Understanding the development trajectory of digital platforms is central to digital platform management. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains’ utility change and people’s adoption and abandonment behavior. We consider a typical blockchain participant to simultaneously play three roles on the platform, user, investor, and laborer, each contributing to blockchains’ multi-faceted utility: providing service for transaction/interaction, providing a medium for digital investment, and providing workspace for online labor. The model describes a three-phase development trajectory for blockchain platforms: a chaotic initial stage, a rapid growth stage, and a mature stage of stable market cycles. The model was used to match 112 token price series, demonstrating robust performance across different fitting setups and outperforming existing models. The study identifies two temporal parameters, the time delay in quitting the platform and the holding time of the platform’s token, that significantly differentiate blockchains’ development trajectories. We extend the model to study forking events; results suggest that fork launch time is more important than forking amplitude in influencing the main chain’s subsequent development and that forking can increase the exposure of the forked platform.
Lu Wang, Jun Zhang, Jian Li, Huayi Yu · 5 authors
Purpose This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF. Design/methodology/approach This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method. Findings The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism. Practical implications This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners. Originality/value The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.
Purpose Blockchain technology has been recognized as a potential solution to the challenges in managing healthcare information. Its adoption in the healthcare industry has garnered the attention of healthcare institutions and governments. Given the significant role of subsidies in promoting technology adoption, this study applies evolutionary game theory to examine the impact of government subsidies on the adoption of blockchain technology by healthcare institutions. Design/methodology/approach First, the authors analyze the interests of government administration departments and healthcare institutions separately in regards to blockchain adoption. Subsequently, the authors develop the payoff matrix of both participants and construct the evolutionary game model. And then, the authors calculate the replication dynamic equations and analyze the decision evolution of both participants through the replication dynamic equations and numerical experiments. Findings The numerical experiments demonstrate that government subsidies are effective in encouraging healthcare institutions to adopt blockchain technology. The study also reveals the necessary amount of subsidy required to guide healthcare institutions towards adoption. Additionally, the validity of the evolutionary game model in analyzing the interaction between governments and healthcare institutions is confirmed by the results. Originality/value Blockchain adoption in the healthcare industry differs from other emerging technologies, as there is the potential for it to reduce revenue for healthcare institutions. This study contributes to the analysis of theoretical models for promoting blockchain in the healthcare industry through subsidies. Additionally, it demonstrates the potential of evolutionary game theory in analyzing the adoption of blockchain technology, and the interaction between governments and healthcare institutions.
Purpose Blockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value. Design/methodology/approach Based on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value. Findings The results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance. Originality/value This is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).
Abstract The growing attention on cryptocurrencies has led to increasing research on digital stock markets. Approaches and tools usually applied to characterize standard stocks have been applied to the digital ones. Among these tools is the identification of processes of market fluctuations. Being interesting stochastic processes, the usual statistical methods are appropriate tools for their reconstruction. There, besides chance, the description of a behavioural component shall be present whenever a deterministic pattern is ever found. Markov approaches are at the leading edge of this endeavour. In this paper, Markov chains of orders one to eight are considered as a way to forecast the dynamics of three major cryptocurrencies. It is accomplished using an empirical basis of intra-day returns. Besides forecasting, we investigate the existence of eventual long-memory components in each of those stochastic processes. Results show that predictions obtained from using the empirical probabilities are better than random choices.
This paper examines factors affecting the adoption of cryptocurrency across 158 countries worldwide. To this end, we collected cryptocurrency adoption data from Chainalysis’s reports and macroeconomic data from the World Development Indicators platform. We find that greater import volumes, larger population size, more sufficient levels of the labor force, higher unemployment rate, and a higher level of electricity access are associated with a greater level of cryptocurrency adoption. On the other hand, a higher level of government spending and a greater level of domestic savings are associated with a lower level of cryptocurrency adoption. In addition, we also find that the population size and level of the labor force have a negative impact on the three subcomponents of the cryptocurrency adoption index including (i) centralized service value received (CeFi); (ii) the volume of exchange trading (P2P); and (iii) the received DeFi value (DeFi). We find that while the import volumes and level of electricity access have an opposite relationship with the centralized service value received and the DeFi value received, GDP has a negative effect on the DeFi value received. Meanwhile, greater government spending and higher domestic savings are associated with a greater level of exchange trade volume P2P. In terms of urbanization, whereas it shows a positive impact on the exchange trade volume P2P, it has the opposite effect on the DeFi value received.
The use of blockchain technology can ensure that data remains untampered with once it is on the chain. However, it doesn’t guarantee the authenticity of data before it enters the chain. In this study, we developed a three-party dynamic evolutionary game model involving core enterprises, small and medium-sized enterprises (SMEs), and financial institutions. Our findings indicate that a blockchain supply chain (BSC) generates more economic benefits than a traditional supply chain (TSC). We then built a dynamic evolutionary game model between core enterprises and SMEs, which revealed that SMEs are influenced by core enterprises and tend to adopt the action strategies of the latter. Additionally, we developed a dynamic evolutionary game model between core enterprises and financial institutions and compared the reward and punishment mechanisms with the synergy payoff mechanism. In the reward and punishment mechanisms, the game is a zero-sum game, where one party’s gains come at the expense of the other party. This mechanism has certain limitations and must meet specific conditions to improve the willingness of enterprises to share data. On the other hand, the synergy payoff mechanism enhances the authenticity of shared data by increasing the payoff for participants. When core enterprises play games with SMEs, the probability of core enterprises uploading real data and the distribution ratio of synergy payoff show an inverted U-shape. Similarly, core enterprises and financial institutions have comparable results in allocating synergy payoff. To leverage the synergy payoff mechanism, the distribution proportion of players participating in the synergy payoff should be considered fair. Finally, we validated our findings by simulating the models. If we can use blockchain technology to enhance the mutual trust between enterprises and banks, both banks and enterprises can achieve sustainable development.
Surmounted environmental concerns and energy challenges have created an augmented awareness among the public and policymakers about alternate energy resources. Using a network approach, this paper aims to investigate the dependence between cryptocurrencies and the alternative energy market using data from January 1, 2018, to December 23, 2021. For this investigation, first, we build a static dependency network for a given set of variables using partial correlations. Then, we demonstrate within-system connections in a minimum spanning tree (MST) to assess the centrality of all variables. Finally, rolling-window estimations are made to exhibit time variations in both dependency and centrality networks. We find that clean alternative markets (SPGCE, ELEVHC & WILCE) and ETH are net risk transmitters to other markets and system-wide net contributors. We also demonstrate how SPGCE is essential for tying together the various parts of the networks and provide convincing evidence of time-varying within-system dependency. Our thorough examination of the dependency analysis offers significant insights to macroprudential regulators, policymakers, and portfolio managers, enabling them to safeguard the most vulnerable markets and choose the best legislative and policy measures to protect investors' interests in the face of unforeseen financial and economic conditions.
Non-fungible token (NFT) bubbles are a problematic issue, and this study aims to predict NFT bubbles using an extended log-periodic power law singularity (LPPLS) model. The classic LPPLS model targets the endogenous nature of bubbles caused by the mimetic behavior of investors without external influences; however, the extended model attempts to incorporate exogenous influences. First, we compare the performance of the two models for NFT price prediction. The exogeneous variable in the extended model is cryptocurrency volatility. Then, we calculate the bubble confidence using both models. The results show that the explanatory power and forecasting accuracy of the extended model are superior in all projects. We also find that the bubble confidence indicator reinforces the results of bubble prediction.
Dhanya Pramod, S. Vijayakumar Bharathi, Kanchan Patil
This study explores the influence of the investors’ personality dimensions on the Non-Fungible Tokens (NFT) technology readiness index (TRI) and financial instrument-specific factors of technology acceptance. The survey comprised of 197 respondents. The responses-data were tested on the conceptual model using SEM (structural equation modeling). TRI 2.0 explored customers’ predispositions towards NFT investments. Mental enablers and inhibitors explained NFT perceived value and NFT perceived trust. The research found that the enabler of TRI (innovativeness) and inhibitors of TRI (insecurity and discomfort) along with perceived trust significantly affect the NFT investment intention It was also found that optimism and perceived value for NFT did not significantly impact NFT investment intentions. These research results shall facilitate government, NFT marketplaces, brands, and private organizations to prioritize TRI enablers and decrease inhibitors to ensure successful NFT investments.
Yogesh K. Dwivedi, Janarthanan Balakrishnan, Ronnie Das, Vincent Dutot
Blockchain research is significantly growing, yet the practical implementation of blockchain among retailers is still in the novice stage. This research aims to study the underlying factors that build resistance toward blockchain among retailers. The study has used innovation resistance theory (IRT) and the dynamic capability model to build the conceptual model. The study used a single cross-sectional design to investigate the proposed model with data collected from 360 retailers. The data were analysed using structural equation modelling estimated with the maximum likelihood model. The study's results showed that the threat of data ownership is the most significant factor that builds resistance towards blockchain, followed by threat severity. The results also showed that managerial capability and innovation capability could indirectly influence the relationship of IRT variables to resistance towards blockchain. The research extends the knowledge in the blockchain and contributes to relevant literature and business practitioners concerned with the results.
A review of a selected theories that influence the adoption of technology will serve as the objective of this paper. In this work, we attempt to discover traits that might improve the possibility of acceptance and ongoing usage of technology such as cryptocurrency adoption. More specifically, we focused on Rogers' Innovation Diffusion Theory (IDT, Theory of Technology Acceptance (TAT), and Technology Acceptance Model. (TAM)/TAM2/TAM3, Theory of Reasoned Action (TRA), Unified Theory of Acceptance and Use of Technology (UTAUT), and Theory of Planned Behaviour (TPB). When researching the tendency of individuals to adopt certain technologies, researchers draw from a wide variety of conceptual frameworks and analytical approaches. In this review, social psychology and its applied notions have been utilised most frequently. As a primary theoretical foundation, the theories centre on people's intentions to engage in a specific behaviour (i.e., adopt and utilise ICT), which is the emphasis of the theories. Research on the adoption and usage of information and communication technologies has made extensive use of both the Theory of Reasoned Action (TRA) and the Theory of Planned Behaviour (TPB). They are two of the key intention-based theories, which means they give the core theoretical underpinnings for other adoption theories, such as the Technology Acceptance Model (TAM) and the Enhanced Technology Acceptance Model. Both the transpersonal relationship analysis and the transpersonal behaviour analysis begin with the fundamental premise that individuals deliberately choose whether or not they will engage in a certain behaviour. In this sense, the adoption and usage intentions are typically seen of as a primary outcome variable that is influenced by a variety of independent variables. This is because of the way that they are typically studied. In the following, we will discuss significant theories regarding the adoption of technology.
Taqwa Hariguna, Athapol Ruangkanjanases, Bakri Bin Madon, Khaled Mofawiz Alfawaz
The paradigm of currency has shifted today in which the transformation from conventional currency to digitalization is getting higher lately. Cryptocurrency is one form of digital currency today. Cryptocurrencies is developed based on blockchain technology. The existence of cryptocurrency makes it a new and popular transaction model among its users, community, industry, and government. This is crucial study to measure the level of acceptability of cryptocurrency to understand the level of users’ sustainability in the future. Through the expectation confirmation model (ECM), this study develops the integration concept between ECM and technology readiness (TR). The method employed to measure the results of the hypothesis in this study was structural equation modeling. There are nine hypotheses proposed in the present study. Of the nine tested hypotheses, it was found that there are eight accepted hypotheses which are positive and have significance, while one hypothesis was rejected. The results of this study can be used as a guide and understanding of cryptocurrencies and the continued use of cryptocurrencies.
Ethereum has recently surged in popularity, as it can hold various digital tokens and decentralized applications.This paper aims to predict UNI's price in USD through dynamic network analysis and time-series analysis.Previous research in this field rarely considers comprehensive network analysis while predicting token price.This paper puts forward a strengthened Bidirectional LSTM model that includes token economical features and network features.We use Root Mean Squared Error (RMSE) to verify the validity and compare it with other LSTM and GRU models on performance.Lastly, a logarithm difference method for data preprocessing was introduced to resolve the lag problems.
This article shows a brief history of Techno-Economic Assessment (TEA) in Communications, a proposed redefinition of TEA as well as the new challenges derived from a dynamic context with cloud-native virtualized networks, the Helium Network & alike blockchain-based decentralized networks, the new network as a platform (NaaP) paradigm, carbon pricing, network sharing, and web3, metaverse and blockchain technologies. The authors formulate the research question and show the need to improve TEA models to integrate and manage all this increasing complexity. This paper also proposes the characteristics TEA models should have and their current degree of compliance for several use cases: 5G and beyond, software-defined wide area network (SD-WAN), secure access service edge (SASE), secure service edge (SSE), and cloud cybersecurity risk assessment. The authors also present TEA extensibility to request for proposals (RFP) processes and other industries, to conclude that there is an urgent need for agile and effective TEA in Comms that allows industrialization of agile decision-making for all market stakeholders to choose the optimal solution for any technology, scenario and use case.
Surajit Bag, Muhammad Sabbir Rahman, Shivam Gupta, Lincoln C. Wood
Purpose The success of SMEs' financial and market performance (MAP) depends on the firms' level of blockchain technology adoption (BCA) and identifying the crucial antecedents that influence SMEs' adoption. Therefore, this research attempts to develop an integrated model to understand and predict the determinants of BCA and its effect on SMEs' performance. The purpose of this paper is to address this issue. Design/methodology/approach The theoretical foundations are the technology–organization –environment (TOE) framework and the resource-based view (RBV) perspective. The authors distributed a survey to SMEs in South Africa and received 311 responses. The covariance-based structural equation modeling (CB-SEM) followed by the artificial neural network (ANN) technique was used for the data analysis. Findings The SEM results showed that SMEs' relative advantage, compatibility, top management support (TMS), organizational readiness (ORD), competitive pressures (COP), external support, regulations and legislation significantly influence SMEs' BCA. However, complexity negatively impacts SMEs' BCA. The analysis results also revealed that SMEs' BCA significantly influences the financial performance of the firms, followed by MAP. Furthermore, model determinants were input to an ANN modeling. The ANN results showed that TMS is the most critical predictor of SMEs' BCA, followed by ORD, COP, external support, and regulations and legislation. Practical implications The results provide valuable information for SMEs when maneuvering their adoption strategies in the scope of blockchain technology. Additionally, from the perspective of an emerging market, the study has successfully contributed the TOE framework and the RBV. Originality/value This study is the first work to explore the determinants of BCA in the context of SMEs from a developing country. This paper is also one pioneer in attempts to develop a causal and predictive statistical model for predicting the determinants of BCA in SMEs' performance.
Marroi Laaraj, Walid A. Nakara, Samuel Fosso Wamba
Blockchain is one of the most promising technologies with a highly disruptive potential, yet many aspects of this innovation remain unclear in the current body of research. One of them is the whole adoption and diffusion process of blockchain technology, which needs more attention from researchers. This study has adopted a qualitative method to investigate the role of consultants in blockchain diffusion, relying on data from 14 semi-structured interviews conducted with blockchain consultants. The various roles of these key players were identified and challenges related to the technology analyzed by means of the Diffusion of Innovation Theory (DOI) and the Technology – Organization – Environment (TOE) framework. According to the results obtained, consultants’ roles range from technology brokers to quality filters. The same results also revealed that the most important barriers to blockchain adoption and diffusion include the lack of knowledge and understanding of the technology, which contributes to promoting unconscious or forced adoption. This paper sheds light on how consulting firms and blockchain-oriented start-ups operate to impact the diffusion of blockchain while dismantling barriers to adoption.
Christian Nedu Osakwe, Michael D. Dzandu, Hayford Amegbe, Mohammed Hersi Warsame · 5 authors
This study seeks to investigate the psychological antecedents toward cryptocurrency investment decision-making. Using extended planned behavior model, data were collected from 517 sample respondents in Kenya and Ghana to test the proposed model. Specifically, we find that skepticism undermines willingness to invest in cryptocurrency via attitude toward cryptocurrency across the two countries studied. We also find that subjective norm and perceived self-efficacy positively influence attitude toward cryptocurrency that, in turn, positively influences willingness to invest in cryptocurrency. The positive relationship between trust disposition and attitude toward cryptocurrency and in turn willingness to invest in cryptocurrency is statistically valid in Kenya but not in Ghana. Contrary to expectations, no negative statistical effect of risk disposition on attitude toward cryptocurrency was found in the Kenya and Ghana sample. Overall, the presented findings in this study enrich empirical understanding about the psychological factors influencing attitude and individuals’ intentions to invest in cryptocurrencies such as Bitcoin and Litecoin.