Blockchain Papers

Daniel Rayne, Ashish Kumar

No abstract is available for this record.

Hani El-Chaarani, Zouhour El Abiad, Sam El Nemar, Georgia Sakka

Purpose This study contributes to examining the factors that drive the adoption of cryptocurrencies for financial transactions in the tourism and hospitality industries. This is crucial to develop tourism and hospitality and stimulate financial inclusion in developing and developed countries. Design/methodology/approach This research paper employs the SEM model and bootstrapping method on a sample of 417 French participants involved in tourism and hospitality industries to reveal the causal pathway between a set of independent factors and the willingness to adopt cryptocurrencies for financial transactions. Findings The empirical findings reveal that ease of use, perceived usefulness, social influence, and financial literacy increase the willingness to use cryptocurrencies. French hotels need to have a strategic orientation, to deal with customers, competitors and changing technological environment. The study also reveals that social influence and financial literacy reduce the level of perceived financial risk and thus, leads to increase the intention to adopt the new type of decentralized currencies. Originality/value In contrast to previous studies that focused on the volatility and risk of cryptocurrencies, this research employs a human-centric approach covering different factors that could lead to the adoption of the new type of currency for financial transactions in tourism and hospitality industries.

Chong Guan, Ding Ding, Jiancang Guo, Yun Teng

Purpose This paper reviews the extant research on Web3.0 published between 2003 and 2022. Design/methodology/approach This study uses a topic modeling procedure latent Dirichlet allocation to uncover the research themes and the key phrases associated with each theme. Findings This study uncovers seven research themes that have been featured in the existing research. In particular, the study highlights the interaction among the research themes that contribute to the understanding of a number of solutions, applications and use cases, such as metaverse and non-fungible tokens. Research limitations/implications Despite the relatively small data size of the study, the results remain significant as they contribute to a more profound comprehension of the relevant field and offer guidance for future research directions. The previous analysis revealed that the current Web3.0 technology is still encountering several challenges. Building upon the pioneering research in the field of blockchain, decentralized networks, smart contracts and algorithms, the study proposes an exploratory agenda for future research from an ecosystem approach, targeting to enhance the current state of affairs. Originality/value Although topics around Web3.0 have been discussed intensively among the crypto community and technological enthusiasts, there is limited research that provides a comprehensive description of all the related issues and an in-depth analysis of their real-world implications from an ecosystem perspective.

Marten Risius, Christoph F. Breidbach, Mathieu Chanson, Ruben von Krannichfeldt · 5 authors

Abstract Initial coin offerings (ICOs) and initial exchange offerings (IEOs) are distinct blockchain-based token offerings. Following multiple frauds associated with decentralized and unregulated ICOs, IEOs are emerging as a novel pathway that relies on centralized crypto exchange platforms acting as intermediaries. However, the question as to how this shift affects fundraising processes in what has traditionally been a decentralized environment remains unresolved. We here address this issue by empirically comparing the performance of ICOs and IEOs through the lens of signaling theory, focusing specifically on the impact of social media information across 305 token offerings (ICOs and IEOs). Our work introduces IEOs and explains how and why the volume and sentiment of social media signals may serve as predictors of fundraising performance. We furthermore find that the impact of these electronic word-of-mouth (eWOM) media signals is reduced in the case of IEOs—in the presence of a central cryptocurrency exchange platform mediator. We delineate implications for investors, ventures, platform providers, and regulators alike.

Fatemeh Delkhosh, Ram D. Gopal, Raymond A. Patterson, Niam Yaraghi

Incentivized blockchain-based online social media (BOSM), where creators and curators of popular content are paid in cryptocurrency, have recently emerged. Traditional social media ecosystems have experienced significant bot involvement in their platforms, which has often had a negative impact on both users and platforms. BOSM can provide additional direct financial incentives as motivation for both bots’ and human users’ engagement. Using the panel vector autoregression and regression discontinuity in time framework, we analyze two distinct data sets from Steemit, the largest and most popular BOSM, to study the impact of bot engagement on human users and the impact of changes in financial reward on user engagement. Interestingly, our findings demonstrate that while increased engagement by bots is positively associated with engagement by human users, the association between bot engagement and human user engagement decreases as the number of votes for a post increases. We also find that shifts in economic incentives significantly influence the behavior of both human users and bots. This research provides significant insights on how social media platforms can leverage economic incentives to influence user behavior and, more importantly, leverage bots’ activity to increase the engagement of their human users.

Yong Eui Kim, Sang‐Min Choi, Dongwoo Lee, Yeong Geon Seo · 5 authors

Personalized recommender systems are used not only in e-commerce companies but also in various web applications. These systems conventionally use collaborative filtering (CF) and content-based filtering approaches. CF operates using memory-based or model-based methods; both methods use a user-item matrix that considers user preferences as items. This matrix denotes information on user preferences, which refers to the user ratings for items. The model-based method exploits the fact that the input matrix is factorized. CF approaches can effectively provide personalized recommendation results to users; however, cold-start problems arise because both these methods depend on the users’ ratings for items to predict users’ preferences. We proposed an approach to alleviate the cold-start problem along with a methodology for utilizing blockchain that can enhance the reliability of the processes of the recommendations. We attempted to predict an average rating for a new item to alleviate item-side cold-start problems. First, we applied the concept of word2vec, treating each user’s item-selection history as a sentence. Then, we derived genre2Vec based on the skip-gram technique and predicted an average rating for a new item by utilizing the vectors and category ratings. We experimentally demonstrated that our approach could generate more accurate results than conventional CF approaches could. We also designed the processes of the recommendation based on the concept of blockchain addressing the smart contract. Based on our approach, we proposed a system that can secure reliability as well as alleviate the cold-start problems in recommender systems.

Natalie Sarrasin, Monica Zumstein, Antoine Widmer

Due to emerging technological trends and the acceleration of change in society, today’s undergraduate students are facing a new reality concerning the requirements and types of skills necessary to succeed. New immersive technologies such as Augmented Reality, Virtual Reality, Artificial Intelligence, Metaverse, Gaming and Non-Fungible Tokens (NFTs) are opening new business opportunities and revenue streams across many sectors. These technologies and trends are transforming the way people communicate, socialize, learn, work, shop and play. Institutions of higher education must also adapt to this constantly changing environment to fully prepare students for future employment. This paper discusses a pedagogical framework developed to create value for learners by exposing them to emerging technologies followed by application of the new knowledge to a practical situation implemented within the context of a University of Applied Science marketing first year bachelor course. Crucial skills are developed such as managing team dynamics, design thinking, creativity, autonomous learning, and critical thinking skills to name only a few. The framework is divided into four phases with the aim to further improve the process for future iterations. The results show students progressed from having little to no knowledge about these new technologies to being able to propose innovative ideas and practical applications in these new fields.

Anna Chukhnina, Grigorii Melnikov, Anton Pecherkin, Aleksandr V. Sokolov · 5 authors

This demo addresses the challenges of creating influencer marketing campaigns, including difficulties in measuring campaign performance and payment risks. Blockchain technology can provide a solution by offering reliable influencer profile generation, transparent reputation models, and template escrow payments. However, communication and processing of payments across ecosystems remain a challenge for Web3 projects. The paper presents B4B.World, an influencer marketing platform that utilizes cross-chain smart contract calls and supports payments in multiple blockchains. The platform offers reputation-based rewards for influencers and allows advertisers to make campaigns using crypto assets or project-based NFTs. B4B.World is the winner both The Illuminate/22 Hack by Moonbeam and BNB Chain Hackathon 23 in Georgia and utilizes the Axelar platform for cross-chain interaction.

Quan Xie, Sidharth Muralidharan

Purpose Non-fungible tokens (NFTs) are gaining popularity as investments and personal indulgences, prompting brands to integrate them into marketing campaigns. Thus, understanding consumer personality traits toward NFTs is essential for success. This study presents a model that explores how social comparison orientation (SCO) influences perceived exclusivity and financial benefits of NFT marketing, subsequently impacting experiential evaluations, willingness to purchase NFTs and brand loyalty. Design/methodology/approach We conducted two experiments to test our model. Study 1 used a quasi-experiment with 1,053 participants and tested the model using partial least squares–based structural equation modeling. In Study 2, we aimed to investigate the causal influence of SCO on NFT marketing effectiveness. We employed a one-factor experiment (social comparison prime: high SCO vs. control) with 123 participants. Findings NFT users frequently engage in social comparisons and prefer branded NFTs that offer exclusivity (social value) and financial benefits (economic value). Social and financial superiority derived from NFTs enhances branded NFT experiences, leading to a stronger willingness to purchase NFTs and building brand loyalty. Perceived exclusivity, financial benefits and experiential evaluation mediate the effects of SCO on willingness to purchase NFTs and brand loyalty. Originality/value This study explores the effectiveness of NFT marketing through the lens of social comparison theory. In doing so, we examined the relationship between SCO and NFT marketing outcomes, revealed the causal influence of SCO on perceived exclusivity and perceived benefits in NFT marketing and shed light on the serial mediation of value- and experience-related constructs.

Victoria L. Lemieux, Nigel Dodd

This paper explores the sociological and cultural implications of blockchain technology, specifically focusing on three prominent blockchain ecosystems: Bitcoin, Ethereum, and Algorand. The study utilizes the concept of the lifeworld, which encompasses collective human perceptions and everyday communicative social interaction, to analyze the formation and perpetuation of lifeworlds within these ecosystems. By employing scene theory as an analytical framework, the research identifies structural and thematic aspects of the lifeworlds represented in the discourse on Reddit and Twitter. The analysis reveals how these virtual spaces shape the unique social orderings, normative politics, and cultural identities associated with each blockchain. The study emphasizes the role of identity expression, cultural attitudes towards money, and the dynamics of boundary work within these scenes. Overall, the paper provides insights into the distinct lifeworlds and dynamics of Bitcoin, Ethereum, and Algorand, showcasing the significance of sociocultural factors in blockchain ecosystems and illustrating how a scenes lens offers insights into dynamics at the ecosystem level that may not be visible in an exploration of blockchain technology at the level of technological category.

Moritz T. Bruckner, Dennis M. Steininger, Jason Bennett Thatcher, Daniel Veit

Abstract Many firms use social media (SM) to solicit online investments. In this study, we examine the interaction between SM attributes and online-investment attributes to determine how this interaction shapes users’ investment decisions. Specifically, we investigate initial coin offerings (ICOs) as an application domain of distributed ledger technology for peer-to-peer investment. We use signaling theory to develop a context-specific explanation for how the interplay of persuasion signals found in SM and technology-enforced lockups shapes individuals’ ICO investment decisions. To evaluate this interplay, we conducted a 2 × 2 factorial experiment with 473 participants. The results show that when an investment does not require a technology-enforced lockup, persuasion signals encourage investments in ICOs; however, when an investment requires a technology-enforced lockup, persuasion signals do not affect investments in ICOs. Furthermore, our analyses suggest that combining a technology-enforced lockup and persuasion signals reduces the ICO’s plausibility. This is the first study to investigate how the willingness to invest in ICOs is influenced by the relationship between technology-enforced lockups and persuasion signals. The findings have practical implications for individuals attempting to make sound decisions on ICO investments, policymakers regulating online investments, and firms seeking to attract investors.

Kirti Sood, Prachi Pathak, Jinesh Jain, Sanjay Gupta

Purpose Research in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context. Design/methodology/approach A fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study. Findings The findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria. Research limitations/implications This survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market. Practical implications The study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large. Originality/value To the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.

Vocational Program Universitas Indonesia, Yulius Eka Agung Seputra

Smart tourism is a rapidly emerging field that combines innovative technologies and tourism practices to enhance the overall travel experience. This journal article investigates the integration of cryptocurrency based on fuzzy logic in the context of smart tourism. The study aims to explore the potential benefits and challenges associated with using cryptocurrency as a payment method and decision-making tool in the tourism industry. By applying fuzzy logic principles, this research examines how cryptocurrency can enhance transaction security, improve financial transparency, and facilitate personalized travel recommendations. The study analyzes the implications of incorporating cryptocurrency based on fuzzy logic in smart tourism, including its impact on transaction efficiency, customer satisfaction, and sustainability. The findings of this study indicate that integrating cryptocurrency based on fuzzy logic has the potential to revolutionize the tourism industry by providing efficient and secure transactions, enabling personalized and tailored travel experiences, and promoting sustainable tourism practices. The results contribute to the existing body of knowledge on smart tourism and offer insights into the practical implications and future directions for implementing cryptocurrency in the tourism sector. This research provides valuable insights for industry stakeholders, policymakers, and researchers interested in the applications of cryptocurrency in the tourism domain. The study also highlights the need for further exploration and testing of this technology in real-world tourism scenarios to fully understand its potential benefits and address any associated challenges. Overall, the integration of cryptocurrency based on fuzzy logic presents an exciting opportunity to enhance the efficiency, security, and personalization of smart tourism experiences, contributing to the growth and advancement of the tourism industry

Adrian Stanciu, Mariana Bernardes, Melanie Viola Partsch, Clemens M. Lechner

Cryptocurrency is an attempt to create an alternative to centralized financial systems using blockchain technology. However, our understanding of the psychological mechanisms that drive cryptocurrency adoption is limited. This study examines the role of basic human values in three stages of cryptocurrency adoption-awareness, intention to buy, and ownership-using the Theory of Planned Behavior (TPB). Logistic regression analysis was conducted on a quota sample of 714 German adults, and the results showed that openness-to-change values increased the likelihood of cryptocurrency awareness, while self-enhancement values increased the likelihood of intention to buy and ownership. These findings were consistent even after controlling for demographic characteristics, attitudinal beliefs, and perceived behavioral control, which are important factors in the TPB. The results suggest that basic human values may influence an individual's decision to adopt cryptocurrency, but the transition from awareness to ownership may be influenced by socio-economic opportunities available to interested individuals.

Chih‐Hsing Liu, Tse‐Ping Dong, Ho Tran Vu

No abstract is available for this record.

Achraf Boumhidi, Abdessamad Benlahbib, El Habib Nfaoui

Reputation generation systems are decision-making tools used in different domains including e-commerce, tourism, social media events, etc. Such systems generate a numerical reputation score by analyzing and mining massive amounts of various types of user data, including textual opinions, social interactions, shared images, etc. Over the past few years, users have been sharing millions of tweets related to cryptocurrencies. Yet, no system in the literature was designed to handle the unique features of this domain with the goal of automatically generating reputation and supporting investors’ and users’ decision-making. Therefore, we propose the first financially oriented reputation system that generates a single numerical value from user-generated content on Twitter toward cryptocurrencies. The system processes the textual opinions by applying a sentiment polarity extractor based on the fine-tuned auto-regressive language model named XLNet. Also, the system proposes a technique to enhance sentiment identification by detecting sarcastic opinions through examining the contrast of sentiment between the textual content, images, and emojis. Furthermore, other features are considered, such as the popularity of the opinions based on the social network interactions (likes and shares), the intensity of the entity’s demand within the opinions, and news influence on the entity. A survey experiment has been conducted by gathering numerical scores from 827 Twitter users interested in cryptocurrencies. Each selected user assigns 3 numerical assessment scores toward three cryptocurrencies. The average of those scores is considered ground truth. The experiment results show the efficacy of our model in generating a reliable numerical reputation value compared with the ground truth, which proves that the proposed system may be applied in practice as a trusted decision-making tool.

Mikhail B. Vialtsev, Mikhail Komarov

The sharing economy has shown significant growth in recent years, reinforced by the emergence and success of companies like Uber, Airbnb, eBay, etc. Consistently, it is attracting more and more attention from both the business and academic communities, which in turn are driving the development and adoption of new technologies in the sharing economy, such as smart contracts. However, which attributes of sharing economy business model would be most effectively modified by smart contracts and what would the qualitative effect? To answer these questions in this paper, we conducted a four-part study. First, we presented a description of the sharing economy and smart contract technology. Second, we considered the previously proposed generalized business model of a sharing economy company. Third, we identified the attributes of this business model to which smart contracts can be most effectively applied. Fourth, we qualitatively presented the effect of using smart contracts for each attribute.

Hyejin Park, Ivan Ureta, Boyoung Kim

Decentralized Autonomous Organizations (DAOs) have gained widespread attention in academia and industry as potential future models for decentralized governance and organization. In order to understand the trends and future potential of this rapidly growing technology, it is crucial to conduct research in the field. This research aims at a data-driven approach for the objective content analysis of big data related to DAOs, using text mining and Latent Dirichlet Allocation (LDA)-based topic modeling. The study analyzed tweets with the hashtag #DAO and all Reddit data with “DAO”. The results were from the identification of the top 100 frequently appearing keywords, as well as the top 20 keywords with high network centrality, and key topics related to finance, gaming, and fundraising, from both Twitter and Reddit. The analysis revealed twelve topics from Twitter and eight topics from Reddit, with the term “community” frequently appearing across many of these topics. The findings provide valuable insights into the current trend and future potential of DAOs, and should be used by researchers to guide further research in the field and by decision makers to explore innovative ways to govern the organizations.

Fuli Zhou, Chenchen Zhang, Tianfu Chen, Ming K. Lim

No abstract is available for this record.

Marco Francesco Mazzù, Rumen Pozharliev, Alberto Andria, Angelo Baccelloni

Abstract Blockchain technology has been designed to improve the transmission of transparent information across a variety of industries and products. Yet, consumers tend to perceive product information provided by blockchain technology (vs. humans) as less credible. As this may not apply to all consumers, it becomes critical for companies to understand how to improve blockchain perceived credibility. This work investigates how individual differences and marketing actions shape consumer responses to product information provided by blockchain technology (vs. humans). Four controlled experiments demonstrate that consumers perceive the information provided by blockchain technology (vs. humans) as having less credibility, which in turn decreases word‐of‐mouth and intention to share information about the product on social media (Study 1). This effect is stronger for consumers with lower need for cognition (Study 2a), which in turn affects willingness to buy and actual behavior (Study 2b). Providing social proof—that is, the number of satisfied customers who recommend blockchain technology—increases blockchain perceived credibility (Study 3). These insights deepen the understanding of how individual differences shape consumer's responses to product information provided by blockchain technology and offer actionable insights on how to boost technology credibility.

Evrim Tan, A. Paula Rodriguez Müller

Disruptive technologies, such as blockchain (BCT), uphold relevant implications to design more transparent, efficient, and effective coproduction. However, evidence on how disruptive technologies affect the design choices and process of coproduction remains limited. Drawing on the unique case of Barcelona, this study analyses how BCT can shape coproduction and how BCT-based coproduction can look. By using a novel framework, our findings suggest that BCT-based coproduction has the potential to lead to new forms and roles in digital coproduction, yet several institutional, social and organizational factors can influence the design choices and, in turn, the implication of such processes.

Rohana Sham, Eugene Cheng‐Xi Aw, Noranita Abdamia, Stephanie Hui‐Wen Chuah

Purpose The purpose of this study is to investigate consumers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT) and complexity theory. Design/methodology/approach By using a purposive sampling method, a configurational model was developed and a questionnaire-based survey was conducted to gather responses from a Malaysian sample. A total of 223 responses were obtained. Partial least square structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) were adopted to analyze the data. Findings The PLS-SEM indicated that performance expectancy, effort expectancy, social influence and affinity for technology interaction were positive cryptocurrency adoption predictors, whereas regulation was a negative predictor. Based on the fsQCA, cryptocurrency adoption could be explained by six configurational paths, which comprised combinations of the proposed causal conditions: the UTAUT factors (performance expectancy, effort expectancy, facilitating condition and social influence), environmental factor (regulation) and individual factors (financial knowledge and affinity for technology interaction). Research limitations/implications This study offers contributions to the theoretical body of knowledge by articulating the relevance of extended UTAUT and extending the established UTAUT model by integrating external environment and personal factors, also showing the linear and nonlinear interplays of performance expectancy, effort expectancy, facilitating conditions, social influence, regulation, financial knowledge and affinity for technology interaction. Practical implications The findings facilitated practitioners’ (cryptocurrency brokers, governments and businesses) fostering of cryptocurrency adoption through the joint consideration of different factors. The factors spanned technological attributes and individual characteristics to regulation. Practitioners should acknowledge that different combinations of the aforementioned antecedents can be equally effective to increase cryptocurrency adoption. The findings suggested that these causal conditions should be considered holistically and that there is no best predictor. Social implications In social terms, the research is expected to contribute to the dissemination of cryptocurrencies and help governments and central banks to develop, regulate and supervise digital currencies, as well as in the implementation of a digital currency ecosystem aligned with sustainable development goals. Economically, the results might foster a high cryptocurrency adoption rate and stimulate crypto-token-based business models and investment opportunities that present new means of revenue generation at individual, organizational and national levels. Originality/value This study offers unique perspectives for the body of knowledge and practice in the cryptocurrency domain, using both symmetric and asymmetric methodologies, by delineating the configurational logic involving technological capabilities, social influences, regulation and individual characteristics in facilitating more efficacious dissemination of cryptocurrencies.

Kaushik Gala

No abstract is available for this record.

Alessia Galdeman, Matteo Zignani, Sabrina Gaito

The current online social network landscape is characterized by competition to get larger audiences leading to massive user migrations which will determine the shape of the future Web. However, user migration phenomena have not been fully understood and their driving mechanisms are still not well identified; in particular, the behaviors of hubs and the influence they exert on their followers are unclear. In this work, we focus on these aspects by analyzing the propensity of hubs to migrate towards a new social platform as a consequence of a shocking event; and the influence they exert on the decision of their neighbors of migrating to a new platform or staying on the native one. We conducted analysis on data made available after a user migration consequence of a hard fork involving two Web3 online social networks based on the blockchains Steem and Hive. Due to the blockchain nature of these Web3 platforms, we got detailed data about social and financial interactions among the users, along with information that allowed a precise reconstruction of the context surrounding the migration. The main findings suggest that different types of hubs apply different strategies when choosing to migrate, e.g. financial hubs diversify their strategy by staying and migrating at the same time. As for hub influence, results suggest that users directly interacting with hubs tend to migrate. In general, findings on influence indicate that understanding the activity and the influence of hubs is crucial in monitoring and controlling the user migration process.