MSMEs in Indonesia are expected to be able to face competition in the era of industrial revolution 4.0. However, there are many problems and obstacles in competitiveness, especially facing global competition, including access to capital, access to information and technology, access to organization and management, and access to business networks and partnerships. Besides, it is often difficult for them to get additional capital through banks or other lenders to increase their business scale. Moreover, a lack of financial and digital literacy causes the low validity of MSMEs' data to lenders. The adoption of blockchain technology is one of the considerations to minimize these MSMEs problems. Meanwhile, this technology is still relatively new to be applied to MSMEs but positively impacts the future. This study aims to measure and analyze MSMEs' readiness in using blockchain technology on a business scale with the TRAM model. This model integrates the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM) models. This study aims to test several variables, including TRI, perceive ease of use, perceive ease of usefulness, attitude toward, and intense use of blockchain technology. Data processing uses the partial least square path modelling (PLS-PM) method. The results showed that TRI was significant on perceived ease of usefulness and perceived ease of usefulness. Then, perceive ease of use is significant towards perceive ease of usefulness and intention to use. Besides, perceive ease of usefulness is significant for attitude. The attitude toward variable is significant for the intention to use in the acceptance of blockchain technology.
Atif Naseer, Enrique Nava Baro, Sultan Daud Khan, Y. Vila · 5 authors
In recent years, cryptocurrency has become gradually more significant in economic regions worldwide. In cryptocurrencies, records are stored using a cryptographic algorithm. The main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social media. Twitter is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media channels. Therefore, this work focuses on extracting Tweets and gathering data from different sources to classify them into positive, negative, and neutral categories, and further examining the correlations between cryptocurrency movements and Tweet sentiments. This paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction; this method is used to predict the prices of four cryptocurrencies, namely, Litecoin, Monero, Bitcoin, and Ethereum. The results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%. The method is validated by comparison with existing methods using visualization tools.
Mauro Sciarelli, Anna Prisco, Mohamed Hani Gheith, Valerio Muto
Purpose The present research aims to identify the determinants for users' behavioral adoption of Blockchain, exploring the relationships among these variables and investigating whether the proposed model can provide a more comprehensive manner to understand the adoption of Blockchain technology. Design/methodology/approach This study adopts the Technology Acceptance Model (TAM) approach and extends it with external constructs: âreduced costâ and âefficiency and securityâ. This paper used a quantitative and exploratory approach through the collection and analysis of data from a total of 108 Italian innovative SME. We have used the Partial Least Squares Structural Equation modeling (PLS-SEM) approach using SmartPLS for model evaluation. Findings The results show that âefficiency and securityâ is an important driver of firms' decision-making process to adopt Blockchain. Moreover, the results show that perceived usefulness is a strong predictor of the intention to use Blockchain in business processes. Originality/value This research advances the literature on technology adoption in business processes, focusing on a particular technology: Blockchain. The field has been strengthened by investigating the determinants of technology adoption, adding new perspectives; both reduced cost and efficiency, and security.
Purpose The purpose of the research is to investigate usersâ adoption of blockchain-based games in China. Design/methodology/approach This research applied existing technology diffusion theories to develop a research model to examine usersâ adoption of blockchain-based games. As a result, a research model with nine research hypotheses was developed. The developed research model was empirically tested using data collected from a survey of 210 blockchain-based games users. Structural equation modeling was applied to analyse the collected data. Findings The results indicated that seven of nine research hypotheses were supported. It was found that trust, perceived usefulness, perceived enjoyment and perceived ease of use were key determinants for usersâ behavioural intention to use blockchain-based games. The most influential relationship in the research model appeared to be the effect of perceived usefulness on usersâ behavioural intention to use blockchain-based games. However, subjective norms did not have significant positive impacts on usersâ behavioural intention to use blockchain-based games. Practical implications The regulatory support from governmental authorities is essential to provide additional legal certainty to build usersâ trust in playing blockchain-based games. Blockchain-based games providers should arrange the training program targeted to the general users to enhance their understanding of the key features associated with blockchain-based games. Blockchain-based games developers should come up with good design solutions to maximize user enjoyment with blockchain-based games by considering additional entertainment elements. Originality/value To the best of the authorsâ knowledge, this study is first of its kind in investigating the adoption of blockchain-based games from usersâ perspectives. This study contributes to the existing literature on the adoption of blockchain technology.
Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that âSpaceX is going to put a literal Dogecoin on the literal moonâ. He later called himself the âDogefatherâ as he announced that he would be hosting Saturday Night Live (SNL) on 8 May 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Muskâs performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers.
The cryptocurrency market is very young, volatile, and highly risky. By the end of 2020, a new bull run started, and the prices of several cryptocurrencies reached record-breaking highs. The factors affecting this rise of cryptocurrencies include the impacts of the COVID-19 pandemic, the economic crisis and the global increase in the inflation rate, as well as the gradual acceptance and adoption of cryptocurrencies by people worldwide. This exploratory research is focused on this last factor, i.e., using cryptocurrency and with it, the associated support of its ecosystem (e.g., mining, staking). A survey was carried out investigating the motivational factors and barriers to investment in cryptocurrency for Czech representatives of Generations Y and Z (18â42 years; n = 468). The geographic scope was nationwide, and quota sampling was used. Notably, this survey was carried out prior to the global COVID-19 pandemic outbreak, and it is thus not affected by the pandemic and its related economic impacts. The article investigates the dependency between the individual motivational factors and barriers from the perspective of the tendency to take risks (using the risk propensity scale), according to gender and representation of Generations Y and Z. The lack of information on this form of investment is considered as the main barrier to investment in cryptocurrency, with respect to sex and generations. Compared to that, a negative experience with investment in cryptocurrency constitutes the most minor barrier. Respondents that have a tendency to take risks are mostly put off by their lack of experience with investment in general. The main motivational factor for investment in cryptocurrency, with respect to sex and generations, is considered to be the speed of increase in cryptocurrency value. On the other hand, the least encouraging factor is the opportunity to use the high volatility of cryptocurrency for speculative trading. Interestingly, this factor mostly encourages respondents that do not have a tendency to take risks. The findings are discussed, along with the presentation of their implications for practice and the directions of further explanatory research.
Given the emerging nature of integrating Blockchain Technology (BCT) into several business fields concerning the interaction between companies and their customers, this study aims to investigate the applications of BCT in marketing through an accurate procedure of locating, selecting and analyzing existing companies using BCT in marketing. A sample that consists of 800 companies was identified using web-scraping methods. The data set was collected from initial coin offerings (ICO) websites as well as from an existing, older landscape of applications. The data set was then intensively analyzed in order to be categorized into five fields of marketing technology. Advertising and ecommerce outgrew the other fields of social & relationship, content & experience and data in absolute numbers, revealing the focus of practitioners in the past as well as gaps for the future. The authors provided future directions for researchers on and development of tools to systematically generate knowledge and improve the application of BCT and the work of practitioners in marketing.
Guych Nuryyev, Anastasia Spyridou, Simon Yeh, Chen-Chang Lo
Hospitality businesses might achieve a competitive advantage by adopting cryptocurrency payments. This study provides insight into the factors that influence hospitality businessesâ intention to use new digital payments based on a conceptual approach. One of the contributions to the literature is in integrating an external variable â perceived security â into the Technology Acceptance Model. Perceived security is considered a strong predictor for a new payment technology adoption. This study also contributes to the academic research by illuminating potential directions for future empirical research.
The tourism industry is increasingly influenced by the evolution of information and communication technologies (ICT), which are revolutionizing the way people travel. In this work we want to investigate the use of innovative IT technologies by DMOs (Destination Management Organizations), focusing on blockchain technology, both from the point of view of research in the field, and in the study of the most relevant software projects. In particular, we intend to verify the benefits offered by these IT tools in the management and monitoring of a destination, without forgetting the implications for the other stakeholders involved. These technologies, in fact, can offer a wide range of services that can be useful throughout the life cycle of the destination.
Ghazanfar Ali Abbasi, Lee Yin Tiew, Jinquan Tang, Yen-Nee Goh · 5 authors
In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model were extended with the inclusion of trust and personnel innovativeness. The model was further validated by introducing a new path model compared to the original UTAUT2 model and the moderating role of personal innovativeness between performance expectancy and price value, with a sample of 314 respondents. Contrary to previous technology adoption studies that used PLS-SEM & ANN as single-stage analysis, this study further enhanced the analysis by applying a deep learning-based dual-stage PLS-SEM and ANN method. The application of deep learning-based dual-stage PLS-SEM & ANN analysis is a novel methodological approach, detecting both linear and non-linear associations among constructs. At the same time, it is regarded as a superior statistical approach as compared to traditional hybrid shallow SEM & ANN single-stage analysis. Also, sensitivity analysis provides normalised importance using multi-layer perceptron with the feed-forward-back-propagation algorithm. Furthermore, the deep learning-based dual-stage PLS-SEM & ANN revealed that trust proved to be the strongest predictor in driving user intention. The introduction of this new methodology and the theoretical contribution opens the vistas of the extant body of knowledge in technology-adoption related literature. This study also provides theoretical, practical and methodological contributions.
Establishing a blockchain food traceability system (BFTS) is increasingly important and urgent to resolve the contradiction between consumers' intention regarding safe food selections and the spread of polluted foods. Using the advantages of blockchain, such as immutability, decentralization, openness, and anonymity, we can build trusted food traceability systems based on these important characteristics. With reliable information, traceability from production to sales can effectively improve food safety. In this research, multiple models, namely, the information success model (ISS) and the Theory of Planned Behavior (TPB) are formed into a conceptual integrated framework to study the intentions' influenced factors of BFTS technology for Chinese consumers to help ensure food safety and the quality of Chinese organic food products. A face-to-face questionnaire survey with 300 valid responses was analyzed by Partial Least Square from the Chinese consumers focusing on the organic food products. This study found that the attitude and perceived behavioral control qualities significantly and positively affect the usage intention in adopting BFTS, while the subjective norms are positively but not significantly correlation with the usage intention in using BFTS. The above results will inform suggestions for productors and academics along with implications to promote BFTS' usage intention.
In order to research how to promote online shopping consumersâ application of after service, build an evolutionary game model of both consumers and e-stores. This paper introduces the variables of supervision and punishment, tries to introduce the smart contract as a powerful service guarantee, and analyzes the influence relationship of variables between the two players and their strategic choices. This paper analyzes the ESS of the system when the relationship among smart contract, revenue, supervision and punishment meets 8 different conditions. Finally, giving suggestions to optimize the after service in online shopping according to the results.
Blockchain technology is a secure distributed ledger for lists of transactions, which has immense potential to solve traditional agri-food supply chain issues. An increasing number of research on blockchain-based traceability applications aims to improve food quality and safety. Still, relatively few works considered user interfaces when developing and reporting their applications, which could lead to usability issues. This paper aims to address this gap by reviewing existing works from user interface perspectives. We gathered 25 review papers on blockchain or agri-food supply chain and 39 research papers that presented screenshots of user interfaces of related applications. We first reviewed 7 review papers that focused on the blockchain-based agri-food supply chain to understand the benefits and challenges in the blockchain applications. We then analyzed 14 blockchain-based agri-food traceability applications and 10 non-blockchain-based agri-food traceability applications. The analysis resulted in categorizations of 5 target user groups, 3 main approaches for collecting data, 5 main approaches for visualizing data, and a discussion of other aspects of user interfaces. However, we found insufficient details and discussions on the user interfaces and design decisions of the applications for further usability assessment. Additionally, user involvement for evaluation is lower in blockchain-based researches than in non-blockchain-based researches. This trend could lead to usability problems of blockchain applications, causing blockchain technology to be underutilized. Finally, we discussed research gaps and future research directions related to user interface design, which should be addressed to ease future blockchain adoption.
Horst Treiblmaier, Daniel Leung, Andrei O. J. Kwok, Aaron Tham
Blockchain technologies are predicted to substantially transform the tourism industry. At present, cryptocurrencies are the most advanced application of public blockchains that promise benefits such as a universal means of payment and minimal fees through the removal of intermediaries. In the tourism industry, though many tourism vendors have been accepting cryptocurrencies and the potential of using cryptocurrencies in travel-related consumption has been intensively documented, existing knowledge about travellersâ intention to use cryptocurrencies for payment purposes is limited. Traditional models do not account for the idiosyncrasies of cryptocurrencies and are therefore less appropriate to foster the understanding of travellersâ adoption of travel-related payments. To fill this knowledge gap, an exploratory study was conducted with 161 travellers from the Asia-Pacific region who have previously consumed travel-related services with cryptocurrencies. Their previous usage experiences are analysed and reported. Through harnessing the correspondence analysis, several technological contingency factors were identified, as well as positive and negative perceptual antecedents. Additionally, their levels of satisfaction and intention to re-use the technology in future trips were investigated. Based on these findings, several propositions are suggested for guiding future research on travellersâ cryptocurrency adoption in the travel and tourism contexts.
Inessa Tyan, Mariemma I. YagĂŒe, Antonio JesĂșs Guevara Plaza
This conceptual paper discusses the potential of blockchain technology for Smart Tourism Destinations. The main focus is placed on Smart Tourism Destinationsâ four major goals that can be achieved by using blockchain technology, namely: enhancing tourism experience, rewarding sustainable behaviour, ensuring benefits for local communities, and reducing privacy concerns. The paper also outlines the major challenges that need to be overcome to successfully implement this innovative technology. This paper attempts to further advance the current knowledge about the possible implications of blockchain technology within the smart tourism domain, and especially Smart Tourism Destinations.
Cryptocurrencies are a new form of digital asset that operate through blockchain technology and whose purpose is to be used as a means of exchange. Some, such as bitcoin, have become globally recognized in recent years, but the uncertainty surrounding cryptocurrencies raises questions about their intended use. This study has the task of investigating the different factors that affect the intention behind the use of cryptocurrencies by developing a new research model and using Partial Least Squares (PLS) to assess it. The results show that all the constructs proposed have significative influence, either directly or indirectly, on the intention behind the use of cryptocurrencies. The findings provide value and utility for companiesâ and cryptocurrenciesâ intermediaries to formulate their business strategies.
Institut Teknologi Sepuluh Nopember, Yunifa Miftachul Arif, Hani Nurhayati, Universitas Islam Negeri Maulana Malik Ibrahim · 10 authors
One thing that tourists need to plan their tourism activities is a recommendation system. The tourism destinations recommendation system in this study has three primary nodes, namely user, server, and sensor. Each node requires the ability to share data to produce recommendations that the user expects through their mobile devices. In this paper, we propose the data-sharing system scheme uses a blockchain-based decentralized network that each node can be connected directly to each other, to support the exchange of data between them. The block architecture used in the blockchain network has three main parts, namely block information, hashes, and data. Each type of node has a different structure and direction of data communication. Where the user node sends destination assessment data to the server node, then the server node sends data from the machine learning process to the user node. The sensor sends dynamic data about popularity, traffic, and weather to the user node as consideration for finalizing the generating recommendations process. In the process of sending data, each node in the blockchain network goes through several functions, including hashing, block validation, chaining block, and broadcast. We conduct web-based experiments and analysis of the data-sharing system to illustrate the system works. The experimental results show that the system handles data circulation with an average time of mine is 84.5 ms in sending multi-criteria assessment data from the user and 119.1 ms in sending data of machine learning result from the server.