both ripe for speculative investment and vulnerable to criminal activity.8 To date, there appears to be no consensus on the regulation of NFTs, neither from the perspective of generally applicable laws, regulatory capture under existing financial market regulation, nor the implementation of new digital asset laws. This paper attempts to highlight several pertinent dangers of NFTs, from a profound misunderstanding of what an NFT transaction entails, their bubble-like pricing, to various criminal activity concerns. By illustrating how existing laws and regulations may not fully capture nor address these dangers, as well as the potential oversight of NFTs in newly proposed digital asset laws, this paper proposes a categorial approach to regulating NFTs, by reducing the current (and likely future) use-cases of NFTs to their constituent categories and in turn, suggesting the most appropriate regulatory approach to each. Ultimately, given the (potential) wide-ranging use-cases of NFTs, this paper proposes that the NFT’s intended use-case described in broad categorical terms, or more aptly, its underlying reference asset and simultaneous conveyance, or lack thereof, should dictate the regulatory approach.
The subject of the study. The effective functioning of decentralized autonomous organizations<br> (DAOs) is associated with moving from the digital level to the real level in order to find or provide<br> information and communicate with the real environment. Obtaining or transmitting necessary<br> information about certain real–world facts, or information from other digital databases that cannot<br> interact directly with the DAO, is provided through oracles as intermediaries between decentralized<br> databases and real–world events.<br> Results of work. In this article, we consider the oracle as a tool for collecting information for DAO,<br> able to ensure transition of information from the unstable and unsecured physical world in the digital<br> environment of blockchain technology, where information acquires new characteristics and values.<br> Oracle, as a tool with a function of information delivery, combines the functions of finding the necessary<br> information with the functions of ensuring the authenticity and encryption of data in the required format.<br> Conclusions. This article gives a general understanding of the concept of the oracle, and its<br> significance for the work of DAO, as well as development of digital projects built using blockchain<br> technology. Classification of oracles for work with DAO is also given together with characteristics of<br> their possible role for organization of data supply. In addition, the possibility of building a DAO with oracle<br> functions to perform non–standard tasks for the transportation and adaptation of information for<br> various purposes in a blockchain environment is considered. The article also presents main problems<br> that may arise in interactions of oracles with DAO, and suggests possible solutions.
This paper discusses the impact of e-governance powered by blockchain in the project and program management industry. With the rise in technological innovations, many countries have turned to e-governance for efficiency in service delivery, transparency, and decision-making. E-governance backed by blockchain technology entails improving the public services provision by implementing structures of information and communication technologies. There are many challenges with the traditional project management approach that causes organizations and its stakeholders’ cost and time. Thus, the introduction of blockchain has given many organizations a new approach to adopt in order to eliminate the challenges associated with the typical project management approach. In spite of the cutting-edge technology of blockchain and its broad applications in program management and e-governance, there are still many challenges that restrain its adoption on a broader scale. The research discusses the challenges of the blockchain deployment in the program management field and e-governance in private and government sectors and it highlights the efforts put by both sectors to make use of the technology. Also, the research covers the opportunities and the advantages of a blockchain adoption in various segments. The paper uses various case studies in the UAE, in both private and government sectors, and a qualitative research approach was implemented. The case studies were on government entities such as Smart Dubai and the Ministry of Health Prevention and also private entities like DP World and Emirates NBD. The paper concludes with recommendations and solutions on how to maximize the benefit of blockchain in the program management industry and how it is improving the decision-making process.
Sebastian Beckschulte, Louis Huebser, Raphael Kiesel, Robert Schmitt
This paper describes the utilization of Distributed Ledger Technology (DLT) as means of a digital backbone – the so-called digital vehicle protocol – across the commercial vehicle industry. Enabling a digital vehicle protocol along the value chain resolves common data management problems, which are still the main inhibitor for advanced analytics methods and serves as a basis for new business models. This contribution demonstrates a per product-data centered approach in which low structured data can be written to and read from any point along the value chain on a product unit-based scope by using DLT. By embedding data post-processing pipelines per product-unit, data easily can be retrofitted to the task at hand. Therefore, it decouples data post-processing from data generation as well as overcoming current data silos within organizations. DLT hereby allows tying processing routines to data leading to a temper-proof digital vehicle protocol. Besides obtaining a stronger product-individual focus, our approach enables an easier integration of stakeholders into the entire business process landscape such as suppliers as well as sellers and leads to future business models such as billing depending on quality defects found during production. Our conceptual framework resolves current problems, i.e. data access, data quality and data processing costs. We align conceptual applicability with regards to a Truck Original Equipment Manufacturer (OEM) within the scope of failure management in production in order to specify implementation details, which reveal new business process models that further can transform commercial vehicle manufacturers from producers to service providers.
Nowadays, business enactments almost exclusively focus on human-to-human business transactions. However, the ubiquitousness of smart devices enables business enactments among autonomously acting machines, thereby providing the foundation for the machine-driven Machine-to-Everything (M2X) Economy. Human-to-human business is governed by enforceable contracts either in the form of oral, or written agreements. Still, a machine-driven ecosystem requires a digital equivalent that is accessible to all stakeholders. Additionally, an electronic contract platform enables fact-tracking, non-repudiation, auditability and tamper-resistant storage of information in a distributed multi-stakeholder setting. A suitable approach for M2X enactments are electronic smart contracts that allow to govern business transactions using a computerized transaction protocol such as a blockchain. In this position paper, we argue in favor of an open, decentralized and distributed smart contract-based M2X Economy that supports the corresponding multi-stakeholder ecosystem and facilitates M2X value exchange, collaborations, and business enactments. Finally, it allows for a distributed e-governance model that fosters open platforms and interoperability. Thus, serving as a foundation for the ubiquitous M2X Economy and its ecosystem.
This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovation breakthroughs. The potential value of data sharing across industrial domains is estimated at over $100 billion, particularly in view of optimising manufacturing processes. Data sharing across domains however faces a series of well-documented challenges associated with the lack of semantic interoperability and related standards, management of trust and sustainability. Solving bottlenecks in data sharing requires a systemic approach to data management, which can account for all aspects of data use, levels of application, attribution and dynamic exchanges. In this paper we propose a high-level ecosystem approach that integrates societal values with digital affordances of industry’s cognitive-assisted processes, remote interfacing, hybrid applications and large-scale value networks. Early development of an Ontology Commons EcoSystem (OCES) is presented as the key enabling framework for Industry Commons interoperability and a series of enabling frameworks form the basis of future research directions in Trusted Data Sharing and Closed-Loop Lifecycle Management for greater sustainability.Abbreviations: AI – Artificial Intelligence; AIOTI – Alliance of Internet-of-Things Innovation; ALM – Asset Lifecycle Management; ALO – Application-Level Ontology; AP – Application Protocol; API – Application Programming Interface; B2B – Business-to-Business; B2C – Business-to-Customer; CDE – Cross-Domain Ecosystem; CDEI – Cross-Domain Ecosystem Interoperability; CL2M – Closed-Loop Lifecycle Management; CNO – Collaborative Networked Organisations; CPS – Cyber-Physical Systems; CSR – Corporate Social Responsibility; DLO – Domain-Level Ontology; DLT – Distributed Ledger Technology; EM – Enterprise Modelling; FAIR – Findable, Accessible, Interoperable and Reusable; GUI – Graphical User Interface; ICE, Industry Commons Ecosystem; IOF – Industrial Ontology Foundry; IP – Intellectual Property; IPR – Intellectual Property Rights; ISN – Intertwined Supply Network; MIR – Music Information Retrieval; MLO – Middle-Level Ontology; MO – Meta-Ontology; OCES – Ontology Commons EcoSystem; PI – Physical Internet; PLM – Product Lifecycle Management; ROI – Return-on-Investment; SC – Supply Chain; SCM – Supply Chain Management; SOS – System-of-Systems; TDS – Trusted Data Sharing; TLO – Top-Level Ontology; TRO – Top Reference Ontology; TUI – Tangible User Interface.
Purpose: The aim of the paper is (1) to analyze the DARQ (Distributed ledger, Artificial Intelligence, Extended Reality, Quantum Computing) technology in terms of its implementations and (2) to compare these technologies with the SMAC technology (Social, Mobile, Analytics, Cloud). We present the thesis that DARQ technologies can help in building information systems aimed at both predicting and monitoring global crises. We argue that the DARQ technology will support the management of network organizations in the first period of development. Design/methodology/approach: The research procedure consists of the following steps: literature analysis, conducting qualitative research and its presentation, obtaining expert opinions and recommendations for further research. Findings: The results of work on the DARQ technology that supports management systems allowed for the evaluation of usability both in terms of the expected effects and the areas of risk of application. Research limitations/implications: Due to the lack of practical applications of all the elements that make up the DARQ technology, the analysis of such components as Extended Reality (Virtual Reality), Quantum Computing (Virtual Computing Technology) is not complete and requires complementary research and a more complete analysis of its applications. We consider the presented work as an introduction to broader research. Originality/value: The thesis has been substantiated that the transition from SMAC to DARQ technology can be done gradually. Both of these technologies are compatible. This may result in gradual and collision-free changes in the quality of the management system. Elements of the new DARQ technology, such as Distributed ledger, Artificial Intelligence, Extended Reality and Quantum computing, allow for abrupt changes in both the management system and the functioning of the organization. Already today, each component of the DARQ technology has a significant impact on various sectors of the economy. However, it should be noted that apart from the positives, the DARQ technology also poses some threats. The article contains conclusions from the research and indicates a recommendation for further work, which concerns extending the application of DARQ technology to predict and monitor disasters and unpredictable events. To this end, we analyze the Black Swan theory (based on the COVID-19 pandemic case study) as the theoretical framework for the use of DARQ technology as a tool to reduce the occurrence of unpredictable events.
Natalia A. Van Heerden, Juan Cabral, Nadia Luczywo
In recent years, cryptocurrencies have gone from an obscure niche to a prominent place, with investment in these assets becoming increasingly popular. However, cryptocurrencies carry a high risk due to their high volatility. In this paper, criteria based on historical cryptocurrency data are defined in order to characterize returns and risks in different ways, in short time windows (7 and 15 days); then, the importance of criteria is analyzed by various methods and their impact is evaluated. Finally, the future plan is projected to use the knowledge obtained for the selection of investment portfolios by applying multi-criteria methods.
Yang Li, Biaoan Shan, Beiwei Li, Xiaoju Liu · 5 authors
The emergence of machine learning (ML) and blockchain (BC) technology has greatly enriched the functions and services of healthcare, giving birth to the new field of "smart healthcare." This study aims to review the application of ML and BC technology in the smart medical industry by Web of Science (WOS) using bibliometric visualization. Through our research, we identify the countries with the greatest output, the major research subjects, funding funds, and the research hotspots in this field. We also find out the key themes and future research areas in application of ML and BC technology in healthcare area. We reveal the different aspects of research under the two technologies and how they relate to each other around five themes.
S. Hanumanth Sastry, Teck Heang Lee, MELISSA TENG TENK TEOH
Technologies such as blockchain technology and data analytics are causing major disruptions in various other professions and the audit profession will be no different in due time. The main aim of the study is to look at whether these technologies of blockchain and data analytics will assist the auditors in the various audit processes such as obtaining sufficient appropriate audit evidence, detection of fraud and exercising professional judgment. This study also aims to identify the future direction that the audit profession is heading with the introduction of these technologies and the potential skills that auditors would require in the upcoming years. Data was collected by the researcher in the form of primary data by conducting interviews. 12 auditors were interviewed. The data collected was analyzed using thematic analysis and the findings are presented accordingly to solve the research objectives. From the study, most respondents believe that these two technologies will assist the auditors in these audit processes in various ways. The study also shows that the auditors would have to equipped with skills such as IT related skills to stay relevant in the audit profession which is transforming to a technological/data driven profession.
Usage of technology to help finance audit process is not a new instance. But since the rise of 4th industrial revolution and emergence of smart technology relatively in a short period of time, adopting technology have its challenges and drawbacks. Data Integrity has been an issue for finance audit process because digital data is easy to tamper. This condition makes audit process become difficult and potential of audit fraud is high. In this study we would like to explore usage blockchain technology as future database engine for AIS. Blockchain as a technology relatively unheard before cryptocurrency albeit its advanced technology in data storage to ensure data integrity. We will explore the advantages and risk in adopting blockchain as well as current state of academics and technology regarding blockchain adoption.
Big Data is mixed with huge, autonomous sources like decentralized and distributed control system. For organizations that use the conventional data processing mechanism to handle and archive these large data sets, these capabilities pose an extreme obstacle. A new model has to be defined and the existing framework must be re-evaluated for the analysis and management of big data. The word Business Intelligence (BI) applies to applications, technology and activities for commercial knowledge gathering, review, incorporation and presentation. Business Intelligence’s primary aim is to facilitate quicker and stronger business decision-making process.” Therefore, the strategic review of the literature must study the trend of Information System (IS) adoption factors as a well-designed strategic diagnostic tool that can be used for essential decision-making systems to enable more effective and reliable action plans. We started with discussing some frameworks required for strategic excellence by examining the potential approaches of Big Data Analytics (BDA) and Business Intelligence (BI). In the end, we would design an integrated application that functions as an organization's strategic performance management diagnostic tool. “In general, the emphasis and reach are on the corporate decision-making mechanism, there are some specifics on the analysis, but every conceivable tool and instrument is not specified, the concept is sufficiently concrete to assist in the creation of steps. This research paper therefore examines the position of the system for big data analytics and market intelligence.
Ifeoluwa Oreofe Oluwafemi, T. Prabhakar Clement, Oluwasanmi Segun Adanigbo, Toluwase Peter Gbenle · 5 authors
The global pharmaceutical industry faces growing threats from counterfeit and substandard drugs, undermining public health, regulatory compliance, and supply chain trust. To address these challenges, this paper evaluates the efficacy of DIDChain-enabled blockchain frameworks, which integrate Decentralized Identifiers (DIDs) with distributed ledger technology to establish real-time provenance verification and anti-counterfeit control. Drawing on a comprehensive body of literature, including conceptual frameworks in digital transformation, cybersecurity, business intelligence, and cloud-based analytics, the study explores how DIDChain infrastructure can enhance transparency, immutability, and interoperability in pharmaceutical logistics. The analysis incorporates findings from prior research on AI-driven fraud detection, supply chain resilience, and data governance models, particularly those applied in the financial, energy, and SME sectors. The evaluation highlights the role of DIDChain in supporting secure product authentication, automated compliance auditing, and cross-border regulatory coordination. This research contributes to emerging discourse on digital trust technologies, offering a scalable and interoperable solution for ensuring drug integrity in complex and globalized pharmaceutical ecosystems.
Abstract The current, fast market changes require enterprises to dynamically adapt the way they conduct their business. This poses many challenges for information technology. Market requirements for immediate response to business changes became the basis of the idea of a real-time information processing (RTE) company. RTE provides real-time information to employees and business partners. Integrated IT systems supporting management constitute a common platform – the foundation of a real-time enterprise. The aim of the article is to present the basic problems of building an IT system that is the basis of a real-time information processing (RTE) company. It is a summary of our work on this type of system. The article justifies the thesis about the need to build a system for the RTE's requirements and the conditions of its implementation. Such a system is designed to provide employees and business partners with the information they need in real time. The use of integrated systems such as ERP, CRM, SCM, and so on provides the ability to implement the main business processes of a real-time enterprise. The article presents both literature analysis and the characteristics of own work on designing IT systems for RTE. Particular attention was paid to the analysis of success factors (determinants) in system design and the use of MUST methodology (MUST is a Danish acronym for theories of and methods for design activities). The final part of the article presents a proposal for further work on IT systems for RTE in the context of existing trends such as DARQ technology (Distributed Ledger, Artificial Intelligence, Extended Reality, Quantum computing).
Befekadu G. Gebraselase, Bjarne E. Helvik, Yuming Jiang
Bitcoin has become the leading cryptocurrency system, but the limit on its transaction processing capacity has resulted in increased transaction fees and delayed transaction confirmation. As such, it is pertinent to understand and probably predict how transactions are handled by Bitcoin such that a user may adapt the transaction requests and a miner may adjust the block generation strategy and/or the mining pool to join. To this aim, the present paper introduces results from an analysis of transaction handling in Bitcoin. Specifically, the analysis consists of two-part. The first part is an exploratory data analysis revealing key characteristics in Bitcoin transaction handling. The second part is a predictability analysis intended to provide insights on transaction handling such as (i) transaction confirmation time, (ii) block attributes, and (iii) who has created the block. The result shows that some models do reasonably well for (ii), but surprisingly not for (i) or (iii).
Nowadays, data are generated in a continuous streaming manner as the inputs of various applications. The sources of such generated data can be wired or wireless sensor networks commonly used in various fields of geographical, traffic, Internet of Things (IoT), financial tickers, Web2 and Web3, e-commerce, social networks, and online communities. The high volume, high variety, and high velocity of data have recently posed the challenge of 3Vs to this field, also known as the Big Data Problem. The 3Vs dimensions of complexities for the big data entails high-speed storage, scalability of database systems, suitable data models, real-time responsiveness and so on. Data model, as the representation schema of data is an essential issue since many others (e.g., DBMS systems’ design, DB languages, etc.) rely on. So, the study of data models is a key and fundamental aspect in structuring, organizing, storing, and manipulating big data. It is also the essence in various areas of cloud migration, web-scale, and so forth. In this paper, we have systematically reviewed different types of data models, the rationale behind them, their applications and support capabilities, and the technologies to switch from one model to another. To address the user needs in various fields, a systematic review method is adopted to classify and present different types and characteristics of data models.
Today’s world is increasingly dependent on technology directly or indirectly. The rapid technological advancement has impacted people to adopt the technology. As cryptocurrency recently commenced, few studies have attempted to investigate this use of technology. In this study, the technology readiness aspects- Optimism, Innovativeness, Discomfort, and Insecurity are used to understand the people’s adoption of cryptocurrency. A multi-approach of Partial Least Squares- Structural Equation Modeling (PLS-SEM) and Deep learning Artificial Neural Network (ANN) analysis was performed. Deep learning Artificial Neural Network (ANN) analysis was performed to complement PLS-SEM findings and predict higher accuracy. This study shows that technology readiness dimensions - Optimism, Innovativeness, Discomfort, and Insecurity have meaningful relationships with cryptocurrency adoption.