Khaladdin Rzayev, ÎθινΏĎÎšÎżĎ ÎŁÎŹÎşÎşÎąĎ, Andrew Urquhart
The network effect, measured by usersâ adoption, is considered an important driver of cryptocurrency market dynamics. This study examines the role of adoption timing in cryptocurrency markets by decomposing total adoption into two components: innovators (early adopters) and imitators (late adopters). We find that the innovatorsâ component is the primary driver of the association between user adoption and cryptocurrency returns, both in-sample and out-of-sample. Next, we show that innovatorsâ adoption improves price efficiency, while imitatorsâ adoption contributes to noisier prices. Furthermore, we demonstrate that the adoption model captures significant cryptocurrency market phenomena, such as herding behaviour, more effectively, making it better suited for forecasting models in cryptocurrency pricing. These results suggest that our methodology for linking early and late adopters to market dynamics can be applied to various domains, offering a framework for future research at the intersection of operational research and financial markets.
In recent years, propelled by societal transformations and technological advancements, emerging technologies founded upon diverse disciplines such as financial and information technology have rapidly evolved. Identifying the trends associated with these emerging technologies and extracting their salient topics is crucial in order to accurately grasp the developmental trajectory of these tools and for their efficient utilization. In this study, we chronologically categorize information derived from five types of multi-source data, including journal articles, patent inventions, and industry reports, into distinct periods. We employ the LDA (Latent Dirichlet Allocation) topic model to identify emerging technological themes within these periods and utilize a dual-index theme lifecycle analysis method to construct a hotspot theme distribution map, thereby facilitating the extraction of significant themes. Through empirical research on blockchain financial technology, we ultimately identify 22 thematic areas of blockchain finance and extracted eight prominent themes, including financial technology, cross-border payments, digital invoices, supply chain finance, and decentralization. By analyzing these themes alongside their respective popularity levels, we validate that the methods above can be used to effectively identify emerging technological hotspots and illuminate their developmental directions.
Zhang Ying, M. Mahdi Tavalaei, Glenn Parry, Peng Zhou
To understand the slow adoption of blockchain technology by organisations, we conduct a systematic literature review of adoption factors using a mixed-methods approach. Using thematic analysis, 880 factors are identified and grouped into 29 themes, which offer a comprehensive overview of the literature. Using statistical analysis, the identified factors are dissected into technological (T), organisational (O), and environmental (E) dimensions (the TOE framework). Themes are further classified as barriers (B), enablers (En), and ambiguous (A) to describe a firm's readiness for blockchain adoption (the BEnA framework). We emphasise the multidimensionality of adoption factors across the TOE dimensions and the conditionality of adoption enablers across the BEnA dimensions. Analysis of research trends shows that recent blockchain adoption literature has focused on elaborating upon existing research themes (involution) rather than on developing new themes (evolution). Based on our analyses, we propose future research directions, including scrutinising the interdependence and multidimensionality of blockchain adoption factors, further examining factors with conditional or unclear effects on adoption, and broadening the contextual, temporal, and theoretical aspects of blockchain adoption research. ⢠Identified 880 factors and 29 themes of blockchain adoption by organisations. ⢠Developed multidimensional theoretical frameworks to analyse factors and themes. ⢠Adoption barriers are mostly unambiguous, while enablers are often conditional. ⢠Recent research on blockchain is mainly an involution rather than an evolution.
Purpose As the global financial ecosystem grapples with the complexities of modernization, blockchain technology emerges as a pivotal catalyst, offering the banking, financial services, and insurance (BFSI) industry unprecedented opportunities for secured digital transformation and enhanced customer trust. To gain a comprehensive understanding of blockchain technology adoption, this study aims to identify the factors and establish the contextual interrelationships among them. Design/methodology/approach The authors have identified the factors affecting blockchain technology adoption in BFSI industry through extensive literature review and expertsâ interviews. After identification of factors, contextual relationship has been established based on expertsâ opinion and total interpretive structural modeling (TISM) approach. Furthermore, factors are categorized into autonomous, dependent, linkage and driving variables using cross-impact matrix multiplication applied to classification analysis. Findings The TISM-based structural model is divided into eight different hierarchal levels in which Government support is placed on the lower most layer (level 8) which indicates that this is the most crucial factor in blockchain adoption. Further social influence and security are placed on seventh and sixth level in the hierarchy. Practical implications The results of this study will help the policymakers to direct the resources from the most crucial factor to other factors in the hierarchy as per their relevance. In essence, this study serves as a guiding compass, steering the course of blockchain technology adoption in the BFSI sector toward a more secure and digitally transformed future. Originality/value In the current landscape, blockchain technology remains in its nascent stage, leaving ample room for exploration and innovation. This study stands as the pioneering effort to comprehensively identify and establish the contextual relationships among the adoption factors of blockchain technology within BFSI industry. Through rigorous TISM analysis, this paper enriches the existing body of knowledge on blockchain technology adoption.
This study explores the adoption of blockchain technology within the Ethiopian National Quality Infrastructure (NQI). Data from 178 professionals representing various organizations and roles were collected to investigate key adoption factors. By integrating the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, external factors (Technology Compatibility, Relative Advantage, Government Support, and Policy) and internal factors (perceived usefulness, perceived ease of use, and intention to use) were examined. A dual-stage analytical approach involving partial least square-based structural equation model (PLS-SEM) and artificial neural network (ANN) analyses was employed. The findings emphasize the significance of technological compatibility, perceived usefulness, and top management support as determinants of blockchain adoption in the NQI. Particularly, the compatibility of the existing system emerges as the most influential factor in adopting blockchain technology within the Ethiopian NQI. This study enhances the understanding of blockchain adoption within the NQI context, providing valuable insights for successful implementation. It contributes to the existing knowledge in this area and offers practical implications for quality infrastructure management.
Business models of industries and ventures enabled by new and emerging technologies are under-developed and fragmented. The blockchain technology promises to disrupt the business models. However, the scholarly literature in blockchain research is only beginning to emerge, and the majority are focused on the technical aspect leaving aside the business model complexities for blockchain applications. This paper fills this gap and proposes a blockchain business model framework. The research utilizes a sequential exploratory research design (SERD), encompassing two key phases: an initial phase involving a literature review and interviews to delineate blockchain business model building blocks and types, followed by a subsequent survey to identify the most pertinent building blocks and types. The findings helped to formulate the framework, necessary building blocks, and block types specifically for the blockchain applications. Organizations can tailor their business model through various configuration options and mechanisms, considering the arrangement of block types within each block according to their significant score levels. By giving priority to those with scores above the block's average, organizations can evaluate the performance of their models and pinpoint areas for enhancement. The proposed framework can be considered as a reference point for developing business models for blockchain applications. ⢠Enhances current knowledge by classifying specific building blocks and types within the blockchain business model. ⢠Outlines the blockchain business model, highlighting possible building blocks and types. ⢠Creates an instrument to configure and measure the blockchain business model. ⢠Determines the significance of different building blocks and types to aid decision-making in providing blockchain solutions.
We examine the linkages between Bitcoin, Ethereum, Tether and USD Coin returnsâin the context of the post-epidemic landscape. Our paper utilizes the underpinning concept of the fractal market hypothesis. By employing our theoretical nexus alongside the continuous wavelet transform, we elucidate the changes in investor demand during notable events. Our results suggest that all four cryptocurrencies exhibited significant volatility in response to the March 2020 pandemic and the Delta variant announcements. Moreover, the fall of Three Arrows Capital and FTX affected all cryptocurrencies, while Silicon Valley Bankâs liquidation only impacted the stablecoins. Pairwise, investors heavily demand stablecoins during financial turmoil, which causes unconditional synchronization. The two cryptocurrency categories are anti-phasing in a market regime where traders are widely unanimous, but in-phasing when the sentiment consists of divergent perceptions. These cross-cryptocurrency phases of demand persist in the long run for USD Coin but are only medium-term for Tether.
Abstract Cryptocurrencies are a new form of digital assets that have gained increasing popularity in recent years. Investors have a dual objective of maximizing profits while minimizing risks. In today's world, there is an increase in the demand for cryptocurrencies, with focus on the emotional aspects as well as on the underlying technical analysis. This abstract provides a synthesis of recent research and insights into the behavior of consumers engaging with cryptocurrencies. Key determinants such as trust, perceived usefulness, and ease of use play pivotal roles in driving consumer adoption of cryptocurrencies. Furthermore, behavioral uncertainty and risk perception emerge as critical considerations impacting investment decisions within this dynamic ecosystem. The abstract also highlights the significant influence of digital platforms and social media on shaping consumer attitudes and behaviors towards cryptocurrencies, underscoring the importance of online discourse and information dissemination in this context. As the cryptocurrency market develops and grows, understanding consumer behavior becomes increasingly paramount for stakeholders, policymakers, and researchers alike. By unraveling the complexities of consumer preferences, motivations, and perceptions, this abstract offers valuable perspectives to inform strategic decision-making and foster sustainable growth in the cryptocurrency industry. This research was based on scientific articles and carefully selected and studied important data from trusted sources like academic journals, financial databases, and websites focusing on cryptocurrency information.
Elona Marku, Maria Chiara Di Guardo, Gerardo Patriotta, David G. Allen
Drawing on complexity theory, we investigate the structuring processes and underlying mechanisms underpinning the emergence of a new technology. Empirically, we track the emergence of blockchain technology by examining international patents issued between 2009 and 2020. Our results indicate that technology emergence follows an evolutionary trajectory that progresses from disordered to structured interactions among the technological elements, culminating in the formation of a technological core that acts as a pole of attraction for further interactions and delineates boundaries within the technological domain. Technology structuring is fueled by what we term âtechnology fitnessâ and âself-reinforcingâ mechanisms that progressively transform primitive structures into more complex, self-organized configurations. Our study offers a novel framework of technology emergence, highlighting how dispersed bits of technological knowledge gradually aggregate into complex structures that define the specific trajectory of a particular domain.
Rohit Sharma, Sahiba Khan, Ranjit Singh, Abhijeet Birari
Cryptocurrency markets are inclined towards speculative usage due to the inherent high risk of financial loss and the potential for substantial gains during transaction completion. In response to this phenomenon, this study represents the inaugural effort to explore the influence of variables such as subjective norms, domain knowledge, impulsive investment tendencies, and self-control on decisions related to speculative investments. Utilising structural equation modelling with a dataset of 367 responses in India, the study is the first of its kind. The research reveals that subjective norms and domain knowledge play a significant role in influencing impulsive investment and self-control. Additionally, impulsive investment exhibits significant associations with decisions involving speculative investments. This insight underscores the complexity wherein individuals, despite exercising self-control, may still engage in speculative decisions that lead to adverse consequences. The findings have practical implications for investors and regulators, offering valuable insights into investment behaviours within the cryptocurrency realm.
Mark P. Doblas, Jishanis Mae G. Becaro, Jayendira P. Sankar, V. Natarajan ¡ 6 authors
This study explores the adoption of cryptocurrency, specifically Bitcoin, in the Philippines. The authors argue that current behavioral prediction models, such as TRA, TPB, and TAM, do not adequately account for the affective constructs of decision-making when high monetary stakes are involved. To address this gap, the authors propose an integrative model that accounts for financial decision-making processes, risk constructs, and population-specific behavioral strategies. The study used a quantitative-based research design and involved 684 university students from one of the major state universities in the Philippines. The findings show that perceived usefulness, attitude toward cryptocurrency, self-efficacy, and descriptive norms significantly influenced the intention to adopt cryptocurrency. Overall, the study confirms the direct influence of instrumental attitude, knowledge of cryptocurrency, descriptive norm, risk tolerance, ease and difficulty, and control on an individualâs intention to use cryptocurrency. The study contributes to exploring a less studied Philippine consumer base and provides empirical findings and insights into Bitcoin adoption in developing Asian economies. JEL Classification: G15. G17, G41, P33, G32.
Nadia A. Abdelmegeed Abdelwahed, Mohammed A. Al Doghan, Ummi Naiemah Saraih, Bahadur Ali Soomro
Purpose Blockchain technology has brought about significant transformation among organizations worldwide. This study aimed to explore the effects of organizational and technological factors on blockchain technology adoption (BTA) and financial performance (FP) in Pakistan. Design/methodology/approach This is a co-relational study which used the cross-sectional data. We gathered the data from the managers of Pakistanâs small and medium-sized enterprises (SMEs), which functioned their industries with blockchain technology. We applied convenience sampling to identify the respondents. Finally, we based this studyâs findings on 274 valid cases. Findings We used structural equation modeling (SEM) in this study, to exert a positive and significant impact on organizational factors such as organizational innovativeness (OI), organizational learning capability (OLC), top management support (TMS) and organizational work climate (OWC) on BTA. In addition, the technological factors, such as complexity (CTY), technology readiness (TR), compatibility (CBTY) and technology capability (TC), have a positive and significant effect on BTA. Finally, this studyâs findings show that BTA positively and significantly impacts FP. Practical implications This studyâs findings will help policymakers and planners to design policies to adopt other blockchain technologies to improve SMEsâ operations. Moreover, this studyâs findings will inspire policymakers and planners to actively seek new ideas, knowledge and skills through acquiring new knowledge to assist with their IT-related decisions. Originality/value This study empirically confirms the role of organizational and technology factors toward BTA and FP among Pakistan's SME managers.
The results indicate a dynamic pattern of interconnectedness throughout history. Based on the findings, the transmission of volatility exhibited a higher magnitude during the period of COVID-19. The issue of high transmission volatility due to limited diversification options concerns investors, green stakeholders, and policymakers alike. This article proposes various potential areas for future research. The ICEA index can potentially assist businesses operating in environmentally sensitive sectors make well-informed policy decisions. It includes sectors such as environmental green bonds, and commodities. Consideration should be given to implementing blockchain technology, as it can consume less power in this particular scenario. By employing a time-frequency paradigm, this study is able to incorporate the investment horizon, a crucial factor to be taken into account when making financial judgments. The advancement of this research could be facilitated by directing our attention toward the implications of our findings on portfolios and developing appropriate measures for their evaluation.
This article investigates the Ethereum Merge, which occurred on 15 September 2022, and we employ the time-series difference in differences (DiD) model and vector autoregression (VAR) models and analyse how the protocol change from proof-of-work to proof-of-stake (PoS) affects the dynamic relationship between cryptocurrency returns and network factors. The results show that the Merge caused a structural change between Ethereum and Bitcoin networks. The network factors of Ethereum show a significant increase compared to Bitcoin, the cointegration has been strengthened and the lag length is shortened after the Merge. The spillover effect on the Bitcoin network can be seen from both DiD and VAR, indicating the increasing impact of the Ethereum network on Bitcoin. The concern of losing the number of participants due to the implantation of PoS on cryptocurrency is not apparent on Ethereum Merge, and it increases the investorsâ attention and involvement.
The development of Internet of Things (IoT) technology has promoted the prosperity of the smart device market. Smart devices provide consumers with a higher level of intelligent experience and can collect consumer data through sensors, enabling platforms to obtain additional demand spillover benefits. This has led to the entry of some IoT platforms into the smart device market, directly competing with smart device manufacturers. In this study, we analyze the impact of different market structures in the smart device market on manufacturers' innovation decisions and platform service pricing decisions within a supply chain composed of an IoT platform and a smart device manufacturer. We also examine the impact of platform entry on the quality, prices, and profits of both parties' products. The research indicates that when the smart device market is not fully covered, platforms can promote manufacturer innovation through price discounts and thus obtain higher demand spillover benefits. Furthermore, when the platform enters the market, the quality of both parties' smart devices increases, but the platform's product price is lower than the manufacturer's despite its higher product quality. Finally, we also find that when demand spillover is significant, platform entry is always driven by platform profits, but is not beneficial to manufacturers.
Abstract This paper proposes the use of social media as a proxy for financial information. Using an extended sample of 53,580,759 tweets and employing text analysis tools (Latent Dirichlet Allocation and Term FrequencyâInverse Document Frequency), we determine the information being exchanged on any given day. We train machineâlearning classifiers and forecast crypto price movements for more than 8000 cryptocurrencies and gauge market efficiency through successful forecasts based on public information. We propose various metrics of market efficiency for cryptocurrency assets and demonstrate that market efficiency is higher during the first 6 months after the Initial Coin Offering. We also examine the efficiency behavior of individual currencies during crisis periods.
Jan 1, 2024¡Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Annika Bengts, Ville Eloranta, Esko Hakanen, Taija Turunen ¡ 5 authors
Business models integrate activities for value creation and capture. While ecosystems have emerged as potent catalysts for value creation through collaborative innovation, the common understanding is that value capture occurs within individual firms. This paper challenges this dichotomy. In an empirical study using a polar types case approach, we first illustrate how two ecosystems employ decentralization technology, specifically blockchain-based Web3 platforms, to elevate value capture to the ecosystem level. We then outline the implications beyond the blockchain domain using two non-Web3 cases. Specifically, we showâfrom the perspectives of value proposition, value constellation, and profit equationâhow business models can rise to the ecosystem level.
Abstract Despite the extensive interest in cryptocurrencies over the past years, their application as a means of payment in eâcommerce and retail purchases continues to be much slower than anticipated. This paper investigates the underlying mechanisms and elements that drive consumer resistance in this space. Drawing upon the stimulusâorganismâresponse paradigm and the innovation resistance theory, the paper explores how the characteristics of the current cryptocurrency landscape contribute to different factors associated with cryptoâpayment rejection. Our findings from empirical and experimental studies reveal how ecosystem volatility and the lack of structural assurances for cryptocurrencies foster negative consumer perceptions, leading to resistance against cryptoâpayment use. The paper develops new insights into the main predictors of consumer resistance to cryptoâpayment, which is a precursor to the mainstream use of cryptocurrencies. Moreover, it sheds light on the interactions among contextâspecific, psychological, and functional determinants of behavioral consumer response.