The goal of behavioral-science research is truth. The goal of design-science research is utility. — MIS Quarterly, 2004
知之为知之，不知为不知，是知也。 — Confucius
Research Agenda 1: Token Platforms
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Do Users of Blockchain IT Infrastructure Value Environmental Sustainability? Evidence from Environmental Impacts Disclosures.
Under Preparation for 2nd round review from Journal of Management Information Systems (FT50)
Conferences: 2024 MIS Quarterly Virtual Paper Development Workshop, 2024 Greater Bay Area Finance Workshop
Reference: [Working paper] [Slides]
Abstract
While the environmental impact has become an important IT governance agenda in recent years, it is unclear whether its disclosure is valued by token holders of platforms based on blockchain IT infrastructure and how these platforms react to changing public awareness of their environmental impacts. We consider Elon Musk's 2021 announcement that Tesla would suspend accepting Bitcoin as payment because of Bitcoin mining's environmental impact as a shock that dramatically increases awareness of Bitcoin mining's environmental impacts. We find that, subsequent to the shock, infrastructure platforms which have larger environmental impacts than application platforms, are more likely to disclose environmental impact information than application platforms and that their token market values grow at a slower rate, consistent with the increased awareness spills over to other token-based platforms. Furthermore, whereas pre-shock environmental impact disclosure by infrastructure platforms reduces token market value growth rates, post-shock disclosure has the opposite effect, consistent with green-costing and green-enhancing, respectively.
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Decentralized Voting in Product Development and Consumer Engagement: Evidence from a Blockchain-based K-Pop Community.
Under Preparation for Resubmission to MIS Quarterly (UTD24, FT50).
Conferences: ICIS 2024, CIST 2024, 2025 HKUST PhD Student Conference
Award: ICIS 2024 Best Short Paper Nominee
Reference: [Working paper]
Abstract
Traditional centralized models allow consumers to provide input, but are often limited by selection biases. Instead, blockchain-based decentralized models extend all consumer voice but face sustainability challenges including unsustained contributions and voting power concentration. Utilizing data from a blockchain-based K-pop platform, this study investigates whether fans continue contributing to the platform after initially participating in voting rounds. Findings indicate that voting power becomes less concentrated over time, likely because voters who have smaller voting power value the equity of decentralized voting and increase both tangible and intangible contributions. Conversely, voters who have larger voting power experience expectation disconfirmation; they begin with high expectations about influencing outcomes but if their preferences are disappointed, they decrease tangible contributions while maintaining intangible contributions. We use value cocreation and expectation disconfirmation theory to explain the phenomenon. This study contributes to blockchain and user innovation research and offers practical insights for platform designers aiming to create equitable, sustainable consumer-driven ecosystems.
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Breaking the Barrier or Breaking the Market? Evidence from Non-Fungible Token Platforms.
In preparation for submission.
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Crisis, Transparency, and User Engagement: An Empirical Analysis of Stablecoin Platforms.
In preparation for submission.
Conferences: ICIS 2024, SCECR 2025
Abstract
Public blockchains with smart contract functionality have revolutionized IT operations by enabling fully algorithmic processes and providing high transparency through realtime and detailed information disclosure. Yet, the impact of this IT operational model on user engagement remains largely unexplored. Leveraging the context of stablecoin platforms, particularly in light of the Terra-LUNA crisis, we construct a large-scale individual-level panel dataset from April 12 to June 1, 2022, and apply a cross-platform difference-in-differences approach. We find that, during crises, users can effectively distinguish between algorithmic and institutional IT operations, as well as their respective types of operational transparency. We also find that the presence of attackers switches user preferences for operational transparency. Higher levels of transparency, characterized by frequent and detailed information disclosures, may be perceived as catalysts for attacks in the post-crisis period, significantly impacting user engagement.
Research Agenda 2: Regulated Digital Currencies
Academic Papers
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Consumer Perceptions and Willingness to Adopt rCBDCs Before and After the e-HKD Pilot.
Under 2nd round review at ACM Distributed Ledger Technologies: Research and Practice
Government Media Coverage: [e-HKD Pilot Programme] [Summary]
Reference: [Working paper]
Abstract
This study investigates the public's perception of retail central bank digital currency (rCBDC) and identifies the factors influencing its adoption. Conducted in collaboration with a prominent bank in Hong Kong, this research involved a hands-on experience with a prototype payment system making using of an e-HKD, being an rCBDC which could be implemented in Hong Kong. Participants' opinions on rCBDCs were assessed through surveys conducted before and after their engagement with the e-HKD pilot. Initially, participants displayed a broadly positive attitude towards rCBDC, although no single factor emerged as a decisive influence on their adoption decision. However, the pilot experience statistically significantly altered perceptions, particularly regarding security, ease of payment, and promotional functions, thereby impacting their willingness to adopt rCBDC. This study underscores the importance of understanding consumer perceptions and suggests that these perceptions are subject to change through exposure to regulatory information campaigns, prototype experiences, and initial models.Consequently, the study recommends a cautious approach to interpreting the reliability of existing survey findings in this domain.
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Informational Experiment on Consumer's Perception of Central Bank Digital Currency as Liquidity Assets.
Conferences: International Conference on Central Bank Digital Currency and Payment Systems
Research Agenda 3: IT Management
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IT Code Reviewer and Code Contributions: Evidence from a Large-Scale Field Quasi-Experiment.
Conferences: 2024 HKUST Business PhD Student Conference, CIST 2024, SCECR 2025.
Under 1st round review
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Extensional Knowledge Representation for Quantum Monte Carlo Analysis: A Design Science Approach.
Media Presence: HKUST IEMS Thought Leadership Brief No. 94. [Brief]
Under Preparation for 2nd Round Review for ACM Transactions on Management Information Systems.
Other Publications (Pre-Doctoral)
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CEV Framework: A Central Bank Digital Currency Evaluation and Verification Framework With a Focus on Consensus Algorithms and Operating Architectures
Publication: IEEE Access, Volume 10, 2022 [Paper]
Government Media Coverage: Monetary Authority of Singapore (MAS) Global CBDC Challenge
Award: Global CBDC Challenge Finalist (Top 5% in over 300+ submissions from 50+ countries)
Abstract
We propose a Central Bank Digital Currency Evaluation and Verification (CEV) Framework for recommending and verifying technical solutions in the central bank digital currency (CBDC) system. We demonstrate two sub-frameworks: an evaluation sub-framework that provides consensus algorithm and operating architecture solutions and a verification sub-framework that validates the proposed solutions. Our framework offers a universal CBDC solution that is compatible with different national economic and regulatory regimes. The evaluation sub-framework generates customized solutions by splitting the consensus algorithms into several components and analyzing their impacts on CBDC systems. CBDC design involves a trade-off between system features - the consensus algorithm cannot achieve all system features simultaneously. However, we also improve the operating architectures to compensate for the weak system features. The verification sub-framework helps verify our proposed solution through empirical experiments and formal proof. Our framework offers CBDC designers the flexibility to iteratively tune the trade-off between CBDC system features for the desired solution. To the best of our knowledge, we are the first to propose a framework to recommend and verify CBDC technical solutions.
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Software Code Quality Measurement: Implications from Metric Distributions
Publication: 23rd IEEE International Conference on Software Quality, Reliability, and Security, Chiang Mai, Thailand (QRS 2023)
Reference: [Paper] [Slides] [IEEE], Acceptance Rate: 21.47%.
Abstract
Software code quality is a construct with three dimensions: maintainability, reliability, and functionality. Although many firms have incorporated code quality metrics in their operations, evaluating these metrics still lacks consistent standards. We categorized distinct metrics into two types: 1) monotonic metrics that consistently influence code quality; and 2) non-monotonic metrics that lack a consistent relationship with code quality. To consistently evaluate them, we proposed a distribution-based method to get metric scores. Our empirical analysis includes 36,460 high-quality open-source software (OSS) repositories and their raw metrics from SonarQube and CK. The evaluated scores demonstrate great explainability on software adoption. Our work contributes to the multi-dimensional construct of code quality and its metric measurements, which provides practical implications for consistent measurements on both monotonic and non-monotonic metrics.
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A UTXO-based Sharding Method for Stablecoin
4th IEEE International Conference on Blockchain Computing and Applications, San Antonio, USA (BCCA 2022) [Paper] [Code]
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Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
6th International Workshop on Cloud Intelligence / AIOps (AIOps '25), Co-located with ICSE '25 [Paper]
Abstract
Traditional banks face significant challenges in digital transformation, primarily due to legacy system constraints and fragmented ownership. Recent incidents show that such fragmentation often results in superficial incident resolutions, leaving root causes unaddressed and causing recurring failures. We introduce a novel approach to post-incident analysis, integrating knowledge-based GenAI agents with the "Five Whys" technique to examine problem descriptions and change request data. This method uncovered that approximately 70% of the incidents previously attributed to management or vendor failures were due to underlying internal code issues. We present a case study to show the impact of our method. By scanning over 5,000 projects, we identified over 400 files with a similar root cause. Overall, we leverage the knowledge-based agents to automate and elevate root cause analysis, transforming it into a more proactive process. These agents can be applied across other phases of the software development lifecycle, further improving development processes.
Patent
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B. Zhu, Yong Xia, Z. Li, Siyuan Jin. (2024). “Network Analysis using optical quantum computing”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007565 A1.
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Siyuan Jin, Yong Xia. (2024). “Method for implementing network consensus algorithm”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007483 A1.
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Siyuan Jin, Yong Xia. (2024). “Transaction security for multi-tier transaction networks”. International Bureau, World Intellectual Property Organization. Publication No. WO2024/007527 A1.
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Siyuan Jin, Yong Xia. (2024). “Blockchain transaction sharding for improved transaction throughput.” International Bureau, World Intellectual Property Organization. Publication No. WO2024/011707 A1.
Supervising
- 2022.10 ~ 2023.10: 7 Msc students on their year-level research projects (Co-supervised with Prof. Bei Zeng, Prof. Qiming Shao, Yuhan Huang and Yichi Zhang) [Details]
- After their research projects, Chang Xu, Shiguang Zhang, and Jiahui Wu got Ph.D. offers.
- Y. Liu received the Best Presentation Award of DDM 6980 Project Presentation.
Services
- Ad hoc Reviewer
- Workshop on Information Technologies and Systems (WITS 2024 X 2)
- International Conference on Information Systems (ICIS 2023 X 2, 2024 X 2, 2025 X 3)
- the Pacific Asia Conference on Information Systems (PACIS 2024 X 2)
- the Quantum Information Processing (QIP 2023 X 1)