Cases of introducing token economy in designs of ICT services are increasing. Users in the early stages of the service are expected to participate in and be active in the service by expecting future price increases in that cryptocurrency. However, the volatility of cryptocurrencies is always intense, and the large volatility may cause users to be more interested in price changes than service activities, which diminishes the incentives for the service activities. In this study, in order to dampen the volatility of cryptocurrencies at the initial stage of their service launch, we assume the case where the service providers make bids to suppress the price changes based on the funds obtained from ICO, and conduct analysis using simulations in artificial market. In order to reproduce the actual price movement in the artificial market, we built an agent model that has the same stylized facts as the price movement of newly listed cryptocurrencies. Then, we introduced a price stabilization agent, and obtained a parameter set that reduces price volatility while suppressing the change in the slope of a simple linear regression compared to the original state using an optimization method. As a result, by introducing the price stabilization agent, we found a parameter set that can reduce the standard division of percentage changes by about 14% from the original price movement, and keep the slope of the simple linear regression trend at a 3.5% change.
Recently, the application of blockchain to the setting, management, and trading of the energy system has formed an innovative technology and has attracted a lot of attention from industry, academia, and research. In this study, we use patent analysis technology to explore the development trends of the energy system with blockchain technology. During the patent analysis process, this study makes corresponding analysis charts, such as patent application numbers over time, patent application numbers for main leading countries, applicants, patent citations, international patent classification (IPC), and life cycle. Relative research and design (R&D) capability of the top ten applicants is estimated and the cluster map of the technology is obtained. The technical features of the top five IPC patent applications are related to the cluster map to show the development of energy blockchain technology. Through this paper, first, the basics of the blockchain and patent analysis are illustrated and, moreover, the reason why and how blockchain technology can be combined with the energy system is also briefly described and analyzed. The results of the patent analysis of energy blockchain technology indicate that the United States leads the way, accounting for more than half of the global total. It is also interesting to note that the participants are not from traditional specific fields, but included electric power manufacturers, computer software companies, e-commerce companies, and even many new companies devoted to blockchain technology. Walmart Apollo, LLC and International Business Machines Corporation (IBM) have the highest number of patent applications. However, Walmart Apollo, LLC ranks first with a greater number of inventors of 36, an activity year of 2 years, and a relative R&D capability of 100%. IBM ranks second with an activity year of 3 years and a research and development capability of 91%. Among various applicants, IBM and LO3 energy started earlier in this field, and their patent output is also more prominent. The IPC is mainly concentrated in G06Q 50/06, which belongs to the technical field of the setting and management of the energy system including electricity, gas, or water supply. Currently, most projects are in the early development stages, and research on key areas is still ongoing to improve the required scalability, decentralization, and security. Thus, energy blockchain technology is still in the growth period, and there is still considerable room for development of the patent in the later period. Moreover, it is suggested that the novel communication module such as the combination of the consortium blockchain and the private blockchain cold also provide their own advantages to achieve the purpose of improving system performance and efficiency.
Tobias Riasanow, Lea Jäntgen, Sebastian Hermes, Markus Böhm · 5 authors
Abstract Digital transformation is continuously changing ecosystems, which also forces established companies to re-evaluate their value proposition. However, only transformations of single ecosystems have been studied. Therefore, this work targets to examine the similarities of digital transformation in five platform ecosystems: automotive, blockchain, financial, insurance, and IIoT. For our analysis, we combine the strengths of conceptual modeling using e3 value with a cluster analysis based on text mining to identify similarities in the respective ecosystems. As a result, we identified 15 clusters. Cluster 01 is the core cluster, containing the roles of organizations from all five ecosystems. Cluster 02–05 are intertwined, as they include roles from at least two ecosystems. Clusters 06–15 are ecosystem-specific that only include roles found in one ecosystem. Scholars and practitioners can use these clusters when analyzing or building a new platform ecosystem, or transforming a traditional ecosystem towards a platform ecosystem.
This paper suggests a model for optimization of societal carbon footprints one person at a time through the decentralization of electricity use and accounting. Our model describes steps involved with developing a decentralized accounting system considering electricity as a "credit product". While describing the basic characteristics of both schemes, we also emphasize capabilities of the proposed model for reducing carbon footprints from other societal choices, for example, purchasing water (energy-water nexus), managing waste, or designing sustainable transportation systems. A simple yet complex model involved with familiar societal financial systems' rules and routines is proposed for achieving a resilient, sustainable, and prosperous future. The proposed model calls for creating a dynamic society (as a system) that can be efficiently adopted to take on challenges threatening the function, survival, and future developments of the societies.
In econophysics, statistical-physics techniques are used to model economical systems. In this thesis, we investigate the entropy and the Computational Information Density (CID) of the Bitcoin blockchain. The CID is defined as the compression ratio of some particular algorithm when applied to the raw data of the state of the system. It is related to entropy as both CID and entropy are measures of information.\nWe find a strong correspondence between the CID and entropy for the Bitcoin blockchain, where features are similar, but without one being a clear function of the other. This can be explained by intercorrelations between one agent and the next, which the entropy does not count. We also calculate some correlations to see if the CID and the entropy have some predictive power for the price, and we find a small correlation, but very small in comparison to the predictive power of the price itself.\nThese results the power of the CID-entropy correspondence and how the Bitcoin blockchain may be used as a useful large-scale toy model for econophysics. We anticipate that these results can be used for a further look into the CID-entropy relation, as the similarities are visible but there is no exact correspondence. Besides this, these results can form a basis for a further look into the predictive power of the CID or the entropy for the price.
Kepler Concordia, a new scientific and musical instrument enabling players to explore the solar system and other data within immersive extended-reality (XR) platforms, is being designed by a diverse team of musicians, artists, scientists and engineers using audio-first principles. The core instrument modules will be launched in 2019 for the 400th anniversary of Johannes Kepler's Harmonies of the World, in which he laid out a framework for the harmony of geometric form as well as the three laws of planetary motion. Kepler's own experimental process can be understood as audio-first because he employed his understanding of Western Classical music theory to investigate and discover the heliocentric, elliptical behaviour of planetary orbits. Indeed, principles of harmonic motion govern much of our physical world and show up at all scales in mathematics and physics. Few physical systems, however, offer such rich harmonic complexity and beauty as our own solar system. Concordia is a musical instrument that is modular, extensible and designed to allow players to generate and explore transparent sonifications of planetary movements rooted in the musical and mathematical concepts of Johannes Kepler as well as researchers who have extended Kepler's work, such as Hartmut Warm. Its primary function is to emphasise the auditory experience by encouraging musical explorations using sonification of geometric and relational information of scientifically accurate planetary ephemeris and astrodynamics. Concordia highlights harmonic relationships of the solar system through interactive sonic immersion. This article explains how we prioritise data sonification and then add visualisations and gamification to create a new type of experience and creative distributed-ledger powered ecosystem. Kepler Concordia facilitates the perception of music while presenting the celestial harmonies through multiple senses, with an emphasis on hearing, so that, as Kepler wrote, ‘the mind can seize upon the patterns’.
The possibility of constructing dynamic measures of complexity as quantum econophysical behaving in a proper way during actual pre-crash periods has been shown. This fact is used to build predictors of crashes and critical events phenomena on the examples of all the patterns recorded in the time series of the key cryptocurrency Bitcoin, the effectiveness of the proposed indicatorsprecursors of these falls has been identified. From positions, attained by modern theoretical physics the concept of economic Plank's constant has been proposed.
Bitcoin represents one of the most interesting technological breakthroughs and socio-economic experiments of the last decades. In this paper, we examine the role of speculative bubbles in the process of Bitcoin's technological adoption by analyzing its social dynamics. We trace Bitcoin's genesis and dissect the nature of its techno-economic innovation. In particular, we present an analysis of the techno-economic feedback loops that drive Bitcoin's price and network effects. Based on our analysis of Bitcoin, we test and further refine the Social Bubble Hypothesis, which holds that bubbles constitute an essential component in the process of technological innovation. We argue that a hierarchy of repeating and exponentially increasing series of bubbles and hype cycles, which has occurred over the past decade since its inception, has bootstrapped Bitcoin into existence.
Osama Sohaib, Walayat Hussain, Muhammad Asif, Muhammad Ahmad · 5 authors
The majority of previous research on new technology acceptance has been conducted with single-step Structural Equation Modeling (SEM) based methods. The primary purpose of the study is to enhance the new technology acceptance based research with the Artificial Neural Network (ANN) method to enable more precise and in-depth research results as compared to the single-step SEM method. This study measures the relation between technology readiness dimension (optimism, innovativeness, discomfort, insecurity) and the technology acceptance (perceived ease of use and perceived usefulness) - and the intention to use cryptocurrency, such as bitcoin. The contribution of this study include the use of a multi-analytical approach by combining Partial Least Squares- Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. First, PLS-SEM was applied to assess which factor has significant influence toward intention to use cryptocurrency. Second, an ANN was employed to rank the relative influence of the significant predictor variables attained from the PLS-SEM. The findings of the two-step PLS-SEM and ANN approach confirm that the use of ANN further verifies the results obtained by the PLS-SEM analysis. Also, ANN is capable of modelling complex linear and non-linear relationships with high predictive accuracy compared to SEM methods. Also, an Importance-Performance Map Analysis (IPMA) of the PLS-SEM results provides a more specific understanding of each factor's importance-performance.
With the advancement of digitization, digital ecosystems are playing an increasingly important role in value creation. The mechanism by which digital ecosystems create value, however, has been generally deemed to be a mixed effect due to various factors. On the basis of signaling theory, this paper explores the effect of information transmission on the value creation capability of a digital ecosystem from two dimensions: the scale and sustainability of value creation. Taking a sample of weekly transaction data from Ethereum during August 2015–August 2018, our research proposes an integrated framework of information transmission in value creating, and discusses the diffusion process of the network effect within the digital ecosystem. As a generally accepted exchange medium, digital currency traffic acts as an observable proxy of information flow in a crypto-digital ecosystem, where the effects of heterogeneity in transaction attributes are filtered. Empirical results show that information transmission positively influences the scale and sustainability of value creation activities in a digital ecosystem by affecting user number and transaction frequency. Further research reveals that user number is the initial driving force of the network effect and a critical factor for the overall ecosystem market capitalization. This research provides a new insight into the design of sustainable value creation mechanisms under digital circumstances.
Purpose The purpose of this paper is to examine users’ decision-making mechanism of speculative investment behavior and its sequential consequences in the Bitcoin context from a dual-systems perspective. Design/methodology/approach Original data were collected via a survey of 334 participants with experience in Bitcoin speculative investment. The partial least squares method was used to test the proposed model. Findings Speculative investment behavior in the Bitcoin context is driven by strong impulse and weak self-control, leading to negative consequences. The extent of the imbalance between the two cognitive systems is greater with the subjective norm than without it, thus facilitating speculative investment behavior. Noteworthy differences in the impulse and self-control effects on Bitcoin speculative investment are found with differences in Bitcoin objective and subjective knowledge. Originality/value This study is the first attempt to empirically investigate users’ decision-making mechanism used when speculating in Bitcoin.
Purpose Given that Blockchain technology poses a growing challenge to the banking industry, this paper aims to analyse the innovation of Blockchain banking with regard to its systemic dimension, as well as dynamics of competition. The empirical research demonstrates how the systemic characteristics of Blockchain banking relate to the pursuit of strategies and to what extent these strategies influence the directional path and level of technology diffusion. Design/methodology/approach The research study uses a case study methodology to explore the strategic competition of Blockchain banking. The study proposes the systemic innovation model for analysing and tracking the path of innovations. The model can be applied to any industry to understand the process of innovation development and the strategies to win market share in the banking industry. This research makes a contribution towards the theory of technology diffusion to understand the directional path of innovations. Findings The analyses of findings reveal the situation whereby most banks still compete to create their own Blockchain banking systems. The analyses, based on the systemic innovation model, also shows the low systemic feature of Blockchain banking at present. From the technology diffusion perspective, the future of Blockchain banking may need cross-chain interoperability to support a full spectrum of payments and value exchanges on the internet of things. Originality/value The main contribution of this paper is the systemic analysis of the latest innovation of Blockchain banking. Given that the research also includes the major banking innovation cases of ATM/cash cards, credit cards and electronic fund transfer at the point of sale/debit cards, the comparative analyses offer strategic insights to predict the progress, as well as pattern of technology development and diffusion for the case of Blockchain banking.
Purpose Although blockchain is often discussed, its actual diffusion seems to be varying for different industries. The purpose of this paper is to explore the blockchain technology diffusion in different industries through a combination of academic literature and social media (Twitter). Design/methodology/approach The insights derived from the academic literature and social media have been used to classify industries into five stages of the innovation-decision process, namely, knowledge, persuasion, decision, implementation and confirmation (Rogers, 1995). Findings Blockchain is found to be diffused in almost all industries, but the level of diffusion varies. The analysis highlights that manufacturing industry is at the knowledge stage. Further public administration is at persuasion stage. Subsequently, transportation, communications, electric, gas and sanitary services and trading industry had reached to the decision stage. Then, services industries have reached to implementation stage while finance, insurance and real estate industries are the innovators of blockchain technologies and have reached the confirmation stage of innovation-decision process. Practical implications Actual implementations of blockchain technology are still in its infancy stage for most of the industries. The findings suggest that specific industries are developing specific blockchain applications. Originality/value To the best of the authors’ knowledge this is the first study which is using social media data for investigating the diffusion of blockchain in industries. The results show that the combination of Twitter and academic literature analysis gives better insights into diffusion than a single data source.
The Fractional Gray Lotka-Volterra Model (FGLVM) is introduced and used for modeling the transaction counts of three cryptocurrencies, namely, Bitcoin, Litecoin, and Ripple. The 2-dimensional study is on Bitcoin and Litecoin, while the 3-dimensional study is on Bitcoin, Litecoin, and Ripple. Dataset from 28 April 2013 to 10 February 2018 provides forecasting values for Bitcoin and Litecoin through the 2-dimensional FGLVM study, while dataset from 7 August 2013 to 10 February 2018 provides forecasting values of Bitcoin, Litecoin, and Ripple through the 3-dimensional FGLVM study. Forecasting values of cryptocurrencies for the n-dimensional FGLVM study, n={2,3} along 100 days of study time, are displayed. The graph and Lyapunov exponents of the 2-dimensional Lotka-Volterra system using the results of FGLVM reveal that the system is a chaotic dynamical system, while the 3-dimensional Lotka-Volterra system displays parabolic patterns in spite of the chaos indicated by the Lyapunov exponents. The mean absolute percentage error indicates that 2-dimensional FGLVM has a good accuracy for the overall forecasting values of Bitcoin and a reasonable accuracy for the last 300 forecasting values of Litecoin, while the 3-dimensional FGLVM has a good accuracy for the overall forecasting values of Bitcoin and a reasonable accuracy for the last 300 forecasting values of both Litecoin and Ripple. Both 2- and 3-dimensional FGLVM analyses evoke a future constant trend in transacting Bitcoin and a future decreasing trend in transacting Litecoin and Ripple. Bitcoin will keep relatively higher transaction counts, with Litecoin transaction counts everywhere superior to that of Ripple.
The research focuses on identifying Bitcoin ecosystem factors and modeling a causal loop diagram of the complete ecosystem. Bitcoin is a complex social, economical and technical system and a brand. Defining Bitcoin is very hard or even impossible, as it is a peer-to-peer phenomenon without central authority or formal definition. System dynamics methods are used to create a causal loop diagram of the Bitcoin ecosystem. Semi-structured expert interviews are used to improve and validate the CLD model and to gain insight about what is Bitcoin, why and how it works and generally about factors related to Bitcoin. Results, in addition to the CLD model, show that Bitcoin is a complex phenomenon without definition and with loads of subjective opinions about what it really is.
Leading experts from academic, industrial and policy-making circles describe Blockchain as a disruptive and game changing technology across various sectors. However, the question, whether Blockchain does already have the properties of a General Purpose Technology (GPT) and, as such, will determine macroeconomic dynamics in the next decades, has been disregarded in the academic literature. This paper covers the research gap by systematically revealing the acknowledged features of a GPT - pervasiveness, innovation spawning effects and scope for improvement - in the newest available Blockchain-related patent data from PATSTAT. To gain insights about pervasiveness, (1) a generality index of Blockchain is compared to respective values of co-existing technologies usually considered (information and communication technology) and not considered (pharmaceutical technology) GPTs. The second feature, innovation spawning is dissected (2) analyzing variety of innovators patenting in Blockchain domain and (3) looking at firms' behavior in terms of entry and exit in line with industrial dynamics. (4) Investigation of evolution patterns of Blockchain patents provides insights about its scope for improvement. The empirical analysis advances the claim that Blockchain does already represent a GPT in the making and, therefore, has a potential to shape a technological era and cause substantial changes in the economic, social and institutional structures.
Distributed Ledger Technologies (DLTs) have become a topic that is being more and more discussed in political, economic and scientific discourses. , also within economic sciences. Their potential to redefine many processes in the economy is growing, and there is a consensus in the scientific community about their revolutionary character. Blockchain is one of the DLTs and one of the breakthrough technologies distinctive for the Fourth Industrial Revolution. The aim of the paper is to draw attention to the potential of blockchain technology for developing countries and how it can contribute to the improvement of quality of life and fighting poverty. Following Schwab's thesis, "the extent to which society embraces technological innovation is a major determinant of progress". Therefore, developing countries should not disregard the potential of blockchain technology that can solve a lot of current problems and provide access to previously unreachable services with a relatively low cost (both implementation and subsequent maintenance cost).