Blockchain Papers

QIUYING CHEN, Nan Wang, Sang-Joon Lee

As tokenized digital assets, Non-Fungible Tokens (NFTs) are becoming part of luxury brands’ digital business infrastructure. Yet it remains insufficiently understood how NFTs can be configured to foster enduring brand loyalty. To address this issue, we integrate necessary condition analysis (NCA) with fuzzy-set qualitative comparative analysis (fsQCA) using survey data from 620 luxury consumers. The framework combines customer-based brand equity conditions with NFT value cues. NCA indicates that all conditions are necessary for high loyalty, with perceived uniqueness, authenticity, and scarcity particularly critical. fsQCA complements this necessity logic and shows that high loyalty arises from multiple equifinal configurations, not a single dominant driver. Four propositions summarize these routes: Proposition 1 (reputation-driven strategy) demonstrates that brand capital can anchor loyalty through awareness and image even when NFT cues are less central; Proposition 2 (limited-access engagement strategy) indicates that scarcity-based access amplifies the loyalty effects of reinforcing associations, experiences, and image; Proposition 3 (privilege lock-in strategy) suggests that tokenized privileges translate engagement into durable attachment via uniqueness and psychological ownership; Proposition 4 (end-to-end assurance strategy) shows that technology adoption aligns authenticity verification with tokenized uniqueness and ownership to reduce friction, build trust, and sustain loyalty under high awareness. The findings position NFT attributes as boundary conditions and configurational ingredients rather than linear drivers of luxury brand loyalty. NFTs build durable loyalty when they serve clear infrastructure functions, such as verification, controlled access, or portable membership. They are most effective when deployed through a configurational strategy that fits brand capabilities and customer readiness.

Oliver Alexy, Oliver Baumann, Ying-Ying Hsieh, Giorgia Sampó

Decentralized Autonomous Organizations (DAOs) represent a radical form of socio-technical systems, where rules are enforced by code and governance is conducted by a distributed network of stakeholders. A critical challenge in designing these systems is achieving consensus without centralized authority, yet how consensus ensures effective governance remains underexplored. This study investigates the design of DAO governance systems, utilizing data from 70 DAOs and applying Fuzzy Set Qualitative Comparative Analysis (fsQCA) to explore which consensus configurations lead to positive organizational outcomes. Our analysis challenges the notion of a single consensus model. Instead, we uncover 13 distinct configurations that characterize successful DAOs. Our key finding reveals a fundamental “ideation-legitimation trade-off”: successful DAOs optimize for broad participation in either the proposal (ideation) stage or the voting (legitimation) stage, but rarely both. These insights provide a nuanced framework for understanding and designing effective governance systems for DAOs.

YujinSeo

This study proposes a structural model for understanding digital trust in smart-market environments by comparing the market-based trust architecture of Korea and the state-based trust architecture of China. Although both countries rely on similar technological foundations—blockchain, data infrastructure, AI systems, and CBDC—their institutional path dependencies and regulatory philosophies have produced divergent trust mechanisms. To explain these differences, the study introduces the 4-Layer Trust Architecture (4LTA–Seo), comprising incentives, rule enforcement, verification (data/AI), and institutional linkage. This framework conceptualizes tokens as digital institutions that integrate these layers to automate trust formation and oversight.Methodologically, the research applies Qualitative Comparative Analysis (QCA) using policy documents, technical whitepapers, and regulatory texts from both countries. It incorporates Zhang & Wang’s DTI (Data–Algorithm–Risk–Privacy) framework to compare how information architectures shape verification dynamics and trust costs. The study analyzes how institutional configurations rearrange the weighting and function of each trust layer, producing different stability and cost outcomes.Findings are expected to show that Korea’s market-driven architecture emphasizes incentives and behavioral inducement, while China’s state-driven model prioritizes rule enforcement and systemic integration. The research clarifies how tokens function as "units of trust" only when embedded within institutionally coherent architectures. Ultimately, the study offers structural insights for reinstitutionalizing trust in digital systems, with implications for Web3 governance, CBDC design, and digital public administration.

Rongen Zhang, Balasubramaniam Ramesh

Abstract Blockchain technology offers the potential to create an open, decentralised governance structure that empowers stakeholders to participate in decentralised engagement. However, how blockchain platforms configure their design elements to establish and maintain decentralised systems with high levels of user governance engagement requires further research. This study investigates the key design elements of blockchain platforms and their ideal configurations for promoting user governance engagement. Due to the complex and interdependent nature of the design elements, we adopt a configurational perspective accompanied by a fuzzy set qualitative comparative analysis (fsQCA) to uncover complex nonlinear relationships among key conditions that are relevant to decentralised governance. Our research identifies five key design elements that facilitate distributed governance ( Access to decision rights , Process visibility , Protocol automation , Incentives for developers/miners , and Incentives for other stakeholders ) based on existing blockchain governance literature. We analyse 14 unique blockchain platform cases that adopted on‐chain governance. Our fsQCA results reveal three ideal types of blockchain governance configurations that are sufficient for high generative user governance engagement: Centralised incentive model , Impartial incentive model , and Automation‐driven model , whereas achieving high evaluative governance engagement requires the presence of all the design elements ( Comprehensive model ). Also, we found Access to decision rights and Protocol automation are necessary conditions for generative governance engagement, and Access to decision right s together with Process visibility is a combined necessary condition for evaluative governance engagement. Relevant theoretical and practical implications for platform designers as well as methodological implications for applying QCA to emerging IS phenomena are discussed.

Daniela Penela

Bitcoin is a virtual currency that provides a completely decentralized secure alternative to the currencies currently used. Nakamoto, the creator of this cryptocurrency, published an article on an encryption mailing list in 2008 with the title “Bitcoin: A Peer-to-Peer Electronic Cash System”, thus giving the creation of this virtual currency. This study aims to analyze the Bitcoin and what factors can influence its price, in the context of a pandemic. This work will focus on the bitcoin price and on five different factors likely to have an influence on his price, such as: Hash Rate, Mining Difficulty, Volatility Index, Google Search and Transaction Cost. The period for this research ranges from 15/03/2020 to 14/11/2021, a total of 96 weeks, to integrate the covid-19 factor into the study. The results show that the variables fsCoinCirculation and fsTransationCost are both necessary conditions for an increase on the bitcoin price, but for low values of bitcoin price there are no necessary conditions. Additionally, findings suggest that Hash Rate influences the price of bitcoin. Finally, fsVix variable was found to be a variable with an important implication in price, namely, in its volatility.

Ming Xia, Zhimin Xie, Hui Lin, Xiangwu He

Blockchain technology is suited to the high-quality development of the digital economy in addressing privacy and data security issues. This study explores the synergistic mechanism of the following six factors from three dimensions based on the Technology-Organization-Environment (TOE) framework theory with a fuzzy set qualitative comparative analysis (fs/QCA) method: technology, organization, and environment, namely, Blockchain service capability, Blockchain knowledge accumulation, government attention allocation, government funding support, industry carrying capacity and blockchain technology R&D environment, on the quality of the digital economy of 43 cities in China. The conclusions are as follows: (1) the absence of government funding regarding the blockchain domain is a condition contributing to the absence of high urban digital economy quality; (2) there are three driving configurations for the high-quality urban digital economy in the blockchain technology adoption perspective, which are as follows: knowledge-industry driven, government-service driven, and R&D-service driven; (3) there is one driving configuration for the absence of high urban digital economy quality, namely the knowledge-R&D-funding-inhibiting type. The relevant policy implications can provide theoretical references for local governments to develop the digital economy with the help of blockchain technology.

Mengyuan Cheng, Heap‐Yih Chong

Blockchain technology is promising toward transforming conventional construction practices to improve collaboration and integration management in engineering-construction projects. The factors affecting the adoption of blockchain technology from the different stakeholder perspectives, however, have not been thoroughly investigated. Following the theory of planned behavior (TPB) and regulatory focus theory (RFT), this study explores the formation mechanisms underlying blockchain technology adoption from a multi-stakeholder perspective. The model was tested through partial least squares-structural equation modeling (PLS-SEM) and the fuzzy-set qualitative comparative analysis (fsQCA) method using data collected from Chinese construction practitioners. PLS-SEM results indicate that institutional pressures, perceived functional benefits, and behavioral control can directly drive blockchain adoption. Although perceived symbolic benefits do not directly affect blockchain adoption, their indirect effects on adoption are fully mediated by adoption intention. The PLS multi-group analysis found multiple path differences among stakeholders. The fsQCA results show that no single factor or its negation is the necessary condition to trigger blockchain technology adoption. The configuration analysis results show four new configurations that trigger the adoption of blockchain technology by owners, contractors, and consultants. This study not only enriches the related research on TPB and blockchains but also helps technology promoters to use strategies tailored to different stakeholders in theory and practice to improve blockchain technology adoption.

Mario Arias-Oliva, Jorge de Andrés Sánchez, Jorge Pelegrín Borondo

This paper assesses the variables influencing the expansion of cryptocurrency (crypto for short) use in households. To carry on the study we apply a consumer-behavior focus and so-called fuzzy set Qualitative Comparative Analysis (fsQCA). In a previous research, that was grounded on Unified Theory of Acceptance and Use of Technology (UTAUT) and Partial Least Squares (PLS), we found that main factors to explain the intention to use of cryptos by individuals were performance expectancy (in fact, it was the main factor), effort expectancy and facilitating conditions. We did not found evidences about the relevance of social influence, perceived risk and financial literacy. This study revisits these results by applying fsQCA instead PLS. Empirical research on factors influencing cryto use is relatively scarce due to the novelty of blockchain techs, so the present paper expands the literature on this topic by using an original analytical tool in this context. The main contribution of this paper consists in showing empirically that fsQCA provides a complementary and enriching perspective to interpret data about the use of cryptos. We obtain again that the most relevant factor to explain the intention of using cryptocurrencies is perceived expectancy and that also effort expectancy and facilitation conditions are relevant. But also fsQCA has allowed us discovering that despite social influence, perceived risk and financial literacy were not significant in the PLS model, they impact on the intention to use cryptocurrencies when are combined with other factors. Social influence acts as an “enable factor” for the rest of explanatory variables and it is linked positively with intention to use cryptos. Also financial literacy is relevant because its lack is a sufficient condition for the non-acceptance of that blockchain tech. Likewise we have checked that perceived risk influences the intention of using cryptos. However, this influence may be positive or negative depending of the circumstances.